VOLUME 10, ISSUE 12, DECEMBER 2023

Abstract: Violation of motorcyclists in special road areas such as pedestrian paths, bus lanes, and toll roads still frequently occurs, posing the risk of accidents and disrupting other road users. Factors contributing to these violations include avoiding traffic jams to reach destinations more quickly. Therefore, a motorcycle detection system has been developed to facilitate the handling of violations by providing information to relevant security personnel. The detection system utilizes the YOLOv5 method, trained with 492 images with varying parameters such as epoch value (200) and batch size (24). Using the YOLOv5 model, it achieves a Mean Average Precision (MAP) value of 89.8%, indicating good detection quality. The detection system can be implemented in real-time using a webcam. Dummy violation data is processed using a Raspberry Pi 4B microcontroller. Testing the detection system in light intensity ranging from 6171 Lux to 140516 Lux demonstrates its quick response capability in sending information via the Telegram application, taking around 171 milliseconds for each data packet. The system effectively detects objects and promptly provides information to relevant security personnel, enhancing performance in addressing violations within the monitored area.

Keywords: Object Detection, Raspberry Pi, Telegram Bot, Traffic Violations, YOLOv5

Abstract: Persea americana, commonly known as avocado, has recently gained substantial popularity and is often marketed as a "superfood" because of its unique nutritional composition, antioxidant content, and biochemical profile. It is the highly valued fruits consumed worldwide, and there are numerous commercially available varieties on the market. It is considered one of the main tropical fruits, as it contains fat-soluble vitamins which are less common in other fruits, besides high levels of protein, potassium and unsaturated fatty acids. Avocado pulp contains variable oil content, and is widely used in the pharmaceutical and cosmetics industry, and in the production of commercial oils like olive oil. Avocado has been recognized for its health benefits, especially due to the compounds present in the lipidic fraction, such as omega fatty acids, phytosterols, tocopherols, carotenoids, chlorophylls, phenols and squalene. This study aimed to present a literature review about nutritional importance, health benefits, application in dairy, food, pharmaceutical and cosmetic industry of avocado and its by-products.

Keywords: Avocado, Nutrition composition, Health benefits, Application in dairy and food industry, Avocado seed, Avocado Peel.

Abstract: Indian Bael or Aegle marmelos is a spiritual, religious and medicinal plant, native of India and Bangladesh and spread throughout South East Asia. Bael has many benefits and uses such as to cure tuberculosis, hepatitis, dysentery, constipation, peptic ulcer, piles, cancer, blood purifier, skin rash, breast milk, useful in worm infestation and stomach related problems. The seasonal variation of total ash , water insoluble ash and water soluble ash content have been investigated from leaves, bark ,wood and root of Aegle marmelos. Comparative account of total ash contents of Aegle marmelos showed higher level in leaves range from (12.950 % to 13.750 %). Comparative account of water insoluble ash contents of Aegle marmelos showed higher level in leaves range from (10.425 % to 11.125 %) than bark wood and root. Comparative account of water soluble ash contents of Aegle marmelos showed higher level in bark (range 3.800 % to 5.475 %) than leaves (range 2.525 % to 3.295), wood (range 2.150 % to 2.600 %) and root (2.100 % to 2.475 %).

Keywords: Total ash, water insoluble ash, water soluble ash, Aegle marmelos.

Abstract: This survey paper explores the intersection of Artificial Intelligence (AI) and Brain-Computer Interface (BCI) technologies, with a specific focus on recent advancements in thought-to-text conversion systems. These systems, powered by Electroencephalography (EEG) signals, represent a groundbreaking leap in assistive technologies, particularly for individuals with speech impediments. By decoding and interpreting imagined speech, AI-BCI systems empower users facing profound disabilities, offering a voice through silent communication. The technical intricacies involve diverse datasets and a combination of signal processing, machine learning, and deep learning techniques. Beyond understanding the technical aspects, the paper emphasizes the importance of evaluating the functional efficacy of these systems. The ultimate success lies in the positive impact on users' lives, as AI-BCI systems redefine communication paradigms and break down barriers for individuals with unique challenges. In enabling silent communication, these technologies aim to create a world where everyone can freely express themselves.

Keywords: Brain-Computer Interface (BCI), Electroencephalography (EEG), Thought-to-text conversion, Speech impairment, Assistive technology, Signal processing, Machine learning, Deep learning, Natural Language Processing (NLP)

Abstract: This study aims to investigate the physico-chemical properties of water collected from the Tattapani source in Nawadih, Balrampur district of Chhattisgarh. The physico-chemical characterization of water is essential for understanding its quality and suitability for various purposes. Water samples will be collected from multiple locations in Tattapani and analyzed for parameters such as pH, electrical conductivity, turbidity, total dissolved solids, major ions (e.g., calcium, magnesium, sodium, and potassium), heavy metals, microbial load, coliform bacteria, nitrates, phosphates, organic matter content, biochemical oxygen demand, pesticides, herbicides, water hardness, and alkalinity. The findings of this study will provide valuable insights into the overall quality of water from the Tattapani source. The results will help assess potential risks associated with water consumption and determine its suitability for drinking, irrigation, and industrial use. This research will contribute to the development of strategies for water management and conservation in the Balrampur district of Chhattisgarh, ensuring the availability of safe and sustainable water resources.

Keywords: Total Alkalinity, fluoride, Total Hardness, Magnesium, Iron.

Abstract: With the rapid progress of technologies like Artificial Intelligence (AI), deep learning, and Machine Learning(ML), the ability to manipulate and modify images has become more accessible. This has led to the emergence of a concerning phenomenon known as deepfakes, where criminals can generate deceptive videos, images, or audio content. In addressing this growing challenge, the present study introduces a comprehensive literature review on numerous approaches including Residual Networks (ResNet), Long Short-Term Memory (LSTM), and Convolutional Neural Networks (CNN) with reference to identification of fake content. The survey reviews popular research outcomes from the year 2017 to the current year. This work is useful in identifying research gaps in the area of fake content identification which can be useful to both experts and future enthusiastic. Despite being a preliminary study in this area, the authors propose this study as a valuable resource which can be used for years ahead.

Keywords: Deepfake, Deceptive content, ResNet, LSTM, and CNN.

Abstract: Energy Saving and Energy Conservation concept is propagated everywhere. Also, different government forms are actively taking part to get fulfil result by organising different activities and Awareness programme. In this case automobile industries manufacturing Electrical vehicle like Two and Four, also awareness about Electrical Vehicle is going more and more. Government forms making scheme about purchase an electrical vehicle, but every technology has own limitation, like EV has more charging time and day by day life of battery reduces. If we not taken care then in charging time and continuously charge then life span of battery reduces, sometime damages cases increase, Consequence Customer of Electrical vehicles become unsatisfied also another customer denied for purchasing. Now days research are going to solve this major problems and doing research on decrease a charging time with effective cooling system to reduce a damage battery case. In this paper we discuss about technologies are innovate by different forms for electrical vehicle charging system.

Keywords: Introduction, Research in battery charger, Recent advancement in battery charger

Abstract: This paper presents the design and construction of a voice operated elevator control system. As we normally see an elevator which might not deal with many safety issues, this system acts as a human-machine communication system. Speech recognition is the process of recognizing the spoken words to take the necessary actions accordingly. Users can also control the electrical devices like fan, door etc. with the help of voice recognition system. This system is extremely beneficial to those who are paralyzed, limited of stature, or severely impaired. The idea for this project is elevator system that accepts destination input via use an external microphone to ride the elevator there target accordingly. The elevator also receives the following inputs: Easy-to-use speed control for different users People with disabilities. With this system, residence and Commercial facilities to minimize elevator costs. Thus, elevator provides experience for people with disabilities and short stature people.

Keywords: Voice control, voice input, microphone, automated elevator, disabled friendly.

Abstract: Diagnosing Autism Spectrum Disorder (ASD) present challenges due to the absence of specific diagnostic tools for definitive identification. ASD is characterized by social communication challenges and restricted or repetitive behaviors, diagnosed based on observed behavior. This survey investigates the landscape of computational models for ASD detection, reviewing methodologies like Naïve Bayes, Support Vector Machine, Logistic Regression, KNN, Neural Network, and Convolutional Neural Network (CNN). The study extends its focus to include the development of an application to identify autism and support for parents. It addresses the increasing role of ML in medical research and aims to comprehensively explore the evolving landscape of ASD detection models. The paper delves into the intricacies of ASD diagnosis, emphasizing the potential synergies between ML methods and creative applications that enhance recognition and parental involvement.

Keywords: Autism Spectrum Detection (ASD), Machine Learning, Diagnostic Challenges, ML-Based Diagnosis, Supportive App.

Abstract: The histochemical studies of leaves and wood of Aegle marmelos are medicinally important plant in India. For histochemical studies the free hand sections of leaves and wood were taken and treated with the respective reagent in localize components, viz. starch, protein, tannin, saponin, fat, glycosides and alkaloids in the tissues.

Keywords: Histochemistry, starch, protein, tannin, saponin, fat, glycosides and alkaloids.

Abstract: The suspension system of two wheelers is depending upon spring type, hydraulic or pneumatic type of suspension systems. This present work gives deals with the magnetic suspension system and the magnetic suspension system is turning out to be the new option to the conventional suspension systems. The aim of this work is to study and investigate the response of two-wheeler suspension system, when it is subjected to road surface irregularities. This research work presents design, construction and working of magnetic suspension system. This system uses magnets and spring as passive dampers, which are used to reduce displacement and acceleration of spring mass in order to improve ride comfort. This type of Suspension has no problem of leakage of oil like hydraulic shock absorber. FEA analysis is carried out over the suspension spring with different materials such as Crome silicon, Carbon steel, NiCr, magnesium and Aluminium. With and without magnetic suspension is analysed for the stress and deformations. It is observed that the carbon steel has minimum deflection and the maximum stress induced in aluminium material.

Keywords: Magnetic, Suspension system, Spring, Spring Material, FEA

Abstract: Nowadays, the construction of the high-rise multi-storey buildings has been increased due to the increasing population. Earthquake is one of the main phenomena causing damage to the structure. As the height of the structure increases, it undergoes larger seismic forces. So, it is important to improve the resistance of multi-storey building to lateral loads. There are many structural systems which resist lateral loads by the addition of different structural systems. The application of the shear wall system and bracing system in reinforced concrete buildings has become widely used to minimize seismic consequences. Both of the systems have significance of the structural performance. Although both systems are used for same the reasons, their effect shows unequal variations and behavior against seismic load. This is for the reason that the values of response factors are miscellaneous for varying structural systems. In this project work, the seismic analysis of Frame Structure, RC Bracing system and Shear Wall system are considered and compared to their results against lateral forces using Etabs Software. Three structural systems are considered, in which one is framed structure, second is braced frame structure and third is shear wall structure with different height of building. G+13 storey and G+15 storey structures are compared for maximum displacement, storey drift and base shear using Response Spectrum Analysis in zone V.

Keywords: Bracings, Shear Wall, Response Spectrum Analysis, Multi-Story Building.

Abstract: The development of a Seed Management System Chatbot, a new tool designed to streamline and increase the efficiency. This chatbot uses natural language processing and artificial intelligence to help researchers, scientists and authors manage the seed data associated with their research. The chatbot provides a user-friendly interface for entering, organizing and retrieving initial information, reducing the burden of manual record keeping and minimizing the risk of data loss. It also helps ensure research traceability and reproducibility by securely storing and managing seed data.

Keywords: Chatbot, Seed Management System, Natural Language Processing, Artificial Intelligence, Research Data Management, Reproducibility.

Abstract: Memory management is a crucial component of operating systems that has an immediate influence on system performance, stability, and reliability. Operating systems depend on paging, segmentation, fragmentation and swapping to effectively manage memory and allocate system resources. However, using conventional teaching methods might make it challenging and hard to learn these concepts. The project "Understanding Operating System Concepts using VR" seeks to address this issue by providing users with a hands-on, interactive approach to learn these techniques. The software application offers a visual representation of each memory management technique, allowing users to observe and understand these concepts clearly. To develop the VR application - Oculus Quest, Unity, C# programming language, custom 3D models using Blender, and Oculus prefabs will be used. The Oculus Quest VR headset, which is integrated using unity's oculus assets, will be used to experience the application which provides a self-contained VR experience. The 3D models for the application will be created using Blender, which will be integrated into unity. C# programming language will be used to implement memory management concepts. Test runs will be conducted to ensure that the VR experience is interactive, and that the ideas are conveyed in an innovative and educational way. The program will be created to be simple to use and accessible, giving curious students a great resource. This project is an innovative way to teach memory management OS techniques to students and enthusiasts of operating system concepts. Using Unity to create a virtual reality environment provides an immersive and interactive experience that can help learners better understand these complex concepts. By visualizing how memory is managed in an operating system, learners can gain a deeper understanding of how these techniques work and how they affect system performance.

Keywords: Memory management, Operating system, Blender

Abstract: In today's digital age, healthcare is a crucial aspect of the medical field, with people seeking relevant health information online. Despite the internet being a valuable resource, the abundance of dispersed clinical data across various websites poses challenges for users in finding beneficial information. An advanced drug recommendation system uses sentiment analysis, machine learning, as well as NLP to analyze user sentiments in drug-related content. ML algorithms process this data, tailoring recommendations to individual profiles and adapting to evolving sentiments over time. NLP plays a crucial role in understanding and contextualizing language nuances in user reviews, ensuring precise sentiment interpretation. This combination of quantitative and qualitative data provides highly personalized, context-aware suggestions, enhancing the overall user experience and enhancing the overall user experience. This paper presents a drug recommender system that leverages sentiment analysis on user-generated drug reviews. Focused on addressing the gap in sentiment analysis research within the healthcare domain, the system aims to aid patients in making informed decisions regarding drug selection.

Keywords: Sentiment Analysis, Natural Language Processing (NLP), Machine learning

Abstract: Some underutilized tubers:Aerial yam (Dioscorea bulbifera), Cocoyam (Xanthosoma robustum) and Water yam (Dioscorea alata) were analysed for their glycemic indices using Invitro method after they have undergone four pre-processing operations of boiling, sprouting, frying, roasting and a set was left untreated. Boiled Cocoyam (Xanthosoma robustum) was significantly different (p<0.05) in terms of glycemic index (40.217)% compared to the other samples while among the processing methods, boiling was significantly different (p<0.05) from sprouting, frying and roasting. The untreated samples were the control samples.

Keywords: Underutilized tuber species, Glycemic Index, pre-processing operations, Dioscorea bulbifera Xanthosoma robustum, Dioscorea alata.

Abstract: The Bionic Arm Project is an innovative attempt aimed at developing advanced prosthetic limbs that replicate the functionality and competence of a human arm. Through cutting-edge technology and engineering, this project seeks to enhance the quality of life for individuals with limb loss, providing them with improved mobility and a greater degree of independence. Prosthetic devices enhance the independence and well-being of countless people around the world. The main characteristic of bionic limbs is that they establish an interface between the biological residuum and an electronic device, providing not only motor control of prosthesis but also sensitive feedback. This paper explores the advancements in bionic arm technology, focusing on the integration of robotics and neural interfaces to enhance limb functionality.

Keywords: Bionic, prosthetic, residuum, interface, innovative, integration.

Abstract: Nowadays, the great boom that computer systems have had is largely due to the fact that these systems are designed with a greater knowledge about the users who will use them, resulting in that these systems help users to reduce, among others, the time to perform their activities, that is, currently for success in the use of the developed systems, the User-Centered Design must be considered. This document describes some prototypes developed under this design that will be of great help to students of the Undergraduate Degree in Software Engineering of the Autonomous University of Yucatán, México, by putting into practice their knowledge acquired in the Human Computer Interaction course, facilitating their learning in software development in real learning scenarios. Likewise, the process of an inspection technique specific to the discipline for interaction in user interfaces is described, making use of the CogTool tool.

Keywords: software, human-computer interaction, design thinking, user-centered design.

Abstract: The goal of this research work is to develop an environmentally friendly catalytic oxidation system for the synthesis of cyclohexanone from cyclohexanol using hydrogen peroxide as the oxidizing agent under phase transfer catalytic conditions with heteropolyacid (dodeca-tungstophosphoric acid) as a co-catalyst. The effect of various reaction parameters is studied for this oxidation system. It was observed that the reaction takes place to a significant extent (89% conversion) in 30 minutes at a temperature of 600C and a speed of agitation of 1200 rpm. The calculated activation energy from the Arrhenius plot for the temperature range of 400C-600C using initial rate of reaction is 1.48 kcal/gmol, which indicates that the reaction may be mass transfer controlled. The initial rate of reaction was independent of the concentration of cyclohexanol in the organic phase for the concentration range studied. The initial rate of reaction was found to be linearly dependent on the concentration of hydrogen peroxide in the aqueous phase, the total concentration of the phase transfer catalyst in the organic phase and the co-catalyst loading. A reaction mechanism is proposed and a kinetic model is developed for this environmentally friendly catalytic oxidation system.

Keywords: Cyclohexanone, Environmentally Friendly Oxidation, Heteropolyacid, Hydrogen Peroxide, Kinetic Model, Phase Transfer Catalysis.

Abstract: This research investigates the effectiveness of mung bean paste as an egg replacer in muffin formulation. The core objective is to study the rheological behavior of mung bean in the ratio of 1:1 and 1:1.5 which would also contribute to increase the protein content of the muffin. The results showed that the proportion of mung bean paste as an egg replacer gave significant effect on moisture content, protein, fat and texture of the muffin.

Keywords: Muffins, Mung Bean Paste, Egg Replacement.

Abstract: The system developed is a device that helps visually impaired patients to lead an independent life. This system is integrated with voice commands. The input to the system is a real-time scenery and the output is the voice output of the names of the recognized objects. Avoiding obstacles is the main goal of our project so that the life of the visually impaired person can be led safely. The algorithm used is YOLO (You Only Look Once). The YOLO algorithm uses a single neural network to simultaneously predict bounding boxes and class probabilities for multiple objects within an image. YOLO, Object recognition, Voice command integration. The proposed system employs YOLO model trained on large datasets to recognize a wide range of everyday objects, including household items, food products, navigation aids, and more. Upon detecting an object through the camera feed, the system provides audio feedback through speech synthesis, conveying information about the recognized object to the user in a clear and concise manner. User feedback and iterative improvements are fundamental to the system's development, ensuring its effectiveness and usability for individuals with diverse visual impairments. Moreover, the system's design prioritizes simplicity, portability, and affordability, aiming to make it accessible to a broader population of visually impaired individuals. object recognition system represents a vital step toward empowering the visually impaired community by providing them with a reliable and intuitive tool to better navigate and interact with their environment.

Keywords: YOLO, Object recognition, Voice commands, Real-time

Abstract: According to data theory, the best system of public finance is that which secures the Maximum social advantage from the operations which it conducts. Cite: S.N Chand, H. L Bhatia, J. V. M Sharma, S. K Singh, Bose. D, Ganeshan. S, "Study and Research Analysis on Public Finance in the field of Management", IARJSET International Advanced Research Journal in Science, Engineering and Technology, vol. 10, no. 12, pp. 170-182, 2023, Crossref https://doi.org/10.17148/IARJSET.2023.101222.

Abstract: Phytochemicals are naturally occurring chemical compounds in plants. They are commonly called as secondary metabolites. These compounds respond the medicinal properties and other valuable properties like dyes, milk latex, resins, gums secretion of the plants. The dyes are extracted from plants for various purposes. In this study we have selected fourteen dye yielding plants namely Lawsonia inermis L., Phyllanthus emblica L., Indigofera tinctoria L. Acacia concinna DC. Hibiscus rosa-sinensis L., Beta vulgaris L., Murraya koenigii L., Eclipta prostrata Roxb. Citrus sinensis L., Aloe vera L., Coffea arabica L., Camellia sinensis L., Cassia auriculata L. Syzygium jambolana L. for the analysis of their phytochemicals. In the results all the plants showed positive response for many qualitative tests.

Keywords: Medicinal properties, Milk latex, Resins, Gums and Eclipta prostrata

Abstract: Purpose: The most often published international journal articles are shown to discover the study fields that are most interested in ML in agriculture. In all, 129 journals were pertinent to the topic of the course. Remote sensing, as a general point, was important because satellite data, for example, provides significant input data for ML systems. Agricultural sustainability, smart farming, and the environment were also major concerns. There was also a high frequency of journals related to computational approaches. Methods that combine various stimuli to make a choice are referred to as EL in this context. One kind of inducer receives labelled samples and builds a model capable of generalizing these examples. As a result, more unlabelled cases may be predicted. Weed identification methods relied heavily on images as input data. Photos derived from in-situ measurements and multispectral images from the aforementioned sources were used to create these images. Regression-based multivariate statistical approaches are the most efficient for indirect selection. Artificial neural networks (ANN) may be used in plant tissue culture research to perform pattern recognition, nonlinear regression, and classification due to their ability to process binary information, continuous information, categorical information, and fuzzy information. A target function is used to establish a starting population and an evaluation of an individual's fitness at the beginning of the process. Accuracy necessitates the acquisition of a big dataset. Each picture in each category has its own set of characteristics that we've extracted. GLCM texture extraction and edge detection are used to extract the features, and the degree of moisture content is measured using these two techniques. Using pixel values, these characteristics define the plant's current state. As an analytical tool, moisture content is one of the most important factors..... Cite: Adlin Jebakumari S, Dr. A. Jayanthiladevi,"Using Machine Learning tools and Techniques, Genetic Disease Analysis Prediction on agriculture crops using AI & ML", IARJSET International Advanced Research Journal in Science, Engineering and Technology, vol. 10, no. 12, pp. 178-192, 2023, Crossref https://doi.org/10.17148/IARJSET.2023.101224.

Abstract: Artificial intelligence (AI) is gaining popularity in a variety of fields, including business and society. However, while investment banking and backend services were among the first banking applications to successfully integrate artificial intelligence, AI is now mostly applied in areas where there is no direct client contact. Because of the importance placed on customer relationships in commercial banking, the deployment of artificial intelligence has received little attention. Artificial intelligence in commercial banking has the potential to have a substantial impact on corporate procedures and client relationships, which could open up new research areas in the field of behavioral finance. According to our research, artificial intelligence can assist commercial banks in reducing lending losses, increasing payment security, automating compliance-related labor, and improving consumer targeting. Researchers are worried about several concerns, including realizing technological advantages, implementing artificial intelligence into commercial operations, and ensuring that users are comfortable with the technology. As a last recommendation, we encourage you to sketch out an overall research strategy for behavioral finance science in the future.

Keywords: Banking Sector, Compliance Process, Machine Learning, Artificial Intelligence

Abstract: A significant amount of study has been done to determine the impact of digital distraction on students from an international viewpoint, according to the evaluated literature that is accessible from the perspective of the research issue. The research on the proposed issue has been minimal in the Indian setting. Moreover, considering the information of the unavoidable prevalence of distraction among today's pupils, it is necessary to develop specific ways for transforming these distractions into manageable factors. Based on the existing research, it is evident that the current generation of students is easily diverted by several variables, both internal and external to the classroom environment. However, attempting to take into account and analyse all of these elements would result in a research scope that is too broad. The current study will specifically examine distractions experienced by students in classroom situations. Considering the extensive impact of the widespread availability of the internet and digital devices, it is important to evaluate the level of distraction experienced by students in the digital realm and its influence on their academic performance. In terms of a wider viewpoint, the current research project will focus on consolidating the existing literature on how digital distractions affect students' academic performance and highlighting the consequent consequences for both students and instructors. Machine learning techniques have been used in the domain of intelligent diagnostics to address these problems, particularly in detecting anomalous data and structural deterioration.... Cite: Kamala S, Dr. A. Jayanthiladevi,"Machine Learning-Based Analysis on Digital Distractions and Academic Performance of Online Engagement", IARJSET International Advanced Research Journal in Science, Engineering and Technology, vol. 10, no. 12, pp. 202-208, 2023, Crossref https://doi.org/10.17148/IARJSET.2023.101226

Abstract: The present study aimed to examine the impact of social media usage on mental health among college students in the Vidarbha region of Maharashtra. With the rapid expansion of digital platforms, young individuals are increasingly exposed to prolonged screen time, which may influence their psychological well-being. A total of 200 students were selected using a purposive sampling technique and divided into two groups: high social media users (more than three hours per day) and low social media users (less than 30 minutes per day). Mental health was assessed using the General Health Questionnaire (GHQ-12), a widely recognized instrument developed by Goldberg to measure psychological distress and well-being. The findings revealed that students with high social media usage experienced significantly higher levels of stress, sleep disturbances, and depressive symptoms compared to low users. In contrast, students with limited social media exposure demonstrated better concentration, decision-making ability, and overall emotional stability. Statistical analysis using independent t-tests indicated significant differences (p

Keywords: Social Media, Mental Health, GHQ-12, College Students, Vidarbha Region, Stress, Depression, Digital Behavior