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2nd International Conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Agrawal, Harsh Singh, Shaurya Pratap Dixit, Shashwat Nagdev, Parth Priya, V. Thaseen, Sumaiya School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore India

ISBN: (纸本)9798350328202

The internet is an essential source of data for individuals across the world. However, disinformation has emerged as a significant problem due to its rapid growth on social media and the prevalence of fallacious news. Conventional strategies for detecting disinformation sites, like manual examination, are tedious and time-wasting. As a result, it is necessary to develop an effective method to find such websites. The goal of this research is to find websites that spread false information and prevent its further spread. The methodology is unique and effective for detecting disinformation websites as it makes use of the OSINT tool Maltego and focuses on websites that spread news having a negative impact such as in politics, health, finance, etc. Thus, the outcome of this research helps users to detect the authenticity of news in an easy and user-friendly manner by footprinting mechanisms. © 2024 IEEE.

关键词： Websites

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NearBySell : A Novel Approach to Localized E-Commerce with Focus on Seller-Customer Interaction and Enhanced Local Retail Network 11

NearBySell : A Novel Approach to Localized E-Commerce with F...

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11th IEEE International Conference on Advances in Computing and Communications, ICACC 2024

作者： Chavan, Vishal Subhash Hake, Ashok Shrimant Rao, Bhukya Nageswar Kotkar, Suyash Sanjay Kolhapur Institute of Technology's College of Engineering Department of Computer Science and Business Systems Kolhapur India

ISBN: (纸本)9798350379136

This paper examines a novel online retail application optimized for local commerce via a location-based matching system. The application supports the sale of new and secondhand items, home goods, and vegetables, requiring users to register and input their locations. Transactions occur only when the buyer's and seller's locations align, reducing logistical challenges. The system features a review mechanism allowing customers to rate sellers, influencing future buyer decisions and seller reputation. Security is ensured through hand-to-hand payments and direct seller delivery, mitigating risks associated with digital payments and third-party delivery. Additionally, the application supports long-term relationships by maintaining permanent connections between customers and sellers. Technical aspects include the development of location-based matching algorithms, review systems, and security measures. Notably, the application incorporates advanced security features such as fake reviews detection and duplicate listings detection to protect both buyers and sellers from fraudulent activities. This study highlights how these components enhance local market efficiency and e-commerce reliability. © 2024 IEEE.

关键词： Location

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Test-Driven Development (TDD) in Small software Development Teams: Advantages and Challenges 5

Test-Driven Development (TDD) in Small Software Development ...

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5th International Conference on Advancements in Computational sciences, ICACS 2024

作者： Ramzan, Hafiz Arslan Ramzan, Sadia Kalsum, Tehmina Institute of Computer and Software Engineering Khwaja Fareed University of Engineering and Information Technology Rahim Yar Khan Pakistan National University of Modern Languages Department of Computer Science Multan Pakistan University of Engineering and Technology Department of Software Engineering Taxila Pakistan

ISBN: (纸本)9798350394764

In the context of small software development teams, this research article gives a thorough investigation of the adoption of test-driven development (TDD) approaches. It aims to highlight the benefits that TDD offers, such as improved code quality through modularization and proactive defect spotting which results in effective debugging and development processes. It also discusses the complex issues that arise when TDD is implemented in smaller teams, such as the learning curve and resource constraints. This study significantly advances the understanding of how TDD can be used to optimize software development techniques in organizations or software houses having small development teams. It also explores the possible advantages and challenges. © 2024 IEEE.

关键词： Modular construction

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Sustainable Teaching and Learning E-learning Model towards Redesigning Transformative Learning Model for Knowledge Sharing & Infrastructure Enhancements Post COVID-19

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Recent Patents on engineering 2025年第2期19卷 1-12页

作者： Veeramanickam, M.R.M. Kaur, Gaganpreet Acakpovi, Amevi Vadrevu, Pavan Kumar Ciro, Rodriguez R. Kalpana, A.V. Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Software Engineering Universidad Nacional Mayor de San Marcos Lima Peru Electrical and Electronic Engineering Department Accra Technical University Accra Ghana Andhra Pradesh India Department of Software Engineering Universidad Nacional Mayor de San Marcos UNMSM Lima Peru Department of Data Science and Business Systems SRM Institute of Science and Technology Kattankulathur Tamilnadu Chennai India

Background: Recently, e-learning has become a very basic, integral part of technology-based learning. Wide trends are increasing day by day because of the demands and its usage based on working remotely due to highly penetrated mobile handheld devices and digital media. The smart campus infrastructure has played a vital role to its full extent towards Z millennium students in the 20th century. The teaching and learning accessibility depends on terms of various cost-based afforda-ble platforms, either with synchronous learning or asynchronous mode of learning. Methods: The current patent research explores the changeling leading to infrastructural reforms as per the need for digital media for e-learning during and after COVID-19 spreads. The perspectives in 2 forms of research study are: 1st working on infrastructural needs and demands for the smart campuses and online learning challenges and 2nd is working on platforms technology utilization for better accessible resources for all learners. This work studied different aspects during and after COVID-19, leading to the importance of uninterrupted internet access, phone, hardware and relia-bility, etc. In this work, the importance of gamification study and flipped classrooms for enhancing learner performance to highly engage them in learning environments focused research model on learner engagement on Gamified perceiving study with Smart PLS-SEM was investigated. Promoting sustainability in its entirety through knowledge transfer and contributions to address various challenges in the redesign of learners' syllabi to meet educational needs, emphasizing online learning to integrate various modes of learner platforms, personalized teaching and learn-ing, peer-to-peer communication for learner enhancement, and student engagement through gami-fication are studied. Results: Learners who are enrolled at the school, college, and university levels of education increased exponentially post-COVID-19. More than 90% responded to sch

关键词： Curricula

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Exploring the scope of Blockchain-based Central Bank Digital Currencies (CBDCs) in Crowdfunding Platforms 7

Exploring the scope of Blockchain-based Central Bank Digital...

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7th IEEE Pune Section International Conference, PuneCon 2024

作者： Ghosh, Satyajit Jaiswal, Rishabh Das, Tapan Vellore Institute of Technology School of Computer Science Engineering and Information Systems Tamil Nadu Vellore India

ISBN: (纸本)9798331527822

This paper introduces an innovative crowdfunding platform utilizing Central Bank Digital Currency (CBDC) to tackle the challenges linked to conventional payment methods and the regulatory limitations of earlier cryptocurrency-based solutions. We present a practical prototype, demonstrating the feasibility of the CBDC approach. An extensive evaluation comparing CBDCs with Ethereum and traditional systems confirms its superior performance. This research marks the initial step toward understanding the potential of CBDCs in crowdfunding, setting the stage for future exploration and innovation in this evolving financial landscape. © 2024 IEEE.

关键词： Blockchain CBDC Cross-border Payment Crowdfunding Digital Currency

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Seasonal Forest Disaster Prediction using Machine Learning Models 5

Seasonal Forest Disaster Prediction using Machine Learning M...

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5th IEEE International Conference on Communication, Computing and Industry 6.0, C2I6 2024

作者： Niranjan, J. Krishnamoorthy, N. Vinothkumar, V. Vellore Institute of Technology School of Computer Science Engineering and Information Systems Tamil Nadu Vellore India

ISBN: (数字)9798350379884

ISBN: (纸本)9798350379884

The forests are natural barriers that help prevent natural disasters such as heavy rainfall, heavy winds, etc. Because these disasters affect the forest, they make way for more disasters in surrounding areas including other forests, affecting animals, cities, and villages, especially tribal populations. This project aims to find solutions by analyzing the forest and its historical data including disaster incidents. The Seasonal Forest Disaster Analysis project harnesses advanced Machine Learning to investigate and mitigate the impact of forest disasters comprehensively. In essence, the Seasonal Forest Disaster Analysis project stands as a testament to the potential of cutting-edge technology and collaborative efforts in tackling some of the most pressing challenges facing our natural world. The Seasonal Forest Disaster Analysis project is a comprehensive endeavor that harnesses advanced Machine Learning & Deep Learning techniques to deeply investigate and mitigate the impact of forest disasters. Three models like CNN with Grad-CAM, ResNet and XceptionNet were proposed, out of which CNN with Grad-CAM produces an Accuracy of 94 %. By integrating a diverse array of datasets, including satellite imagery, climate data, and historical records, the project is geared towards effectively identifying, categorizing, and predicting a spectrum of seasonal forest disasters, including but not limited to wildfires, droughts, and floods. This integration enables the creation of a sophisticated framework that not only examines past occurrences but also foresees potential future hazards through predictive modelling. © 2024 IEEE.

关键词： Drought

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Diabetic Retinopathy Detection using Deep Learning Framework and Explainable Artificial Intelligence Technique 14

Diabetic Retinopathy Detection using Deep Learning Framework...

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14th International Conference on Cloud Computing, Data science and engineering, Confluence 2024

作者： Posham, Uppamma Bhattacharya, Sweta School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore India

ISBN: (纸本)9798350344837

Diabetic retinopathy (DR) is a serious eye condition induced by diabetes that can result in eyesight. In order to overcome the vision impairment of diabetes mellitus patients, it is essential for early age prevention by medical practitioners. In the traditional approach, ophthalmologists conduct various screening tests to detect DR but fail to achieve accurate and conclusive diagnosis due to the associated time consuming processes. In order to eliminate such burden on the ophthalmologists, deep learning and machine learning techniques have evolved rapidly playing a significant role in the classification of diabetic and non diabetic patients. In this paper, the proposed framework implements a publicly available Benchmark APTOS 2019 Gaussian-filtered DR image dataset using a customized CNN model, yielding an enhanced accuracy of 98 %. In addition, the framework also employs a LIME explainer visualization model to provide enhanced transparency and interpretability to the generated predictions. This eliminates the 'blackbox' -ed nature of the predicted results from the traditional ML process and enables healthcare providers to take clinical decisions with confidence providing visual representations of the significant features that contribute towards an outcome. © 2024 IEEE.

关键词： Diagnosis

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Cybersecurity Landscape on Remote State Estimation:A Comprehensive Review

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 851-865页

作者： Jing Zhou Jun Shang Tongwen Chen the Department of Electrical and Computer Engineering University of AlbertaEdmonton AB T6G 1H9Canada the Department of Control Science and Engineering and Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 200092China

Cyber-physical systems(CPSs)have emerged as an essential area of research in the last decade,providing a new paradigm for the integration of computational and physical units in modern control *** state estimation(RSE)is an indispensable functional module of ***,it has been demonstrated that malicious agents can manipulate data packets transmitted through unreliable channels of RSE,leading to severe estimation performance *** paper aims to present an overview of recent advances in cyber-attacks and defensive countermeasures,with a specific focus on integrity attacks against ***,two representative frameworks for the synthesis of optimal deception attacks with various performance metrics and stealthiness constraints are discussed,which provide a deeper insight into the vulnerabilities of ***,a detailed review of typical attack detection and resilient estimation algorithms is included,illustrating the latest defensive measures safeguarding RSE from ***,some prevalent attacks impairing the confidentiality and data availability of RSE are examined from both attackers'and defenders'***,several challenges and open problems are presented to inspire further exploration and future research in this field.

关键词： Cyber-attacks Kalman filtering remote state estimation unreliable transmission channels

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A Novel Design of Random Number Generators Using Chaos-Based Extremum Coding

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IEEE Access 2024年 12卷 24039-24047页

作者： Araki, Shunsuke Wu, Ji-Han Yan, Jun-Juh Kyushu Institute of Technology Kawazu Iizuka Graduate School of Computer Science and Systems Engineering Fukuoka820 Japan National Chin-Yi University of Technology Department of Electronic Engineering Taichung41107 Taiwan

This paper proposes a new chaos-based extremum coding method to realize a true random number generator (RNG). Based on the chain rule, we innovatively introduce two parameters into the dynamics of chaotic systems to modulate the speed and amplitude of state responses. Then, by discretizing the continuous modulated chaotic system, the corresponding discrete chaotic system can be obtained, which allows the use of low-cost micro-controllers for implementation, enhancing system stability, and reducing costs. Also, a novel chaos-based extremum coding approach is proposed for generating a random extremum-coded sequence (RECS). Using this RECS to switch and decide modulation parameters significantly improves the randomness of the sequences generated by the RNGs. To highlight the contribution of this RNG design, the randomness and security of the RNGs are evaluated by statistical tests such as NIST, Diehard, and ENT. Through comparisons with recent published works, the results show that the proposed chaotic extremum-coded RNG can demonstrate superior performance with a higher level of randomness. © 2013 IEEE.

关键词： Statistical tests

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Online Information-Based Product Evolution Course Mining and Prediction

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International Journal of Information Technology and Decision Making 2024年第2期23卷 599-627页

作者： Chen, Yuh-Jen Chen, Yuh-Min Department of Accounting and Information Systems College of Business Intelligence National Kaohsiung University of Science and Technology Kaohsiung City Taiwan Institute of Manufacturing Information and Systems College of Electrical Engineering and Computer Science National Cheng Kung University Tainan City Taiwan

In today’s fiercely competitive business environment, product design and development play critical roles in an enterprise’s success;therefore, consumer demand must be understood. Enterprises used to understand their consumers’ demands through time-consuming questionnaire surveys and statistical analyses. As the Internet and the popularity of virtual communities have grown, more consumers are leaving comments about their perceptions of the appeal of products on online social media platforms, thus enabling enterprises to more objectively understand consumers’ product preferences and demands. Therefore, determining how to effectively assist enterprises in analyzing valuable information beneficial to product design and development that can be gleaned from the large amount of social media data available is critical to promoting an enterprise’s competitive advantage in the product market. However, previous studies have primarily focused on understanding consumer viewpoints of products through review articles or electronic word-of-mouth (eWOM;it is a common channel for spreading product appraisals) from online social media. For these review articles and eWOM that can imply consumer demand for product features, there were no relevant studies focused on analyzing consumer demand by using both online review articles and eWOM for product feature evolution. Therefore, for new product features, this study developed a mechanism for product evolution course mining from product-related review articles (such as product functions or specifications) and eWOM on online social media to realize the prediction of future product features or specifications, and then assist enterprises in rapidly and accurately grasping product development trends to effectively discern key reference information for product design and development. The study was achieved by (1) designing a process for online information-based product evolution course mining and prediction, (ii) developing techniques related to

关键词： Forecasting

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