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2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Khonde, Tanvi Patle, Sneha Talvekar, Shreya Hajbe, Jahnavi Faculty of Engineering and Technology Department of Computer Science and Design Maharashtra Wardha442201 India

ISBN: (纸本)9798331505745

A virtual chatbot assistant is an interactive application designed to simulate human-like communication and respond to user inquiries promptly. It focuses on building an interesting user interface and putting simple conversational logic into practice;this article presents the development of a chatbot using HTML, CSS, and JavaScript. Developers can make these fundamental web technologies useful in the creation of accessible and user-friendly chatbot systems for any kind of application. The literature indicates that chatbot technology is under development, which includes the merging of AI and natural language processing to enhance the capabilities of conversations. This handbook is an invaluable tool in making useful chatbots by linking the needs of the users with contemporary online technology. © 2025 IEEE.

关键词： Chatbots

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FPGA Processor In Memory Architectures (PIMs): Overlay or Overhaul ?

FPGA Processor In Memory Architectures (PIMs): Overlay or Ov...

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International Conference on Field Programmable Logic and Applications

作者： MD Arafat Kabir Ehsan Kabir Joshua Hollis Eli Levy-Mackay Atiyehsadat Panahi Jason Bakos Miaoqing Huang David Andrews Department of Computer Science and Computer Engineering University of Arkansas Department of Computer Science and Computer Engineering University of South Carolina Department of Computer Science and Computer Engineering Cadence Design Systems

The dominance of machine learning and the ending of Moore's law have renewed interests in Processor in Memory (PIM) architectures. This interest has produced several recent proposals to modify an FPGA's BRAM architecture to form a next-generation PIM reconfigurable fabric [1], [2]. PIM architectures can also be realized within today's FPGAs as overlays without the need to modify the underlying FPGA architecture. To date, there has been no study to understand the comparative advantages of the two approaches. In this paper, we present a study that explores the comparative advantages between two proposed custom architectures and a PIM overlay running on a commodity FPGA. We created PiCaSO, a Processor in/near Memory Scalable and Fast Overlay architecture as a representative PIM overlay. The results of this study show that the PiCaSO overlay achieves up to 80% of the peak throughput of the custom designs with 2.56 x shorter latency and 25% - 43% better BRAM memory utilization efficiency. We then show how several key features of the PiCaSO overlay can be integrated into the custom PIM designs to further improve their throughput by 18%, latency by 19.5%, and memory efficiency by 6.2%.

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Navigating the Interplay of Privacy, Security and Ethics on Social Media

Navigating the Interplay of Privacy, Security and Ethics on ...

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Communication & Computing (WCONF), World Conference on

作者： R Rajagopal M Senbagavalli Deepak Raj D.M Riya Kumari Deepanshu Gupta Anusha Gupta Department of Computer Science and Engineering Alliance College of Engineering and Design Alliance University Bangalore India

ISBN: (数字)9798350395327

ISBN: (纸本)9798350395334

Social media has changed the way people interact with the digital world, communicate, and exchange information. It has also brought privacy, security, and ethics into sharper relief. A fundamental concern is privacy, which includes people's rights to manage their personal data. Social networking sites are repositories of user data, which gives rise to worries about illegal access and privacy violations. Furthermore, complex algorithms make it more difficult to maintain privacy by obfuscating the distinction between invasive surveillance and individualized experiences. To protect user data and retain confidence, security is important. Social media users are vulnerable to online risks like phishing and identity theft, though, because of their interconnectedness. It's always difficult to strike a balance between security precautions and consumer comfort. The ethical implications of data monetization, algorithmic biases, and disinformation are particularly significant. Platforms face societal challenges such as digital harassment and political manipulation in addition to problems with data ownership, transparency, and responsibility. To overcome all of these, we have come forward with a solution that has 3 features. With the help of machine learning algorithms and python libraries, we made a solution that helps the users with these three concerns of social media.

关键词： Ethics Privacy Data privacy Machine learning algorithms Navigation Blogs Cyberbullying Passwords Libraries Security

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Smart Farming Advisor: Optimized Crop Selection and Growth Procedure using Random Forest

Smart Farming Advisor: Optimized Crop Selection and Growth P...

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8th International Conference on Inventive Computation Technologies, ICICT 2025

作者： Angel Anna Prathiba, E. Aathavan, G. Dhineshkumar, P. Karthi, P. Department of Computer Science and Design Erode Sengunthar Engineering College Tamilnadu Erode India

ISBN: (数字)9798331512248

ISBN: (纸本)9798331512255

The system analyses climate, soil characteristics, and past agricultural output trends based on district, taluk, and pin code inputs using machine learning techniques. It offers crop suggestions that are optimized to maximize yield potential and support sustainable farming by utilizing predictive analytics. It also integrates pest and disease prediction models to reduce risks and helps farmers follow best farming practices, such as the optimal time to sow, when to fertilize, and how to water. In addition to choosing crops, the system provides financial insights by projecting revenues depending on budget, market trends, and land acreage. It recommends crops with high demand and analyses price changes to assist farmers in making well-informed selections. Additionally, a land rent and search module in the system helps users locate appropriate agricultural property according to location, soil quality, and cost, making it accessible to both new and growing farmers. The system additionally offers a thorough explanation of fundamental agricultural requirements, including soil preparation, seed selection, irrigation methods, and pest control strategies, in order to facilitate all-encompassing farming operations. The system equips farmers with the tools they need to increase production, boost profitability, and implement sustainable agricultural practices by providing well-organized information and insightful recommendations. © 2025 IEEE.

关键词： Crop Prediction Financial Insights Machine Learning Sustainable Farming

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AI -Driven Detection of Gastrointestinal Disease based on Advanced Deep Learning Techniques 4

AI -Driven Detection of Gastrointestinal Disease based on Ad...

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Izankar, Sakshi V. Puri, Chetan Burle, Rushikesh Computer Science and Design Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research Maharashtra Wardha India Artificial Intelligence and Machine Learning Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research Maharashtra Wardha India

ISBN: (纸本)9798331523923

Esophageal, gastric, and colorectal cancers (CRC) are some of the gastrointestinal (GI) cancers threatening global health with CRC being particularly concerning due to its high fatality rate. While early diagnosis is crucial in improving treatment efficiency, barriers such as image noise and visual subjective assessments during diagnostics such as colonoscopies often render it inconceivable. For better diagnostic accuracy in detecting gastrointestinal disease via endoscopic images, the research explores whether highly advanced artificial intelligence (AI) models such as Vision Transformers (ViTs) and pre-trained DenseNet201 can be effective. We compare these models to popular deep learning techniques such as Support Vector Machines (SVM), ResNet50, VGG19, and GoogleNet. At a training accuracy of 99.9% and a validation accuracy of 98.8%, experiments on the KVASIR dataset indicate that Vision Transformer is superior to other models since it can learn long-range dependencies. The robustness of deep learning models for identifying GI disease is exemplified by the superior performance of DenseNet201, ResNet50, and InceptionV3, all of which possess high accuracy, precision, and recall values. The paper illustrates the potential of Vision Transformers, when combined with transfer learning and pre-trained CNN models, to revolutionize endoscopic diagnoses and provide a valuable resource to help physicians manage gastrointestinal conditions more effectively. © 2025 IEEE.

关键词： Endoscopy

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Optimization method for a radar situation interface from error-cognition to information feature mapping

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Journal of Systems engineering and Electronics 2022年第4期33卷 924-937页

作者： WU Xiaoli WEI Wentao CALDWELL Sabrina XUE Chengqi WANG Linlin School of Design Art&Media Nanjing University of Science&TechnologyNanjing 210094China School of Mechanical Engineering Southeast UniversityNanjing 211189China College of Mechanical and Electrical Engineering Hohai UniversityChangzhou 211100China School of Computer Science Australian National UniversityCanberra 2600Australia

With the rapid development of digital and intelligent information systems, display of radar situation interface has become an important challenge in the field of human-computer interaction. We propose a method for the optimization of radar situation interface from error-cognition through the mapping of information characteristics. A mapping method of matrix description is adopted to analyze the association properties between error-cognition sets and design information sets. Based on the mapping relationship between the domain of error-cognition and the domain of design information, a cross-correlational analysis is carried out between error-cognition and design *** obtain the relationship matrix between the error-cognition of correlation between design information and the degree of importance among design information. Taking the task interface of a warfare navigation display as an example, error factors and the features of design information are extracted. Based on the results, we also propose an optimization design scheme for the radar situation interface.

关键词： radar situation interface error-cognition information feature mapping visual information display

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A Comprehensive Assessment of Fuzzy Rule-based Systems for Heart Attack Prediction 2

A Comprehensive Assessment of Fuzzy Rule-based Systems for H...

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2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Ugale, Om Puri, Chetan Gote, Pradnyawant M. Faculty of Engineering and Technology Department of Computer Science and Design Maharashtra Wardha442001 India

ISBN: (纸本)9798331505745

Heart disease is a leading global cause of death, highlighting the need for accurate and efficient risk assessment methods. Traditional models often fail to address the uncertainty and vagueness in medical data. A Fuzzy Rule-Based System (FRBS) offers a solution by leveraging fuzzy logic to handle imprecise inputs like age, blood pressure, and lifestyle factors. The system uses fuzzification to convert crisp inputs into fuzzy sets, applies expert-defined IF-THEN rules through an inference engine, and translates outputs into interpretable risk scores via defuzzification. FRBS provides a flexible and patient-centric approach, accommodating linguistic variables and ambiguous data. Applications include real-time monitoring through wearable devices and telemedicine platforms, enhancing preventive care and empowering early detection of heart disease. This innovative system bridges the gap between medical uncertainty and actionable insights, improving healthcare © 2025 IEEE.

关键词： Fuzzy rules

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The Evolving Role of Telemedicine in Expanding Access to Healthcare: Benefits, Barriers, and Future Directions 2

The Evolving Role of Telemedicine in Expanding Access to Hea...

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2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Talvekar, Shreya Khonde, Tanvi Hajbe, Janhavi Patle, Sneha Faculty of Engineering and Technology Department of Computer Science and Design Maharashtra Wardha442001 India

ISBN: (纸本)9798331505745

Telemedicine, the remote delivery of medical treatment via digital technology has become essential, particularly for rural and disadvantaged populations. The benefits of telemedicine are reviewed in this research, including increased access to care, lower costs, and better chronic illness management. Although the COVID-19 pandemic's acceleration guaranteed continuity of care, technological constraints, legal concerns, and data privacy considerations hindered the full potential from being achieved. The article addresses the barriers to wider adoption and examines research showing the benefits of telemedicine. It ends with suggestions for infrastructure investments and legislative modifications to broaden the use of telemedicine and lessen healthcare inequities. © 2025 IEEE.

关键词： COVID-19

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Predictive Analytics in Smart Transportation: Integrating AI and IoT to Forecast Traffic Volumes

Predictive Analytics in Smart Transportation: Integrating AI...

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International Conference on Trends in Electronics and Informatics (ICEI)

作者： Parampreet Kaur Ved Prakash Mishra Akash Badhan School of Computer Science and Engineering LPU India School of Engineering Architecture and Design Amity University Dubai School of Engineering Architecture and Interior Design Amity University Dubai UAE School of Computer Science and Engineering Lovely Professional University Phagwara India

ISBN: (数字)9798331544607

ISBN: (纸本)9798331544614

The integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies presents a transformative opportunity to come up with smart transportation systems. This research basically explores the application of these technologies that could help in predictive analysis of traffic volumes, thereby enhancing urban mobility management and reducing congestion. In this a predictive model has been developed using linear regression based on synthesized data which includes different variables such as time of day, day of week, and peak traffic hours due to high congestion on roads, reflecting typical urban traffic conditions. The objective is to improve the accuracy and reliability of traffic prediction by leveraging real-time data from IoT sensors and historical traffic patterns. The model's performance was evaluated through metrics such as the Mean Squared Error (MSE) and R-Squared values, with results which indicate a strong predictive capability. Additionally, error distribution analysis heighted areas for potential improvements and model refinement in future. This paper discusses the implications of our findings for traffic management systems and proposes directions for future research to optimize the hybridization of AI and IoT technologies in enhancing the adaptability and efficiency of urban transportation networks.

关键词： Adaptation models Accuracy Smart cities Predictive models Real-time systems Smart transportation Reliability Artificial intelligence Predictive analytics Autonomous vehicles

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Analytic Hierarchy Process of Digital Book Content Display Method on Large Displays 4

Analytic Hierarchy Process of Digital Book Content Display M...

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4th IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2024

作者： Koyama, Junnosuke Yamada, Toshiva Temma, Seiya Nakamichi, Noboru Graduate School of Engineering Fukuyama University Fukuyama Japan NTT TechnoCross Corporation Tokyo Japan Fukuyama University Faculty-of-Engineering Department of-Computer Science Fukuyama Japan Fukuyama University ANKER DESIGN Inc. Fukuyama Japan

ISBN: (纸本)9798350395914

The development of information technology and the digitization of books have led to the widespread use of electronic bookshelves that display a group of books on a display and the use of larger displays. In this study, we investigate the display method of digital book contents on a large-screen wall displays, an environment with few restrictions on the display size of book contents. We set up eight display patterns by combining four image display patterns that combine images of the front cover, spine, and back cover, and two image size patterns of actual and standard sizes. As a result of the pairwise comparisons with 52 participants, it was confirmed that the 'Front cover and Spine' display method was highly evaluated by those who placed importance on the ease of identification. © 2024 IEEE.

关键词： bookshelves digital twin library museum

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