IMPROVING ROBUSTNESS AND SECURITY IN GENERATIVE MODELS
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
Generative models, particularly Generative Adversarial Networks (GANs), have transformed areas like image synthesis, data augmentation, and creative content generation. However, the robustness and security of these models remain critical concerns due to their susceptibility to adversarial attacks and other forms of exploitation. This paper explores the challenges in ensuring the robustness and security of generative models, reviews current methods for enhancing their resilience, and suggests future research directions to advance this important area.
Keywords – Generative Adversarial Networks (GANs), Robustness, Security, Adversarial Attacks, Adversarial Training, Defensive Distillation, Robust Optimization, Hybrid Defense Mechanisms, Explainable AI, Continuous Monitoring, Model Vulnerability, Evasion Attacks, Poisoning Attacks, Inference Attacks, Adversarial Examples, Computational Efficiency, Model Performance, Adaptive Frameworks, High-dimensional Data Representations, Model Integrity and Reliability.
REVIEW PAPER ON IMAGINARY NUMBERS IN ELECTRICAL ENGINEERING
Tripati Gupta¹, Saanuj Sharma², Saksham Jain³ Raghav Dharwal4
1Associate Professor, Department of Mathematics, Jaipur Engineering College and Research Centre, Jaipur, Rajasthan, India
2, 3,4Jaipur Engineering College and Research Centre, Jaipur, Rajasthan, India
ABSTRACT
The concept of imaginary numbers, particularly encapsulated by unit i, represents a pivotal advancement in mathematical thought, challenging traditional notions of numerical reality. Initially perceived as a paradoxical entity due to its definition as the square root of -1. This paper delves into the origins and evolution of ‘i’, tracing its roots from the early musings of mathematicians grappling with unsolvable equations to its formal integration within the framework of complex numbers. The mathematical community’s acceptance of ‘i’ as a legitimate and practical entity marked a paradigm shift, enabling solutions to previously intractable problems in fields such as electrical engineering, quantum mechanics, and signal processing.
Keywords – Electrical Engineering, Imaginary numbers.
SCALABLE MACHINE LEARNING WITH DATABRICKS: CHALLENGES AND OPPORTUNITIES
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
Scalable machine learning (ML) is essential for handling large datasets and building robust models in various domains. Databricks, a unified data analytics platform, offers a powerful environment for scalable ML, combining distributed computing capabilities with ML frameworks like Apache Spark. In this paper, we explore the challenges and opportunities associated with scalable ML on Databricks. We discuss key challenges such as data preprocessing, model training, and performance optimization, and examine strategies for overcoming these challenges. Additionally, we highlight the opportunities presented by Databricks for accelerating ML workflows, improving model scalability, and enabling real-time analytics. By addressing these challenges and leveraging the capabilities of Databricks, organizations can unlock the full potential of scalable ML for driving innovation and decision making.
Keywords – Scalable machine learning, Databricks, Apache Spark, distributed computing, challenges, opportunities.
FOURTH ORDER LAPLACE TRANSFORM IN BICOMPLEX SPACE WITH APPLICATION IN PERIODIC FUNCTION
Tripati Gupta1, Samyan Garg2
1Associate Professor, Jaipur Engineering College and Research Centre, Rajasthan
2Jayshree Periwal High School, Jaipur, Rajasthan
ABSTRACT
In this paper we will evaluate fourth order Laplace transform of Periodic function. Bicomplex numbers are pairs of complex numbers with commutative ring with unity and zero-divisors which describe physical interpretation in four dimensional space and provide large class of frequency domain.
Keywords – Bicomplex numbers, Fourth order Laplace Transform.
TOXIC COMMENT CLASSIFICATION USING NATURAL LANGUAGE PROCESSING
1MS. Punita Panwar, 2Shivam Yadav, 3Mohak Bardwa, 4Anchit Parwal, 5Ishaan Joshi
1Assistant Professor, Department of Artificial Intelligence & Data Science, JECRC College
2B.Tech Student, Department of Artificial Intelligence & Data Science, JECRC College
3B.Tech Student, Department of Artificial Intelligence & Data Science, JECRC College
4 B.Tech Student, Department of Artificial Intelligence & Data Science, JECRC College
5B.Tech Student, Department of Artificial Intelligence & Data Science, JECRC College
ABSTRACT
Deep Learning has significantly advanced the field of text classification, offering valuable applications. Techniques such as Tokenization, Stemming, and Embedding play pivotal roles in this process. This study explores the application of these techniques alongside various algorithms for classifying online comments based on toxicity levels. A neural network model is proposed for comment classification, and its accuracy is compared with other ” models including Long Short Term Memory (LSTM), Naive Bayes Support Vector Machine, Fasttext, and Convolutional Neural Network. Comments undergo tokenization or vectorization initially to generate a dictionary of words, followed by the creation of an embedding matrix. Subsequently, the comments are passed to the model for classification. The proposed model achieves an accuracy of 98.15%.
Keywords – Identification of Toxic Comments, Long Short-Term Memory, Convolutional Neural Networks, Naïve Bayesian Analysis, Support vector Machines, FastText.
BLUE BRAIN TECHNOLOGY
1Mr. AshaRam Gurjar, 2Khushi Verma, 3Jalaj Bohra, 4Rakshit Sharma
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
The brain is the most complex organ in human body. The aim of blue brain technology is to upload the complete information in the brain into a computer. We can achieve this even after the death of a human body. In this way, preserve the knowledge and intelligence. The Blue Brain technology is the latest invention in the field of neural networks. This technology will open doors in the field of artificial intelligence. The blue brain technology provides a comprehensive simulation of internal connectivity of the cerebral parts with the external artificial intelligent network. This study of human brain will lead to a total outline of the flow of the electrical signals through the brain. The intelligent neurons are a part of cortex accessible in the human brain. This new technology has made way for considerable improvement in supercomputing, also known as high performance computers.
Keywords – Blue Brain, Virtual, Artificial Intelligence, Connectivity.
DECENTRALIZED SOCIAL NETWORKS
1Mr. AshaRam Gurjar, 2Shruti Sharma, 3Raina Gupta, 4Shashank Sharma
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Decentralized social networks are emerging as a promising alternative to centralized platforms, offering increased privacy, user control, and censorship resistance. However, their widespread adoption faces challenges such as usability, scalability, regulatory compliance, and innovation. This paper explores the advantages, challenges, and future scope of decentralized social networks, highlighting the need for user-friendly interfaces, scalable solutions, regulatory engagement, and ongoing innovation. Despite these challenges, decentralized social networks have the potential to revolutionize online interaction, providing a more secure, private, and user-centric alternative to traditional social media platforms.
Keywords –
MOBILE CLOUD COMPUTING
1AshaRam Gurjar, 2Dr. U.K. Pareek, 3YashviNama, 4Vishnu Kumar, 5Subrat Shukla
1Assistant Professor, Department of Information Technology, JECRC College
2Professor, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
5B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Mobile cloud computing (MCC) has emerged as a transformative technology, enabling ubiquitous access to computational resources and services for mobile users. This paper presents a comprehensive review of MCC, existing MCC applications. This research paper explores various challenges faced by MCC, including security, band width constraints, device diversity, and Interoperability and standardization challenges. Through studies and examples, the paper showcases the practical applications and benefits of MCC in improving the efficiency, safety, and reliability cloud computing. Finally, the paper delineates prospective avenues for research and innovation in this domain, accentuating the promise of continued advancements in Mobile Cloud Computing technology.
Keywords – Mobile Cloud Computing
PRIVACY-PRESERVING KEYSTROKE AUTHENTICATION ON SMARTPHONES
1Brijesh Kumar Singh, 2Meghansh Agarwal, 3Rachit Koolwal, 4Aman Goyanka, 5Piyush Gupta
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
5B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
This study examines the feasibility of utilizing keystroke dynamics for continuous authentication of smartphone users, addressing the rising need for enhanced security measures. Traditional password based authentication methods serve as the primary defense against unauthorized access to sensitive smartphone and online data. keystroke dynamics authentication framework seamlessly integrated into modern Identity and Access Management (IAM) systems to provide continuous authentication. To protect user privacy, we incorporate privacy-preserving techniques including permutation, substitution, and suppression, preventing service providers from reconstructing the originally typed text. involves assessing authentication accuracy using real user data, with additional analysis of the impact of privacy preserving techniques on accuracy. Our findings indicate a consistent Equal Error Rate(EER) of approximately for user classification and for user clustering when applying the permutation technique, like results obtained without this technique. Conversely, employing the substitution technique leads to an EER increase of for user classification for user clustering. Additionally, the suppression technique results in a proportional escalation of EER with the number of suppressed keystrokes. This study provides insights into the practical implications of implementing keystroke dynamics for continuous smartphone authentication.
Keywords – Biometrics Technology, Fingerprint Reader, Mobile devices, Laptop,
fingerprint or Digital Security.
STUDY OF AN ADVANCE MULTICLASS LUNGS DETECTION USING MACHINE LEARNING
Brijesh Kumar Singh1, Aman Kabra2, Akhilesh Yadav3, Vinay khatri4
1 Assistant Professor, Department of Information Technology, JECRC College, Jaipur
2B.Tech Student, Department of Information Technology, JECRC College, Jaipur
3B.Tech Student, Department of Information Technology, JECRC College, Jaipur
4B.Tech Student, Department of Information Technology, JECRC College, Jaipur
ABSTRACT
Lung cancer and its various subtypes complex genetic variations represent a major challenge precise diagnoses and selection of individual treatments. The Study examines the application of advanced machine learning Multiclass classification techniques for lung cancer subtypes base donhistological and genomic data. AND comprehensive datasets covering various sample types subtypes of lung cancer, including non-small cell lung cancer (NSCLC), such as adenocarcinoma and squamous cell carcinoma-cell lung cancer and small cell lung cancer (SCLC) and Rare subtypes were used. Study used advanced machine learning, which integrates deep learning algorithms and ensemble methods for distinguishing complex patterns within Data.[1] Convolutional neural networks (CNN) were used to extract complex features from histopathological images, captures detailed characteristics specific to each cancer Subtype. Genetic data were analyzed at the same time ensemble methods such as Random Forest and Gradient enhancer that allows integration of multiple genomes functions. The developed model showed exceptional accuracy, Sensitivity and specificity in the classification of various lung tumors subtypes insights genetic markers and main histological features of the subtype Rank. analysis with advanced machine learning techniques for classifying different lung cancer subtypes based on extensive data collection, including histopathological tests images and genome profiles[2]. convolution neuron networks (CNNs) were used to extract complex spatial data. features from histological images that capture subtle nuances specific to each subtype. At the same time team methods, including Random Forest and Gradient Boost were used to analyze multivariate genomic dataholistic understanding of the genetic landscape. Our results showed exceptional performance Integrated model, characterized by high precision and sensitivity in the classification of non- small cell lung cancer (NSCLC) subtypes. such as adenocarcinoma and squamous cell carcinoma, small-cell lung cancer (SCLC) and rare subtypes. Models The prediction function has been further improved Validity analysis, explanation of the most important genetic markers and histological features essential for subtype differentiation.
Keywords – Machine Learning, CNNs, RF, CAD, NSCLC, SCLC, KNN, DL, PCA.
FACE RECOGNITION USING NEURAL NETWORK
1Brijesh Kumar Singh, 2Prabal Jain, 3Pintu Suman, 4Tanuja
1 Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Facial recognition technology has garnered significant attention due to its wide-ranging applications in security, surveillance, and personal identification systems. This paper proposes a novel approach to face recognition utilizing neural networks. Traditional methods of face recognition often rely on feature extraction techniques, such as Eigenfaces or Local Binary Patterns, followed by classification using techniques like Support Vector Machines or k-Nearest Neighbors. However, these methods may struggle with variations in lighting conditions, facial expressions, and occlusions. Overall, our study showcases the potential of neural networks, particularly CNNs, in advancing the field of facial recognition, paving the way for enhanced security systems, personalized user experiences, and improved human- computer interaction.
Keywords – Face Recognition, Convolutional Neural Network (CNN), Image Processing, Neural Networks, Classifications.
WHEN TO CROSSOVER FROM EARTH TO SPACE FOR LOWER LATENCY DATA COMMUNICATIONS?
Ms. Deepika bansal, Mitesh chouhan, Khushi Trivedi, Grahit Goyal
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
For data communications over long distances, op- tical wireless satellite networks (OWSNs) can offer lower latency than optical fiber terrestrial networks (OFTNs). However, when is it beneficial to switch or crossover from an OFTN to an OWSN for lower latency data communications? In this work, we introduce a crossover function that enables to find the crossover distance, i.e., a distance between two points on the surface of the Earth beyond which switching or crossing over from an OFTN to an OWSN for data communications between these points is useful in terms of latency. Numerical results revealthat a higher refractive index of optical fiber (or ) in an OFTN and a lower altitude of satellites (or ℎ) in an OWSN result ina shorter crossover distance. To account for the variation in the end-to end propagation distance that occurs over the OWSN,we examine the crossover function in four different scenarios. Numerical results indicate that the crossover distance varies with the end- to end propagation distance over an OWSN andis different for different scenarios. We calculate the average crossover distance over all scenarios for different ℎ and and use it to evaluate the simulation results. Furthermore, for a comparative analysis of OFTNs and OWSNs in terms of latency, we study three different OFTNs having different refractive indices and three different OWSNs having different satellite altitudes in three different scenarios for long-distance inter- continental data communications, including connections between New York and Dublin, Sao Paulo and London, and Toronto and Sydney. All three OWSNs offer better latency than OFTN2 (with 2 = 1.3) and OFTN3 (with 3 = 1.4675) in all scenarios. For example, for Toronto–Sydney connection, OWSN1 (with ℎ1 = 300 km), OWSN2 (with ℎ2 = 550 km) and OWSN3 (with ℎ3= 1,100 km) perform better than OFTN2 by 18.11%, 16.08%, and 10.30%, respectively, while they provide an improvement in latency of 27.46%, 25.67%, and 20.54%, respectively, compared to OFTN3. The OWSN1 performs better than OFTN1 (with 1= 1.1) for Sao Paulo–London and Toronto–Sydney connections by 2.23% and 3.22%, respectively, while OWSN2 outperforms OFTN1 for Toronto–Sydney connection by 0.82%. For New York–Dublin connection, all OWSNs while for Sao Paulo–London connection, OWSN2 and OWSN3 exhibit higher latency than OFTN1 as the corresponding average crossover distances are greater than the shortest terrestrial distances between cities in these scenarios. Multiple satellites (or laser inter-satellite links) on its shortest paths drive up the propagation distance to the extent that OWSN3 ends up with a higher latency than OFTN1 for the Toronto–Sydney inter-continental connection scenario although the
related average crossover distance is less than the shortest terrestrial distance between Toronto and Sydney. The challenges related to OWSNs and OFTNs that may arise from this work in future are also highlighted.
Keywords – Crossover distance, crossover function, LEO, network latency, optical fiber terrestrial networks, optical wire- less satellite networks, satellite constellations.
MULTIPLAYER – ONLINE GAMING AND NETWORKING
1Deepika Bansal, 2Prasann Parnami, 3Saksham Sharma, 4Rohit Sankhla, 5Piyush Kumar
1Assistant Professor, Department of Information Technology, JECRC, College
2B.Tech Student, Department of Information Technology, JECRC, College
3B.Tech Student, Department of Information Technology, JECRC, College
4B.Tech Student, Department of Information Technology, JECRC, College
ABSTRACT
This paper delves into the pivotal role of networking within multiplayer computer games, emphasizing its significance in facilitating seamless interactions among players. Through a comprehensive review of existing techniques, we aim to shed light on advancements geared towards enhancing networking in distributed interactive real-time applications. Our survey focuses on literature pertaining to various domains, notably military simulations, networked virtual environments, and multiplayer computer games, offering insights into the diverse research efforts within these fields. Central to our discussion are key themes such as resource management, consistency, responsiveness, and networking at the application level. By examining these aspects, we strive to provide a nuanced understanding of the complexities involved in optimizing networking performance for interactive gaming experiences. Through this exploration, we aim to elucidate the challenges faced in ensuring smooth and reliable communication between game clients and servers. Furthermore, we highlight emerging trends and innovative approaches that have emerged to tackle these challenges, offering a glimpse into the evolving landscape of networking technologies within the gaming industry. Overall, our paper serves as a valuable resource for researchers, developers, and enthusiasts alike, seeking to delve deeper into the intricacies of networking in multiplayer gaming environments.
Keywords – computer games, networked virtual environments, online entertainment, distributed interactive simulation.
FRESH FRUIT RECOGNITION USING IOT
1Ms. Deepika Bansal, 2Sanchay Jain, 3Sameer Maheshwari, 4Yashwant Sharma, 5Pratham Kumar Singh
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
5B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
The Internet of Things (IoT) has revolutionized various industries, and its application in the food industry has gained significant attention. This paper introduces an innovative IoT-based Food Freshness Detection System designed to address the critical issue of monitoring and ensuring the freshness of perishable food items. The system utilizes a combination of sensors, communication technologies, and data analytics to provide real- time information on the freshness status of food products. The detected freshness levels are then displayed on a user-friendly mobile application, empowering individuals to make informed decisions about food consumption and minimize waste.
Keywords – Crossover distance, crossover function, LEO, network latency, optical fiber terrestrial networks, optical wire- less satellite networks, satellite constellations.
CLOUD COMPUTING-EDGE COMPUTING AND CLOUD INTEGRATION
1Ms. Deepika Bansal, 2Manisha Gehlot, 3Jatin Lakhotia, 4Himanshu Mishra
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Cloud computing has revolutionized the way businesses and individuals manage and access data and applications. However, its widespread adoption has also brought forth numerous security challenges that must be addressed to ensure the integrity, confidentiality, and availability of data. It delves into the security concerns prevalent in cloud computing environments and explores various solutions proposed by researchers and practitioners. There are unique characteristics of cloud computing that contribute to its security vulnerabilities, such as multi-tenancy, resource sharing, and reliance on third-party service providers. Subsequently, it discusses the primary security threats faced by cloud users and providers, including data breaches, insider threats, denial-of service attacks, and compliance issues.
Keywords – data breaches, multi-tenancy, compliance framework, encryption.
WHEN TO CROSSOVER FROM EARTH TO SPACE FOR LOWER LATENCY DATA COMMUNICATIONS?
1Mrs. Kusum Yadav, 2Priyanshu Garg, 3Saloni shrivastav, 4Sahil chandani
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
For data communications over long distances, op- tical wireless satellite networks (OWSNs) can offer lower latency than optical fiber terrestrial networks (OFTNs). However, when is it beneficial to switch or crossover from an OFTN to an OWSN for lower latency data communications? In this work, we introduce a crossover function that enables to find the crossover distance, i.e., a distance between two points on the surface of the Earth beyond which switching or crossing over from an OFTN to an OWSN for data communications between these points is useful in terms of latency. Numerical results revealthat a higher refractive index of optical fiber (or ) in an OFTN and a lower altitude of satellites (or ℎ) in an OWSN result ina shorter crossover distance. To account for the variation in the end-to end propagation distance that occurs over the OWSN,we examine the crossover function in four different scenarios. Numerical results indicate that the crossover distance varies with the end- to end propagation distance over an OWSN andis different for different scenarios. We calculate the average crossover distance over all scenarios for different ℎ and and use it to evaluate the simulation results. Furthermore, for a comparative analysis of OFTNs and OWSNs in terms of latency, we study three different OFTNs having different refractive indices and three different OWSNs having different satellite altitudes in three different scenarios for long-distance inter- continental data communications, including connections between New York and Dublin, Sao Paulo and London, and Toronto and Sydney. All three OWSNs offer better latency than OFTN2 (with 2 = 1.3) and OFTN3 (with 3 = 1.4675) in all scenarios. For example, for Toronto–Sydney connection, OWSN1 (with ℎ1 = 300 km), OWSN2 (with ℎ2 = 550 km) and OWSN3 (with ℎ3= 1,100 km) perform better than OFTN2 by 18.11%, 16.08%, and 10.30%, respectively, while they provide an improvement in latency of 27.46%, 25.67%, and 20.54%, respectively, compared to OFTN3. The OWSN1 performs better than OFTN1 (with 1= 1.1) for Sao Paulo–London and Toronto– ydney connections by 2.23% and 3.22%, respectively, while OWSN2 outperforms OFTN1 for Toronto–Sydney connection by 0.82%. For New York–Dublin connection, all OWSNs while for Sao Paulo–London connection, OWSN2 and OWSN3 exhibit higher latency than OFTN1 as the corresponding average crossover distances are greater than the shortest terrestrial distances between cities in these scenarios. Multiple satellites (or laser inter-satellite links) on its shortest paths drive up the propagation distance to the extent that OWSN3 ends up with a higher latency than OFTN1 for the Toronto–Sydney inter-continental connection scenario although the related average crossover distance is less than the shortest terrestrial distance between Toronto and Sydney. The challenges related to OWSNs and OFTNs that may arise from this work in future are also highlighted.
Keywords – Crossover distance, crossover function, LEO, network latency, optical fiber terrestrial networks, optical wire- less satellite networks, satellite constellations.
DIGITAL VIDEO EDITING
1KusumYadav, 2Rishi Vyas, 3Kanak Soni, 4Kanheya Lal Dhakar
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Video editing can be a very tedious task, so it’s no surprise that artificial intelligence is increasingly being used to streamline the workflow or automate tedious tasks. However, it is very difficult to get an overview of what intelligent video editing tools exist in the research literature and the automation needs of video editors. So, we’ve identified the field of smart video editing tools in research and are surveying the opinions of professional video editors. We also summarized the current state of the art in artificial intelligence research with the intention of identifying what are the possibilities and current technical limitations towards truly intelligent video processing tools. The findings contribute to the understanding of the field of intelligent video editing tools, highlight unmet needs for automation, research, and provide general suggestions for further research on intelligent video editing tools.
Keywords – AI, video editing, Adobe Premier, Da Vinci Resolve.
DIFFERENTIATION IN 4G TO 5G WIRELESS SYSTEM
1Naveen Kumar Kedia, 2Aditya Shah, 3Anjali Singh, 4Gaurav Agarwal
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Our pursuit of the 5G Wireless System delves into the groundbreaking evolution of Wireless Communication technology. As the world teeters on the brink of the 5G era, this abstract delivers a succinct overview that demands attention. It underscores the existing challenges in wireless networks, confronting issues such as bandwidth limitations, high latency, IoT integration, security concerns, and the imperative for global standardization. The abstract meticulously outlines proposed solutions, placing emphasis on millimeter-wave spectrum utilization, Massive MIMO technology, network slicing, edge computing, and state-of-the-art security measures. These innovations hold the potential to revolutionize wireless connectivity, propelling us into an era of swifter and more efficient data transmission for smartphones, all the while empowering real-time applications such as IoT, autonomous vehicles, and augmented reality. It accentuates that 5G is poised to redefine human interactions with technology and society, acting as the bridge that spans the digital divide. The narrative doesn’t shy away from recognizing the significance of future work, placing particular emphasis on global standardization, advancements in security, expanded reach of edge computing, heightened user experiences, and a commitment to greater energy efficiency. The 5G wireless system stands as a beacon, promising a world that is more connected, efficient, and secure than ever before.
Keywords – 5G, millimeter wave (mmW), massive multiple input and multiple output (MIMO), IoT, small cell, mobile edge computing (MEC), beamforming.
FAKE NEWS DETECTION USING ARTIFICIAL INTELLIGENCE
1Naveen Kumar Kedia, 2Harshit Purwar, 3Yashwant Singh Sisodiya, 4Vishal Singh
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
In contemporary times, the proliferation of fake news has led to a range of issues, spanning from satirical articles to entirely fabricated stories and even instances of planned government propaganda in certain media outlets. The prevalence of fake news and a decline in trust in the media pose significant challenges with far-reaching consequences in our society. The term “fake news” has evolved beyond purposely misleading stories, with some individuals now using it to dismiss factual information that contradicts their preconceived opinions.
The impact of disinformation on American political discourse gained substantial attention, particularly in the aftermath of the presidential election. The term ‘fake news’ became widely used to describe factually incorrect and misleading articles primarily created to generate revenue through page views. This paper aims to develop a model capable of accurately predicting the likelihood that a given article is fake news. Amid media scrutiny, Face book has been a focal point of criticism and has taken steps to address the issue. The platform has implemented a feature to flag fake news for users, and they have publicly stated their efforts to distinguish such articles in an automated manner However, achieving this are a complex task. An effective algorithm must be politically unbiased, considering that fake news exists across the political spectrum, and it should provide equal balance to legitimate news sources on both ends of that spectrum. Moreover, determining the legitimacy of news articles poses a formidable challenge.
Keywords –
CROP YIELD PREDICTION USING ML TECHNIQUES
1Naveen Kumar Kedia, 2Saurabh Kumar, 3Ankit Kumar, 4Saroj
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Looking at the current situations that Indian farmers are dealing with, we have noticed that there have been a lot of suicides in India over a long period of time. The cause of these suicides is the frequent changes in the Indian Government system and the weather. Farmers may lack knowledge of the crops that are most suited to their soil’s quality, nutrients, and composition. This project that seeks to assisting farmers in evaluating the soil’s quality to ensure a decent crop production. Before cultivating in an agricultural field, the farmer might use the prediction to estimate the crop’s production. A key strategy for finding a workable and efficient solution to this issue is machine learning. The results aren’t particularly accurate given the current method, which includes manual counting, climate-smart pest management, and satellite photography. The major goal of this research is to use several machine learning approaches to forecast the agricultural production. Among the classifier models utilized here, Random Forest offers the highest accuracy, followed by Logistic Regression and Nave Bayes. By taking into account variables like temperature, rainfall, area, and other characteristics, the predictions provided by machine learning algorithms will assist farmers in choosing which crop to cultivate to induce the greatest yield. This ties the technology and agricultural sectors together.
Keywords – Agriculture, Machine Learning, Prediction, and Crop Yield.
QUANTUM CRYPTOGRAPHY
1Naveen Kumar Kedia, 2Yuvraj Upadhyay, 3Yuvraj Singh Rathore, 4Aksha Mishra
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Quantum Cryptography and Computing represent pivotal endeavors in the quest to expand human knowledge, secure our future, and fulfill our innate curiosity about the cosmos. This paper examines the multifaceted significance of space exploration and colonization, encompassing scientific, technological, economic, and existential dimensions. Through an analysis of current space exploration efforts, technological advancements driving progress, and ethical and policy considerations, this paper provides insight into the opportunities and challenges inherent in humanity’s cosmic endeavors. By critically examining the motivations, aspirations, and implications of space exploration and colonization, we aim to chart a course toward a future where humanity not only explores the cosmos but also thrives among the stars, embracing our destiny as a spacefaring species. Join us on this journey of discovery, exploration, and colonization that promises to shape the trajectory of humanity’s future among the stars.
Keywords –
BLOCKCHAIN BASED DIGITAL VOTING SYSTEM
1Nimisha swami, 2Nikita Agarwal, 3Dixit Bansal, 4Deepanshu Moorjani
1Assistant Professor, Department of Information Technology, JECRC College
2B. Tech Student, Department of Information Technology, JECRC College
3B. Tech Student, Department of Information Technology, JECRC College
4B. Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Election stands as cornerstone of democracy, pivotal for maintaining a fair and equitable society. However, conventional voting systems suffer from inherent flaws such as opacity, susceptibility to manipulation, and potential human errors. In response to these challenges, blockchain technology has emerged as a promising solution, offering enhanced election security and transparency. This research paper presents a detailed blueprint and implementation of a blockchain-based electronic voting system. Leveraging distributed ledger technology, the proposed system ensures the secure and transparent recording of votes, thus mitigating the risk of manipulation or alteration of results. Notably, the system prioritizes voter anonymity and guards against in stances of double voting. Built upon the Ethereum blockchain platform, the system utilizes smart contracts to automate the voting process, including tasks such as vote counting and tallying. This decentralized approach eliminates the need for centralized authority, enhancing the system’s integrity and resilience. Compared to traditional voting mechanisms, the proposed blockchain-based electronic voting system demonstrates superior performance in terms of transparency, security, and efficiency Moreover, its adaptable design facilitates seamless integration with existing election processes, rendering it a viable option for future adoption. While platforms like Simply Voting and Election Buddy offer secure and customizable online voting services for businesses, blockchain-based e-voting systems present unique advantages in terms of security, transparency, and decentralization.
Keywords – Blockchain, Electronic Voting, Smart Contracts, Consensus Algorithms, identity verification, privacy, security, trust, authentication.
NFC UNBOUND: EXPLORING POTENTIAL
1Nimisha Swami, 2Ayushisharma, 3Gaurav Gupta, 4Aditya Singh Naruka
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
NFC play a pivotal role in facilitating personalized user experiences across various online platforms, from e-commerce to streaming services and social media. This paper presents a comprehensive investigation into the application of machine learning techniques in recommendation systems. Through a synthesis of existing literature andempirical analysis, the study explores the methodologies, algorithms, and advancements that underpin the efficacy of recommendation systems. The research delves into the fundamental principles of machine learning, including collaborative filtering, content-based filtering, and hybrid approaches, elucidating their respective strengths and limitations. Moreover, it scrutinizes recent developments in deep learning models such as neural collaborative filtering and attention mechanisms, which have demonstrated superior performance in capturing intricate user preferences and item characteristics. Furthermore, the paper scrutinizes the challenges and ethical considerations inherent in recommendation systems, including privacy concerns, algorithmic bias, and the need for transparency. By synthesizing theoretical insights with practical applications, this research contributes to a nuanced understanding of how machine learning can be leveraged to enhance recommendation systems, paving the way for more personalized and effective user experiences in diverse online domains.
Keywords – Recommendation Systems, Machine Learning Techniques, Personalized User Experiences, Collaborative Filtering, Content-based Filtering.
CYBER SECURITY: SAFEGUARDING THE DIGITAL REALM
1PiyushGautam, 2KanikaMittal, 3MananyaGaur, 4Divisha Sharma
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
In an era where our lives are fundamentally intertwined with the digital sphere, the protection of our digital assets and infrastructure stands as an increasingly critical concern. This abstract preview an in depth investigation into the expansive domain of cybersecurity, encompassing threat landscapes, defense mechanisms, and the evolving panorama of cyber warfare. The exploration begins with an introduction to the multifaceted nature of cybersecurity, emphasizing the significance of safeguarding information, systems, and networks against a multitude of threats. From classic malware to sophisticated phishing and ransomware attacks, the discussion underscores the diversity and complexity of threats facing individuals and organizations. This examination scrutinizes the anatomy of cyber-attacks, dissecting the methodologies and tactics employed by threat actors. Real-world case studies will be employed to underscore the impact and repercussions of successful cyber intrusions, providing tangible illustrations of the aftermath of breaches. Moreover, the discourse delves into proactive cybersecurity measures, exploring frameworks, best practices, and compliance measures necessary for mitigating risks. It examines the role of emerging technologies, such as artificial intelligence, the Internet of Things, and blockchain, both as potential fortification tools and as potential vulnerabilities. This comprehensive analysis emphasizes the role of institutions and governments in establishing robust cybersecurity policies, while also stressing the crucial role of individuals in fostering a culture of security awareness and proactive measures.
Keywords – Cybersecurity, Phishing, Ransomware, Security, Vulnerabilities.
STUDY OF ENHANCEMENT OF FACE DETECTION IN EXTREME CONDITION WITH MACHINE LEARNING
1Piyush Gautam, 2Ayush Gautam, 3Ansh Singh, 4Garvit
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Machine Learning systems play a pivotal role in facilitating personalized user experiences across various online platforms, from e-commerce to streaming services and social media. This paper presents a comprehensive investigation into the application of machine learning techniques in recommendation systems. Through a synthesis of existing literature and empirical analysis, the study explores the methodologies, algorithms, and advancements that underpin the efficacy of recommendation systems. The research delves into the fundamental principles of machine learning, including collaborative filtering, content-based filtering, and hybrid approaches, elucidating their respective strengths and limitations. Moreover, it scrutinizes recent developments in deep learning models such as neural collaborative filtering and attention mechanisms, which have demonstrated superior performance in capturing intricate user preferences and item characteristics. Furthermore, the paper scrutinizes the challenges and ethical considerations inherent in recommendation systems, including privacy concerns, algorithmic bias, and the need for transparency. By synthesizing theoretical insights with practical applications, this research contributes to a nuanced understanding of how machine learning can be leveraged to enhance recommendation systems, paving the way for more personalized and effective user experiences in diverse online domains.
Keywords – Recommendation Systems, Machine Learning Techniques, Personalized User Experiences, Collaborative Filtering, Content-based Filtering.
RECOMMENDATION SYSTEM USING MACHINE LEARNING
1Piyush Gautam, 2Abhay Bansal, 3Aryan Khandelwal, 4Sparsh Gupta
1Assistant Professor, Department of Information Technology, JECRC College
2B. Tech Student, Department of Information Technology, JECRC College
3B. Tech Student, Department of Information Technology, JECRC College
4B. Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Recommendation systems play a pivotal role in facilitating personalized user experiences across various online platforms, from e-commerce to streaming services and social media. This paper presents a comprehensive investigation into the application of machine learning techniques in recommendation systems. Through a synthesis of existing literature and empirical analysis, the study explores the methodologies, algorithms, and advancements that underpin the efficacy of recommendation systems. The research delves into the fundamental principles of machine learning, including collaborative filtering, content-based filtering, and hybrid approaches, elucidating their respective strengths and limitations. Moreover, it scrutinizes recent developments in deep learning models such as neural collaborative filtering and attention mechanisms, which have demonstrated superior performance in capturing intricate user preferences and item characteristics. Furthermore, the paper scrutinizes the challenges and ethical considerations inherent in recommendation systems, including privacy concerns, algorithmic bias, and the need for transparency. By synthesizing theoretical insights with practical applications, this research contributes to a nuanced understanding of how machine learning can be leveraged to enhance recommendation systems, paving the way for more personalized and effective user experiences in diverse online domains.
Keywords – Recommendation Systems, Machine Learning Techniques, Personalized User Experiences, Collaborative Filtering, Content-based Filtering.
WEB SCRAPING
1Ms. Preeti Sharma, 2Megha Sharma, 3Prerana Sharma, 4Rishika Sharma
1Assistant Professor, Department of Information Technology, JECRC College
2B. Tech Student, Department of Information Technology, JECRC College
3B. Tech Student, Department of Information Technology, JECRC College
4B. Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Web scraping, the automated extraction of data from websites, has emerged as a pivotal tool in various domains including academia, business, and research. This paper presents a comprehensive exploration of web scraping, elucidating its techniques, ethical considerations, and far-reaching implications. This research paper presents a detailed blueprint and implementation of Web Scraping. Delve into the technical underpinnings of web scraping, elucidating various methodologies such as Beautiful-Soup, Scrapy and Selenium, along with their applications and limitations. We discuss the intricacies of navigating through website structures, handling dynamic content, and overcoming challenges posed by anti-scraping mechanisms.
Keywords – Web extracting, Dynamic content handling, Scalability, Selenium, Beautiful-Soup, Legal compliance, Parse-Hub.
STUDY ON CYBER CRIME AWARENESS
1Ms. Rama Bhardwaj, 2Aayush Bansal, 3Akash Dagur, 4Akshat Chaurasia
1Assistant Professor, Department of Information Technology, JECRC College
2B. Tech Student, Department of Information Technology, JECRC College
3B. Tech Student, Department of Information Technology, JECRC College
4B. Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Internet use has become part of everyday life for most people. The number of internet users has increased enormously, as has the number of cybercrimes. Cybercrime is a crime committed using a computer and a network. The threat of cybercrime is an ever-present and growing reality in both personal and professional lives. With the advent of the Internet, old crimes have taken on a new face. The purpose of this study is to raise awareness about cybercrime in the modern world and raise awareness about greater cybersecurity. The article attempts to analyze cybercrime awareness among Internet users of different ages and education levels. A linear regression model was used to analyze both objectives. The article showed that there was a connection between age groups and education among respondents. Therefore, it is the responsibility of every internet user to be aware of cybercrime and security and help others by educating them.
Keywords – Cyber-crime, Cyber criminals, Cyber security, Internet, IT Act, Awareness.
FULL STACK WEB DEVELOPMENT
1Ms. Rama Bhardwaj, 2Aman Jain, 3Ankit Manda, 4Ankit Yadav
1Assistant Professor, Department of Information Technology, JECRC College
2B. Tech Student, Department of Information Technology, JECRC College
3B. Tech Student, Department of Information Technology, JECRC College
4B. Tech Student, Department of Information Technology, JECRC College
ABSTRACT
This paper provides the summary on varied aspects of full stack web development. Full stack web development could be a pace growing branch of CS sector because of its successive step towards making the long run in the IT industry. Full stack developers manage the rear end (backend) and front- end development of web site or an online application. They handle the info, clients, system engineering and style. Full stack developer is in demand since of their skills and mastery of web development, due to this vast demand the remuneration of full stack developers is additionally high as compared to alternative jobs. Full stack developer in the main works on web stack, native application stack or mobile stack.
Keywords – Full stack web development, Front-end, Back-end, Programming, Server side, Client-side, Development.
NEUROMORPHIC COMPUTING: AN IN-DEPTH REVIEW OF CONCEPTS
1Mr. Rohit Chhabra, 2Mr. Nishant Gupta, 3Mr. Nikhil Singh Shekhawat, 4Sneha Gupta, 5Preksha Parashar
1Assistant Professor, Department of Information Technology, JECRC College
2B. Tech Student, Department of Information Technology, JECRC College
3B. Tech Student, Department of Information Technology, JECRC College
4B. Tech Student, Department of Information Technology, JECRC College
5B. Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Neuromorphic computing, inspired by the structure and function of the human brain, has emerged as a promising paradigm for next-generation computing systems. This review paper provides an overview of the key concepts, recent advancements, and prospects in neuromorphic computing. We discuss the principles of neuromorphic hardware architectures and algorithms, highlighting innovations in energy-efficient processing, real-time learning, and event-driven computation. Additionally, we explore the diverse applications of neuromorphic computing across domains such as artificial intelligence, robotics, sensor networks, and brain- machine interfaces. Finally, we address the ethical and societal implications of neuromorphic computing and propose future research directions for advancing this transformative field. Through this review, we aim to provide insights into the state-of-the-art in neuromorphic computing and inspire further exploration and innovation in this rapidly evolving domain.
Keywords – Artificial Neural Network, Spiking Neural Networks, Memristors Networks, Sensor Networks, Real-time processing.
DREAMSCAPE: WHERE REALITIES UNITE
1Rohit Chhabra, 2Ishita Sharma, 3Ishita Jain, 4Khushi Garg
1Assistant Professor, Department of Information Technology, JECRC College
2B. Tech Student, Department of Information Technology, JECRC College
3B. Tech Student, Department of Information Technology, JECRC College
4B. Tech Student, Department of Information Technology, JECRC College
ABSTRACT
As the digital landscape continues to evolve, the concept of the metaverse has emerged as a transformative force, poised to redefine how individuals interact, work, and socialize in the digital realm. This report delves into the multifaceted dimensions of the metaverse, exploring its technological foundations, potential applications, societal implications, and the profound impact it could have on various industries. The report begins by elucidating the fundamental components that constitute the metaverse, examining the convergence of augmented reality (AR), virtual reality (VR), artificial intelligence (AI), and blockchain technologies. It provides an in-depth analysis of the current state of metaverse development, highlighting key advancements, challenges, and the collaborative efforts of tech giants and startups in shaping this virtual frontier. A critical aspect of the report is the exploration of the metaverse’s potential applications across industries, including but not limited to gaming, education, healthcare, commerce, and remote collaboration. By investigating use cases and success stories, the report elucidates how the metaverse stands to revolutionize traditional business models and offer innovative solutions to real world challenges.
Keywords – Metaverse, Virtual Reality, Augmented Reality, Blockchain, Industry Applications.
FRESH FRUIT RECOGNITION USING IOT
1Ms. Richa Upadhyay, 2Ayush Kothari, 3Ashish Sharma, 4Konika Nagar
1Assistant Professor, Department of Information Technology, JECRC College
2B. Tech Student, Department of Information Technology, JECRC College
3B. Tech Student, Department of Information Technology, JECRC College
4B. Tech Student, Department of Information Technology, JECRC College
ABSTRACT
The Internet of Things (IoT) has revolutionized various industries, and its application in the food industry has gained significant attention. This paper introduces an innovative IoT-based Food Freshness Detection System designed to address the critical issue of monitoring and ensuring the freshness of perishable food items. The system utilizes a combination of sensors, communication technologies, and data analytics to provide real-time information on the freshness status of food products. The detected freshness levels are then displayed on a user- friendly mobile application, empowering individuals to make informed decisions about food consumption and minimize waste.
Keywords – Internet of Things (IoT), food industry, freshness detection, perishable food, sensors, communication technologies, data analytics, real-time monitoring, mobile application, informed decision-making, waste minimization.
AUTONOMOUS VEHICLES USING NEURAL NETWORKS
1Ms. Richa Upadhyay, 2Arti Solanki, 3Muskan Gola, 4Mayank Sharma
1Assistant Professor, Department of Information Technology, JECRC College
2B. Tech Student, Department of Information Technology, JECRC College
3B. Tech Student, Department of Information Technology, JECRC College
4B. Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Autonomous vehicles (AVs) have emerged as a disruptive force in the transportation industry, promising a revolutionary shift in mobility. This paper provides a comprehensive overview of the technological advancements, societal implications, and prospects of autonomous vehicles. The development of AVs is propelled by breakthroughs in artificial intelligence, sensor technology, and connectivity. Machine learning algorithms enable AVs to perceive and interpret their surroundings with unprecedented accuracy, while LiDAR, radar, and cameras provide real-time data crucial for navigation and decision-making. Moreover, advancements in vehicle-to-everything (V2X) communication systems facilitate coordination between AVs and infrastructure, enhancing safety and efficiency. The adoption of AVs stands to revolutionize various sectors, including transportation, urban planning, and logistics. Improved traffic flow, reduced congestion, and lower accident rates are anticipated benefits, leading to enhanced productivity and quality of life. Furthermore, AVs offer newfound independence to individuals with disabilities and the elderly, transforming accessibility and inclusivity in transportation. However, the widespread deployment of AVs raises complex ethical, regulatory, and cybersecurity challenges. Questions surrounding liability in the event of accidents, data privacy concerns, and job displacement in the transportation sector necessitate careful consideration. Additionally, ensuring the resilience of AVs against cyber threats is imperative to prevent potential malicious attacks.
Keywords – Biometrics Technology, Fingerprint Reader, Money Pad, Digital or Electronic Casher Digi- cash or E-cash or E-Cash or Digital Money.
GRAPHICAL PASSWORD AUTHENTICATION
1Ms. Richa Upadhyay, 2Sneha, 3Hritika Binawara, 4Kartik Ashiya
1Assistant Professor, Department of Information Technology, JECRC College
2B. Tech Student, Department of Information Technology, JECRC College
3B. Tech Student, Department of Information Technology, JECRC College
4B. Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Graphical passwords provide a promising alternative to traditional alphanumeric passwords. They are attractive since people usually remember pictures better than words. Considering the traditional username-password authentication, the alphanumeric passwords are either easy to guess or difficult to remember. Also, users generally keep the same passwords for all their accounts because it is difficult to remember a lot of them. Alternative authentication methods, such as biometrics and graphical passwords are used to overcome these problems associated with the traditional username-password authentication technique. The advantages of graphical passwords include heightened security, improved usability, and diversified authentication methods, fostering user-friendly experiences. However, challenges such as susceptibility to shoulder surfing and the lack of standardization pose obstacles to widespread adoption. This approach enhances security by tapping into users’ cognitive abilities, rendering the system resistant to common attacks such as brute force attempts and phishing.
Keywords –
DREAM SCAPE TECH: UNVEILING AUGMENTED REALMS & VIRTUAL WONDERS
1Dr. Smita Agarwal, 2 Harsh Vardhan Singh, 3Ishan Goyal, 4Naman Malawat
1Professor, Department of Information Technology, JECRC College
2B. Tech Student, Department of Information Technology, JECRC College
3B. Tech Student, Department of Information Technology, JECRC College
4B. Tech Student, Department of Information Technology, JECRC College
ABSTRACT
As technology advances, the realms of augmented reality (AR) and virtual reality (VR) have transcended the boundaries of novelty, emerging as transformative forces in diverse fields. This abstract navigates through recent research endeavors, encapsulating the dynamic landscape of AR and VR applications in healthcare and education. In the surgical theater, real-time augmented reality navigation (Chang & Park, 2018) has evolved into a beacon of precision, guiding surgeons through intricate procedures with unparalleled accuracy. The marriage of AR technologies with emergency response training (Turner & Garcia, 2017) propels first responders into virtual crises, cultivating a heightened state of readiness through immersive simulations.
Keywords – virtual reality, pain management, healthcare, non-pharmacological approach, rehabilitation, chronic pain management.
LEARNING LATENT REPRESENTATION FOR IOT ANOMALY DETECTION
1Dr. Smita Agarwal, 2Saransh Jain, 3Rajat Sharma, 4Rishika Jain
1Professor, Department of Information Technology, JECRC College
2B. Tech Student, Department of Information Technology, JECRC College
3B. Tech Student, Department of Information Technology, JECRC College
4B. Tech Student, Department of Information Technology, JECRC College
ABSTRACT
In this paper, we seek to highlight the concept of Internet of Things (IoT) in general, as well as reviewing the main challenges of the IoT environment by focusing on the recent research directions in this topic. Recently, IoT has emerged as a new technology that is used to express a modern wireless telecommunication network, and it can be defined as an intelligent and interoperability node interconnected in a dynamic global infrastructure network, also it seeks to implement the connectivity concept of anything from anywhere at any time. Indeed, the IoT environment possesses a large spectrum of challenges has a broad impact on their performance, which can be divided into two categories, namely, i) General challenges: such as communication, heterogeneity, virtualization and security; and ii) Unique challenges: such as wireless sensor network (WSN), Radio Frequency Identification (RFID), and finally Quality of service (QoS) that is considered as a common factor between both general and special challenges. In addition, this paper highlights the main applications of the IoT.
Keywords – IoT; heterogeneity; virtualization; WSN; RFID; QoS
CHILD TRACKING DEVICE
1Dr. Smita Agarwal, 2Ridhima Solet, 3Riya Sharma, 4Lalit Laxkar
1Professor, Department of Information Technology, JECRC College
2B. Tech Student, Department of Information Technology, JECRC College
3B. Tech Student, Department of Information Technology, JECRC College
4B. Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Keywords – SMS; Wi-Fi; Bluetooth
NEUROMORPHIC COMPUTING
1Ms. Rama bhardwaj, 2Aman Jain, 3Akshat Verma, 4Arpit Sharma
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Neuromorphic computing promises to improve energy efficiency by an order of magnitude compared to the traditional von Neumann computing paradigm. The aim is to develop an adaptive, fault-tolerant, space-saving, fast and energy-efficient intelligent system by learning and imitating brain functions, which can be achieved through innovations at various levels of abstraction, including materials, devices, circuits, architecture and algorithm. This summary discusses the fundamental concepts, applications, and implications of neuromorphic computing. Unlike traditional von Neumann architectures, neuromorphic systems aim to mimic the parallel processing, fault tolerance, and energy efficiency of biological neural networks. Based on neuroscientific principles, these systems integrate hardware and software to emulate synaptic connections, enabling the development of intelligent machines capable of learning, adapting and performing complex cognitive tasks.
Keywords – Neuromorphic Computing, Von Neumann Architecture, Human Brain Functionality, Energy-Efficient Computing Spiking Neural Network, Artificial Intelligence, ANN.
AUGMENTED REALITY (AR) AND VIRTUAL REALITY (VR)
Mr. Rohit Chhabra, Vibhor Mittal, Shruti Gupta, Shivam Garg
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Augmented Reality (AR) and Virtual Reality (VR) are rapidly evolving technologies with the potential to revolutionize how we interact with digital content and the physical world. AR overlays digital information onto the real world, enhancing our perception and understanding of the environment. VR, on the other hand, immerses users in a completely digital environment, providing a sense of presence and immersion. Both AR and VR have applications across various industries, including gaming, education, healthcare, and retail.
Keywords –
BEYOND SIGHT: EXPLORING THE IMPACT OF MULTISENSORY VIRTUAL REALITY ON LEARNING EXPERIENCES
Ms. Preeti Sharma, Priyanshu, Darpan Mendiratta
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
In the realm of virtual reality (VR), the exploration of multisensory experiences has emerged as a compelling avenue, transcending the visual realm to incorporate touch, smell, and taste. This research endeavors to investigate the transformative potential of multisensory VR in the domain of learning experiences. By delving into the integration of additional senses beyond sight, such as touch, smell, and taste, the study aims to decipher the impact of these multisensory stimuli on the cognitive engagement and memorability of learning content. The abstract sets the stage for a comprehensive exploration of how extending the sensory dimensions within VR can reshape the landscape of educational technology, offering insights into the nuanced ways in which learners interact with and retain information in a multisensory virtual environment. Through an interdisciplinary lens, this research seeks to unravel the implications of multisensory VR on learning, presenting a forward-looking perspective on the fusion of technology and education.
Keywords –
BLOCKCHAIN IN GOVERNMENT SERVICES
1Ms. Nimisha Swami, 2Komal Bhamu, 3Keshav Soni, 4Charushi Jain
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
Blockchain, a Distributed Ledger Technology, is a disruptive and revolutionary technology that enables transacting data in a decentralized structure without the need for trusted central authorities. Many industries have taken steps to unleash the potential of blockchain technology, including the government sector, and early adopters are exploring the use of blockchain as one of the critical capabilities needed to create new business models and to radically transform government services and functions. However, despite this interest in adopting Blockchain technology, there is a lack of Blockchain frameworks or reference models/architecture that address government services in literature. In this paper, we propose a novel blockchain model that can be adopted by governments to establish a government-led blockchain ecosystem for government services. The blockchain model is proposed based on the outcomes of our analysis of the permissioned blockchain platform, and analysis of the blockchain powered housing rentals use case that is being implemented by the Dubai Government. The proposed blockchain model outcomes include a blockchain governance structure, participants and roles definition, and network architecture design which explains the deployment options and components. We also explain the model lifecycle and blockchain services, and we shed light on the security and performance of the model. The study also includes exploring many blockchain use cases used by governments through proofs of concept or prototypes. Our analysis of Hyperledger Fabric design features shows the platform’s relevance to government services and use cases.
Keywords – Blockchain Government services, Hyperledger fabric.
QUANTUM COMPUTING
1Mr. Naveen Kumar Kedia, 2Akshat Singh, 3Arpit Raychand Sansi, 4Deven kumawat
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
This research paper considers the many possibilities of quantum computing, exploring both established and unexplored areas. From quantum algorithms to functional logic gates, this research explores the current state of quantum computing, highlighting progress and ongoing challenges. This main research interests include decoherence dynamics, complex quantum measurements, and the search for unified quantum descriptions.
The project addresses the complexity of decoherence, shows arguments that break symmetry and gives insight into irreversibility in a system by exploring entropy-like parameters. Although the success of relativity remains to be seen, the report highlights the importance of understanding and controlling quantum measurements and recognizing quantum properties shared by inspections and inspectors. Report on the interaction between theoretical progress and practical application, showing the need to move from observation to control of quantum effects. As electronic circuits reach the quantum world, the discovery of quantum materials requires not only theoretical innovations but also practical applications of quantum concepts. Looking ahead, the paper shows successful development for quantum computing. The constant race to shrink the electric field is based on the nature of quantum reality, and the combination of theoretical development and technological development is the key to a new challenge. Although the future is still uncertain, the combination of theoretical insights and practical applications promises a quantum future full of problems and undeniable potential, pushing quantum computing to the brink of ground-breaking discoveries and advances.
Keywords – Cryptography, Quantum cryptography, post-quantum cryptography.
QUANTUM COIN FLIPPING
1Mr. Naveen Kumar Kedia, 2Kanishk Sharma, 3Hardik Maheshwari, 4Vishaka Mulani
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
The Quantum Coin Flipping Game introduces a novel and intriguing paradigm by merging the concepts of quantum mechanics and classical game theory. Participants engage in a quantum empowered version of the traditional coin flipping game, where the outcome is determined through the principles of superposition and entanglement. Unlike classical coin flipping games, this quantum variant ensures unprecedented levels of unpredictability and security. In the game, players share entangled quantum states and independently perform measurements, yielding random outcomes based on the inherently probabilistic nature of quantum systems. The entanglement between particles guarantees that the final result is not influenced by external factors and remains secure against attempts at manipulation. This unique combination of quantum principles and gaming dynamics introduces an element of strategic decision-making for participants, as they navigate the quantum landscape to maximize their chances of a favorable outcome. The Quantum Coin Flipping Game extends beyond mere entertainment, finding applications in quantum cryptography, quantum communication, and quantum computing.
Keywords – paradigm, superposition, entanglement, variant, probabilistic, quantum cryptography.
WEB APPLICATIONS SCALABILITY
1Mr. Naveen Kumar Kedia, 2Divyanshu Agrawal, 3Hardik Maheshwari, 4Rajat jain
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
In today’s digital landscape, the scalability of web applications stands as a cornerstone for businesses striving to meet the demands of an ever-evolving user base while ensuring efficient resource utilization. This research paper embarks on a comprehensive exploration of the critical challenges inherent in achieving scalability within web applications. Through a systematic investigation encompassing the identification of scalability challenges, adept management of variable user loads, optimization of resource efficiency, adoption of microservice architecture principles, fine-tuning of load balancing mechanisms, and harnessing the transformative potential of Docker, this paper endeavors to illuminate the intricate interplay between these factors and their collective impact on scalability.
By delving deep into the intricate fabric of web application scalability, this paper aims to offer actionable insights and strategic guidance for developers and businesses alike. Through the lens of real-world scenarios and empirical evidence, it seeks to unravel the complexities surrounding scalability challenges and present viable solutions tailored to the demands of today’s dynamic digital environment. The paper concludes certain insights for creating resilient web applications capable of thriving in a fast-paced digital environment.
Keywords –
CONTINUAL LEARNING AND ADAPTATION IN NLP
1Mr. Naveen Kumar Kedia, 2Dr. U.K. Pareek, 3Balpreet Kaur, 4Rohit Baghel, 5Pankaj Sain
1Assistant Professor, Department of Information Technology, JECRC College
2Professor, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
5B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
In today’s digital landscape, the scalability of web applications stands as a cornerstone for businesses striving to meet the demands of an ever-evolving user base while ensuring efficient resource utilization. This research paper embarks on a comprehensive exploration of the critical challenges inherent in achieving scalability within web applications. Through a systematic investigation encompassing the identification of scalability challenges, adept management of variable user loads, optimization of resource efficiency, adoption of microservice architecture principles, fine-tuning of load balancing mechanisms, and harnessing the transformative potential of Docker, this paper endeavors to illuminate the intricate interplay between these factors and their collective impact on scalability. By delving deep into the intricate fabric of web application scalability, this paper aims to offer actionable insights and strategic guidance for developers and businesses alike. Through the lens of real-world scenarios and empirical evidence, it seeks to unravel the complexities surrounding scalability challenges and present viable solutions tailored to the demands of today’s dynamic digital environment. The paper concludes certain insights for creating resilient web applications capable of thriving in a fast-paced digital environment.
Keywords – Continual Learning, Adaptation, Natural Language Processing, Incremental Learning, Transfer Learning, Meta-Learning, Sentiment Analysis, Machine Translation, Question Answering, Language Modelling.
GENERATIVE AL IN HEALTHCARE
Ms. Nikita Gupta, Chirag Soni, Nikhil, Gravit
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
This research paper explores the burgeoning field of Generative Artificial Intelligence (Al) and its transformative impact on the healthcare sector. With an increasing focus on data- driven decision making, generative Al emerges as a powerful tool for addressing critical challenges in medical research, diagnosis, and personalized treatment. The paper delves into the application of generative Al in medical imaging, where models like Generative Adversarial Networks (GANs) play a pivotal role in image synthesis and augmentation. Additionally, the research examines the role of generative Al in disease diagnosis, drug discovery, and the burgeoning field of personalized medicine. Ethical considerations, including bias mitigation and responsible deployment, are scrutinized to ensure the ethical use of generative Al in healthcare. Furthermore, the study explores the generation of synthetic data for research purposes, addressing the scarcity of real-world datasets. The abstract concludes by highlighting the promising prospects of generative Al in healthcare and the potential it holds for revolutionizing patient care, medical research, and training environments for healthcare professionals.
Keywords – data breaches, multi-tenancy, compliance framework, encryption.
MEAN STACK
1Dr. Smita Agarwal, 2Rani Yadav, 3Tanishka Narula, 4Arpit Agarwal
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
MEAN is actually combination of different JavaScript frameworks and a NoSQL or document based Database technology which is used for web development. In MEAN stack M stands for MongoDB, E stands for Express JS, A stands for AngularJS, N stands for Node JS. This paper provides the introduction to concept and describes the MEAN stack open sourceand explain the meaning of them along with their future scope. Thispaper also describe the use of MEAN stack for communicate with IOT (internet of things) devices. JavaScript is used as scripting language for client-side programming that runs in any supportive browser. The most crucial part in a web development project is choice of the right combinations of front-end framework, back-endserver, and database environment. This paper focuses on the benefits of the using the MEAN stack.
Keywords – Node, JavaScript, Server.
ECHOES UNVEILED: NAVIGATING RECENT ADVANCEMENTS AND ETHICAL DILEMMAS IN VOICE MORPHING TECHNOLOGY
Ms. Preeti Sharma, Divyansh Garg, Aryaman Sharma, Charu Jain
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
In the age of digital communication, voice morphing technology has emerged as a powerful tool with both innovative applications and ethical implications. This comprehensive review delves into recent advances in voice morphing technology, exploring its technical foundations, state-of-the-art techniques, and emerging applications across various domains. Moreover, the paper examines the ethical considerations surrounding voice morphing, including issues related to privacy, security, identity theft, and potential misuse. Through an interdisciplinary lens, this research aims to provide a nuanced understanding of the transformative potential and ethical challenges inherent in voice morphing technology, offering insights for policymakers, researchers, and practitioners navigating this rapidly evolving landscape.
Keywords – Voice Morphing, Speech Synthesis, Deep Learning, Neural Networks, Text-to-Speech, Speaker Recognition, Emotion Recognition, Speaker Adaptation, Voice Conversion, Generative Adversarial Networks (GANs), Variational Autoencoder (VAE), Mel Spectrogram, WaveNet, Adversarial Training, Privacy Concerns, Security Implications, Identity Theft, Fraud Detection, Cultural Representation, Societal Impact.
AUGMENTED REALITY VS VIRTUAL REALITY
1Ms. Nikita Gupta, 2Devanshi Tiwari, 3Chirag Bhatia, 4Anurag Sharma
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
The evolution of Augmented Reality (AR) and Virtual Reality (VR) technologies has brought about a transformative shift, offering immersive experiences that transcend traditional boundaries. AR enhances the real world with digital overlays, while VR creates entirely simulated environments. Despite remarkable progress, challenges like hardware limitations, ethical concerns, and user acceptance impede widespread adoption. To address these issues, a multifaceted approach is essential, necessitating continuous hardware innovation, clear ethical guidelines, and user education. In education, VR and AR have shown significant promise, enhancing student motivation and engagement. Analysing social media data revealed public positivity towards both general and educational uses of AR and VR, emphasizing their potential across various domains. Overall, overcoming challenges and fostering user acceptance are pivotal for unlocking the full potential of AR and VR in reshaping our experiences across diverse sectors.
Keywords – Augmented Reality, Virtual Reality, View Master, STEM Education.
PROTECTING PATIENTS AND DATA: A PAPER OF CYBER SECURITY IN HEALTHCARE
1Brijesh Kumar Singh, 2Varnika Jain, 3Kamal Verma, 4Jayant Mishra
1Assistant Professor, Department of Information Technology, JECRC College
2B.Tech Student, Department of Information Technology, JECRC College
3B.Tech Student, Department of Information Technology, JECRC College
4B.Tech Student, Department of Information Technology, JECRC College
ABSTRACT
India’s healthcare digitization, like Ayushman Bharat, fuels progress, but opens doors to cyber threats. This paper examines patient data risks, outdated infrastructure, and evolving attacks. While social engineering and phishing exploit human vulnerabilities, hope lies in solutions like MeitY’s cybersecurity frameworks and Aadhaar authentication. Emerging technologies like blockchain and AI, along with international collaboration, hold promise. A multi-pronged approach, combining robust frameworks, advanced technologies, awareness training, and continuous adaptation, is vital to secure India’s digital healthcare future.
Keywords – Healthcare cybersecurity, Cyber threats, Legacy infrastructure, Ransomware attacks, Patient safety.