TO TRAVEL, TO EXPLORE AND TO ADVENTURE USING TRAVELMATE
Srushti Dantulwar1, Sanskruti Itankar1 , Kashish Surjuse1, Mrunmayee Awatade1 , Pinky Gangwani2
1Students,Department of Computer Engineering,Cummins College of Engineering for Women Nagpur, India
2Assistant Professor, Department of Computer Engineering, Cummins College Of Engineering For Women, Nagpur, India
ABSTRACT
Welcome to TravelMate, your ultimate companion for seamless travel experiences. At TravelMate, we understand that every journey is a unique adventure, and we are dedicated to enhancing your travel moments with convenience, inspiration, and personalized services. It simplifies the entire travel process. With a user-friendly interface and advanced technology, we empower you to customize your travel plans effortlessly. Whether you are a spontaneous traveler or a meticulous planner, TravelMate adapts to your style, offering real-time suggestions and insights to make informed decisions. Our team of travel experts scours the globe to bring you insider tips, hidden gems, and unique experiences, ensuring that your journey is not only memorable but also enriched with cultural discoveries. At TravelMate, we prioritize your safety and peace of mind. We also provide comprehensive travel insurance options, giving you the confidence to explore the world worry-free join vibrant community of fellow travelers through the TravelMate social platform. Let TravelMate be your compass, guiding you to extraordinary destinations and unforgettable memories. Start your journey with us today and redefine the way you explore the world.
Keywords –Travel Planner, Customized Itineraries, Curated Travel Guides, Real-time Updates, Solo Travel, Social Networking
Optimizing Cloud Security with Fusion Feature Selection Techniques and an Ensemble Classifier for Intrusion Detection
M.Kavitha¹, Dr.A.John Sanjeev Kumar²
¹Assistant Professor, Department of Computer Science, Thiagarajar College, Madurai, India
²Head and Assistant Professor, Department of Data Science, The American College, Madurai, India
ABSTRACT
With growing usage of cloud computing environments in various organizations, both public and private usage models, has led to a significant rise in cyber related threats, posing risks to data confidentiality and integrity. On addressing this concern, a cloud based intrusion detection system (IDS) is proposed in this paper, focusing on enhancement of classification accuracy through improved feature selection and the application of the crow search mechanism (CSA) to weigh the ensemble model. The feature selection process integrates both filter based system and automation supportive prototypes, aiming in deriving an enhanced feature sets. The ensemble classifier comprises diverse machine and deep learning models, including long short term memory (LSTM), and a fast adaptable learning network (FLN). It is utilized on generation of optimal weights for the ensemble model, enhancing prediction results. The performance evaluation Experiments were conducted on datasets and outcomes indicates that the proposed methodology outperformed than conventional approaches in terms of data originality and it’s integrity. Additionally, the identification lev and falsehood alarming rate (FAR) for numerous attack types demonstrated with improved efficacy across datasets.
Keywords – Cloud infrastructure, threat detection, LSTM, deep learning.
ANALYSIS OF AN ANDROID APPLICATION FOR TOURIST
Srushti Dantulwar¹, Sanskruti Itankar¹ , Kashish Surjuse¹, Mrunmayee Awatade¹ , Dr.Amit Thakare²
¹Students,Department of Computer Engineering,Cummins College of Engineering for Women Nagpur, India
²Associate Professor, Department of Computer Engineering, Cummins College Of Engineering ForWomen, Nagpur, India
ABSTRACT
Greetings from Sang Hamare, the best travel companion you’ve ever had. At Sang Hamare, we are committed to making your travel experiences even more memorable by providing you with convenient, motivational, and individualized services since we recognize that every journey is a unique adventure. It makes traveling easier overall. We enable you to easily modify your trip arrangements with our cutting-edge technology and user-friendly UI. Sang Hamare adjusts to your style, whether you are an impulsive traveler or a careful planner, providing real-time recommendations and insights to help you make wise choices. In order to make sure that your trip is not only unforgettable but also packed with cultural discoveries, our team of travel experts searches the world for insider information, undiscovered jewels, and unique experiences. Sang Hamare places a high priority on your security and peace of mind. We also provide complete travel insurance plans, allowing you to experience the world without fear and connect with a lively traveler community on the Sang Hamare social media site. Allow Sang Hamare to serve as your compass, leading you to amazing places and treasured memories. Rethink how you travel the world by embarking on your adventure with us today. We also provide complete travel insurance plans, allowing you to experience the world without fear and connect with a lively traveler community on the Sang Hamare social media site. Allow Sang Hamare to serve as your compass, leading you to remarkable locations and priceless experiences. Rethink how you travel the world by embarking on your adventure with us today.
Keywords –Travel planner, personalized itineraries, carefully chosen travel guides, instant updates, solo traveling, and social media.
YOUTUBE VIDEO SUMMARIZER: A WEB BASED APPLICATION FOR CONCISE VISUAL AND TEXTUAL SUMMARY
Gauri Mandar Puranik¹, Nidhi Kamath², Nakshatra Akhadkar³, Gargi Dusane4
¹Assistant Professor at GCOERC Nashik,
²Student at GCOERC Nashik,
³Student at GCOERC Nashik,
4Student at GCOERC Nashik
ABSTRACT
In today’s world, YouTube has become a treasure trove of entertainment and knowledge, offering a vast array of content with varying degrees of quality and information. The problem we face today is selecting the most appropriate content for our needs. Our system is designed to assist our users in swiftly identifying the most suitable content, thereby saving them valuable time that might otherwise be spent on clickbait videos and leading thumbnails. The system utilizes the power of Python, along with its frameworks, libraries, and Natural Language Processing (NLP) capabilities to generate both textual and visual summaries. These summaries give them a quick and accurate overview of the original content, saving them precious time and increasing their productivity.
Keywords –Framework, Knowledge, Libraries, NLP, Python, YouTube.
A NOVEL APPROACH FOR: EMERGENCY CALLER ROUTING AND HOSPITAL ROUTING SYSTEM USING AI
Ms. Swati. R. Khokale¹, Ms. Swati. R. Khokale², Amey Muke³, Rakesh Mahto4, Laxmichhaya Patil5
¹Assistant Professor, Department of Computer Engineering, Guru Gobind Singh College of Engineering and Research Centre, Nashik, Maharashtra, India
2,3,4,5Student, Computer Science Engineering, Guru Gobind Singh College of Engineering and Research Centre, Nashik, Maharashtra, India
ABSTRACT
This research paper presents the design and implementation of an innovative emergency calling system leveraging the synergistic capabilities of Artificial Intelligence (AI) and Blockchain technologies. Traditional emergency response systems often encounter challenges such as delayed response times, inaccurate information dissemination, and vulnerabilities in data security. Our project aims to overcome these limitations by integrating AI algorithms for real-time analysis of distress calls and Blockchain for secure and transparent data management. We provide a comprehensive overview of the current state of emergency calling systems, highlighting their deficiencies and areas for improvement. Through the development of our system, we demonstrate how AI enables swift identification and classification of emergencies, facilitating rapid dispatch of resources. Furthermore, Blockchain technology ensures the integrity, immutability, and confidentiality of emergency data, enhancing trust and reliability in the system. Through empirical evaluation and case studies, we validate the effectiveness and efficiency of our solution in improving emergency response operations. This project represents a significant advancement in the field of emergency communication systems, offering a robust and scalable framework for ensuring public safety and crisis management in modern society and offers a transformative approach for comprehensing solution to emergency response operation.
Keywords – AI, Blockchain, Emergency Call System, Handling Multiple Calls, Routing.
LUNG CANCER DETECTION AND GENERIC DRUG RECOMMENDATION SYSTEM
Ms Farhat Patel¹, Ms Vaidika Barve², Ms Shruti Darekar³, Mr Varad Mahajan4
¹Assistant Professor at Guru Gobind Singh College of Engineering and Research Centre, Nashik
2,3,4,5Student at Guru Gobind Singh College of Engineering and Research Centre, Nashik.
ABSTRACT
Lung cancer remains one of the leading causes of cancer-related deaths worldwide, making early detection crucial for improving patient outcomes. This project introduces a multifaceted approach to combat lung cancer by combining advanced diagnostic techniques with a personalized drug recommendation system. The goal is to enhance the early detection of lung cancer while also offering more effective and cost-efficient treatment options through the utilization of generic drugs. The first component of the project focuses on lung cancer detection. We employ technologies such as deep learning and image analysis to process medical imaging data, including histopathological images, in order to identify early signs of lung cancer. By leveraging machine learning, we can detect and classify abnormalities in lung images with a high degree of accuracy, thereby enabling timely diagnosis and treatment. The second component of our project addresses the challenge of recommending generic drugs to lung cancer patients. The high cost of cancer medications can place a significant financial burden on patients and healthcare systems. Our recommendation system takes into account the patient’s medical history, the stage and type of lung cancer, and the latest medical research. By analysing this information, we provide personalized condition. The integration of these two components creates a holistic solution for addressing lung cancer. Early detection enhances the chances of successful treatment, while generic drug recommendations alleviate the financial burden on patients and healthcare providers. By combining advanced technology with medical expertise, this project aims to improve patient outcomes, reduce the economic strain of treatment, and ultimately contribute to a more efficient and affordable healthcare system for lung cancer patients.
Keywords – Lung cancer, Haralick features, artificial neural network, Convolutional neural networks, Digital pathology, Drug Recommendations, Collaborative filtering.
STUDY ON NETWORK LIFETIME QUALITY IN WSN UTILIZING POWER BALANCED ROUTING METHOD
Sandeep Bhardwaj¹, Prof. (Dr.) Pratap Singh Patwal²
¹Research Scholar, School of Technology and Computer Science, Glocal University, Mirzapur Pole Saharanpur (U. P.) India.
2Research Supervisor, School of Technology and Computer Science, Glocal University, Mirzapur Pole Saharanpur (U.P) India.
ABSTRACT
Wireless Sensor Networks is a real time system that is used in communication system. The WSN consists of nodes with the insufficient power to collect the important information from the field. So many researchers use a different algorithm to prolong the network lifetime they are DEFL, MTE, and MDR. In this work we have proposed an Artificial Bee Colony algorithm. This is an energy efficient algorithm and consumes energy with balancing to increase the network lifetime with optimal path and reduce a packet loss. Algorithm quickly identifies the shortest path on each
node. It is optimizing the routing paths and provides a successful multipath data transmission.
Keywords –
SOLAR GRID QUALITY ANALYSIS AND ENERGY OUTPUT PREDICTION
M Satish Kumar¹, K P Charun², R Anitha³, C Deepthi4, G Venkateswara Madhav5
¹Associate Professor/MCA M. Tech, Sri Venkateswara College of Engineering and Technology (Autonomous) Chittoor, Andhra Pradesh-517217
2,3,4,5MCA Students, Sri Venkateswara College of Engineering and Technology (Autonomous) Chittoor, Andhra Pradesh-517217
ABSTRACT
The impending global energy crisis necessitates innovative strategies to maximize the use of renewable energy sources. As non-renewable resources deplete rapidly due to increasing industrial and residential demands, the urgency of embracing renewable alternatives, especially solar energy, becomes crucial. However, the operational challenges inherent in solar energy infrastructure must be effectively addressed. In this context, we introduce a sophisticated framework designed to intelligently forecast the future energy output of solar panels within a solar power station. Simultaneously, our framework aims to identify and evaluate the condition of solar panels, pre-empting any anomalies that could compromise energy generation efficiency. By harnessing advanced machine learning and deep learning techniques, our automated approach achieves significantly improved accuracy compared to traditional methods, thereby unlocking the full potential of artificial intelligence in managing renewable energy.
Keywords – Solar Grid Performance, Quality Analysis, Energy Output Prediction, Photovoltaic System Efficiency, Renewable Energy Forecasting.
UNEQUAL CLUSTERING AND ROUTING PROTOCOL FOR A SUSTAINABLE WSN-BASED INTERNET OF THINGS BASED ON GREY WOLF OPTIMIZATION AND FUZZY LOGIC
Sandeep Bhardwaj¹, Prof. (Dr.) Pratap Singh Patwal²
¹Research Scholar, School of Technology and Computer Science, Glocal University, Mirzapur Pole Saharanpur (U. P.) India.
²Research Supervisor, School of Technology and Computer Science, Glocal University, Mirzapur Pole Saharanpur (U.P) India.
ABSTRACT
With the ever-growing application of Wireless Sensor Networks (WSN)-based Internet of Things (IoT), it has gained enormous attention in the public and research domains. The energy constraint of WSN limits its applicability. In the paper, we have proposed a hybrid of Grey Wolf Optimisation along with Fuzzy Logic (FL) for energy-efficient Cluster Head (CH) selection, cluster formation, and cost-effective routing which improves Quality of Service (QoS) that can enhance the applicability of WSN in the diverse domains of IoT. The proposed work is simulated, and performance assessment is done on the basis of QoS metrics namely FND, HND, throughput, average energy, average node load and latency. The obtained results exhibit significant enhancement in the network lifetime with an enhanced stability period, higher throughput, reduced latency, and lessen traffic load and load-balanced network towards its comparative making it suitable for wide applicability in WSN based IoT.
Keywords – Grey Wolf Optimisation, Fuzzy Logic, Unequal Clustering, Routing, Energy Efficiency, WSN, IoT.
A REVIEW STUDY ON THE PROPERTIES AND THE APPLICATION OF LASER IN DIFFERENT ASPECT
Aliza Imran1, Chirag Jain2, Vinay Makhija3, Manoj Pathak4, Dr. Pradeep Kumar Sharma5
ABSTRACT
Light Amplification by Stimulated Emission of Radiation (LASER) was introduced in 1960 by Theodore Mainman. LASER works on the principle of stimulated emission, it has properties of coherency and a high amount of monochromaticity making it reach extremely high powers. LASER has fulfilled many applications in various industries, be it optical communication and storage, LASER cutting and machining, LIDAR, military and defense, meteorology and geophysical applications, LASER imaging and holography, healthcare and aesthetics, and many more. The applications are widespread in various industries and continue to expand till date. This paper will focus on delivering the excerpt of various applications and advancements in LASER technology.
DOI – 10.30696/JAC.XVIII.1.2024.128-141
Keywords – LIDAR, Optical Communication, Military and Defence, Healthcare, Microlasers.
ENVIORNMENT AND OZONE LAYER REDUCTION
Dr. Avani Pareek1, Dr. Barkha shrivastava2, Rekha Vijay3
1,2Associate Professor, JECRC Foundation, Jaipur
3Assistant Professor, JECRC Foundation, Jaipur
ABSTRACT
Ozone, or O3, a stratospheric layer, plays a major role in human survival. It acts as a shield, absorbing most of the sun’s UV radiation. It is approximately 15–35 kilometres above Earth’s surface. There are regional and seasonal differences in the thickness of the ozone layer. It is necessary for a number of planetary, biological, and environmental events. There are many different situations where what people do have a significant effect on the environment. Ozone layer damage is one of these. Examining the causes, mechanisms, biological impacts, and mitigation strategies for the ozone layer’s depletion is the aim of this essay. Chlorofluorocarbons and halons are potent ozone depleters. The ozone layer’s predicted depletion is a major source of concern for both the environment and human health due to the expected increase in UV radiation received at the earth’s surface. The prospects for ozone recovery are yet unknown. As part of a review study, data regarding the effects of ozone depletion on humans was analysed and compiled from a variety of sources, including e-books, yearly and environmental reports from respectable organizations, and several articles published in international journals.
DOI – 10.30696/JAC.XVIII.1.2024.142-151
Keywords –UV radiation, chloro-floro carbon, atomic oxygen, ozone.
EFFECT OF CLIMATE CHANGES
Dr. Barkha shrivastava1, Dr. Avani Pareek2, Rekha Vijay3
1,2Associate Professor, JECRC Foundation, Jaipur
3Assistant Professor, JECRC Foundation, Jaipur
ABSTRACT
Climate change is a significant factor that puts the lives of all people on Earth in danger. Long-term human changes, innate natural processes, outside pressure, or any combination of these can all lead to changes in climate. According to data gathered from ice cores and other sources, climate change is to blame for the acknowledged extreme temperature variations, increase in greenhouse gas emissions, and sea level changes that have been observed over the preceding centuries and even decades. The increase in greenhouse gas emissions will have a substantial effect on important sectors of the global economy, including industry and agriculture. Human welfare and health services would suffer as a result, and advancement would be hampered overall. Large sections of many factors, such as rising sea levels and decreasing temperatures, will cause the planet to become uninhabitable; however, some scientists believe that the likelihood of a new ice age starting has been delayed or slowed down by the increase in greenhouse gas concentrations.
We have discussed every scenario that could arise from climate change, such as rising sea levels, increased temperatures, greenhouse gas emissions, and other dire consequences for all living species of plants and animals as well as people.
DOI – 10.30696/JAC.XVIII.1.2024.152-156
Keywords – Climate Change, Environment, Anthropogenic Changes, Greenhouse Gases, Sea Level Change.
REAL TIME MOBILE APPLICATION FOR WILDLIFE DETECTION
Harshul Vatsa1, Himanshu Verma2, Vishal Saxena3, Pradeep Kumar Sharma4, S. K. Dixit5
ABSTRACT
The human beings massively depend on the natural assets and bounties for their survival but the tragedy at play is, we hardly opt to give a wee bit back to the nature. Well, to society’s books, we thought of adding a genuine page of care and action for the animals. As the tech savvy generation, technology came to our first sight for showering any contribution to the good. Tracking and detecting animals has never been an easy task for any geography. This put our minds to hustle for a solution benefitting both human and the animals by making their unnecessary encounters lesser. So, through this work an application is developed that would be using the power of image recognition to identify the different wildlife animals all around us and to transmit the animal’s location in real-time as well as maintain a database of their geographical presence.
DOI – 10.30696/JAC.XVIII.1.2024.157-163
Keywords –System Monitoring, Wildlife Detection, Wildlife Protection.
HUMAN VALUES IN THE COMMUNITY
Dr. Rekha Mithal1, Dr.Kamlesh Maharwal2, Amit Mithal3
1Professor, Department of Chemistry, Jaipur Engineering College & Research Centre, Jaipur, India
2Librarian, Jaipur Engineering College & Research Centre, Jaipur, India
3Associate Professor, Department of Computer Science & Engineering, Jaipur Engineering College & Research Centre, Jaipur, India
ABSTRACT
Without human values, human civilization might not be able to survive very long. It is imperative that we have this conversation and raise awareness of human values in today’s culture. Human values serve as both the foundation and tenets of existence. They are necessary for people to behave well. There is no getting around the fact that there are many crises facing the modern global civilization. The contemporary society is well aware of the human worth issue. Values that are fundamental to being human are referred to as basic human values. Since they highlight the underlying goodness of both individuals and society as a whole, values like truth, honesty.
DOI – 10.30696/JAC.XVIII.1.2024.164-168
Keywords –Values, society, culture.
REAL TIME AWSS INTEGRATION WITH CENTRALISED MILITARY CLOUD DATABASE AND ML
Kashish Parwani1, Abhishek Matoria2
Associate Professor1, Jaipur Engineering College and Research Centre, Jaipur
Student2, Jaipur Engineering College and Research Centre, Jaipur
ABSTRACT
This paper explores the integration of automatic weapons systems (AWSs) with military cloud computing, databases, and machine learning (ML). Cloud-based ML offers advantages for AWS by enabling faster data processing, improved target recognition, and real-time decision-making. However, the integration presents challenges in communication, data security, and ethical considerations. The paper investigates these challenges and proposes solutions for secure, reliable, and responsible implementation. By examining the technical aspects and ethical implications, this research aims to inform the development of a robust framework for integrating AWS with military cloud and ML technologies. This framework can ensure the effectiveness of AWS while maintaining ethical principles and mitigating safety risks.
DOI – 10.30696/JAC.XVIII.1.2024.169-173
Keywords – Log Automatic Weapons Systems (AWSs), Machine Learning (ML), Cloud Computing.
A REVIEW STUDY ON ROBOTIC HEALTHCARE REVOLUTION
Khushi Kothari1, Kinjal Jain2, Harshil Jain3, Vishal Saxena4, Manoj Pathak5
1Jaipur Engineering College and Research Center, Jaipur
ABSTRACT
The past two decades have witnessed the rise of robotics as a challenging, emerging, developing and innovative field of research for academicians and industries. Robot can be defined as a machine that is capable of taking on a wide range of tasks with more autonomy and degree of freedom (DoF) than human beings. Presently, healthcare services and systems have become very complicated and include several entities that are marked by shared, distributed, heterogeneous devices, sensors together with information and communication technology or ICT. Internet of things (IoT) has integrated robots in things so that they connect with other things via internet. The application of robotics in healthcare facilities has guaranteed possibilities in the course of treating patients, increasing relief of clinicians and avoiding the patients as well as the healthcare staff. This chapter shows clearly the long terms benefits of people’s existence in healthcare facilities such as e-health, medical emergency using robotics and IoT.
DOI – 10.30696/JAC.XVIII.1.2024.174-183
Keywords – Medical robotics, Healthcare robotics, Assistive robotics, Rehabilitation robotics, Surgical robotics, Health design, Health information technology, Evidence based medicine.
REVIEW OF INVISIBLE BARRIERS: SECURITY AND PRIVACY RISKS IN IoT APPLICATIONS
Mahima Vyas1, Kashish Vijay2, Vishal Saxena3, Pradeep Kumar Sharma4, S. K. Dixit5
ABSTRACT
Internet of things (IoT) is an interconnected wireless network where smart nodes (IoT devices) interact with each other in order to exchange data through the communicating medium. The Internet of things (IoT) and other contemporary ideas promise to improve quality of life, better business potential, economic production, and effective management of operation through universal connection and the introduction intelligent physical items. IoT networks are capable of collecting, pre- rocessing and transmitting massive amounts of data. IoT opened doors for better communication for people. But the attacker opened doors of attacks to IoT systems to make use of user’s sensitive information. Given that these networks deal with real word part of our lives as well as critical infrastructure, cyber security in such networks is critical. This study delves into the critical security and privacy concerns that arise within the Application layer of IoT systems. We systematically review and categorize the prevalent threats, including data breaches, unauthorized access, and privacy invansion, highlighting how these vulnerabilities can be exploited by malicious actors.
DOI – 10.30696/JAC.XVIII.1.2024.184-192
Keywords –Internet of things (IoT), Application layer, Security concern, Privacy concern, Universal connections, Data Breaches.
ARTIFICIAL INTELLIGENCE IN HEALTHCARE: TRANSFORMING PATIENT CARE AND ADVANCING MEDICAL RESEARCH
Muskan Goyal1, Mridul Khandelwal2, Ms. Monika Yadav3
1,2Student, Jaipur Engineering College and Research Centre, Jaipur, Rajasthan ,India
3Assistant Professor, Department of CSE, Jaipur Engineering College and Research Centre, Jaipur, Rajasthan , India
ABSTRACT
Artificial intelligence, through improving diagnostic accuracy, is personalizing treatments and expediting drug discovery in healthcare. This paper is aimed at some of those advancements, methodologies, case studies, and associated ethical and implementation challenges in AI for healthcare. Artificial intelligence, in all forms—machine learning, natural language processing, and computer vision—is finding increasingly wider integration into the healthcare system worldwide. The capability of AI to analyze large volumes of data and detect patterns beyond human capability is a driver for major advancements in the care of patients and in medical research. Based on the analysis of recent developments and case studies, this study has brought out the fact that AI is redefining healthcare delivery and research methodologies in offering novel opportunities toward enhancing patient outcomes and fostering innovation.
DOI – 10.30696/JAC.XVIII.1.2024.193-200
Keywords – Artificial Intelligence, Healthcare, Machine Learning, Patient Outcomes
ESTIMATION OF QUALITY TRAITS IN INDIAN MUSTARD AFTER MUTATION
Purnima sogarwal1, Gharvit singhal1, Bhavna sharma1, Uma sharma1, Arun kumar2, Anukool vaishnav1, Anubhuti sharma2
1Department of Biotechnology GLA University, Mathura
2ICAR-DRMR Sewar, Bharatpur
ABSTRACT
Indian mustard PM21 and PM30, were pre-treated with gamma rays and EMS (Ethyl methyl sulphate) at varying concentrate with increasing exposure time. When compared to the control, the antioxidant capacity has increased while phytic acid concentration decreased. EMS treatment and gamma rays enhances the free radical scavenging activity. Our results shows increased nutritional traits after treatment and reduction of antinutritional parameters, because it provides increased nutritional benefits. Furthermore, Phytic acid and glucosinolates were also effectively reduced by mutation.
DOI – 10.30696/JAC.XVIII.1.2024.201-209
Keywords – Gamma radiation, Indian mustard, and EMS, Glucosinolates, Phytic acid antioxidants.
ARTIFICIAL INTELLIGENCE AND ITS IMPORTANCE
Dr. Rekha Mithal1, Amit Mithal2, Dr. U.K Pareek3
1Professor, Department of Chemistry, Jaipur Engineering College & Research Centre, Jaipur, India
2 Associate Professor, Department of Computer Science & Engineering, Jaipur Engineering College & Research Centre, Jaipur, India
3Professor, Department of Mathematics, Jaipur Engineering College & Research Centre, Jaipur, India
ABSTRACT
Computerized reasoning (A.I.) is a multidisciplinary field whose objective is to mechanize exercises that by and large requires human knowledge. Late outcome in A.I. incorporates mechanized clinical diagnosticians and framework that consequently tweaked equipment to specific prerequisites. Generally, generative A.I. and human conceptual reasoning are two unique things. Generative A.I. can be an amazing asset for creating new satisfied entities. However it’s anything, but a swap for human.
DOI – 10.30696/JAC.XVIII.1.2024.210-214
Keywords –A.I and applications in different fields.
RFID TECHNOLOGY INTEGRATION IN LIBRARIES: AN ANALYSIS
Kamlesh Maharwal1, RekhaMithal2, Rohini Mahajan3, Sunil Kumar Srivastava4
1,2,3,4Jaipur Engineering College and Research Centre, Jaipur, Rajasthan, India
ABSTRACT
This investigative piece offers an all-inclusive guide for the effective use of Radio- requency Identification (RFID) technology into higher education libraries. RFID technology provides a novel way to improve security, expedite library operations, and reduce stoner gestures. The document provides a step-by-step implementation framework that includes staff training, stoner education, software integration, needs assessment, budget allocation, and RFID factor selection. The composition also emphasizes how important it is to have security features like anti-theft systems and checkout stations that are pleasant to stoners. RIFD can be considered to be an effective tool for higher education libraries that are planning to upgrade their library services. It can assist in monitoring of various operations as well as ensuring compliance to the norms.
DOI – 10.30696/JAC.XVIII.1.2024.215-219
Keywords –RFID, Education, automation of libraries, Management, Identification.
OPTIMIZING WEB PERFORMANCE: A REVIEW OF CURRENT TECHNIQUES
Harshul Vatsa1, Himanshu Verma2, Manoj Pathak3, S. K. Dixit4
ABSTRACT
This paper highlights current web development technologies in the IT industry and its measure. Developers of web-based applications are confronted with a bewildering array of available choice formats, languages, frameworks, and technical objects. They investigate, identify, and evaluate technology for creating Web applications. They determine that although most of the Web’s connection issues have been resolved. The confusion of technology for Web-based apps that this area lacks a dependable model that is suited to it.
DOI – 10.30696/JAC.XVIII.1.2024.220-225
Keywords – Back-end and Front-end development.
ROLE OF COMMUNICATION SKILLS IN PERSONALITY DEVELOPMENT
Saguna Chaturvedi1, Rashmi Kaushik2
1Associate Professor, JECRC Foundation, Jaipur
2Associate Professor, Jagannath University, Jaipur
ABSTRACT
Glowing smile is the first thing that enables people to connect. A smile of confidence can prepare the platform of a better personality reflecting uniqueness and attraction. The way you communicate with others, your word choice, your physical movement, your capacity to cope up with unpleasant situation mark the standard of your personality. My present study in this paper deals with the development of personality through communication skills. The author also tries to highlight the effectiveness of communication skills on the development of personality, and various tips for improving our personality as well as skills of communication at the same time. A good personality helps us to create a harmonious family, society, country, and the world. A good person, having knowledge of maintaining social, economic, religious and political diversities, can give a sweet smile and say goodbye to bitter circumstances, and thus, establishes his or her dynamic personality.
DOI – 10.30696/JAC.XVIII.1.2024.226-230
Keywords – Communication, Personality, Effective, Development, Skill.
STUDY OF HARMFUL EFFECTS OF RADON AND OTHER NATURALLY OCCURRING RADIATIONS
Sarita Garg1, Seema Bansal2, Swarnima3
1,2Department of Physics, Jaipur Engineering College and Research center, Jaipur India
3Department of Civil Engineering, Jaipur Engineering College and Research center, Jaipur India
ABSTRACT
The past two decades have witnessed the rise of robotics as a challenging, emerging, developing and innovative field of research for academicians and industries. Robot can be defined as a machine that is capable of taking on a wide range of tasks with more autonomy and degree of freedom (DoF) than human beings. Presently, healthcare services and systems have become very complicated and include several entities that are marked by shared, distributed, heterogeneous devices, sensors together with information and communication technology or ICT. Internet of things (IoT) has integrated robots in things so that they connect with other things via internet. The application of robotics in healthcare facilities has guaranteed possibilities in the course of treating patients, increasing relief of clinicians and avoiding the patients as well as the healthcare staff. This chapter shows clearly the long terms benefits of people’s existence in healthcare facilities such as e-health, medical emergency using robotics and IoT.
DOI – 10.30696/JAC.XVIII.1.2024.231-238
Keywords – Medical robotics, Healthcare robotics, Assistive robotics, Rehabilitation robotics, Surgical robotics, Health design, Health information technology, Evidence based medicine.
AUTONOMOUS DATA FACTORIES: LEVERAGING GENERATIVE AI FOR OPTIMIZATION
Kashish Parwani1, Sandeep Das2, Sarvam Mittal3, Rahul Raj4
1Associate Professor JECRC Jaipur, India
2Data DevOps Engineer at EPAM Systems Limited, Gurgaon, India,
3IT analyst at TCS Pune, India, 4 System Engineer, Indore, India
ABSTRACT
The paradigm shift towards autonomous data factories has revolutionized contemporary data management practices, aiming to automate tasks across the data lifecycle. In this paper, we explore the potential of leveraging generative artificial intelligence (AI) techniques to enable self-adaptation and optimization within autonomous data factory environments. Specifically, we investigate methodologies such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) and their applicability in automating data generation, content creation, and model refinement processes. By harnessing generative AI capabilities, data factories can evolve into dynamic ecosystems capable of responding to evolving data requirements and optimizing system performance in real-time. We discuss the challenges and opportunities associated with implementing generative AI in autonomous data factories and provide insights into future research directions in this burgeoning field.
DOI – 10.30696/JAC.XVIII.1.2024.239-245
Keywords – Autonomous data factories, generative artificial intelligence, self-adaptation, optimization, Generative Adversarial Networks, Variational Autoencoders.
FLUORIDE IN GROUND WATER OF RAJASTHAN, INDIA A CHALLENGING TOXICOLOGICAL AND GEO ENVIRONMENTAL ISSUE: A REVIEW
Shalini Kulshrestha1
1Professor, Department of Chemistry, Jaipur Engineering College & Research Centre, Jaipur, India
ABSTRACT
Fluoride is often called a two-edged sword, inadequate intake of fluoride causes dental caries whereas excess intake causes dental and skeletal fluorosis and other ill effects on human health. Its excess ingestion into human body slowly converts the working, productive and healthy population into nonfunctional, unproductive and burden on society. The seriously affected people become a live dead body which does not able to perform their daily life function. It becomes an evil for socioeconomic, mental, physical and healthy development of affected population in world wide. The major sources of fluoride in water are geogenic and anthropogenic. Excess ingestion of fluoride affects not only calciferous tissues but other tissues and physiology of human body also. The health problems linked to fluoride are depend on socioeconomic status, literacy level, nutrition level, geography of habitation and availability of facilities to population. This paper presents a review, which focuses on the sources of fluoride in drinking water, status and its ill effects on habitants in Rajasthan, which becomes a big challenging toxicological and geo-environmental issue.
DOI – 10.30696/JAC.XVIII.1.2024.246-254
Keywords –Fluoride, dental fluorosis, skeletal fluorosis, geogenic and anthropogenic.
A COMPREHENSIVE STUDY ON VARIOUS ASPECTS OF GENERATIVE ADVERSARIAL NETWORKS (GANS)
Avi Maheshwari1, Akash Kumawat2, Aakash Gupta3, Dr. Sunil Srivastva4
1,2,3Students, JECRC Jaipur, India
4Associate Professor, JECRC Jaipur, India
ABSTRACT
GANs have emerged as one of the foundational frameworks of contemporary generative learning, providing state of the art solutions for generation as well as data augmentation. In this detailed work, we explore the specifics of GANs to include a description of their raw ideas, structural complexities, and the training of the adversaries that allow the GANs to work. At the center of GANs is the learning process of the generator and discriminator, a pair that is engaged in a principled form of deceit concluding in the formula for the loss function that defines the learning process. The paper also discusses other types of GANs which are a small subset of GAN classes that have been uniquely designed to address various hurdles or improve the performance of these models in particular tasks. Starting from image generation to more bandwidth and advanced domain adaptation tasks, GANs have established their supremacy. But we also know that the road to full attainment of the capabilities of GANs is not without some challenges; this paper also discusses the challenges and limitations within GANs such as training instability and mode collapse problems, and possible resolution to them. At the end of the paper, the authors discuss possible future trends in GAN research and development, underlining the requirement of better stability, targeted, and explainable models. In an attempt to present the concept of GANs in simple terms, this research paper will seek to avoid the use of overly technical language to explain the concept of the technology to readers, as well as to general readers interested in knowing more about this type of self-supervising unsupervised learning algorithm so as to be useful reference body of information for anybody who wishes to get acquainted with or work on this technology in any possible following advancements.
DOI – 10.30696/JAC.XVIII.1.2024.255-271
Keywords – Generative Adversarial Network, Unsupervised Learning, Generator, Discriminator, Convolutional Neural Network, loss function, biases, weights.
DNA: THE ULTIMATE DATA-STORAGE SOLUTION
Dr. Tripati Gupta1, Ronak Khandelwal2, Riya Sharma3, Milan Verma4
1Associate Professor, Department of Mathematics, Jaipur Engineering College and
Research Centre, Jaipur, Rajasthan, India
2, 3, 4 Students Jaipur Engineering College and Research Centre, Jaipur, Rajasthan, India
ABSTRACT
The global demand for data storage is currently outpacing the world’s storage capabilities. DNA, the carrier of natural genetic information, offers a stable, resource- and energy-efficient and sustainable data storage solution. In this review, we summarize the fundamental theory, research history, and technical challenges of DNA storage. From a quantitative perspective, we evaluate the prospect of DNA, and organic polymers in general, as a novel class of data storage medium [1].
DOI – 10.30696/JAC.XVIII.1.2024.272-280
Keywords –DNA storage, information, Carbon coding
REVIEW ON ENVIRONMENTAL AWARENESS AND CLIMATE CHANGE
1U.K.Pareek, 2Yaghvendra Kumawat, 3Rekha Mithal ,4Pradeep Sharma & 5Naveen
Goyal
1, 2,3,4Jaipur Engineering College and Research Center, Jaipur Rajasthan
5Student, Jaipur Engineering College and Research Center, Jaipur Rajasthan
ABSTRACT
Environmental awareness is the idea of being well informed about the environment. It refers to the set of principles, opinions, and modals that help us contribute to the well-being of the natural environment thus analyzing and understanding the problems associated with it. Environmental awareness is the recognition of the delicate balance between human activities and the natural world. It encompasses the understanding of the interconnectedness of ecosystems, the impact of human actions on the environment, and the importance of sustainable practices for the well-being of both present and future generations.
DOI – 10.30696/JAC.XVIII.1.2024.281-287
Keywords – Environmental Psychology, Green washing and Misinformation, climate change, global warming.
SOME INFINITE AND FINITE SUMMATION FORMULAE INVOLVING I-FUNCTION
Yaghvendra Kumawat1, Chandan Singh Ujarari2 , Umesh Kumar Pareek3, Sunil Kumar Srivastava4
1,3,4Associate Professor, Department of Mathematics, Jaipur Engineering college and Research Centre, Jaipur, Rajasthan, India
2Assistant Professor, Department of Mathematics, Graphic Era Hill University, Dehradun, India.
Rajasthan, India
ABSTRACT
In this paper we shall obtain some infinite and finite summation formulae involving I-function. A large number of finite and infinite series for I-function can be summed up by using the well-known summation theorems for ordinary hypergeometric series in the main results. The method used in deriving these series is also simple and direct and does not impose heavy restrictions on the parameters. These summation formulae are of interest in themselves and yield, in turn, a large number of other results as their particular cases. We present one particular case of our main summation formulas, which are also novel and interesting on their own, as an illustration.
DOI – 10.30696/JAC.XVIII.1.2024.288-296
Keywords –
EXPLORING THE EFFICACY OF ROLLUPS’ A COMPARATIVE STUDY OF OPTIMISTIC AND ZK ROLLUPS AND THEIR POPULAR IMPLEMENTATIONS
Akshita Jain1, Yogita Punjabi 2, Ruchi Mathur 3
1Student, Jaipur Engineering College and Research Centre (JECRC Foundation), Jaipur, India
2Asst. Professor, Jaipur Engineering College and Research Centre (JECRC Foundation), Jaipur, India
3Professor, Jaipur Engineering College and Research Centre (JECRC Foundation), Jaipur, India
ABSTRACT
Scalability is a grave challenge for blockchain technology with consequent repercussions on performance. In recent years, scaling Ethereum has been one of the most deliberated and trending subjects in the crypto and blockchain space. This debate particularly intensifies during periods of high network activity, such as the craze of CryptoKitties in 2017, 2020’s DeFi Summer, and 2021’s crypto bull market. Lately, network congestion has intensified significantly due to the rising popularity of Decentralized Finance (DeFi), Non-fungible tokens (NFTs) and yield farming. The unparalleled surges in demand during these times, resulted in tremendously high gas fees, making it hard and expensive for commonplace users to pay for their transactions. To overcome these limitations, this paper aims at analysing the available Layer II scalability solutions while highlighting the main differences among the examined frameworks, while focusing on theoretical as well as practical real world aspects. The first section is an introduction about the scalability issue, the blockchain trilemma and the available layers of solutions. It gives a small overview about Layer1 solutions and the concept of sidechain and then dwells in depth on Layer 2 solutions. Since the Ethereum Layer 2 (L2s) ecosystem has grown tremendously in terms of the number of available systems, system architectures, and their complexity, a deep understanding of these systems is increasingly imperative. So, in the second section, we address the question of what are layer 2 scalability solutions and what do they offer, by doing a comparative study of types of L2s and presenting a tabular summary of the same. Then we analyse the trends and key aspects such as scalability, security, decentralization, privacy, etc. and conclude that rollups are the most effective and adopted solution. With their potential to significantly boost blockchain scalability while preserving transaction privacy and security, they are rightly referred as the Holy Grail of scaling. In the third section of our paper we then answer the questions: What advantages do Rollups offer? And, how have they become the most anticipated and awaited scaling solution of them all? We then present a comparison between Optimistic and Zk Rollup. Through comparative evaluations and discussions of technical challenges and future directions, we elucidate zkRollup’s role in shaping the future of decentralized systems and the blockchain technology. In section four, we will do an in-depth breakdown of the implementations of Optimistic and Zk Rollup, by highlighting their potential and analysing the Zero knowledge proofs. We then conclude this paper by providing insights into Emerging Trends, Potential Enhancements and topics for future research and development on rollups and blockchain technology as a whole.
DOI – 10.30696/JAC.XVIII.1.2024.297-315
Keywords –Blockchain, Ethereum, scalability, rollups, optimistic, zk, implementations, zkproofs, Layer-2.
TECHNOLOGY INTEGRATION IN ENGLISH LANGUAGE TEACHING AND LEARNING: BENEFITS AND CHALLENGES
Sonia Khubchandani1, Prakhar Sharma2, Rakshit Gupta3
Associate Professor, Jaipur Engineering College and Research Centre, Jaipur
Student2,3, Jaipur Engineering College and Research Centre, Jaipur
ABSTRACT
The aim of the paper is gathering evidence of the series of benefits of technology integration in English language teaching and learning, if there are so, what obstacles and challenges emerge and how they are overcome. This study investigates series of experiences, benefits of integrating technology in English Language learning in Indonesia. Moreover, this work explains what challenges that need to be overcome in integrating technology in language learning. Data is obtained through interview technique. This study employs qualitative analysis in order to obtain information about what experiences, benefits and challenges in using technology in language learning. This study involves seven participants. The results show that some benefits of integrating technology in English language learning are learners can do some coding, practice online quizzes or tests, improve speed of answering questions, improve scores in English tests, learn another foreign language, do some collaborative learning, encourage independent learning, have opportunities to write, speak, listen, and read in English, do online learning, get online references, use of multiple computer application, obtain the latest information, translate, have opportunities to use multi-media presentation as well as demonstrate new method of teaching. Some challenges in technology integration are type of technology used, the rapid changes of technology development, the number of classes taught, class size, cost, time, age, lecturers’ workload, ability to use.
DOI – 10.30696/JAC.XVIII.1.2024.316-331
Keywords –technology, language learning, challenges and obstacles.
A STUDY ON CEMENT REPLACEMENT WITH GLASS POWDER
Swarnima1, Seema Bansal2, Abhinav Aggarwal3, Deepti4, Sarita Garg5
1,3Assistant Professor, Jaipur Engineering college & Research Centre, Jaipur
2Associate Professor, Jaipur Engineering college & Research Centre, Jaipur
5Professor, Jaipur Engineering college & Research Centre, Jaipur
4Assistant Professor, Kanoria PG Mahila Mahavidhyalaya, Jaipur
ABSTRACT
In daily life we use glass in many forms. Glass is non-biodegradable material so it does not provide an environment friendly solution. Because of this, there is strong need to use waste glasses. The aim of this present work was to use glass powder as a replacement of cement to assess the pozzolanic activity of fine glass powder in concrete. This paper summarizes information on the mechanical & durability properties of cement containing a fine glass powder. It is shown on this paper that concrete mixtures could be proportioned to achieve similar or higher compressive strengths. This investigation looks at the partial replacement of cement by waste glass powder. Glass powder is replaced separately for both 200 microns and 400 microns for every 10%, 20%, 30% and 40%. These results are compared with nominal concrete (0% replacement of glass powder).
DOI – 10.30696/JAC.XVIII.1.2024.332-342
Keywords – Glass powder, Fine aggregate, Coarse aggregate, Compressive strength, Split tensile strength Flexural strength.
INTERNET OF THINGS (IoT) IN HEALTHCARE
Radha Dubey1, Prachee Bagoria2, Mr. Daulat Ram Beniwal3
1,2Student, Jaipur Engineering College and Research Centre, Jaipur, Rajasthan, India
3AssistantProfessor, Department of CSE, Jaipur Engineering College and Research Centre, Jaipur, Rajasthan, India.
ABSTRACT
The potential of integrating the Internet of Things (IoT) into healthcare has revolutionized the sector in ways never witnessed before. IoT facilitates the interconnecting of devices, capturing data, and information exchange in real-time, considerably improving health monitoring, diagnosis, and management of disease conditions. The proposed research is aimed at exploring the use of IoT for advancing personalized healthcare. It focuses on IoT’s capabilities in real-time health condition monitoring, early diagnosis, delivering tailor-made care, and enhancing the overall efficiency of the healthcare system. The methods used in the research will include both qualitative and quantitative approaches, including a literature review on IoT applications within healthcare and data analysis from case studies on the application of IoT technology for personalized healthcare. The findings of the study underline the good prospects for IoT application to be used in enhancing personalized healthcare, including remote patient monitoring, data-driven disease prediction, tailoring treatment customization, and cost efficiency within the healthcare system. However, the process of applying IoT technology also comes with its challenges, such as data privacy, system security, and cross-platform integration, which have to be overcome to reap full benefits. The study thus concludes that the application of IoT in healthcare promises an effective and efficient future in the area of personalized healthcare. However, technical, ethical, and security challenges must be overcome in order to have successful implementation. Understanding the benefits and risks associated with IoT adoption in healthcare will allow necessary measures to be undertaken to ensure improved personalized healthcare in the future.[4][12]
DOI – 10.30696/JAC.XVIII.1.2024.343-350
Keywords – IoT, Healthcare, Real-time patient monitoring, Data privacy, Personalized healthcare.
REVIEW OF MACHINE LEARNING ALGORITHMS FOR IT OPERATIONS
Manju Vyas1, Anima Sharma2, Deepika Bansal3, Neelkamal Chaudhary
Jaipur Engineering College & Research Centre, Jaipur, India
ABSTRACT
In today’s dynamic landscape, Earthquakes pose significant threats to human safety, infrastructure, and the environment. The accurate prediction of earthquakes is necessary for the development of early warning systems, disaster planning, risk assessment, and scientific research. This project aims to predict the magnitude and probability of Earthquakes occurring in a particular region from the historical data of that region using various Machine learning models. Early prediction of seismic events remains a challenging task, but advancements in machine learning and the availability of vast seismic datasets offer new opportunities for developing effective prediction models. In numerous applications and systems, it is crucial to find more efficient real-time detection of anomalies in time series data. ranging from intelligent transportation, structural health monitoring, heart disease, and earthquake prediction. Although the range of applications is wide, anomaly detection algorithms are usually domain-specific and build on experts’ knowledge. This research paper proposes a comprehensive earthquake prediction model that integrates machine learning techniques with seismological data analysis. The model aims to improve accuracy, reliability, and timeliness in forecasting seismic events, thereby contributing to enhanced preparedness and mitigation strategies. Moreover, the discussion covers regional and global seismic data sets used, and tools employed, to predict earthquakes for different geographical regions.
DOI – 10.30696/JAC.XVIII.1.2024.351-366
Keywords –Earthquake prediction, Predictive models, Technology Advancement, Machine Learning, Predictive models, Expert systems, Systematic Mapping Study (SMS).
MODELLING OF EFFECTIVE THERMAL CONDUCTIVITY OF HIGH POROSITY PERIODIC MATERIALS
1Pradeep Kumar Sharma, 2Manoj Pathak, 3Vishal Saxena, 4U.K.Pareek & 5S. K. Dixit
1, 2, 3, 4,5Jaipur Engineering College and Research Center, Jaipur
ABSTRACT
A theoretical model for predicting effective thermal conductivity (ETC) of highly porous two-phase systems has been developed. The arrangement has been divided into unit cells .For determining the effective thermal conductivity, the unit cell can be divided into two or three layers in series. The conductivity of each layer, in turn, is derived by applying the parallel law of thermal resistances. By combining these layers which are in series the effective thermal conductivity of unit cell is derived. The theoretical expressions so obtained values of effective thermal conductivity that are quit close to the experimental results.
DOI – 10.30696/JAC.XVIII.1.2024.367-378
Keywords – Effective thermal conductivity, Unit cells, Porous media, Parallel and Series resistors model.
SPIKING NEURAL NETWORK: BRIDGING THE GAP BETWEEN BIOLOGICAL BRAIN AND AI
Ankita Yadav1, Ashish Sharma2, Ruchi Mathur3, Yogita Punjabi4
1,2 Students, JECRC Jaipur, India
3Professor, JECRC Jaipur, India
4Associate Professor, JECRC Jaipur, India
ABSTRACT
Spiking neural network is a new method of artificial neural network, which is more aligned with the human brain. It considered more with neural processing and brain like intelligence. SNN is a hardware friendly and energy saving tool, which works on sparse event driven model. SNN is a powerful tool for deep learning, gradient learning, and reinforcement learning. Neural networks in AI includes interconnected artificial neurons or nodes structure, which helps further improvement in energy efficiency and processing speed of transforming information. SNN applied time series prediction and showcasing their potentialin forecasting and predictive analytics. In this paper, we will review the mechanism, training process and its algorithms for todays high demanding applications like image recognition, video recognition, natural language processing and speech recognition etc. We will know about synaptic plasticity, approximate Backpropagation through time(BPTT). This paper establish a precise mapping between the biological parameters of SNN and parameters of Deep neural network (DNN), we will talk about advantages, opportunities, challenges and its key concepts in between. Finally this paper lookout for the future development of SNN in the direction of biological mechanism, network training, network designing, computing platform, and communications.
DOI – 10.30696/JAC.XVIII.1.2024.379-396
Keywords – Neuron, Neural Network, SNNs, Supervised learning, unsupervised learning, reinforcement learning, algorithms.
LEVERAGING eBPF FOR RUNTIME SECURITY
1Neeraj Kr Singh, 2Shruti Arya & 3Abhishek Jain
1Asscociate Professor, Jaipur Engineering and Research centre, Jaipur, India
2Assistant Professor, Jaipur Engineering and Research Centre, Jaipur, India
3Assistant Professor, Jaipur Engineering and Research Centre, Jaipur, India
ABSTRACT
eBPF is considered an optimal tool for security due to its unique ability to run user-defined programs safely within the Linux kernel. This capability allows eBPF to dynamically observe, filter, and act upon system-level events without significant performance overhead. Because eBPF operates in-kernel, it has direct access to a wealth of system and network data, enabling real-time monitoring and deep visibility into system behaviour. This low-level access facilitates advanced security use cases like anomaly detection, policy enforcement, network traffic analysis, and application profiling. Additionally, eBPF’s sandboxed environment ensures that security programs run safely without compromising system stability, making it an ideal platform for robust, dynamic security solutions.
DOI – 10.30696/JAC.XVIII.1.2024.397-406
Keywords – eBPF, Runtime Security, Linux Security Module(LSM).