VOLUME 10, ISSUE 7, JULY 2023

Abstract: Incubation is a technology that provides an opportunity for farmers to produce chicks from eggs without the need for the mother hen. It is one of the fastest ways of transforming eggs into chicks. To meet the high demand that the poultry industry is facing, the need to maximize poultry production should be addressed. Hence, this research study aimed to develop and test a digital egg incubator that can autonomously incubate eggs while allowing a user to remotely monitor the egg incubation and hatching process in a mobile app using Internet-of-Things (IoT) technology. The innovation of a prototype autonomous egg incubator with-internet of things application was developed overarching the objectives to determine the production yield of the prototype automated egg incubator, determine the efficiency of the prototype automated egg incubator in terms of the number of eggs hatched, humidity, temperature, and egg turning, evaluate the prototype automated egg incubator embedded system using the ISO-IEC 25010 system product quality evaluation, and determine its acceptability o in terms of its usability, functionality, and performance. Henceforth, the field testing and experimentation data of this study showed that the device garnered 100% efficiency score in terms of maintaining temperature, humidity, and CO2 (ventilation), as well as managing the egg-turning mechanism. In addition, the IoT Egg Incubator and Hatching device's average output of 94% efficiency in egg hatching with a production yield of 0.94 further supports the claim. Furthermore, the conducted ISO-IEC 25010 System Product Quality Evaluation for the proposed device indicated that the evaluating panel of IT experts found the embedded system to be excellent in terms of functional suitability, performance efficiency, usability, and reliability. Moreover, the Acceptability Evaluation in terms of its usability, functionality, and performance was very acceptable and indeed useful and functional, and it can incubate and hatch poultry eggs adequately.

Keywords: Agriculture, Technology, Internet-of-Things, Developmental Research

Abstract: In case of industrial equipment there is a requirement of material to be transfer from one place to another place. This process may require the heavy load lifting and raw material movement etc. material handling is important to transfer the material at right place at right time for its good working environment. That's why requirement of the crane for the purpose of material handling from one place to another place is necessary. This work will helpful for the specific requirement of such application of material handling in case of process industry. Basically, such industries require more human interfere for proper completion of the work. We have designed material handling system for one of the industries where aluminum bars are manufactured using extrusion process.

Keywords: 3D model of material handling system, design of material handling system elements.

Abstract: Advancements in electronics have made devices smaller, cheaper, and faster in recent years. This project aims to control the speed of a fan based on temperature sensors, which are essential in smart home applications. Home appliance fans require manual operation with regulators, which can be time-consuming and uncomfortable. To reduce this effort, the project designs an "Automatic Temperature Controlled" fan. The fan is controlled by heating the sensor, the Thermistor, which is dependent on the temperature of the device. As the temperature increases or decreases, the fan's speed increases or decreases. This can be used for cooling the animal shed or controlling room temperature based on the Thermistor's properties. The Thermistor decreases its resistance with increasing temperature, increasing electrical conductivity and voltage across it. This allows for automatic fan control when the device's temperature varies. Experiments can be conducted to evaluate the efficiency of this circuit, utilizing temperature sensors to save energy and promote efficiency.

Keywords: thermistor, fan speed, temperature sensor

Abstract: The manually operated grain collector and bagging made of locally available materials using local manufacturing technology was designed, fabricated, and tested for collecting and bagging of grains (paddy) dried on concrete pavement. The invention belongs to the technical field of agricultural machines, and relates to a tool applied when grains are collected after being aired, in particular to a manual grain bagging machine. Grains are automatically loaded into a dustpan by pushing the manual grain bagging machine with hands, a hand wheel of a drive assembly is rotated so that a gear can push a rack to move upwards at first and then move horizontally, and a stop bar on the dustpan is blocked by a left arc baffle and a right arc baffle so that the dustpan can tilt to pour the grains into an opening bag. A simple manually operated grain collector and bagging had the following major components: frame, wheel, long pipe, vertical stand frame (bars), horizontal bars, collector, and bag. Radial flat bladed type base plate, slot bar, sweeping box, bagging area, frame and the conveyance system. Results showed significant differences on the collecting capacity, and noise level. Other parameters such as collecting efficiency, air velocity, augmented cracked grain percentage. The design was made based on certain assumptions and calculations and the collector was built, tested and evaluated.

Keywords: Grain Collector, Bagging Machine

Abstract: Fences can be defined as arrangement that provides an obstruction, enclosure, or a boundary, made up of posts or stakes linked together by boards, wire, or rails. The chains run vertically and are bent into a zigzag pattern so that each "zig" hooks with the wire immediately on one side and each "zag" with the wire immediately on the other. The manufacturing of chain-link fencing is called weaving. Preparing zigzag shape wire is a quite challenging task and cannot be done using basic mechanisms. So here we design a smart mechanism to automatically bend wires in order to get zigzag shaped wire for mesh. These wires can then be linked together to create chain link or meshes. For this system we make use of a wire bobbin to supply raw wire to the system, a D.C. motor with shaft connected to a unique mechanism that achieves our bending requirements. The system is a small yet complex system that achieves the task with ease.

Keywords: Wire Fence, Motor, Solar panel

Abstract: In this project we are generating electrical power as non-conventional method by simply running on the train of people on the foot step. Non-conventional energy system is very essential at this time to our nation. Non-conventional energy using foot step needs no fuel input power to generate the output of the electrical power. This project using simple drive mechanism such as rock and pinion assemble and power storage mechanism. For this project the conversion of the force energy in to electrical energy. The control mechanism carries the rack & pinion, D.C generator, battery and inverter control. We have discussed the various applications and further extension also. So this project is implemented to all foot step, the power generation is very high. The initial cost of this arrangement is high.

Keywords: Nonconventional method, Electricity generation, Foot step

Abstract: Mobile jammer circuits are electronic devices designed to disrupt or block cellular communication signals within a specified range. This abstract presents a concise overview of a mobile jammer circuit, outlining its purpose, components, and functionality. Mobile jammer circuits utilize the principles of radio frequency (RF) interference to interfere with the transmission and reception of mobile phone signals. The primary objective of these circuits is to create a localized electromagnetic disturbance, rendering nearby mobile devices unable to establish or maintain connections with cellular networks. The circuit consists of various components, including power sources, oscillators, amplifiers, and antennas. The power source provides the necessary energy to operate the jammer circuit. Oscillators generate high frequency signals that are amplified by the amplifier circuitry.

Keywords: Radio frequency

Abstract: Microcontroller-based Green House control devices automate equipment and quantities in greenhouses, reducing human monitoring and ensuring optimal plant growth, crop yields, and resource efficiency. These systems are crucial for agriculture and horticulture sectors, as they control soil moisture, temperature, and other climatic parameters, enabling high-frequency data acquisition and reduced labor requirements. This project aims to design a micro-controller-based circuit that monitors and records temperature, humidity, soil moisture, and sunlight in the natural environment, enabling maximum plant growth and yield. Utilizing a low-power ATMEL AT89S52 chip, the circuit communicates with sensor modules in real-time, controlling temperature, moisture, humidity, and day light in greenhouses. A 16x2 character LCD displays information. This economical, portable, and low-maintenance solution integrates monitoring devices and provides suggestions for remedies. The study focuses on determining the effectiveness and functionality of greenhouse control devices.

Keywords: green house, heating, radiation, temperature, watering, ventilation

Abstract: The COVID-19 Pandemic is a global crisis that has hit County entirely. The evolution of the disease and its economic impact is highly uncertain. Because of its high infectivity, high mortality and incubation period, the main preventive measures are to control social distance and isolation, which makes many economic activities impossible. There is a Sharp Contraction in movement of an economy and Companies are expected to register the poor growth in the business and financial Performance remains sluggish ,even on pandemic some Industry had massive growth, So this Paper intends to compare the performance of sector and growth impact due to COVID-19 activity comparing this economic factors with those sectors. This paper covers measure to recovery of Indian economic from pandemic period. This Paper is completely based secondary data which is collected from the multiple ethical sources.

Keywords: COVID -19, Industry, Economy Factors, Financial Performance

Abstract: One of the most effective methods for maximizing the use of available energy is trigeneration. This research study examines the use of waste heat (flue gases) released by the Afam V1 gas turbine power plant for the simultaneous production of electricity, clean water and cooling using a single stage vapour absorption chiller (VAC) by combining steam with a Rankine cycle and a heat recovery steam generator (HRSG). The trigeneration system's main source of energy comes from the flue gases released during the gas turbine power cycle. The thermal energy recovered from the steam cycle's condenser and the extra heat present in the flue gases are used to power desalination and cooling cycles that are tailored to the villas' specific cooling requirements. The trigeneration system's financial and environmental advantages in terms of savings in expenses and a decrease in carbon emissions were examined. The trigeneration system achieves energy efficiency of around 82%-85% as opposed to combined cycles at 50%-52%. Implementing a waste thermal recovery tri-generation system reduces standardized carbon dioxide emission per MWh by 51.5%. The payback period for the trigeneration system is 1.38 years, and its total net present value for the duration of the project is $66 million.

Keywords: air gap membrane distillation, tri-generation, techno-economic, waste heat, steam cycle, absorption chillers, flue gases.

Abstract: The efficient use of utilities (electric energy, steam, and water) constitutes today's major problem in ensuring industry competitiveness and sustainability. The proposed study focuses on lowering the cost of steam and power generation at a petrochemical industry that uses a co-generation system to generate both electricity and steam. In this scenario, there is a trade-off between work and heat supply that cannot be easily characterized by heuristics or localized control loops. The use of an optimization model is provided based on the necessities of energy demands, and it is easily exposed the landscape that minimizes power and high-pressure steam level generation. There was a potential economy of 46 t/h in the generation of steam in boilers and a decrease of 6 MW in electric power usage.

Keywords: Utilities, Turbines, Steam, Optimization, Power, and Mixed Integer Programming

Abstract: The objective of this project work is to develop portable thermoelectric refrigeration system capable of maintaining temperatures between 8 °C and 13 °C. The main system consisted of thermoelectric module as cooling generator along with insulated cabin. Thermoelectric elements perform the same cooling function as Freon-based vapour compression or absorption refrigerators. To ensure the success of this project several criteria's are to be satisfied such as portability, size and cost of the system. The design of the preservation is based on the principles of thermoelectric module (i.e. Peltier effect) to create a hot side and a cold side. The cold side of the thermoelectric module is used for refrigeration purposes; provide cooling to the chamber. On the other hand, the heat from the hot side of the module is rejected to the surroundings with the help of heat sinks and fans. After gathering experimental data's and necessary guidelines from research papers on the thermoelectric refrigeration systems, the initial design of the model was made. Based on the heat load calculations, the thermoelectric module is selected. The system was fabricated and was experimentally tested for the cooling purpose. The capability of the system to maintain the required temperature and the time for reaching the same were analysed. The results showed that the system can maintain the storage temperature at 8°C and 13 °C under ambient temperature up to 30 °C with minimum power consumption of 64 Watt. The proposed thermoelectric module, to maintain the storage temperature, satisfied the design criteria.

Keywords: Peltier Module, Refrigeration

Abstract: It is crucial for agricultural production that weeds be reduced. Because they compete with crops for essential resources like water, nutrients, and sunlight, weeds can severely reduce crop yields. It is essential to choose the appropriate herbicides, choose planting locations, and manage cultivation depth to reduce crop damage while managing weeds efficiently. The goal of the project is to create a deep learning-based system for automatically identifying weeds in agricultural fields to overcome this constraint. Convolutional neural networks (CNNs) are used in this proposed system since they are effective for picture categorization tasks. A big dataset named Weed, which consists of high-resolution images of numerous weed species, is put together to train and test the systemYOLOv3, YOLOv5, and Faster R-CNN are among the deep learning detection models that were trained using the Weed dataset. This shows that the Weed dataset may someday prove to be a useful training resource for the creation of a real-time weed identification program.

Keywords: Weed Identification, Deep Learning, CNN Algorithm, Image processing, Color Index.

Abstract: World War I, often known as the First World War or the Great War, was an international struggle that engulfed the majority of the European countries, as well as Russia, the United States, the Middle East, and other regions, between 1914 and 1918. The war opposed the Allies-primarily France, Great Britain, Russia, Italy, Japan, and, starting in 1917, the United States-against the Central Powers-primarily Germany, Austria-Hungary, and Turkey. The Central Powers were defeated at its conclusion. In terms of the amount of death, destruction, and carnage, the war was essentially unprecedented. The people of Europe largely welcomed the start of the war in August 1914 with optimism and joy, and it sparked a wave of patriotic fervor and celebration. Few people believed that a conflict between the great European powers could last for so long or be so devastating, and the majority thought that their country's side would win in a matter of months. Either out of patriotism, as a defensive conflict imposed by national need, or out of idealism, as a conflict to uphold right against power, the honor of treaties, and international morality, people embraced the war..........

Abstract: The study endeavours to analysis fundamental position of major listed FMCG companies using ratios. Fundamental analysis, the share price of a company is determined by all the fundamental factors. The purpose of study is HUL, COLGATE, MARICO, GODREJ and DABUR were chosen, to analysis was done using past five year computed date of price to earnings, return on equity, dividend per share, earnings per share, book value per share starting 2018.This study provides a precise presentation of data and guidelines that will help a fresh investor as well as a venture investor to know vital aspects of investing. This study helps to the investors to choose a safe investment and to identify the growth opportunities in the future.

Keywords: Fundamental analysis, investment.

Abstract: Drinking fluoridated water is a big health concern in various nations. The current study focuses on fluoride removal by a) zirconium-impregnated hybrid anion exchange (HAIX-Zr) resin, b) synthetic hydroxyapatite (HAP), and c) co-precipitation with calcium and phosphate. Fluoride absorption by HAIX-Zr resin was fairly quick, with 60% elimination achieved in 30 minutes. Fluoride absorption by HAIX-Zr resin followed the pseudo-second order kinetic model, and adsorption data best suited the Freundlich isotherm. Fluoride removal ability of the resin reduced as pH and bicarbonate concentration increased. Continuous flow packed-bed studies with genuine groundwater were also carried out.

Keywords: Groundwater, fluoride removal using Zirconium Synthetic hydroxy lapatite calcium and phosphate

Abstract: This project aims to achieve vital cycle switching, a technique that removes complete cycles or fractions of cycles from an AC signal. This technique is used to manage AC power in linear loads, such as heaters in electric ovens. The project uses a comparator for zero crossing detection, fed as an interrupt to a microcontroller of the 8051 family, to generate triggering pulses. These pulses are then driven by opto-isolators to trigger the TRIAC, achieving integral cycle control as per the input switches interfaced to the microcontroller. A series motor or lamp can be used to verify the output, but this may cause an imbalance in the input current or voltage waveform as the cycles are switched on and off across the load. A lamp is provided in the project for demonstration purposes, but the real objective is to verify whether the load switches on at zero cross of the waveform during random switching. The power supply consists of a step-down transformer 230/12V, which steps down the voltage to 12V AC, converts it to DC using a Bridge rectifier, removes ripples using a capacitive filter, and regulates it to +5V using a voltage regulator 7805. The project can be enriched by using a feedback mechanism to automatically maintain the desired output to the load by appropriate cycle stealing. Integral cycle switching is achieved by using a microcontroller of the 8051 family programmed in assembly/C language, ensuring that the actual time-average voltage at the load is proportionately lower than the whole signal. A comparator is used for zero crossing detection, and the microcontroller produces output based on the received interrupt and generates triggering pulses. These pulses drive opto-isolators to trigger the TRIAC, achieving integral cycle control as per the input switches interfaced to the microcontroller.

Keywords: microcontroller, Bridge rectifier, current

Abstract: The information security has become one of the most significant problems in data communication. So it becomes an inseparable part of data communication. In order to address this problem, cryptography and steganography can be combined. This paper proposes a secure communication system. It employs cryptographic algorithm together with steganography. After that, a discrete wavelet transforms (DWT) based steganography is employed to hide the encrypted message in the cover image by modifying the wavelet coefficients. The performance of the proposed system is evaluated using peak signal to noise ratio (PSNR). The main purpose of this article is to present a new security system that enables exchange data more securely and by altering the file content structure, detecting illegal access and stopping the illegal operation.

Abstract: As the world continues to grow and as cities continue to become more crowded and congested, our normal modes of transportation will not be able to handle these overpopulated areas. The answer to this transportation problem lies in the world of electro magnetism and superconducting magnets. Electromagnets and superconducting magnets have allowed us to create a magnetic levitating train nicknamed "MAGLEV" that floats on the track instead of being directly on it. This has a lot of potential to create trains that are super fast with low maintenance requirements. China is the first country in the world to commercially use MagLevs, and has already helped ease the congestion on the six lane highway leading from the Pudong Shanghai International Airport to Shanghai Lujiazui financial district. This new technology has already helped China in a short period of time and can certainly help other cities around the world that are just as congested as Shanghai. Ion thrusters have proven to be an appropriate and efficient alternative to standard propulsion systems. With very low demand on fuel thanks to very high specific impulse generation, ion thrusters can easily compete with chemical propulsion systems, the produced thrust is far lower. The system is often used for various mission demands like orbiting station keeping for geostationary satellites, orbit and attitude controlling and multi-goal missions.

Keywords: Magnetic Levitation, Ionic Propulsion, Thrusters, Magnets.

Abstract: Orthogonal Frequency Division Multiplexing (OFDM) is considered to be a promising technique against the multipath fading channel for wireless communications. However, the main drawback of OFDM system is the high Peak to Average Power Ratio (PAPR) of the transmitted signals system which leads to power inefficiency in RF section of the transmitter. Many PAPR reduction schemes have been proposed to overcome this problem. This paper present different PAPR reduction techniques and conclude an overall comparison of these techniques.

Keywords: Bit error rate (BER), Multicarrier, Orthogonal frequency division multiplexing (OFDM), Peak to average power ratio (PAPR).

+91-7667918914 iarjset@gmail.com 0 Items International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal ISSN Online 2393-8021 ISSN Print 2394-1588 Since 2014 Home About About IARJSET Aims and Scope Editorial Board Editorial Policies Publication Ethics Publication Policies Indexing and Abstracting Citation Index License Information Authors How can I publish my paper? Instructions to Authors Benefits to Authors Why Publish in IARJSET Call for Papers Check my Paper status Publication Fee Details Publication Fee Mode FAQs Author Testimonials Reviewers Topics Peer Review Current Issue & Archives Indexing FAQ’s Contact Select Page Comparitive Study of Steel fiber and Glass fiber Reinforced Concrete by Using Manufactured Sand (M-sand) as Fine Aggregate Nakul N, Dr. Y.M. Manjunath

Abstract: In this paper fiber reinforced concrete is a two-phase material consisting of a matrix which is reinforced with randomly oriented small diameter fibers to improve the mechanical properties of the matrix. It increases the tensile strength of the concrete. Two types of fibers have been used in this paper i.e steel fiber and glass fiber. Steel fiber reinforced concrete is a homogeneous distribution of randomly oriented discontinuous and discrete steel fibers. It is available in the forms of Carbon steel or stainless steel. It has a high tensile and compressive strength. The Glass fibers are formed by drawing the molten material rapidly from a melted batch in a crucible or furnace. Glass fibers do not have a negative effect on the well-known high compressive strength of concrete. Thus, it shows that the fiber reinforced concrete is in good workable condition rather than without super plasticizer. The addition of 2% steel fiber and 0.5% -1% of glass fiber in concrete is found to be optimum as well as effective and economical as it gives good compression, tensile, and flexural strength for the concrete.

Keywords: Glass fiber, Steel fiber, concrete strengthening, compressive strength. Downloads: | DOI: 10.17148/IARJSET.2023.10722 How to Cite: [1] Nakul N, Dr. Y.M. Manjunath, "Comparitive Study of Steel fiber and Glass fiber Reinforced Concrete by Using Manufactured Sand (M-sand) as Fine Aggregate," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2023.10722 Copy Citation Call for Papers Rapid Publication 24/7 April 2026 Submission: eMail paper now Notification: Immediate Publication: Immediately with eCertificates Frequency: Monthly Downloads Paper Format Copyright Form   Submit to iarjset@gmail.com or editor@iarjset.com   Submit My Paper Author CenterHow can I publish my paper? Publication Fee Why Publish in IARJSET Benefits to Authors Guidelines to Authors FAQs (Frequently Asked Questions) Author Testimonials IARJSET ManagementAims and Scope Call for Papers Editorial Board DOI and Crossref Publication Ethics Editorial Policies Publication Policies Subscription / Librarian Conference Special Issue Info ArchivesCurrent Issue & Archives Conference Special Issue Copyright © 2026 IARJSET This work is licensed under a Creative Commons Attribution 4.0 International License. Open chat

Abstract: With the increasing levels of technology, the efforts being put to produce any kind of work has been continuously decreasing. The efforts required in achieving the desired output can be effectively and economically be decreased by the implementation of better designs. Conveyor systems are one of the most commonly used equipment in almost every industry. They help in achieving different kinds of functions and by automating them you can get the added advantages of flexibility and safe practices. Besides, they also help in enhancing the performance and cost-effectiveness of your processes. This conveyor system we can modify according to application and also can be developed as per height and width of job/ application. In this project, we have tried to develop a new mechanism for sugarcane lifter for tractor trolley loading and unloading purpose. Here we have used the chain and sprocket concept to manufacture the proposed mechanism. Our main objective of developing the mechanism is understanding the usage of various mechanical machine tools and also measuring tools. We have tried to develop a mechanism which can be used for loading the sugarcane in both trucks or trolley and bullock cart which is comparatively very small in height for loading purpose. Our project uses special chain drive system, D.C gear motor, bearing, shaft, and carrier. As a consequence of poor management and the under-utilization of equipment, loading has been identified as an inefficient and costly operation. Studies have shown that technology and management can contribute to improved loading accuracy. We have developed a mechanism which will help to increase the loading accuracy and efficiency of the work.

Keywords: Sugarcane, Bearing, Conveyor, Carrier, Cost

Abstract: The debate on the use and abuse of plastics vis-à-vis environmental protection can go on, without yielding results until practical steps are initiated at the grassroots level by everyone who is in a position to do something about it. The plastic wastes could be used in road construction and the field tests withstood the stress and proved that plastic wastes used after proper processing as an additive would enhance the life of the roads and also solve environmental problems. The present write-up highlights the developments in using plastics waste to make plastic roads. The rapid rate of urbanization and development has led to increasing plastic waste generation. As plastic is non-biodegradable in nature, it remains in environment for several years and disposing plastic wastes at landfill are unsafe since toxic chemicals leach out into the soil, and under-ground water and pollute the water bodies. Due to littering habits, inadequate waste management system / infrastructure, plastic waste disposal continue to be a major problem for the civic authorities, especially in the urban areas. As stated above, plastic disposal is one of the major problems for developing countries like India, at a same time India needs a large network of roads for its smooth economic and social development. Scarcity of bitumen needs a deep thinking to ensure fast road construction.

Keywords: roads, grassroots level, practical steps, plastic wastes, road construction.

Abstract: Eliminating acid gases, the most prevalent method in natural gas sweetening, is through the application of alkanolamine reactions. Numerous alkanolamine approaches every one of these have been extensively studied processes can be used to perform acid gas removal depending on the both sweet gas and sour gas parameters., Never the less one of the remaining lingering concerns is the financial implications on the process. In the present investigation, (DEA+MDEA) And mixed DGA, DEA Procedures are used to natural gas sweetening that is generated in one of the natural gas fields with significantsH2S/CO2 Ratio. A total of seven cases are created for each procedure in order to examined how the coolers operational setting affect the process performance. To ensure that lean amine hitting the absorber is a specified temperature ,the cooler function is changed for each cases .ASPEN HYSYS is used to simulate each scenario ,and ASPEN Fiscal analysis is used to access its economic viability .According to the finding of this investigation ,as the temperature of lean-amine rises so do the appropriate solution flow rate .Nevertheless ,performing both the DGA and DEA operations at greater quantities of lean amine temperature resulted in lower process capital cost and cooling duty .In the scenario of the DEA +MDEA the proceeding running at decrease lean amine temperature also led to reduced hydrocarbon collection. Works Cited: NNADIKWE JOHNSON, ENGR. ONUABUCHI AZUNNA,ENGR. TITUA OKPANACHI, GILLOW, TARE CAROLINE" ALKANOLAMINE SOLUTION PERFORMANCE IN CARBON-DIOXIDE CHEMICAL ABSORPTION PROCESSES: INFLUENCE OF LEAN ALKANOLAMINE DEGREE", IARJSET International Advanced Research Journal in Science, Engineering and Technology, vol. 10, no. 7, pp. 184-197, 2023. Crossref https://doi.org/10.17148/IARJSET.2023.10726

Abstract: For the purpose of a petrochemical facility located at Indorama Eleme Petrochemical, Nigeria, a dynamic simulation framework was designed, calibrated, and validated. The mathematical model was validated and calibrated based on plant monitoring results that spanned a period of three years. As a result, the model achieved an accuracy of 11.7 mg/L for effluent chemical oxygen demand (COD), 0.52 mg/L for the concentration of ammoniacal nitrogen (NH3-N), and 3.27 mg/L for the total amount of suspended solids (ASS), respectively. Since then, the simulation model has been put to use for troubleshooting throughout operational upsets, planning plant transformations, and developing possibilities for improvement. In this case study, the simulation model was utilized to help in troubleshooting and rectification of a plant upset caused by the entrance of a surfactant compound, which resulted in excessive effluent TSS and COD levels. During the resulting troubleshooting actions, the model was effectively utilized, and it gave crucial insights that supported the plant operators in promptly responding and restoring the equipment to a normal functioning state. Works Cited: TITUS OKPANACHI, NNADIKWE JOHNSON, ONUABUCHI AZUNNA,GILLOW, TARE CAROLINE" EXPLORING THE EFFICIENT TREATMENT OF PETROCHEMICAL WASTE WATER USING ADVANCED SIMULATION SOFTWARE FOR WASTE WATER PLANT", IARJSET International Advanced Research Journal in Science, Engineering and Technology, vol. 10, no. 7, pp. 198-212, 2023. Crossref https://doi.org/10.17148/IARJSET.2023.10727

Abstract: The debate on the use and abuse of plastics vis-à-vis environmental protection can go on, without yielding results until practical steps are initiated at the grassroots level by everyone who is in a position to do something about it. The plastic wastes could be used in road construction and the field tests withstood the stress and proved that plastic wastes used after proper processing as an additive would enhance the life of the roads and also solve environmental problems. The present write-up highlights the developments in using plastics waste to make plastic roads. The rapid rate of urbanization and development has led to increasing plastic waste generation. As plastic is non-biodegradable in nature, it remains in environment for several years and disposing plastic wastes at landfill are unsafe since toxic chemicals leach out into the soil, and under-ground water and pollute the water bodies. Due to littering habits, inadequate waste management system / infrastructure, plastic waste disposal continue to be a major problem for the civic authorities, especially in the urban areas. As stated above, plastic disposal is one of the major problems for developing countries like India, at a same time India needs a large network of roads for its smooth economic and social development. Scarcity of bitumen needs a deep thinking to ensure fast road construction.

Keywords: roads, grassroots level, practical steps, plastic wastes, road construction.

Abstract: Road safety is a concern of all authorities. One of the most important safety concerns is excessive speed in bullock cart at in loading condition which results in accidents, injuries, death, as well as damage in public property. Therefore, the imposition of automatic speed is essential and important in municipality's arsenal to prevent and combat excessive speed. The speed control system that we used in this project depends on IR Sensor with Arduino. The system consists of an IR Sensor, an Arduino board, and a brake system bullock cart. By using this prototype speed control system, speed controlling can be done through sensors, in efficient and cheaper way.

Keywords: IR Sensor, Arduino Board, Brake System

Abstract: The performance and advantages of microstrip patch antennas such as low weight, low profile, and low cost made them the perfect choice for communication systems engineers. They have the capability to integrate with microwave circuits and therefore they are very well suited for applications such as cell devices, WLAN, navigation systems and many others. Antenna arrays are widely used in various applications due to their ability to enhance system performance by providing increased gain, directivity, and beam shaping capabilities. This study specifically examines a variety of microstrip patch antenna arrays that resonate at 3.1GHz, utilizing an FR-4 Epoxy substrate with a dielectric constant of 4.4 and a height of 1.6mm. Generally, the spacing between antenna elements is kept lambda/2, in this project we analyzed that effect of increasing the number of elements maintaining array size same, on the parameters of array, like radiation pattern, gain, return loss and directivity. The design and analysis of the array are carried out using numerical electromagnetic simulation tool HFSS.

Keywords: Microstrip Patch, Radiation Pattern, VSWR, Gain.

Abstract: The aim of this project is to usage of bending machine to bending rods for stirrups which are used to withstand loads in beam and columns. Stirrups both end bend with 90 degrees right angle. The main objective of our project is to implement the hydraulic rod bending machine in the construction sites with less cost compared to the existing bending machines, and increasing the productivity of the stirrups. The design of the automatic metal stripping and bending machine will utilize subsystems which together compose the machine.

Keywords: Bending Machine, TMT Bar

Abstract: Movable bridges are designed and constructed to change its position and occasionally its shapes to permit the passage of vessels and boats in the waterway. This type of bridge is generally cost effective since the utilization of long approaches and high piers are not required. When the waterway is opened to vessels and ships, traffics over the bridge would be stopped and vice-versa. Moveable bridge is a bridge that can change position (and even shape in some cases) to allow for passage of boats below. This has a lower cost of building because it has no high piers and long approaches but its use stops the road traffic when the bridge is open for river traffic. The oldest know movable bridge was built in the 2nd millennium BC in the ancient Egypt. History also knows for one early movable bridge built in Chaldea in the Middle East in 6th century BC. Since then they were almost forgotten until middle Ages when they again appeared in Europe. Leonardo da Vinci designed and built designed and built bascule bridges in 15th century. He also made designs and built models of swing and retractable bridges. Industrial revolution allowed for new technologies like mass-produced steel and powerful machines and it is no surprise that new types of modern movable bridges appeared in 19th century. They are built even today but many movable bridges that are still in use in United States are built in early 20th century. In time, some of them are repaired with lighter materials and their gears are replaced with hydraulics

Keywords: Traffic, Movable bridges

Abstract: One of the primary challenges has been traffic congestion. India is one of the world's quickest and largest economies. Because India has such a large population, there are a large number of private vehicles on the road, causing traffic congestion. As a result, we've introduced the new way to address this issue. In the event of an emergency, on the roadside if there is heavy traffic and an emergency vehicle needs to pass. We can allow the vertical movement of the footpath so that cars can simply crawl on to it and clear their way by employing a hydraulic traffic reduction system, which uses a hydraulic mechanism beneath the sidewalk. By incorporating this system into the construction of the new road, we will be able to save money while also assisting in times of need. As a result, we can reduce traffic congestion during inclement weather and emergencies.

Keywords: Traffic, Hydraulic system

Abstract: This research examines how coil design and other geometric aspects affect the characteristics of single phase flow and convective heat transfer. Copper tubes with internal diameters of 9.5mm, 1.5mm thickness, and 3000mm length were used in experiments on helical, conical, and spiral coil heat exchangers. According to the findings, helical coil heat exchangers had a convective heat transfer rate that was 9.54% greater than that of conical and spiral coil heat exchangers. As mass flow rate rose, Nusselt numbers climbed, demonstrating the efficiency of helical coil heat exchangers. The modeling of heat exchangers was carried out using computational fluid dynamics (CFD) software, and the CFD tool was utilized to confirm the experimental results of water outlet temperature. The results showed good agreement.

Keywords: spiral coil, flow rate, CFD, heat exchanger, geometry

Abstract: The quality of water entering into water distribution network often provides requirements for corrosion and scaling in areas lacking adequate treatment methods, which can cause serious problems. The most commonly used corrosion indices are Langelier saturation index (LSI), Ryznar stability index (RSI). This study aimed to evaluate the corrosion and scaling potential of water resources in Udaipur, Rajasthan. Therefore, the corrosion and scaling potential of groundwater resources were investigated according to LSI, RSI. Scaling and corrosion are from common indicators of water quality and can cause economic and health damages. According to the results, total hardness and TDS had high mean values, but the values of pH, temperature, and alkalinity were rather admissible. As well, most of the water resources of studied area had low to moderate corrosivity according to LSI and RSI. On the basis of LSI, around 50% result showing that water was slightly scale forming and corrosive and remaining 50% showing that water was scale forming but non-corrosive as mentioned in table 3. Ryznar Stability Index (RSI) showing that 4.5% samples were heavy corrosion, 9.0% samples were light scale, 50% samples were light scale or corrosion, and 36% samples were corrosion significant

Keywords: Scaling, Corrosion, LSI, RSI, Groundwater

Abstract: The objective is to create a visually striking display that utilizes the phenomenon of persistence of vision to generate the illusion of floating images or messages in mid-air with easy implementation technique. This project aims to create a captivating visual display that utilizes the phenomenon of persistence of vision to create the illusion of static or moving images. By rapidly flashing or changing the displayed content in synchronization with the viewer's perception, the POV display creates a continuous image that appears to defy reality. The project leverages an ESP32 microcontroller, which serves as the central control unit for the display. Individual LEDs are used as the light source, arranged in a linear configuration, which is mounted on the blades of the fan. The LEDs are selectively activated in a precise sequence, taking advantage of the persistence of vision phenomenon, to create the perception of a static or moving image. The software implementation includes programming the ESP32 to control the LED activation patterns, timing, and synchronization with the fan's rotation. The display content, such as text, patterns, is designed to be mapped to the LED activation sequence, considering the speed of the rotating fan blades. The objective is to create a visually striking display that utilizes the phenomenon of persistence of vision to generate the illusion of floating images or messages in mid-air with easy implementation technique. This will enable small-scale businesses to advertise their business or products at a very subsidized cost.

Keywords: ESP 32, LED's, 9v battery, 220ohms Resistor, Firebase, Mobile Application, Arduino IDE.

Abstract: There is a relationship between earnigs and education and education is very crucial for equitable societal development "Mincerian" earnings function is taken as a starting point for existence of a relationship between education and earnings.

Keywords: Education, earnings, human capital inequalities, Mincerian, rate of return.

Abstract: The project aims to design and develop a machine for extracting coco peat from coconut husk efficiently and cost-effectively. Coco peat, also known as coir pith, is a by-product of the coconut industry and has several uses; the extraction of coco peat from coconut husk traditionally involves manual labour, which is time-consuming, labour-intensive, and not cost- effective. The machine is expected to increase the efficiency and productivity of coco peat extraction, reduce labour costs, and improve the quality of the final product.

Keywords: Coco Peat, Extraction, Coconut husk, Coco Fibre

Abstract: These days in Mumbai there not much land left for new development so there is a quick expansion in development field in edge district like Navi-Mumbai, Panvel, Vasai-Virar locale. Thus, there is a need of multi-story building. In seismic and wind examination of working by involving ETABS in this undertaking we for the most part manage investigation, taking into account stacks that is, seismic burden and wind load. Vasai-Virar goes under seismic zone 3. We have taken g+30 story building. The construction higher than G+5 is viewed as under the seismic stacking. In this task we examination and plan of building involving rectangular section for financial construction. We figure out the boundaries like Twisting moments, shear force, Story shear and firmness, upsetting second, story float and so on of building Talk about the outcomes coming from the Straight Powerful Examination (Response Spectrum Analysis) Technique.

Keywords: Multi-Storied Building, Seismic and Wind Analysis, Response Spectrum Analysis.

Abstract: Sand has become a very important mineral for society due to its many uses mainly in infrastructural activities. Sand and gravel have long been used as aggregate for construction of roads and buildings. Today, the demand for these materials continues to rise. In India, the main source of sand is from river flood plain sand mining, in-stream mining, coastal sand mining, paleo channel sand mining, and sand mining from agricultural fields. As one of the driest states in India, Rajasthan's entire river surface constitutes very less percentage of the total surface water resources in India. This paper discussed about the scope and impact of river sand mining in Ajmer, Rajasthan. The rivers in the district are monsoon fed rivers. These rivers flow more rigorously in rainy season and carries sufficient load of sediments which are produced due to erosion of the country rocks in the catchment. The running water transport and deposit sediments in river beds. Sand mining has many positive impacts on the economy and on the quality of life of people. However, if extracted in excess amount beyond the replenishment rate, it has an adverse and destructive impact, on the river system. Total Mining areas cover about 31.94 sq km area in Ajmer district which is 0.38 % of the entire area of the district. Maximum concentration of the Built-up mining areas, in south western part of the district

Abstract: The effect of varied concentrations of dilute acid on the reducing sugar content of jackfruit seeds (JFS) and its potential as a raw material for bioethanol production was investigated in this study. Raw JFS is known to be rich in starch, which can be converted into fermentable sugar using dilute acid hydrolysis by utilising microbial activity. The reducing sugar concentration of the native and pre-treated biomass sample was determined by the 3,5-dinitro salicylic acid using a UV-VIS spectrophotometer. Dilute acid pretreatment (DAP) was carried out at varied acid concentrations (1 - 5%, v/v) and solid biomass loading of 10% w/v at a constant temperature of 121℃ for 15, 30, and 45 minutes. After pretreatment, the highest reducing sugar yield (2.01 ± 0.03 mg/g) was obtained at 1% (v/v) hydrolysed for 15 mins. There was a 57.03% increase in reducing sugar yield after pretreatment with dilute acid.

Keywords: Bioethanol, pretreatment, reducing sugars Artocarpus heterophyllus.

Abstract: We The purpose of this report is to use charcoal filter for indoor air pollution, which is growing concern, with adverse effects on human health and well-being. After a years of research and various technologies have been developed to address this issue, and surprisingly one effective approach is the use of activated charcoal filters for indoor air purification. These filters effectively trap and eliminate a wide range of indoor pollutants including VOC, formaldehyde, odours, and airborne chemicals that significantly improve the quality of indoor air without leaving any harmful chemicals. The pollutant in air to eliminate by this filter is particulate matter (2.5micrometer to 10micrometer) and gaseous. These filters can be incorporated into standalone air purifiers, offering flexibility and adaptability to various indoor environments. They are easy to install and require regular maintenance to ensure optimal performance. Periodic replacement of filters is necessary to maintain their effectiveness over time. To boost up the performance of this filter in the system other filters have been introduced, which eliminate the larger and major pollutants before expose to this filter.

Keywords: Air pollution, activated charcoal, pollutant, effects, techniques, etc.

Abstract: The advent of smart agriculture systems has revolutionized the agricultural industry by leveraging advanced technologies to enhance productivity and efficiency. This research paper presents a smart agriculture monitoring and control system that utilizes image processing techniques for effective crop management. The system aims to enable farmers to monitor crop health, predict suitable crop, and optimize irrigation practices in real-time through image analysis. A comprehensive literature review explores the existing smart agriculture systems and the utilization of image processing techniques in agricultural applications. The block diagram section outlines the system architecture and the various stages involved in the image processing pipeline, including image acquisition, pre-processing, crop health monitoring, and irrigation optimization. The implementation section presents the design steps required for the system. The data collection process and the training of algorithms are described, highlighting the steps taken to ensure accurate and reliable analysis. The results and discussion section evaluates the performance of the system, utilizing appropriate evaluation metrics and presenting analysis results.

Keywords: Image processing, Data collection, Data analysis, Raspberry Pi .

Abstract: PoSH (Protection of Women from Sexual Harassment) Act, 2013 The PoSH Act has been implemented to prevent and protect women from sexual harassment at the workplace and thereby ensure a safe working environment for women. This supreme court judgment defined the ambit of Sexual Harassment as including an uninvited or unwelcome sexual favour or sexual gestures from one gender towards the other gender The PoSH Act, as mandatary compliance, requires every company having more than ten employees to constitute an Internal Complaints Committee (ICC) in the prescribed manner to receive and address the complaints of any sort of sexual harassment from women in a time-bound and extremely confidential manner so this paper studies about key Provisions of POSH Act and comprehensive Study of the implementation and effectiveness of the Prevention of Sexual Harassment (POSH) Act in Indian workplaces.

Keywords: Sexual Harassment, Workplace, Vishakha Guidelines

Abstract: Nature provides goodness and nourishment for man. There are many useful plants around that could be a source of food and wellness, but are seldom left untapped, like the banana pseudo-stem and the sweet purple potato. Hence, this study was conducted to determine the acceptability of banana pseudo-stem with purple sweet potato tops, citrus, and organic honey drink. The study used the Experimental-Developmental method of research using a Completely Randomized Design (CRD). The sensory qualities were evaluated by ten (10) semi-trained panelists and the acceptability of the products was evaluated by one hundred (100) consumers. Scorecards with the Nine (9) Points Hedonic Scale was used to obtain the data. The mean and Analysis of variance (ANOVA) were used to analyze the data set at a 0.01 level of significance. The findings of the study revealed that sensory qualities of banana pseudo-stem juice with purple sweet potato tops and organic honey were generally positively evaluated by the semi-trained panelists as revealed by their respective ratings in terms of their appearance, aroma, taste, and texture. The banana pseudo-stem with purple sweet potato tops, citrus, and organic honey drink was generally liked extremely by the consumers. Of the three treatments, Treatment C (with lemon) was the most preferred. There was a significant difference in the sensory qualities of banana pseudo-stem with purple sweet potato tops, citrus, and organic honey in terms of appearance, aroma, taste, and consistency in favor of Treatment C (Lemon Flavor). Likewise, there was a significant difference in the general acceptability of banana pseudo-stem with purple sweet potato tops, citrus, and organic honey drink in terms of appearance, aroma, taste, and consistency in favor of Treatment C (Lemon Flavor). Furthermore, the product could last for at least 30 days when chilled and at least 7 days when left at room temperature. Likewise, the product has a pH of 5 which indicates it was slightly acidic due to its citrus fruit content and was safe for human consumption as the results of microbial analysis of the product and based on the BFAD standard for microorganism test for products belonging to the ready-to-drink beverages. Hence, it was suggested that considering the appeal of the product to the probable target market. There is a huge possibility of mass production of the formulated product of the banana pseudo-stem with purple sweet potato tops, organic honey, and citrus for commercialization.

Keywords: Banana Pseudo-Stem, Sweet Potato Tops, Citrus, and Organic Honey

Abstract: The furniture industry in Capiz is an unorganized sector, a micro-small enterprise mostly home-based business with sole proprietorship. This study ascertained the production and marketability of the furniture industry in Capiz in terms of its challenges, sustainability, and prospects. Participants of the study were the 18, DTI registered furniture owners in Capiz, identified through purposive sampling. A researcher-made survey questionnaire and interview guide for gathering data. The data were analyzed and interpreted using the mean, percentages, and thematic analysis. A mixed-method research design using a convergent-parallel approach was employed. Results showed that the participants of the study were dominated by males, ages 31 to 51 years old, college graduates, and 4-10 years in business. Wood furniture was produced weekly and monthly based on order, used machine tools and workers mostly paid in "pakyaw". They displayed their product within the area and through an online platform, catered to individual customers, and on a cash basis. The industry's production was highly sustainable despite the challenges encountered, while, sustainable for marketability. The industry encountered challenges primarily on the start-up capital and the procurement of tools and machinery, labor force, and lacking and limited skills in designing, and only some of the owners attended seminars and training. They relied on their personal experience and personally trained their workers. Likewise, competition in marketing was a challenge because similar designs and furniture types were produced at varying prices, including customer satisfaction, delivery, and display or exhibit. Based on the results and analysis, the furniture industry in Capiz has greater prospects despite of the challenges. If given attention, support, and collaboration with the government agencies concerned, it can be organized into a cooperative for finances and identity, upgrading of quality and design using upgraded tools and machinery, glocal marketing, increase employment, and recognized entrepreneurs by affiliating with the established furniture industry in the country.

Keywords: Challenges, Production, Marketability, wood industry

Abstract: This research was conducted with the aim to determine the correlation between antioxidant content and antidiabetic properties of stevia black tea mixtures with various proportions. The research design used was a completely randomized design with one factor. The factor is the proportion of black tea: stevia with 5 levels of proportion, namely the proportion of black tea: stevia (in % by weight) used respectively is 88:12, 76:24, 64:36, 52:48 and 40: 60. Tea is brewed by steeping every 2 g of stevia tea in 200 mL of hot water at 94 ± 5 °C for 4 ± 1 minute. And the tea was filled in a glass jar, then stored at ambient temperature (28 ± 2 °C) for 3 days. After 3 days, the tea drink was analyzed. The parameters analyzed were total phenols and inhibition of the alpha-amylase enzyme. The data obtained from testing these parameters were then analyzed using regression Minitab 17 with a significance level of 5%. The relationship between total phenol and amylase inhibitory ability is directly proportional, positive, and cubic equation type

Keywords: total phenol, amylase, black tea, stevia

Abstract: Cloud computing has revolutionized the way businesses and individuals access and manage their data and applications. As the adoption of cloud technologies continues to grow, understanding the key technological-centric dimensions that shape its effectiveness and impact becomes crucial. This research paper presents a comprehensive review of the technological-centric dimensions in cloud computing, examining their significance in current cloud-based services and future trends.

Abstract: The aim of this study was to develop a muffin made from chestnut, squash, and malunggay leaves. Specifically, it aimed to (1) describe the sensory qualities of the product formulated in terms of appearance, aroma, taste, and texture; (2) determine the acceptability of muffin in terms of sensory qualities among five treatments; (3) find out if there is a significant difference in the sensory qualities of the product among five treatments in terms of appearance, aroma, taste, and texture; (4) find out if there is a significant difference in the acceptability of product among five treatments in terms of four sensory qualities; (5) determine the shelf-life of muffin considering room temperature; and (6) submit the best treatment of muffin for microbial and proximate analysis. The researcher used Completely Randomized Design (CRD) with five (5) treatments in three replications. The first, second, and third replications of treatments were evaluated by ten (10) semi-trained panelists who were Food Technology Teachers of Capiz State University. The final product was evaluated by seventy (70) consumers. The Nine Point Hedonic Scale was utilized to rate the products. The statistical tools used to analyze the results were the mean, Analysis of Variance (ANOVA), and the Post Hoc Test. The findings of the study revealed that the sensory qualities of the Chestnut and Squash muffin with Malunggay leaves were evaluated by the semi-trained panelists with five treatments in terms of appearance Treatment A got a very much appealing, very much pleasant, very much delicious, and very much soft and intact in terms of appearance, aroma taste, and texture. Treatment B was very much appealing, very much pleasant, very much delicious, and moderately soft and intact. Treatment C was very much appealing, very much pleasant, very much delicious, and very much soft and intact. Treatment D was very much appealing, very much pleasant, very much delicious, and moderately soft and intact. Treatment E was very much appealing, extremely pleasant, extremely delicious, and very soft and intact as evaluated by semi-trained panelists. The consumers' acceptability of the chestnut and squash muffin with Malunggay leaves considering the sensory qualities that all products of chestnut and squash were all extremely liked as evaluated by seventy (70) consumers. However, product E got the highest result in all quality attributes. There was no significant difference found in the sensory qualities and consumer's acceptability of chestnut and squash muffin with malunggay leaves among five treatments in terms of appearance, aroma, taste, and texture. Shelf-life of treatment E of chestnut and squash muffin with malunggay leaves when stored at room temperature, could last for three (3) days with no changes in the sensory attributes when sealed well. The chestnut and squash muffin with malunggay leaves was safe for human consumption based on the results of microbial analysis of the product and based on the BFAD standard for microorganism tests for products belonging to the baked goods category.

Keywords: Chestnut, Squash, Malunggay Leaves, and Muffin, Product-Formulation, Shelf-Life

Abstract: This study aimed to develop a curing agent alternative to the synthetic curing agent. Alagaw leaves "Premna odorata blanco" has its own property to preserve. Experimental-development method of research using completely randomized design (CRD) and the nine point Hedonic Scale were used in evaluating the product. The sensory qualities of the cured meat applied with alagaw curing agent were evaluated by ten (10) semi-trained panelists in three (3) trials during product formulation, and one hundred (100) consumers to evaluate the acceptability. Analysis and interpretation of data were the mean and the analysis of variant (ANOVA) used as statistical tools set at 0.01 alpha level. The alagaw curing agent "Premna odorata blanco" has a pH of 5 which is acidic in nature in all different oil solvents, and maceration extractions used (olive oil, sunflower oil, and palm oil)with 50% concentration (% = w/v). The sensory qualities of cured meat with alagaw leaves extraction in sunflower oil appearance found "extremely appealing", while in palm oil "very much pleasant" in the aroma. In terms of taste, olive oil was "extremely delectable" and in texture, olive oil was found to be "very much tender". Regardless of the oil used, Treatment B of 10ml proportion was preferred by the semi-trained panelist which was used for consumer testing. The alagaw in olive oil extraction was liked extremely by the consumers in sensory qualities except in texture. The shelf-life of the cured meat with macerated Alagaw leaves "Premna odorata blanco" as a curing agent when exposed to freezing temperatures (32°F or 0°C) sustained its sensory qualities. The cured meat was observed in the shelf-life and it lasted for 60 days maintaining good sensory qualities without negative changes. There was a significant difference in sensory qualities of alagaw curing agent in terms of appearance and taste by the semi-trained panelist. However, in terms of aroma and texture, there were no significant differences. The shelf-life of cured meat with Alagaw leaves "Premna odorata blanco" as the curing Agent when exposed to freezing temperature. The cured meat lasted for eight (8) weeks and four (4) days or sixty (60) days. Observation showed that cured meat at room temperature had no molds developed until 15 days, but in the chilling temperature, sliminess and foul odor appeared, with discoloration on the twenty-seventh day, and mold development on the thirtieth day. The sample meat with alagaw curing agent submitted for E.coli microbial analysis to Negros Prawn Producers Cooperative Analytical for Diagnostic laboratory (NPPC) was within the acceptability level. Likewise, the sample of 200g meat was tested for fat percentage (Soxhlet Extraction method) of 23.90; fiber percentage (lepper modification method) of 1.74; and protein percentage (kjeldahl method) of about 14.71 as per Negros Prawn Producers Cooperative Analytical and Diagnosis Laboratory (NPPC).

Keywords: Maceration, Curing Agent, Premna odorata blanco

Abstract: The employability of Beauty Care graduates faces diverse challenges impacting their job market readiness, necessitating effective measures for addressing these issues. This study aimed to bridge employability gaps among Senior High School (SHS) graduates in the Beauty Care industry through the adoption of the Triple Helix Collaboration. Qualitative and quantitative data analysis methods were employed using a mixed-method concurrent embedded approach. A purposive sampling technique was utilized, resulting in a total of 72 participants, including 60 SHS graduates and 12 Triple Helix representatives. Quantitative data were analyzed using mean and Pearson-r, while thematic analysis was applied to the qualitative data. The findings revealed that SHS graduates perceived a high level of competence among the Academe, Government, and Industry Partners in terms of knowledge, skills, and attitude. The study emphasized the positive relationship and collaborative efforts among these helices in developing employability skills, which have the potential to significantly enhance graduates' employability. Notable strengths identified in the Triple Helix Contribution included work immersion programs, employment support, knowledge and skills enhancement, collaborations and partnerships, and initiatives to improve wages and work conditions. However, limitations were noted, such as the limited engagement in quality assurance and remedial actions and the absence of monitoring and evaluation programs due to financial constraints. The study also highlighted influential factors in the Beauty Care industry, with Training and Development Factors identified as the most significant. Addressing these factors, including Employment Factors, Government Support, Curriculum and Design Programs, and Institutional Factors, holds significant importance in improving employability outcomes and aligning graduates with the evolving job market in the Beauty Care industry.

Keywords: Triple Helix, Collaboration. Employability, Gap, Competency

Abstract: Adolescence is a unique and critical period in the human life-cycle. It is the transition period from childhood to adulthood between the ages of 10 to 19. Adolescence is a period of experiencing rapid physical, cognitive, and psychosocial development which affects how adolescents feel, make decisions, interact and think about themselves and about the world around them. Global covid 19 has disrupted the mental health of many adolescents developing negative emotions in them. Quarantine and social distancing during the covid-19 pandemic had increased levels of loneliness as well as social isolation, which had produced physical health along with mental health related consequences among adolescents. The purpose of the study aims to explore the prevalence of perceived loneliness in adolescents after Covid 19. The population for the study included students from various schools. The data was collected by a convenience sampling method using google forms with a mean age of 15.5 years. Out of the total 218 responses, avoiding the incomplete responses 204 responses (102 female and 102 male adolescents) were used for this study. The standardized questionnaire of perceived Loneliness scale was used for this study. The collected data were assessed using descriptive statistics and found that the Perceived loneliness mean of female adolescents was 114.40 and of male adolescents was 113.10, which indicates that female adolescents experience a higher range of perceived loneliness than male adolescents. The study concluded that female adolescents experienced an elevated range of perceived loneliness.

Keywords: Female Adolescents, Male Adolescents, Perceived loneliness, Post Covid 19.

Abstract: Body image represents how one perceives their body and acts as the most important part of an individual's image of self. An individual's physical appearance is the first feature that is judged by people when they encounter each other. On the other hand, a notable measure of mental health is one's satisfaction with his or her body image and positive attitude towards the body. Adolescence is the period of transformation of not only the physical aspects but also the psychological aspects, that occurs between puberty and adulthood. Hence, this study intends to examine the relationship between body image and psychological health of adolescents.The data was collected from 200 college-going students aged between 18 to 21 using convenience sampling. The standard questionnaire on body image and mental health were used. The mean score for body image was 59.90, which indicates moderate body image satisfaction and the mental health mean score revealed moderate depression with a mean score of 11.60. The collected data was analyzed using Pearson r (r (199) = -.424, p <.01). The result indicates a significantly negative correlation between body image and mental health among adolescents. Thus, the study concludes that body image and mental health have an inverse relationship.

Keywords: Adolescence, mental health, Body image.

Abstract: In the process of the rapid development of mobile networks, music recommendation systems (MRSs) have experienced considerable success in recent years. Conventional music recommendation systems are, however, in general based on the simple user-track relationships or the content of songs and recommend songs according to intrinsic factors. Furthermore, they do not consider the users' contextual factors towards providing them with a more interpretable, efficient and smart recommendation experience. To address these issues, we propose anovel Heterogeneous Information Network-based Music Recommendation System (HIN-MRS). By considering the extrinsic factors, such as contextual factors, internal factors, such as the user's personalized preference, and the heterogeneous relationship between items of song information, this method can perceive the user's music selection from multiple aspects, automatically maintain the user's playlist and improve the user's music experience. First we used the obtained textual data to extract the user's music preference to provide the topic which is usually related to the contextual factors, by means of which an HIN-MRS can realize the perception of the mobile environment. Second, after determining the topics, we built a small-scale HIN of songs according to topics and used a graph-based algorithm to generate recommendations. The recommendation method based on an HIN renders the recommendation process more efficient and the recommendation results more accurate and increases the user's satisfaction. The results of our final experiments also prove the significant advantages of the proposed model over the conventional approaches.

Keywords: MRS, HIN, SVD, PMF, LDA, SDA, CNN, LRU

Abstract: Image processing techniques have developed as highly effective tools for interpreting medical pictures and assisting in the accurate detection and characterisation of brain cancers. The early detection of a brain tumor is critical for accurate diagnosis and treatment planning. This study gives a thorough examination of the various image processing techniques used in the field of brain tumor identification. The paper goes over the many processes of identifying brain tumors, such as picture capture, preprocessing, segmentation, feature extraction, and classification. The study examines the various approaches and algorithms used in each stage, highlighting their strengths and weaknesses. In addition, current advances, problems, and future possibilities in brain tumor detection utilizing image processing approaches are presented. This review study contains useful information for both scholars and practitioners.

Abstract: Data sharing has emerged as one of Internet of Things' most advantageous cloud computing applications as it has developed. Even if the evolution of technology has been visually appealing, data security is still one of its challenges because improper usage of data can result in a variety of negative effects. We provide a proxy re-encryption method in this paper for safe data exchange in cloud contexts. Identity-based encryption enables data owners to outsource their protected information to the cloud, while proxy reset encryption construction allows authorized users to access the data. Due to the limited resources of Internet of Things devices, an edge device serves as an intermediary in order to handle demanding calculations. Additionally, we successfully distribute cached material in the proxy by using information-centric networking capabilities, hence enhancing the quality of service by making efficient use of the network capacity. Additionally, the foundation of our system concept is blockchain, a ground-breaking technology that permits decentralised data sharing. It achieves very fine regulation of access to data and reduces inefficiencies in centralised systems. The security study along with the assessment of our plan demonstrate the potential of our strategy for guaranteeing data security, confidentiality, and integrity

Keywords: security,integrity, ground breaking technology.

Abstract: The main aim of this paper is to understand the investor's awareness level towards crypto currency, with a special reference to Malappuram District in Kerala. Descriptive research design is adopted to conduct the study and data's are collected from investors who are dealing with various investment options and share trading. Crypto currency investment is an innovative investment instrument most of the investors are regularly dealing with these investments without complete knowledge. The findings are generated is based on the awareness level of investors towards crypto currency in terms of Risk, Return, safety, legal procedure, liquidity, Technology and overall investment objectives. Awareness about crypto currency in terms of these factors highlighted the need for proper awareness system should be followed, improve their knowledge about crypto currency, and take necessary actions to reduce risk and uncertainty in individual level.

Keywords: level of awareness, risk, return, crypto currency, Bitcoin

Abstract: One-third of acute groin injuries are hip flexor-related, yet little is known about the specifics of these injuries. This study aimed to compare particular muscle injuries with reported injury scenarios and use magnetic resonance imaging (MRI) to describe acute hip flexor injuries in athletes with acute groin discomfort. Three sports seasons saw the prospective and sequential inclusion of male athletes with acute groin discomfort. Within 7 days following the accident, an MRI was carried out utilizing a dependable evaluation method and a standardized methodology. Included were all athletes whose acute hip flexor muscle injuries were determined by MRI. A total of 156 athletes-of whom 33 athletes with a median age of 26 years (range, 18-35)-presented with acute groin discomfort. sixteen rectus femoris, twelve iliacus, seven psoas major, four sartorius, and one tensor fascia lathe injuries were reported. Kicking and running were the main causes of rectus femoris injuries while changing directions caused iliacus injuries more frequently. Tendonous damage was seen in 10 (63%) of the rectus femoris lesions. The MTJ was primarily the site of the iliacus and psoas major injuries, two of which contained tendinous damage. In these muscles, we have highlighted specific damage sites that may be important for these injuries' clinical diagnosis and outcome. The majority of proximal rectus femoris injuries also involved tendinopathy. However, different acute iliacus and psoas injuries mostly happened at the MTJ. Only the iliacus or psoas major was injured during a change of direction, whereas rectus femoris injuries occurred primarily during kicking and sprinting.

Keywords: diagnosis; groin pain; hip; iliopsoas; imaging; muscle injuries; rectus femoris; thigh.

Abstract: Object detection is a fundamental task in computer vision that plays a vital role in various applications, including surveillance, autonomous driving and robotics. This journal paper represents an innovative approach to object detection using the YOLOv4 (You Only Look Once version 4) algorithm, aimed at improving visual perception and achieving state-of-the-art results [1][9]. The proposed technique leverages the power of deep neural networks and machine learning to detect and localize objects within an image with remarkable accuracy and efficiency [3]. YOLOv4, as a highly optimized object detection framework, combines advanced techniques such as feature pyramid networks, multi-scale prediction, and enhanced training strategies to enhance detection performance across different object scales and categories. In this study, extensive experiments were conducted using diverse datasets, including commonly used benchmark datasets and custom datasets relevant to specific domains. The performance evaluation of the proposed approach demonstrates its superiority over existing object detection methods, showcasing significant improvements in terms of precision, recall, and mean average precision (mAP) metrics [5] [9]. Moreover, the paper explores the potential applications of the YOLOv4 algorithm, highlighting its effectiveness in real-time object detection scenarios. The algorithm's capability to achieve high processing speeds enables its deployment in resource-constrained environments, making it suitable for various practical applications [4]. The findings of this research contribute to the field of computer vision by presenting an advanced approach to object detection that enhances visual perception and achieves state-of-the-art results. The proposed method utilizing the YOLOv4 algorithm offers improved accuracy, efficiency, and real-time performance, making it a valuable tool for applications requiring robust object detection capabilities.

Keywords: Object detection, YOLOv4, Machine Learning, state-of-the-art results.

Abstract: This study emphasises the importance of design coherence in allowing consumers to comprehend and interact with it meaningfully. The study identifies four essential aspects of coherence design: the employment of consistent elements, the establishment of a strong visual hierarchy, the utilisation of meaningful interactions between pieces, and the provision of user feedback. The advantages of coherence design include improved usability, a better user experience, and more user happiness.

Abstract: A neurological condition called Parkinson's disease (PD) affects 60% of persons over 50. Parkinson's disease (PD) patients struggle with speech impairment and movement issues, which makes it difficult for them to travel for appointments for treatment and monitoring. Early discovery of PD enables treatment, allowing patients to live normal lives. The necessity to identify PD early, remotely, and correctly is highlighted by the world's aging population. The application of machine learning techniques in telemedicine to identify PD in its early stages is highlighted in this research. During the training of 3 ML models, research was done using the MDVP audio data of 195 PD and healthy individuals. When Random Forest classifier, AdaBoost and Decision Tree results are compared, ADaBoost is found to be the best Machine Learning (ML) technique for PD identification. The AdaBoost classifier model has a good f-beta Score. We hope to encourage the use of machine learning (ML) in telemedicine through the findings of this paper, giving Parkinson's disease patients a new lease of life.

Keywords: Parkinson's Disease, MDVP Data, AdaBoost, Random Forest Classifier.

Abstract: The major cause of death worldwide in recent years has been heart disease. This issue is being raised globally as a result of changes in dietary habits, working cultures, and other aspects of daily living. The creation of a technique that can identify early indications and so save many lives is one method for treating and diagnosing this disease. Researchers can estimate the prevalence of heart disease in high-risk groups using machine learning (ML) techniques. For efficient prevention, management and treatment of diseases, it is crucial to create precise and trustworthy approaches for early illness prediction through automation. In previous publications, multiple experts have discussed efforts to create the optimum techniques for predicting heart disease. This study compares three commonly used heart disease prediction methods. These results can be utilised to assist in creating precise and effective models that aid physicians in lowering the count of heart disease fatalities. The cardiovascular systems of three ML algorithms-Logistic Regression (LR), Support Vector Machine (SVM), and Random Forest (RF)-are compared in this study.

Keywords: Logistic Regression, Support Vector Machine, Random Forest, Heart disease prediction.

Abstract: Wireframe design modeling is a crucial aspect of the software and product development lifecycle. It serves as the foundation for creating visually appealing, functional, and user-friendly interfaces across various domains, such as web development, mobile applications, and user experience design. This research paper aims to provide a comprehensive study of wireframe design modeling, exploring its underlying principles, methodologies, tools, applications, and potential future trends. The research draws upon an extensive review of literature, case studies, and expert insights to present a holistic view of wireframe design modeling and its significance in contemporary technology-driven industries. The research begins by exploring the historical evolution of wireframe design, tracing its roots from traditional paper-based prototypes to modern digital frameworks. We delve into the various wire framing techniques and software available to designers, highlighting their strengths and limitations. Additionally, the paper investigates the incorporation of wireframes into different design processes, such as Agile and Lean methodologies, to understand how they facilitate collaboration and iteration. This research paper consolidates the current state of wireframe design, revealing its significance in user-centered product development.

Keywords: wireframe, mockups, modelling

Abstract: Introduction to Cloud Computing and its Significance in the Modern Business Landscape. In today's digital age, cloud computing has emerged as a transformative technology that is reshaping the way businesses operate and deliver services. Cloud computing refers to the delivery of computing resources, including servers, storage, databases, networking, software, and analytics, over the internet on a pay-as-you-go basis. Rather than relying on traditional on-premises infrastructure, organizations can now access and utilize a vast array of IT services through cloud service providers. The significance of cloud computing lies in its ability to offer numerous benefits that empower businesses to become more agile, innovative, and cost-efficient. Some of the key reasons why cloud computing has become indispensable in the modern business landscape include Scalability and Flexibility, Cloud computing allows businesses to scale their IT resources up or down as needed, depending on fluctuations in demand. Whether facing a sudden surge in traffic or during periods of reduced activity, organizations can dynamically adjust their resources to avoid overprovisioning and unnecessary costs. Cost Efficiency, By adopting a pay-as-you-go model, businesses can avoid large upfront capital expenses for hardware and infrastructure. Cloud computing enables predictable and more manageable operational expenses, as organizations only pay for the resources they consume. Global Accessibility, Cloud services are accessible from anywhere with an internet connection. This global accessibility enables distributed teams and remote workforces to collaborate seamlessly, fostering increased productivity and efficiency.

Keywords: Cloud Adoption, Cloud Migration, Multi-Cloud, Hybrid Cloud, Cloud Security

Abstract: Competence stage with grouped tools services, which pertains to a structured system for arranging and overseeing tools and services to boost the development of competency. The study investigates the theoretical underpinnings of competence development, explores the advantages of employing grouped tools services, and showcases a case study to demonstrate its application in a particular field. The results underscore the efficacy of this approach in promoting skill acquisition, facilitating knowledge sharing, and fostering collaboration among individuals and organizations.

Abstract: This paper proposes a new approach to session bearing with runtime graphics. The proposed approach uses a central navigation system to simplify the management of different types of analytical activities, security references, server orientations, network control, domain control, and data references. The central navigation system also provides multiple levels of security and multiple aspects of defined statistics. This allows users to easily control and manage all aspects of their sessions, regardless of their location.

Keywords: Session bearing, runtime graphics, security, network control, data management, central navigation system

Abstract: In this day and age of popular instant messaging programmes, Short Message Service (SMS) has lost importance and has become the domain of service providers, commercial houses, and various organisations that utilise this service to target common consumers for marketing and spamming. Acurrent trend in spam messaging is the use of content in regional language written in English, which makes identification and filtering of such communications more difficult. In this paper, an expanded version of a typical SMS corpus including spam and non-spam texts is used, which is enhanced by the addition of labelled messages. According to local cell phone users, text messages in regional languages like Hindi or Bengali written in English have been utilised. The Monte Carlo method is utilized for learning and categorization in Using a collection of characteristics and machine learning strategies that are regularly employed by researchers. The findings show how different algorithms perform in effectively tackling the given task.

Keywords: Network security, data storage, privacy key, Machine Learning, GCR-MN, CNN

Abstract: The abstract introduces a novel system for managing sensitive projects using business intelligence and separation techniques. This system enables the simultaneous organization of multiple client projects, placing a strong emphasis on automation. It employs a flexible separation technique to recognize individual identities and ensure adherence to specific regulations. The incorporation of triggered activities supports global expansion for organizations and enhances behavioural communication, contributing to the development of unique identities. The system provides systematic references to facilitate guided working, incorporating an inbuilt reporting and allocation system. Various help mechanisms, such as digital knowledge orientation, browsing, and tagging techniques, assist in defining tasks. Users can access data references for situation automation within the structured platform and generate custom reports for efficient navigation. The system's navigational aspects promote cost-effective practices, making it workable across different institutional references and locations. By enhancing privileged deferential process management, the proposed system boosts efficiency and effectiveness for organizations. It empowers them to handle multiple projects simultaneously, automate tasks, and improve behavioral communication. With its flexibility and scalability, the system proves adaptable to various organizational settings, ultimately contributing to better project management and outcomes.

Keywords: Automation, reports, triggered activities, Business Intelligence, data management, Global expansion.

Abstract: This research paper introduces an innovative approach to revaluation panel using dimension analysis, aiming to improve the accuracy and efficiency of data prediction. By harnessing a range of mathematical tools, this method enables the identification and comprehension of diverse dimensions within a dataset. The extracted information is then employed to construct a predictive model, facilitating more reliable value predictions. Compared to conventional techniques, the proposed approach offers several advantages. Firstly, it enhances accuracy by considering the multifaceted nature of the dataset. Secondly, it proves to be highly efficient, especially when dealing with large datasets. Lastly, its transparency empowers the panel to comprehend the model's development process, promoting greater understanding and trust in the results. The effectiveness of the proposed approach is demonstrated through its application to a real-world dataset. The obtained results convincingly establish its superiority in accuracy and efficiency over traditional methods.

Keywords: Dimension analysis, data prediction, predictive model, real-world data, large dataset

Abstract: Cloud computing is the latest technology in today's generation. Cloud computing is growing rapidly nowadays. E-learning is becoming very popular. It is virtual distance learning using the Internet. E-learning usually needs many hardware and software resources, cloud computing isproviding all the facilities which e-learning needs and it is one of the ideal technologies to usein learning. Cloud computing helps students, teachers, researchers, and administrators. In the present education system, it is very difficult for educational systems to provide quality educationfor students. Even if the fracture and facilities provided by the institution are high, it isstill notable to provide quality education and progress. This problem can be solved by the Internet. Cloud computing is used in many fields because it is more advantageous and it is providing many services which are required in every field. Using the cloud all the students, teachers, researchers can easily access any information from anywhere using the internet. Cloud deliversbetter services in educational sectors. Cloud computing is power and it will grow more by providing many benefits. Cloud computing is cost-effective. Companies can use cloud computing for their growth. Cloud computing has a bright future and it provides benefits in many fields. Including educational institutions, many organizations can benefit through cloud computing.

Keywords: Cloud computing, Mobile computing, Distance Education, Database

Abstract: The system is made to be elastic and scalable. It offers dynamic provisioning on-demand and distributes resources across a global network using a number of fog computing approaches. As a result, the system is able to swiftly add or remove resources as needed without compromising the user experience and respond to shifting demand Additionally, the system offers a number of features that enhance productivity and manageability. Users can keep an eye on the system and track performance thanks to integrated dashboards. Users can share data and work together on projects information allocation.

Keywords: On demand utilities, wizards, dynamic provisioning, security and requirements.

Abstract: The importance of livestock management systems has increased recently as a result of concerns about food safety. In addition to inadequate production and food safety, improper livestock management also puts the security of the animals and traceability at risk. Complete documentation for the livestock management system is now required due to the growing problems. In order to handle the cattle effectively, a Graphical User Interface (GUI) will be suggested in this study. Bovine animals are divided into four groups by the GUI: dairying, feedlot- fattening, breeding, and killing. Visual Studio Code(VS Code) will be used to design the GUI.In the context of sound agricultural practise, many farmers today have embraced a variety of strategies to maintain the health and well-being of their cattle. Animal deaths and decreased productivity would result from failing to maintain the health of cattle. Traditional methods, which include recording animal data on paper, are a significant time waster and unsafe, making them ineffective for good farming practise. As a result, electronic-based livestock management systems are required to assist farmers and livestock veterinarians in exchanging information in order to avoid harmful diseases from infecting their cattle before they become serious problems. The project at hand A quick and effective technique has been developed thanks to the widespread use of Radio Frequency Identification (RFID) technology for livestock health management in the creation of animal profiles, but there are a few requirements that must be met, such as the RFID frequency selection and the quantity of animals on the farms. The study has effectively shown the efficiency of RFID technology when it comes to solving common difficulties on farms, despite the fact that using RFID devices in animal raising is not a novel technique in current practise. The development of this monitoring system has made use of integrated methods for reporting and recording animal health records using web-based application platforms like Postgres, Node.js, Express.js and React.js. Additionally, Postgres SQL and JavaScript programming function as scripts.The RFID Based Livestock Health Management System was created utilizing open source software to ensure that system development costs may be minimized as much as feasible. Farmers can now more easily obtain real-time animal health information and share it with other interested parties thanks to the usage of computers and portable RFID readers.

Keywords: GUI, Livestock, VS Code, RFID, Health.

Abstract: In the modern digital era, organizations heavily rely on technology to manage and process sensitive data, making it a prime target for cybercriminals seeking to exploit security vulnerabilities. To enhance the security of organizational data, a novel approach known as "cogent frames" has emerged in security engineering. Cogent frames prioritize clear and concise communication, fostering better understanding between security engineers and stakeholders. This improved communication leads to more informed security decisions. This research paper delves into the study of cogent frames in security engineering, analysing its advantages and the potential challenges during implementation. The findings highlight cogent frames as a valuable asset for bolstering data security within organizations. However, it also stresses the need for a thorough awareness of the challenges involved and a willingness to allocate sufficient resources for successful implementation".

Keywords: Security Engineering, Cogent frames, Security Decision, Security Vulnerabilities, Authentication.

Abstract: For Agriculture 4.0 cyber security, the system, evaluate, and analyse intrusion detection systems. We discuss cyber security risks as well as assessment criteria that were employed in the performance evaluation of an intrusion detection system for Agriculture 4.0. Then, we assess intrusion detection systems in light of upcoming technologies such as cloud computing. Intrusion detection is a critical security issue in today's cyber environment. A large range of strategies based on machine learning methodologies have been developed. So, in order to detect the infiltration, we created machine learning algorithms. A network-based intrusion detection system (NIDS) is often installed at network points such as gateways and routers to detect network traffic intrusions. We deliver a complete report based on the machine learning approach employed. We emphasise the problems and future research areas for Agriculture 4.0 cyber security intrusion detection. IDSs employ artificial intelligence-based approaches such as machine learning and cloud computing to identify harmful conduct. Finally, we can identify the IDS using machine learning and save the observed data in free cloud storage.

Abstract: All the service mechanism, ubiquitous access and utility provisions are offered so that advanced functions can be designed and deployed in accordance with the needs of various organisations. Any required design can be applied in such a way that modification elements can be implemented directly onto the prebuilt pages and resources that are offered. Users even have the option of self-designing, where a variety of component categories are offered that can relate to various aspects of frame designing and database design. A suitably manageable and any form of technological coherence working style need is supported for the materials needed for creating references.

Keywords: service mechanism, self-designing, design and development, database design.

Abstract: Dimensionality reduction techniques play a crucial role in pattern analysis by reducing the complexity and noise in high-dimensional data. However, understanding the impact of dimensionality reduction on pattern analysis can be challenging, as it involves intricate mathematical operations and transformations. This research paper presents a visual journey into data insight by exploring the effects of dimensionality reduction methods on pattern analysis tasks. We propose a novel visualizer that provides an intuitive and interactive interface to facilitate the exploration and analysis of reduced-dimensional data. The visualizer incorporates various visualization techniques, including scatter plots, heatmaps, and interactive projections, to effectively represent the patterns and relationships within the reduced data. Furthermore, we conduct a comprehensive evaluation of popular dimensionality reduction methods, such as Principal Component Analysis (PCA), t-SNE, and UMAP, using real-world datasets. Through our experiments, we demonstrate how the visualizer aids in uncovering hidden patterns, understanding the trade-offs of different dimensionality reduction methods, and assisting in decision-making for downstream pattern analysis tasks. The findings highlight the importance of visual approaches in enhancing the interpretability and effectiveness of dimensionality reduction techniques in pattern analysis.

Keywords: Pattern analysis, dimensionality reduction, visual analysis, scatter plots, heatmaps, interactive projections, PCA, t-SNE, UMAP.

Abstract: The research paper on "Catalog Design and Management" delves into the critical aspects of creating and maintaining effective catalogs to optimize sales and enhance user experience. Catalogs have long been a fundamental tool in marketing and sales strategies, enabling businesses to showcase their products or services to potential customers. In this study, we explore the elements that contribute to successful catalog design, including visual appeal, layout, and branding consistency. We investigate the advantages and disadvantages of both digital and physical catalog formats and analyse their impact on businesses and users. Additionally, we delve into catalog management strategies, addressing the challenges of updating and personalizing catalogs in a dynamic market environment.

Keywords: catalog, analyse

Abstract: The Employee Task Tracking System is web-based technology that enables administrators to register new employees in the design after fulfilling the required authentication procedures. This capability is only available to administrators who have access the structure. Administrators have the ability to use the system to not only create new divisions but also delegate duties to other members of the team. The database needs to contain every piece of information pertaining to staff members, such as their names, addresses, and Social Security numbers. Users of this web application have an easier time managing, documenting, and keeping track of their records as a result of the capabilities that the design provides. With an use of a system known as Employee Task Tracking, businesses are given the ability to control and exercise command over every aspect of their operations. The software design can used to keep information about employees employed by a company, and those employees can be assigned particular duties based upon information that saved in the structure. It is necessary to the proper operation of the design to have an administrator who is capable of entering information on employees, departments, and the responsibilities of their jobs.

Keywords: Employee, task tracking, logistic regression, methodologies.

Abstract: The escalating complexity of cybercrime poses challenges to traditional law enforcement methods. To combat this threat, data analytics has emerged as a promising approach. This paper explores the application of data analytics techniques to analyse the cybercrime underground economy. It examines data sources like publicly available information, dark web data, and cybersecurity incidents. Various methodologies, including machine learning, natural language processing, and anomaly detection, are discussed to identify trends and predict threats. Ethical considerations and successful case studies are also explored. The study highlights data analytics as a valuable tool in understanding cybercrime and devising proactive strategies for threat mitigation, emphasizing the need for collaboration among stakeholders.

Keywords: crimeware-as-a-service, crimeware, hacking, machine learning.

Abstract: In the realm of data management, Master Data Management (MDM) has emerged as a crucial practice for organizations seeking to consolidate, cleanse, and govern their critical data assets. Informatica MDM, a leading solution in this domain, offers both on-premises and cloud-based deployment options. This research paper aims to explore and compare the key differences between Informatica MDM On-premises and Cloud, highlighting their distinctive features and benefits. The paper begins by discussing the fundamental concept of MDM and its significance in data-driven enterprises. Subsequently, it presents an overview of "Informatica MDM", elucidating its core functionalities and highlighting its position as a market leader. The analysis then delves into a comprehensive comparison between the on-premises and cloud deployment models, focusing on critical aspects such as "scalability, flexibility, security, performance, cost, and maintenance". Through an in-depth examination of these factors, this paper wants to give a clear or aims to provide insights into the trade-offs and considerations that organizations must weigh when selecting between Informatica MDM On- premises and Cloud. It concludes by offering recommendations based on specific business requirements and future trends in the MDM landscape.

Keywords: Master Data Management (MDM), Informatica MDM, On-premises, Cloud, scalability, flexibility, security, performance, cost, maintenance.

Abstract: This research paper presents a pioneering approach to incident processing within the realm of business intelligence (BI) by harnessing the potency of artificial intelligence (AI) techniques, with a specific emphasis on association analysis. The efficient handling of incidents is essential for organizations to promptly address issues and make informed choice based on insights extracted from their data. However, traditional incident processing methods often fall short in effectively capturing and leveraging the wealth of information contained within the data. To overcome these obstacles, this paper proposes an AI-based framework that combines machine learning, natural language processing, and association analysis algorithms to enhance incident handling, automate resolution processes, and enable proactive decision-making. The proposed methodology encompasses a comprehensive workflow that encompasses data ingestion, pre-processing, and analysis stages. It integrates AI techniques to detect, classify, and prioritize incidents, leveraging advanced algorithms to identify patterns and correlations through association analysis. Through extensive experimental evaluation, the effectiveness and performance of the AI-driven incident processing framework are examined, providing insights into its superiority compared to traditional approaches. Real-world applications and case studies highlight the practical implications and benefits of this framework, including enhanced operational efficiency, cost reduction, and improved decision-making. The research findings outlined in this paper contribute to the advancement of incident processing in BI, serving as a valuable resource for researchers, practitioners, and decision-makers seeking to leverage AI for more proactive and data-driven incident management.

Keywords: Incident processing, Business intelligence, Artificial intelligence, Association analysis, Machine learning

Abstract: The research paper presents an in-depth study of the "Defect Diary" project, an innovative web application designed to address the challenges encountered in defect management during software development. The primary objective of the application is to provide a centralized platform where users can record and store details about defects along with their corresponding solutions. This facilitates knowledge sharing among software development teams, leading to more efficient defect resolution processes. The research paper elaborates on the planning, design, implementation, testing, and deployment phases of the project, showcasing a well-organized and predictable development process. An exhaustive analysis of the functional requirements of the application is provided in the research paper. Each requirement is thoroughly addressed, offering a comprehensive solution for defect identification, resolution details, related keywords, and more. The paper also explores the user interface design of the application, presenting wireframes and mockups that demonstrate the application's visual appeal and user-friendly nature. Rigorous testing and quality assurance processes were conducted to ensure the reliability and accuracy of the application. Test scenarios and test cases were devised, validating the application's robustness and adherence to functional requirements. Overall, the research paper offers valuable knowledge for software developers, testers, and organizations interested in improving their defect management practices. The "Defect Diary" project exemplifies the successful application of software engineering principles to create a user-centric and efficient defect management solution.

Keywords: Defect Management, Software Development, ASP.NET MVC, C#, Knowledge Sharing, Software Defects, Solution Repository, User-Centric.

Abstract: Encryption technology is a critical component in ensuring the security and confidentiality of sensitive information in today's interconnected world. This research paper presents a comprehensive analysis of how encryption technology facilitates security across various domains. The paper explores encryption algorithms, protocols, and techniques used in secure communication, data protection, access control, and authentication. It examines encryption's role in maintaining the integrity of data during transmission and storage. The challenges and limitations associated with encryption solutions are discussed, along with potential future directions and emerging trends in the field. With the increasing threat of unauthorized access to sensitive data, encryption technology plays a vital role in safeguarding information. The research paper provides an in-depth understanding of encryption principles, including symmetric and asymmetric encryption algorithms, key management, and digital signatures. It explores encryption's application in secure communication through SSL, TLS, VPNs, and secure messaging protocols. Additionally, the paper delves into data protection and confidentiality, examining encryption techniques for databases, files, and disks.

Keywords: Cryptographic technology, security facilitation, secure communication, data protection, authentication, cryptographic algorithms, protocols, access control, data integrity.

Abstract: Data as a Service (DaaS) has transformed data management procedures by allowing businesses to utilize and get access to external data sources via a cloud-based architecture. This study examines the development of DaaS and how it has affected data management. The study looks at the factors that led to the development of DaaS, the technical developments that have aided in its expansion, and how data management has changed in the DaaS era. The study examines the advantages and difficulties of using DaaS solutions and emphasizes the consequences for data governance, data integration, and data quality control. The results help us comprehend how DaaS has developed and how it has revolutionized data management processes.

Keywords: Data as a Service (DaaS), data management, cloud computing, data integration, data governance, data quality management, technological advancements, external data sources, cloud-based model.

Abstract: The research is all about the migration. How the companies, who are working on-prem are migrating to cloud? W hy do they are require to migrate while they are already performing satisfactorily ? Is the migration really necessary?[3] Or Can these companies survive without cloud ? These are the questions answered in this research. To justify the answers and validate the research I have taken the example of well established company "Informatica". If you have had any experience with data, then it is highly likely that you are familiar with Informatica[9]. For individuals, who are not acquainted about it I have given a breif and further also told how it works.

Abstract: Iris recognition is a highly effective and reliable biometric authentication technique, leveraging the unique and stable patterns within the iris. In this research, we present an innovative iris recognition system that harnesses the power of deep learning models and employs image similarity metrics to achieve robust and efficient iris classification. The primary aim of this study is to develop an accurate and rapid iris recognition system suitable for access control and attendance management applications. Through rigorous experimentation, we demonstrate the effectiveness of our proposed approach, showcasing its superiority over traditional feature-based methods. Our results showcase the potential of deep learning, specifically Convolutional Neural Networks (CNNs), in enhancing the accuracy and efficiency of iris recognition, making it an ideal solution for various biometric authentication scenarios.

Keywords: Biometric Authentication, Convolutional Neural Networks (CNNs), Deep Learning-Based Classification.

Abstract: The Default Detect System (DDS) is a comprehensive software program created to make it easier to find, report, and fix software bugs or problems. Throughout the bug lifetime, this approach makes it easier for developers, testers, and stakeholders to collaborate and communicate effectively. DDS has an intuitive user interface that enables users to submit thorough bug reports that include descriptions and prioritization, assuring accurate and transparent statuses of found issues. Delivering high-quality goods is crucial in the quick-paced industry of software development, thus it's important to ensure a seamless and effective procedure. In contemporary development workflows, a default detect system (DDS) is a crucial tool that allows teams to quickly locate, document, and fix problems. This abstract gives a brief description of a ground-breaking DDS that was created to improve user experiences, accelerate development cycles, and foster collaboration.

Keywords: developers, bugs, quick-passed, stakeholders

Abstract: Alzheimer's disease, a prevalent form of dementia, progressively impairs cognition, behavior, and memory, affecting daily functioning due to structural brain changes. While it constitutes a substantial majority of dementia cases, other treatable conditions, such as thyroid issues and vitamin deficiencies, can manifest similar symptoms. This paper presents a machine learning system that employs logistic regression and support vector machines to develop a predictive model for early Alzheimer's disease detection. Using diverse datasets, the model's effectiveness is evaluated using accuracy, sensitivity, and specificity as performance metrics. The project aims to contribute to early detection, enabling timely interventions and improving affected individuals' quality of life. Moreover, the findings may provide insights into Alzheimer's disease mechanisms, facilitating targeted treatments. By emphasizing the significance of diverse datasets and advanced machine learning techniques, this research seeks to enhance Alzheimer's disease understanding and detection, ultimately leading to improved healthcare outcomes.

Keywords: Alzheimer's disease, machine learning, support vector, logistic regression.

Abstract: Effective management of liquidity obligations is a crucial concept that companies must acknowledge for risk analysis and improved positioning. The system is designed to cater to various types of commercial activities and working positioning analysis, allowing for versatile usability. It incorporates multiple overviews, integrating integrity regulations and graphical conversion stages to offer optimal references for better understand ability. The system facilitates controlled transactions through a variety of features and includes inbuilt formats to manage commercial work-ability. Financial and company settings are incorporated, each with their own default references and gateways, enhancing credibility and security for the commercial analysis and viability. Capitalization and comparative enforcement analysis are provided, empowering users to better control statistical formations and strategically plan organizational activities. The system also supports planning recommendations, situational analysis, stability planning, and measures for acknowledging hypotheses, all contributing to a cost-effective understanding for organizations utilizing the system.

Abstract: Content-based Image Recovery (CBIR) techniques have undergone substantial research given the development of digital photographs. CBIR services are often highly expensive in terms of computational and storage costs. Therefore, choosing to outsource CBIR service to a cloud server with a lot of resources is a wise decision. However, since the cloud server cannot be completely trusted, privacy protection becomes a significant issue. In this study, we suggest a CBIR outsourcing strategy. based utilizing a brand-new bag-of-encrypted-words (BOEW) architecture. Through color value replacement, block permutation, and intra-block pixel combination, the picture is encoded. The cloud server then uses the encrypted information to generate local histograms. picture blocks. The cluster centres are employed as the encrypted visual words, and all of the Regional graphs grouped together. The bag-of- Pattern for coded words (BOEW) constructed in this manner A characteristics vector format or a normalized histogram of the encrypted visual words, that represents each image. The distance at Manhattan between vectors of features on a remote platform may be used to directly evaluate picture similarity. The suggested scheme's safety and precision of searches are demonstrated based on research findings and safety analysis.

Keywords: BEOW, CBIR, Digital Images, encryption

Abstract: The "Media-Based Subliminal Technology Provider" is a cutting-edge company specializing in the development and deployment of advanced subliminal technology for various media platforms. Through the use of subtle visual or audible cues, this technology uses people's actions, attitudes, or perceptions to its advantage-often without their knowledge. The company's area of expertise is creating and disseminating customized subliminal messages via television, radio, web content, and other multimedia platforms.

Keywords: media, subliminal

Abstract: The Smart Helmet System is an innovative and intelligent wearable technology designed to enhance safety and protect individuals working in hazardous environments. This advanced system integrates cutting-edge sensors, communication modules, and data processing algorithms to detect and mitigate potential risks effectively. The helmet's embedded sensors monitor various environmental parameters, such as temperature, gas concentration, and sound levels, to identify potential dangers. Real-time data is transmitted to a centralized control unit, enabling timely alerts and ensuring swift responses in critical situations. The Smart Helmet System not only reduces the risk of accidents but also promotes proactive safety measures and contributes to a safer work environment overall.

Keywords: Smart Helmet System, Hazardous Environments, Wearable Technology, Safety Enhancement

Abstract: Information security awareness serves an important part in safeguarding organizations and individuals against a multitude of cyber threats and data breaches. Despite the fact that many attempts have made to improve information security awareness programs, many still struggle to effectively engage users and instill a strong security-oriented mindset. This study proposes an interpretive framework for information security awareness that aims to enhance the effectiveness and impact of awareness initiatives.When it comes to security references, they are categorized based on various factors such as data protection, data transfer, accessibility, compatibility, and compliance with environmental regulations. These categorizations help users establish their own references with clear and understandable guidelines. Multiple types of project references can be created, and various portal references can be defined to cater to different requirements. The system also allows for the establishment of different user types, ensuring that technical aspects are well-defined and easily managed. Additionally, the system supports all types of control systems, and reports in depth are given for better insights.The portal definitions are properly structured and segmented, allowing organizations to identify and implement their own security preferences and working preferences while utilizing the system on the service.

Keywords: Safeguarding, Cyber threats, Data breaches, Awareness programs.

Abstract: This research paper presents a comprehensive investigation into implementing data protection measures in cloud services through a Third-Party Administrator (TPA). As cloud technology adoption grows, data security becomes a major concern for organizations. The TPA model offers a promising solution, acting as an independent entity responsible for deploying robust security mechanisms. The study starts with an extensive analysis of current data protection in cloud services, identifying potential vulnerabilities and threats. By examining existing security protocols and best practices, the research develops a well-structured framework seamlessly integrating the TPA into the cloud infrastructure. Collaboration with cloud service providers and security experts is crucial. The TPA is granted access to monitor and manage security, complemented by regular audits for continuous data protection. Transparency and trust-building are emphasized. Clearly defined roles and responsibilities instill confidence in data owners. Compliance with data protection regulations and industry standards mitigates legal and reputational risks. The proposed approach's efficacy is rigorously evaluated through extensive testing and simulations of various security scenarios. Analyzing the TPA's responses to potential threats assesses its ability to safeguard data in real-time.

Abstract: According to research findings, data deduplication is a highly effective data compression method used in cloud storage to eliminate duplicate instances of recurring data, thereby conserving storage space and bandwidth. To ensure the confidentiality of sensitive data while enabling deduplication, a convergent encryption approach has been developed for encrypting data before outsourcing. Our study represents the first explicit effort to address the concept of authorized data deduplication, aiming to enhance data security. Unlike traditional deduplication systems that solely focus on the data itself, our analysis takes into account the varying privileges of users during duplicate checks. Furthermore, we propose several innovative deduplication architectures that facilitate authorized duplicate checks in a hybrid cloud setup. Based on our research and security analysis, this approach aligns with the most secure practices defined in the proposed security model.To validate our proposal, we implement a prototype of the authorized duplicate check mechanism and conduct testbed tests. The results demonstrate that our method introduces minimal overhead compared to standard operations.

Keywords: deduplication, convergent encryption, privileges, data compression, cloud storage.

Abstract: Cloud computing has emerged as a powerful paradigm that provides scalable, flexible, and cost-effective solutions for handling vast amounts of data storage, processing, and accessibility. As cloud services gain increasing adoption among businesses and individuals, the paramount concern becomes data security. The "Data Security Model for Cloud Computing" project has been devised to tackle the critical challenges of safeguarding sensitive information stored and processed within cloud environments. This research project introduces a comprehensive data security model meticulously designed to ensure the confidentiality, integrity, and availability of data in cloud computing environments. The proposed model encompasses multiple layers of security measures, addressing both technical and administrative aspects to shield data from unauthorized access, data breaches, and other potential threats. The first layer concentrates on access control mechanisms, employing Role-based access control (RBAC) and attribute-based access control (ABAC) to restrict data access solely to authorized users. Additionally, multi-factor authentication (MFA) is integrated to add an extra layer of security, mitigating the risk of unauthorized access due to compromised credentials. The second layer emphasizes data encryption techniques, securing all data at rest, in transit, and during processing using robust encryption algorithms. This ensures that even if an unauthorized entity gains access to the data, it remains incomprehensible without the appropriate decryption keys. The third layer centers on data integrity and auditing, utilizing digital signatures and hashing algorithms to verify data integrity, enabling prompt detection of any unauthorized modifications to data. Regular audits are conducted to monitor and analyze user activities, facilitating the timely identification of potential security breaches. The fourth layer addresses physical security at the data centers, implementing access controls, surveillance systems, and intrusion detection mechanisms to safeguard the physical infrastructure hosting cloud services. The fifth layer focuses on security in virtualization and isolation, deploying hypervisor-based virtual machine isolation and containerization technologies to ensure a strong separation between different cloud tenants, effectively preventing data leakage between them. Furthermore, the proposed data security model thoroughly considers legal and compliance aspects by examining data residency and data sovereignty regulations, ensuring data is stored in compliant locations and adheres to relevant laws. To validate the effectiveness of the proposed model, a prototype implementation is developed and tested in a simulated cloud environment, conducting extensive performance evaluations to assess the overhead introduced by security measures and optimize the model for real-world cloud deployments. In conclusion, the "Data Security Model for Cloud Computing" project presents a robust and holistic approach to address the data security challenges associated with cloud computing. By integrating access controls, data encryption, data integrity verification, physical security measures, and compliance considerations, the model aims to instill confidence in cloud users regarding the protection of their sensitive data. As cloud adoption continues to grow, this research serves as a valuable contribution to enhancing data security and trust in cloud computing environments.

Keywords: Data Security, Cloud Computing, Model, Confidentiality, Integrity, Availability, Access Control, Role- Based Access Control (RBAC), Attribute-Based Access Control (ABAC), Multi-Factor Authentication (MFA),Data Encryption, Encryption Algorithms, Data at Rest, Data in Transit, Data Processing, Digital Signatures, Hashing Algorithms, Auditing, User Activities, Security Breaches, Physical Security, Data Centers, Virtualization, Isolation.

Abstract: The rapid growth of data sharing and exchange in various applications has brought forth significant concerns regarding data privacy and security. Malicious data publishers pose a serious threat to sensitive information, jeopardizing data integrity and confidentiality. To address this issue, this research paper presents a novel framework for "Sanitizable Access Control Against Malicious Data Publishers" that enables data recipients to effectively sanitize and filter data received from untrusted sources.The proposed system leverages cryptographic techniques and access control mechanisms to provide a secure and flexible environment for data sharing. Data encryption and sanitization techniques ensure that sensitive information remains protected even when handled by malicious publishers. Trust management and verification mechanisms authenticate the identities of data publishers and recipients, preventing unauthorized access. The sanitizable access control model is designed to empower data recipients with the ability to dynamically enforce access policies, enabling them to adjust data sanitization levels based on trust evaluations and the intended use of the data. Furthermore, an audit trail mechanism is implemented to track data access, usage, and modifications, ensuring accountability and transparency.

Keywords: Sanitizable Access Control, Malicious Data Publishers, Data Integrity

Abstract: The role of a Global Commercial Domain Designer has emerged as a critical component in today's rapidly evolving global business landscape. As companies seek to expand their reach beyond traditional borders, the Global Commercial Domain Designer plays a vital role in identifying and analyzing new markets with growth potential. This abstract provides an overview of the concept of a Global Commercial Domain Designer and its significance in strategic decision-making for targeted market expansion. In the digital age, businesses face unprecedented opportunities and challenges in reaching a global customer base. The Global Commercial Domain Designer serves as a key facilitator in this endeavor, responsible for conducting market research, analyzing consumer behavior, and assessing competitive landscapes to identify untapped opportunities in international markets. Cloud computing also facilitates real-time collaboration and communication among global teams, thereby streamlining the market entry process and enabling businesses to make agile, data-driven decisions. The Global Commercial Domain Designer leverages cloud-based collaboration platforms to work seamlessly with cross-functional teams across diverse time zones, enhancing the efficiency and effectiveness of the global market expansion strategy.

Keywords: Global Scale, security facilitation, potential growth, collaboration, secure communication.

Abstract: This research paper presents the design and development of a Software Wizard Design for Applications system aimed at providing organizations with advanced customization and robust security features. The SWDFA system incorporates user-friendly interfaces and step-by-step wizards to facilitate easy navigation and utilization for various activities, making it a cost-effective and efficient solution. Additionally, the system ensures comprehensive notifications, remote accessibility, and mobile access, enabling adaptability to different environments. To guarantee a highly secure infrastructure, the SWDFA system implements identity access management, data protection measures, and threat detection capabilities. The research also explores the collaborative nature of the SWDFA system's design process, enabling reliable and scalable work environments for multiple users. Furthermore, the integration of cloud references and platforms enhances usability and accessibility, making the SWDFA system a comprehensive tool for organizations seeking enhanced productivity and security.

Keywords: dvanced customization, Robust security features, Comprehensive notifications, Remote accessibility, Mobile access, User-friendly interfaces.

Abstract: This research paper presents a comprehensive study on the application of Support Vector Machine (SVM) for Hepatitis disease diagnosis and prediction. The proposed SVM-driven model achieves a remarkable accuracy of 96% in predicting Hepatitis with a minimum mean square error. Additionally, the potential integration of Convolutional Neural Networks (CNN) for anticipating the occurrence of various diseases is discussed, pointing towards future research directions in this area

Keywords: Hepatitis, disease diagnosis, prediction, Support Vector Machine (SVM), Convolutional Neural Networks (CNN)

Abstract: This paper introduces an Organization Optimization System (OOS) that integrates machine learning (ML) and Python programming to efficiently host various activities, including campaigns, competitions, and other events involving multiple organizations. The system utilizes data-driven decision-making to streamline resource allocation, enhance participant engagement, and maximize outcomes. This paper presents the architecture, key components, and implementation details of OOS, along with case studies showcasing its effectiveness in optimizing organization-hosted activities. Organizations worldwide are facing unprecedented complexity, technological advancements, and increasing competition, necessitating a structured approach to enhance efficiency, productivity, and overall performance. The proposed framework amalgamates various organizational aspects, including leadership, culture, processes, technology, and human resources, into a cohesive system for sustained success. The research encompasses both theoretical insights and practical case studies, offering valuable guidelines to leaders and decision-makers seeking to optimize their organizations.

Keywords: Organization Optimization, Leadership, Culture Processes Technology Human Resources Efficiency

Abstract: Application called "Evergreen" makes it possible for farmers to use the best methods for organic farming. Crop rotation, green manure, compost, and biological control are all covered in a piece on Evergreen that offers techniques and facts. The application analyzes clickstream information to assess the enterprise's performance as a channel-to-market. It is interested in the pages that customers spend the most time on, the things they add to or remove from their shopping carts, and the products they buy. People use a specific pattern to browse through applications based on their interests, so they can view the internet pages that speak to them. The visitor's path is known as their clickstream. The "Evergreen" application's primary goal is to make it simple for farmers to get information about various plant types, growing suggestions, purchasing plants, and current events using mobile platforms. When consumers shop, they prefer to do so online since they can easily compare prices between different retailers. It is important to have a solid understanding of users' purchasing and browsing habits on e-commerce applications so that online retailers can make their system more user-friendly and beneficial as the number of websites grows. One such method is the prediction of user purchase of a specific product. Analyzing users' surfing habits, which largely reveal their interests, is one of the traditional methods of collecting user data. clickstream data that show the browsing routes, frequency of visits, and amount of time spent per category based on the clickstream data counting the number of users online, analyzing user buying behavior to predict the likelihood of a purchase as well as visualize the overall user pattern. The click stream data is analyzed to identify different paths taken by the visitors and the sequence of pages that lead to payment. According to this analysis, the application includes overall organization transaction visualization, specific category sales visualization (history), SMS -based user interaction, GPS-based user interaction using users' order history, click-based user interaction, category-based sales data visualization, and category-based user interaction using Google Analytics. To maximize the revenue for the website, particular, visualization techniques for the ratio of live users to applications are advised.

Abstract: The primary objective of designing this informatics system is to enable automation and facilitate seamless integration with various platforms. It allows for the utilization of multiple types of base maps, catering to different reference styles for exploration and providing various layer information preferences. The system is tailored for an embedded architecture, where objects are designed with multiple layers and can be easily transferred to different platforms and machines. The embedded architecture operates intelligently to perform diverse tasks based on specific conditions. One of the key features of the system is its compatibility for establishing multiple layer modifications and reusability, allowing for the execution of various operational tasks. Real-time analysis can be applied through multiple projections, enabling the use of maps according to specific situations and requirements. The system incorporates information analysis and projections based on scientific models, facilitating direct resource extraction using third-party resources. Moreover, the system can identify different heights of physiographic contributions, ensuring accurate information mapping of Legends and exploratory digitalization objects. These objects can be customized with different sets of information using conditional setups. The system operates with shared intelligence, ensuring effective information transition when embedded. This capability supports real-time automatic activities and recognition. Overall, the system aims to streamline automation and enhance the efficiency of information processing and analysis.

Keywords: Real-time Projections, Exploration, Resource Extraction

Abstract: Social media sites are used by millions of individuals all around the world. Users' interactions with social media platforms such as Twitter and Facebook have a significant impact on their daily lives, with occasionally negative effects.The majority of social media platforms have become a platform for fraudsters to transmit a significant number of worthless and dangerous stuff. For example, Twitter has become widely accepted all platforms time, allowing an excessive amount of spam. Unwanted tweets are sent to customers in an attempt to market services, which not only harms genuine users but also disrupts resource utilisation. Furthermore, the capability for distributing misleading information offered to customers under false pretences has expanded, allowing harmful content to propagate. Identifying spammers and recognising a phoney Twitter accounts have lately been a major topic of research in modern online social networks (OSNs). In this paper, we look at methods for detecting spammers. A taxonomy for recognising Twitter spam approaches is also provided, which categorises the tactics based on their ability to detect: (i) bogus material, (ii) spam based on URL, (iii) spam in hot subjects, and (iv) phoney users.

Keywords: Social media, Spammers, OSN, Twitter, Fraud.

Abstract: Machine Learning has recently played an important part in the healthcare business, and among all of the major diseases, sentiment ailment is one of the furthermost crucial and vital diseases to forecast. The quantity of instances is rapidly increasing every day. Because it has been initiate that four individuals amongst the ages of 30 and 50 have a stroke every minute, we are spread over appliance scholarship procedures to alleviate this problem. The heart disease dataset was utilised by Kaggle for this project. This research examines and displays employing a variety of machine-learning categorization techniques, such as naive Bay Probabilistic Forest, and SVM, in identifying cardiovascular conditions, and others. Later on, the Stacking Ensemble Learning Technique is utilised to progress the routine of our classification models. Cardiology, Data Analysis, Data Mining, Diseases, Pattern Classification, Support Vector Machine, Heart Disease Prediction, Artifical Nueral Network (ANN).

Abstract: The agricultural sector significantly contributes to the nation's overall economic progress and advancement. The Agricultural Technology system is currently confronted with a multitude of challenges arising from the phenomenon of climate change. Machine learning (ML) has emerged as a highly efficient approach to addressing problems by generating effective and valuable solutions. Crop yield prediction involves calculating a crop's production by analyzing available facts and considering diverse aspects, such as weather circumstances, soil quality, water availability, and temperature. This study investigates and establishes the application of the Linear Regression methodology for the purpose of forecasting agricultural yield by utilizing historical data from prior years. The primary goal of this project is to determine a solution for addressing the challenge of financial loss. The models are constructed utilizing authentic agricultural data and subjected to testing by representative samples. The crop yield prediction model aims to support end users, specifically farmers, in forecasting crop yield before engaging in crop cultivation on agricultural land. The Linear Regression Machine algorithm is employed to predict precise outcomes. The existence of a substantial dataset will facilitate the enhancement of the decision-making model.

Keywords: Crop Yield Prediction, Cultivation, Environment, Estimation, Factors, Linear Regression Technique

Abstract: The proposed IDS model is aimed at detecting network intrusions by classifying all the packet traffic in the network as benign or malicious classes. The Canadian Institute for Cyber security Intrusion Detection System (CICIDS2017) dataset has been used to train and validate the proposed model. The model has been evaluated in terms of the overall accuracy, attack detection rate, false alarm rate, and training overheadDDOS attacks based on Canadian Institute for Cyber security Intrusion Detection System (KDD Cup 99) dataset has been used to train and validate. We are used for comparison for 2 dataset (CICIDS2017 and KDD Cup 99 ) Then, we have to implement the Deep learning algorithms is Proposed Method Classification Using LSTM algorithm Model predict .Testing dataset for anomaly detection model finally classified attack or normal. Finally, the experimental results shows that the performance metrics such as accuracy, precision, recall and confusion matrix.

Abstract: This study aimed to design, develop dress pattern maker software and evaluate its functionality, accuracy, performance efficiency, and usability. The study was subjected to a technical presentation of a group of technical experts in the field of computers and the dress-making industry was invited to scrutinize the functionality of the study. The system was also subjected to its final evaluation by computer programmers, dressmaking teachers from the academe, practitioners in the industry, as well as dressmaking students for its acceptability. The data-gathering instrument used to evaluate the system was adopted from ISO/IEC 25010 questionnaire and a researcher-made questionnaire that passed the validity and reliability requirements. Data gathering was made online in compliance with the COVID-19 Health and Safety protocols. The testing and evaluation of the software had been conducted from May 26 to June 15, 2021, by the nine (9) dressmaking teachers, seven (7) practitioners, and the fourteen (14) fashion students at Antique, Capiz, Iloilo City, and Iloilo Province Region VI-Western Visayas. The mean average and t-test were used in the interpretation of data based on the criteria on the parameters of the study. The design of the software was made up of computer programs. In the programming language that was used is Visual C#, the Graphics class provides methods for drawing objects to the display device. Many different shapes and lines can be drawn using a Graphics object. These methods include DrawLine, DrawArc, DrawClosedCurve, DrawPolygon, and DrawRectangle. The system was designed to generate a digital system of making dress patterns that will replace the conventional way of making dress patterns. The system produced an accurate and efficient way of drafting the pattern of the front blouse, back blouse, front skirt, back skirt, set-in sleeve, and sports collar. The evaluation revealed that the device was highly acceptable to the respondents in terms of its functionality, accuracy, performance efficiency, and usability. The self-instruction module was highly acceptable in terms of content, organization, presentation, and assessment as evaluated by the end users.

Keywords: dress pattern maker, self-instruction module, dressmaking

Abstract: Problem solving requires analytical reasoning skills and comprehension. It is sometimes difficult to solve a problem due to misrepresentation of words problem. Thus, visual representation is an important factor in problem solving. This research determined the effects of the Concrete-Pictorial-Abstract-Approach on the Mathematics Problem Solving Performance of the First Year Bachelor of Industrial Technology students at Capiz State University, Main Campus. This study employs quasi-experimental research design, the matching only of pre-test and post-test of the experimental and control group. There were fifty-two (52) participants coming from two (2) different sections, twenty-six (26) of whom were the experimental group and the other twenty-six (26) were the control group. The research instrument used is a researcher made test in Mathematics problem solving validated by three experts in Mathematics teaching, and pilot tested at Capiz State University, Main Campus. The instrument underwent reliability test and the result show a reliability index of 0.76 Cronbach alpha. Descriptive statistics was aided by frequency, mean, and percentage standard deviation and mean gain while the inferential tools were the t-test for independent samples and Wilcoxon Signed Rank Test for related samples. All levels of significance were set at 0.05 alpha. Descriptively the pre-test of the mathematics problem solving performance of the two instructional groups was "low". The post-test of the mathematics problem solving performance of the experimental was "high" while the control group instructions was marked average. Mathematics problem solving performance mean gain of the experimental group showed development from "low" to "high". The inferential analysis revealed that there were no significant differences in the pre-test scores of the two groups of mathematics problem solving performance.

Keywords: quasi-experimental, block model approach, visualization

Abstract: The development of strategies in education is the main backbone of teaching and learning process between students and teachers to measure the desired task. The primary objective of this descriptive-correlational study was to develop a welding tool storage organizer on wheels and determined its level of acceptability and the usability of its different features. The device was evaluated by the 30 teachers and 30 welders/ shop owners. The level of competency-based performance of the 30 students who used the developed welding tool storage organizer was also determined for School Year 2022-2023. Moreover, the study determined if there were significant relationships among the level of acceptability and usability of the different features of the developed welding storage organizer as evaluated by teachers and welders/shop owners and the level of competency-based performance of the students using the developed welding tool storage organizer. The study was conducted at selected schools in the Division of Capiz, Division of Roxas City, and Capiz State University where the respondents. The shop owners who evaluated the acceptability and usability of the developed welding tool storage organizer on wheels were also from the selected welding shop in the province of Capiz. For the students' respondents, measuring their competency-based performance, the study was conducted at Sapian National High School, School Division of Capiz. The research instrument used by the researcher was a survey questionnaire/evaluation sheet to determine the acceptability and usability of the product. The statistical tools utilized in this study were the percentage, mean and Pearson product -moment correlation for the inferential question which was set at .05 alpha level. The data were analyzed using the Statistical Package for Social Science (SPSS) Software. The findings of the study revealed that developed welding tool storage organizer on wheels was "very acceptable" as evaluated by the teachers and welding shop owners. The device as also "very usable" as evaluated by the teachers and welding shop owners. The students who used the developed welding tool storage organizer were "very competent" in their competency-based performance. Finally, there were no significant relationship among the acceptability and usability of the developed welding tool storage organizer and the level of competency-based performance of the students. Works Cited: GEORGE B. GALLENA, MAIED " ACCEPTABILITY AND USABILITY OF THE DEVELOPED WELDING TOOL STORAGE ORGANIZER ON WHEELS AND STUDENTS' COMPETENCY-BASED PERFORMANCE", IARJSET International Advanced Research Journal in Science, Engineering and Technology, vol. 10, no. 7, pp. 663-670, 2023. Crossref https://doi.org/10.17148/IARJSET.2023.107110

Abstract: Currently, the risk of network information is high. Insecurity is rising in both quantity and severity. Hackers' most popular tactics nowadays are to target end-to-end technology and exploit human weaknesses. Approaches include social engineering, phishing, and pharming. The use of malicious Uniform Resource Locators (URLs) to deceive users is one stage in carrying out these assaults. As a result, malicious URL detection is gaining popularity. Several scientific studies employing machine learning and deep learning approaches have been published, demonstrating a range of methods for identifying malicious URLs. In this paper, we present a machine learning-based malicious URL detection technique based on our hypothesized URL behaviors and attributes. In addition, Bigdata technology is being utilized to improve the identification of harmful URLs based on anomalous behavior. In summary, the proposed detection system consists of a novel set of URL attributes and behaviors, a machine learning algorithm, and bigdata technologies. The testing results indicate that the proposed URL characteristics and behavior can significantly improve the ability to detect malicious URLs. The proposed approach should be regarded as an optimized and user-friendly solution for dangerous URL detection.

Keywords: URL; malicious URL detection; feature extraction; feature selection; machine learning

Abstract: Biscuits are often branded as a nutritious and convenient way to consume a staple food or cereal grain. The products of this study were evaluated as to sensory qualities and acceptability in terms of appearance, aroma, taste, texture, and crispness. Significant differences in the sensory qualities and acceptability were also determined. Proximate and microbial analysis of the best treatment was submitted and the shelf-life and temperature were also studied. The study was an Experimental-Developmental research with the used of Completely Randomized Design (CRD). The study was conducted in three trials and one (1) final process for consumers' evaluation by the sixty (60) tasters. Scorecards with the Nine (9) Point Hedonic Scale were used to obtain the data. The Arithmetic mean and Analysis of variance (ANOVA) were used to analyze the data into alpha level set at 0.01. Findings on the sensory evaluation of root crop biscuits with green leafy vegetables showed that cassava flour with kulitis was the best in all five quality attributes. The acceptability of root crops biscuits with green leafy vegetables among the three products was in favor in cassava flour with kulitis which was "Liked Extremely" by the consumers across all qualities. There were no significant differences in the sensory qualities of the root crop biscuits considering the three products. There was a significant difference in five quality attributes the appearance, aroma, taste, texture and crispiness in favor of Cassava with Kulitis. The maximum shelf-life of root crop biscuits with green leafy vegetables at room temperature was fifteen (15) days and thirty (30) at chilling temperature. Therefore, the root crop biscuits with green leafy vegetables was safe for human consumption as the results of microbial analysis of the product and based on the BFAD standard for microorganism test for products belonging to the baked goods category.

Keywords: Product Formulation, Analysis, Shelf-life, Biscuits, Root Crops and Green Leafy Vegetables

Abstract: Drying is a mass transfer process consisting of the removal of water or another solvent by evaporation from a solid, semi-solid, or liquid. This process is often used as a final production step before selling or packaging products. Dried Kulitis leaves can be used as tea, use for cereal, and cookies too. This study determined the extent of the utilization of dried kulitis (Amaranthus spinosus) leaves for varied food products. The products were evaluated as to sensory qualities and acceptability in terms of appearance, aroma, taste, and texture. Significant differences in the sensory qualities and acceptability were also determined. Microbial and proximate analysis of the best treatment and the shelf-life were also studied. The study used the Experimental-Developmental method of research using a Completely Randomized Design (CRD). It was conducted in three (3) products with different treatments with three trials. The sensory qualities were evaluated by ten (10) semi-trained panelists and the acceptability of the products were evaluated by seventy (70) consumers. Scorecards with the Nine (9) Points Hedonic Scale was used to obtain the data. The mean and Analysis of variance (ANOVA) were used to analyze the data into alpha level set at a 0.01. The sensory qualities of the varied food products with dried kulitis leaves were evaluated by semi-trained panelists with three (3) different treatments. Kulitis tea with a combination of lemon and ginger for Product A got a very much clear and sparkling, very much pleasant, very much delicious, and very much smooth in terms of appearance, aroma, taste, and texture. Kulitis bar cookies with sweet potato for product B got very much appealing, extremely pleasant, extremely delicious, and very much crisp. Kulitis cereal with sweet potato for product C got a very much appealing, extremely pleasant, extremely delicious, and extremely soft and intact as evaluated by semi-trained panelists. The consumers' acceptability of varied food products with dried kulitis leaves considering the sensory qualities that all the products of dried kulitis leaves were Liked Very Much as evaluated by seventy (70) consumers, however, product C (Kulitis bar cookies) got the highest result in all quality attributes. There was no significant difference found in the sensory and consumers' acceptability of varied food products with dried kulitis leaves among the three treatments. Shelf-life of the varied food products with dried kulitis leaves when stored at room temperature could last for 2 weeks with no changes in the sensory attributes when sealed completely. Likewise, the microbial analysis of the best treatment of cereal flakes with dried kulitis got a result of Aerobic Plate Count <250 cfu/g sample, Total Coliform Count <1.8 MPN/g sample, and Molds and Yeast Count <10* cfu/g sample based on the BFAD reference criteria. Moreover, cereal flakes with dried kulitis leaves were safe for human consumption as the results of microbial analysis of the product and based on the BFAD standard for microorganism tests for products belonging to the baked goods category.

Keywords: Drying, Dried Kulitis Leaves, Cereal Flakes, Cookies, and Tea

Abstract: These days, using matrimonial services might help people to discover their true partner. The popularity of fake accounts on these platforms, however, has intensified into a significant issue for both users and service providers. The detection of fraudulent profiles is a critical problem for the reliability and validity of marriage services. The method outlined in this article makes use of AI to identify fake matrimonial site profiles. The technology uses machine learning algorithms to identify and report problematic accounts. The recommended strategy can improve the reliability and validity of websites that deal with marriage by lowering the likelihood of fraudulent activities.

Abstract: Taro stalk kimchi is a dish made from the stalks of taro plants that have been fermented with various seasonings. While kimchi is typically associated with cabbage, taro stalk kimchi offers a unique and distinct flavor profile. The products of this developmental-experimental study were evaluated as to sensory and acceptability qualities in terms of appearance, aroma, taste, and texture. Significant differences in the sensory qualities and acceptability were also determined. Proximate and microbial analysis of the best treatment was submitted and the shelf-life was also studied. The study used the Completely Randomized Design (CRD) and was conducted in three replications and one (1) final process for consumer preference evaluation by one hundred (100) tasters. Scorecards with Nine (9) Point Hedonic Scale were used to obtain the data. The mean and analysis of variance (ANOVA) were used to analyze the data with the alpha level set at 0.01 for the inferential test. Treatment A (Abalong) Kimchi was extremely appealing, extremely pleasant, extremely delicious, and extremely crunchy. Treatment B (Gabi China) was extremely appealing, extremely pleasant, extremely delicious, and very much crunchy. Treatment C (Gutaw) was very much appealing, extremely pleasant, very much delicious, and very much crunchy. Abalong, Gabi China, and Gutaw stalk kimchi were liked extremely by the consumers with Gabi China kimchi getting the highest results in all quality attributes. There was no significant difference in the sensory qualities of the taro stalk kimchi among the treatments in terms of appearance, aroma, taste, and texture. Moreover, there was no significant difference in the acceptability of taro stalk kimchi among the treatments considering the sensory qualities. The shelf-life of the Gabi China stalk kimchi when stored at room temperature was seven (7) days and six (6) months when sealed well. The taro kimchi was safe for human consumption based on the results of microbial analysis of the product and based on the BFAD standard for microorganism test for products belonging to the fermented vegetables ready to eat.

Keywords: Taro Stalk, Taro Corm, Kimchi, and Shelf-life

Abstract: Birds are an integral part of our ecosystem and play a key role in maintaining nature. The use of drones poses a serious threat to birds. Drones can disturb bird populations and cause damage and possibly death. Drones have the potential to cause serious damage to the ecosystem and bird habitats. The development of a system capable of accurately identifying and categorizing drones and birds is essential to reducing this risk. The YOLOv4 and YOLOv5 models are going to be utilized in the construction of the model that we intend to develop for this project, which is going to be able to identify drones as well as birds. This is because the use of drones provides a considerable threat to bird populations. Once the models have been trained, we will first determine how well they did on a test set, and then we will determine how well they did on a validation set. It is of the highest significance to develop a system that is capable of precise detection and classification of both drones and birds in light of the growing frequency of the use of drones, which constitutes a substantial threat to bird populations. The performance of the YOLOv4 and YOLOv5 models will be assessed for the purpose of detecting birds and drones, and the model that has the best overall performance will be chosen as the winner of the competition. The accuracy of this model is 94% it is estimated according to whether an object in question is a bird or a drone.

Keywords: YOLOV4, YOLOV5, CNN.

Abstract: It is necessary to have an awareness of the child's personality in order to comprehend the child's emotional and social development. However, traditional methods of evaluation, such as questionnaires, observations, and interviews, may be laborious, subjective, and pricey. An automated system for assessing a child's personality based on their emotional speech may be created with the help of convolutional neural networks (CNN), which is the approach that was recommended. The system will analyse a child's emotional speech in order to draw conclusions about the child's personality traits. When compared to more traditional methods of assessing personality, the system will need significantly less time and will produce more accurate results.

Abstract: Carbon nanotubes (CNTs) are cylindrical allotropes of carbon. They were discovered in the year 1991 and they have a unique structure. Due to the huge production and applications of carbon nanotubes, they have attracted many industries and companies towards themselves as they are used in nanotechnology, membranes, capacitors, polymers, metallic surfaces, ceramics, nanomedicine etc. The main motive of this paper is to highlight the basic adsorption capacity of the Carbon nanotubes, and it also reveals that the thermal and chemical stability make them suitable materials as new stationary phases and pseudostationary phases. And also for adsorbents in solid-phase extraction (SPE) and solid-phase microextraction (SPME). This article describes the latest applications of Carbon nanotubes (CNTs) in chromatography.

Keywords: Carbon nanotubes, Chromatography, Stationary phase, Membranes, Extraction

Abstract: One of the flexible sheet metal forming methods is multi-point forming (MPF). MPF is mostly utilized in automotive and aerospace prototypes to cut down on time and costs. To comprehend the impacts of forming orientation on multi-point formation, two alternative forming orientations have been explored in this work. Deform 3D, a finite element program, was used to model and analyse multi-point forming (MPF) orientations. The V-type shape was created using 0.5 mm thick sheet metal made of aluminium 1100. According to the necessary load of sheet metal in simulations, three different diameters, 10 mm, 12 mm, and 14 mm, were examined. The findings indicate that, in comparison conventional forming10 mm pin forming was a more suitable forming type for this shape.

Keywords: Finite element, Multi-point, Forming, Sheet metal

Abstract: This study explores the Internet of Things (IoT) and hydroponics fusion, providing a thorough analysis of its benefits and possibilities for future agriculture. Since it uses fewer resources, increases crop yields, uses less water, and has less of an impact on the environment, the soilless farming technique known as hydroponics has become quite popular. Hydroponic systems with IoT integration can monitor vital environmental variables including temperature, humidity, pH levels, nutrient concentrations, and light intensity in real-time, allowing for data-driven decision-making and precise management of growing conditions. Additionally, IoT-based hydroponics encourages resource efficiency by reacting to shifting climatic patterns and supporting it through water recycling and precise fertilizer delivery. It also helps climate-smart farming methods. While early setup expenses and connectivity/reliability issues are significant drawbacks, the long-term gains of greater productivity outweigh these issues.

Keywords: Hydroponics, IOT and Sensors

Abstract: In machine learning, transfer learning has become a potent technique that enables models to use their previous knowledge and representations to perform better on new tasks or domains. By using pre-trained models that have acquired general features from massive datasets or comparable jobs, this strategy gets beyond the constraints of data availability and processing resources. several approaches to knowledge transfer between domains are provided by several forms of transfer learning, including inductive, transductive, unsupervised, semi-supervised, multi-task, and zero-shot transfer learning. Transfer learning has many uses in e-commerce, including fraud detection, product classification, and recommendation and picture search. This paper gives a thorough guide to classifying e-commerce products using transfer learning approaches, highlighting the advantages of knowledge transfer and the efficiency of fine-tuning models for particular use cases.

Keywords: transfer learning, e-commerce, image classification, text classification, data collection, fine tuning.

Abstract: The Convolutional Neural Network (CNN) has shown remarkable versatility across various applications. One such emerging area of research is age range estimation using CNN, which finds applications in numerous domains and continues to be a state-of-the-art field for investigation, aiming to enhance estimation accuracy. In our proposed work, we leverage a deep CNN model to identify people's age ranges. Initially, we employ the MTCNN technique to extract only face images from the dataset, discarding unnecessary features unrelated to the face. To improve the model's performance, we utilize data augmentation through random crop techniques. Our approach also incorporates transfer learning, where a pretrained face recognition model, VGG-Face, serves as the foundation for building our age range identification model. The effectiveness of our work is evaluated on the Adience Benchmark, where the performance on the test set significantly surpasses existing state-of-the-art methods. Overall, our research demonstrates the prowess of CNN-based age range estimation, showcasing promising results and contributing to the advancement of this domain.

Keywords: Computer Vision, Image Detection, Feature Matching, MTCNN, NumPy, OpenCV, PyTorch , FaceNet , P-Net, O-Net , R-Net , NMS , Face-Alignment.

Abstract: The rapid proliferation of the Internet of Things (IoT) has brought about heightened concerns regarding system security. Organizations must focus their efforts on safeguarding IoT devices, as even a single vulnerability could result in catastrophic system failures or large-scale cyberattacks. IoT security teams are grappling with growing complexities, including diverse inventories, operational challenges, and increasing threats. In particular, wireless communication networks, widely used in various sectors such as military, healthcare, and transportation, are highly susceptible to security breaches. As IoT continues to shape our future, ensuring data integrity, confidentiality, authentication, and authorization in IoT networks remains paramount. To tackle these pressing challenges, extensive research and deployment of robust security and privacy protocols are essential to protect against potential attacks and secure the promising potential of IoT applications. [1,2]

Keywords: Internet of Things (IoT), security issues in IoT, security, privacy, data integrity, confidentiality, authentication, access control, IoT applications.

Abstract: The healthcare sector is constantly looking for innovative methods to deal with the problems that it faces on a daily basis, including data security, interoperability, and confidentiality for patients. Global healthcare systems might see a revolution thanks to the growing concept of blockchain technology. This study examines the potential of blockchain technology to change the healthcare industry by showing its main applications, uses, and drawbacks. This study attempts to illuminate the opportunities and difficulties related to the use of blockchain by offering an in-depth study of how it might improve healthcare delivery, and patient outcomes. It also provides the light on the moral and legal problems that need to be solved if blockchain technology in healthcare is to be used to its full potential.

Abstract: The paper describes research contribution towards Programming Augmented Reality API using open-source software tools such as Python and OpenCV. This API inputs an image scans and describes the same for unique features, match the features with user input image and then overlay the desired image over the existing image. All the work was created in Python programming language utilizing Pycharm IDE, OpenCV and Numpy Libraries.

Keywords: Computer Vision, Image Detection, Feature Matching, Augmented Reality, OpenCV, Numpy, ORB Algorithm, Homography Matrix and FLANN's Algorithm.

Abstract: Identification of weeds is a task in agriculture fields for farmers. it is helpful for the farmers to identify the type of weed present in the agricultural lands. This method will save the time and we need some knowledge to identify it. if we see the recent advances in deep learning, weeds has been possible to identify automatically. In this paper we will propose a deep learning-based approach for identification of weeds using a Mass Regional-convolutional neural network (MR-CNN). The proposed system has used large set of datasets for various images and previously trained MR-CNN models for achieving high accuracy of weed species. This model has been trained on different dataset of images collected from different plants and fields. The result shows that the proposed system has different methods in identifying of weeds and high accuracy, it will be more accurate for identification of weeds in agriculture

Keywords: weed identification, agriculture, crop yield, image datasets, Deep learning, Machine learning.

Abstract: In today's world, the exponential growth of data is transforming the way we operate. The sheer volume of data being generated from diverse fields is astounding. Consequently, the value of data has become crucial in every aspect of decision-making. In the Big Data era, data exploration and visualization systems hold immense significance. Navigating and visualizing vast datasets pose a complex challenge for companies. To gain accurate insights from this massive data deluge, organizations must adhere to specific protocols. Implementing the right strategies for data analysis empowers businesses to optimize their processes and uncover untapped product and service opportunities. Failing to do so might lead to missing out on valuable insights. To address this, recent exploration and visualization systems should meet certain prerequisites and overcome various challenges. These systems must efficiently handle massive volumes of data from diverse sources to remain effective. In this context, understanding the different techniques and tools available for visualizing datasets becomes crucial. Their capabilities to handle and support extensive data from various sources will be instrumental in making sense of the ever-expanding data landscape.

Keywords: Data Visualization, Big Data, SNA, BA, SMA, BIA, BDA, Tableau, Power BI.

Abstract: Ethereum 2.0 is an update to the current Ethereum blockchain that aims to address the scalability, security, and sustainability issues with the first network. The upgrade will be carried out in phases and come with various important improvements. It's crucial to remember that Ethereum 2.0 has been developed over a long period of time and gradually, thus the features and specifications may have changed since the last release. Because ETH 2.0 is a completely other project, the moniker Ethereum may be a little confusing. EHT2 will speed up transactions without compromising security while also enhancing the blockchain's programmability and scalability.

Keywords: Ethereum 2.O, PoW, PoS, Sharding

Abstract: This paper focuses on different switching strategies of dual active bridge DC-DC converter. The structure of non-linearity of the device and power flow is a critical problem in BDC. This paper presents a comparative analysis on Alternate phase-shift modulation (APM) schemes such as triangular current modulation (TRM), modified triangular current modulation and Hybrid modulation scheme. A feedback linearized controller is designed to attain better dynamic response for different load. This controlling analysis of isolated bidirectional full bridge converter (IBDC) is controlling of power under different switching strategies to improve their performance of converter for nonlienarity.

Keywords: Isolated bidirectional full bridge converter (IBDC), Alternate phase-shift modulation (APM), triangular current modulation (TRM).

Abstract: This essay aims to examine the performance, benefits, and drawbacks of every generation of mobile wireless technologies that are now in use. The article discusses the creation and growth of several mobile wireless technology generations, as well as their relevance and benefits over one another. Mobile wireless networks have seen up to five scientific revolutions and progress in the last several decades, from 1G to 4G. The focus of current studies in the field of mobile wireless technology is on the advanced deployment of 4G and 5G technologies. The term "5G" has yet to be in use on a formal basis. The three main areas of research in 5G are the Worldwide Wireless Internet (WWW), Dynamic Ad-hoc Wireless Networks (DAWN), and the Real Wireless World. In this research, we propose a novel network design for the next mobile phone network, 5G. The mobile device in the suggested design has the capability of switching the Radio Accessing Technology (RAT) following specific user needs.

Keywords: Include at least 5 keywords or phrases

Abstract: The United States has undergone a remarkable metamorphosis, transitioning from its position as a formidable cyber superpower to assuming the pivotal role of a global protector, effectively shaping and influencing the cybersecurity practices of nations across the globe. This comprehensive article delves into the intricate dimensions and multifaceted nuances of the United States' profound impact on international cybersecurity. Through a meticulous examination of its exemplary leadership in cyber diplomacy, unwavering commitment to combating the ever-evolving landscape of cyber-crimes, proactive involvement in shaping the contours of international cybersecurity regulations, and synergistic collaborations with diverse nations, a profound and holistic understanding unfold of the United States' journey from a paramount cyber powerhouse to its ascendancy as a steward of global cyber defense. This in-depth analysis not only sheds light on the far-reaching consequences of the United States' actions and policies but also provides invaluable insights into the ever-evolving security landscape in the digital era, underscoring the indispensable nature of its transformative trajectory on the overarching global cybersecurity ecosystem

Keywords: Cyber superpower, Cybercrime, Hacker, Cybersecurity practices, United States, International Impact

Abstract: In an era of accelerated digital payments, securing financial transactions goes far beyond encryption and authentication. This study presents an enhanced, multidimensional framework for smart payment system security that integrates developer-led secure software design, explainable AI, cross-border compliance, and inclusive user experience. By examining evolving threats-including biometric spoofing, blockchain exploits, and quantum computing-this research proposes advanced threat modeling strategies for next-generation payment architectures. It also addresses systemic challenges such as integrating DevSecOps in CI/CD pipelines, achieving legal interoperability across jurisdictions, and mitigating bias in AI-driven fraud detection. Drawing on case studies from FinTech, remittance, and e-commerce ecosystems, the framework emphasizes usability, governance, and transparency as pillars of long-term trust. The study concludes with strategic recommendations for developers and financial institutions aiming to build secure, scalable, and ethically sound digital payment platforms equipped to meet the demands of a global, interconnected economy.

Keywords: Smart Payment Security, DevSecOps, Blockchain and Identity Verification, Fraud Detection, CI/CD Pipeline Integration