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检索条件"任意字段=International Conference on Computer Technologies in Physical and Engineering Applications"

共 41551 条记录，以下是11-20 订阅

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Implementation and Analysis of PUF Architectures for Enhanced Security 14th

Implementation and Analysis of PUF Architectures for Enhance...

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14th EAI international conference on Broadband Communications, Networks, and Systems, BROADNETS 2024

作者： Singh, Sangeeta Noorain, Azmath Reddy, G. Sanjeeva Goud, Srimanthula Manish Department of ECE Vardhaman College of Engineering Telangana Hyderabad India

ISBN: (纸本)9783031811678

physically Unclonable Functions (PUFs) [Coined in 2001 and 2002] are innovative physical security objects that produce unclonable measurements of physical objects. It acts as an equivalent to the biometrics of human being as it can securely generate and store secrets, PUFs allow advancements in the physical implementation of an information security system. To implement multiple applications, various PUFs were invented using different technologies. Thus, this paper compares and summarizes the characteristics of a set of PUFs using CMOS VLSI technology. The PUF architectures namely RO PUF, CRO PUF, and TERO PUF were designed using Cadence Virtuoso 45 nm technology. It was observed that, when all the constraint parameters were kept the same, according to the implemented sequence, there was a decrease in the usage of memory by 10%. While comparing CRO from RO there is a decrease of 82% in power and 51% in delay, for CRO to TERO there is a 19% decrease in power and a 49% increase in delay as there is a decrease in the number of used transistors. © ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering 2025.

关键词： Memory architecture

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DLIoMT: Deep Learning Approaches for IoMT-Overview, challenges and the future

DLIoMT: Deep Learning Approaches for IoMT-Overview, challeng...

引用

2025 international conference on computer, Electrical and Communication engineering, ICCECE 2025

作者： Harshni, V. Singh, Satyendr Indhumathi, R. Kumar, Neelam Sanjeev Chowdhury, Subrata Patra, Sudhansu Shekhar Srm Institute of Science and Technology Department of Bme Ramapuram campus Chennai India Bml Munjal University Computer Science & Engg Department Gurugram India Vadapalani Campus Chennai India Sreenivasa Institute of Technology and Management Studies Department of Computer Science and Engineering Andra Pradesh Chittoor India Deemed to be University School of Compter Applications Odisha Bhubaneswar India

ISBN: (纸本)9798331513894

An artificial intelligence (AI) system works by combining a computer program and algorithms to make a device more efficient and intelligent for tasks that are typically performed by humans. Deep learning, machine learning, conventional neural networks, recognition, and fuzzy logic are a few of the subsets of AI with unique capabilities and functions that can enhance modern medical science. Such innovations simplify human interference in clinical diagnostic procedures, decision making, and medical imaging. To improve human health, connected biomedical network devices and software applications are interconnected to form the Internet of Medical Things (IoMT), the next generation of bioanalytical tools. This review paper provides in-depth analysis of the IoMT encasing its definition, technologies, applications, challenges, and future prospects. © 2025 IEEE.

关键词： Electronic health record

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A Comprehensive Survey on Enhancing Digital Twin Security Systems with Explainable AI Techniques 3

A Comprehensive Survey on Enhancing Digital Twin Security Sy...

引用

3rd international conference on Intelligent Data Communication technologies and Internet of Things, IDCIoT 2025

作者： Lalithadevi, B. Krishnaveni, S. Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India Department of Computational Intelligence SRM Institute of Science and Technology Kattankulathur India

ISBN: (纸本)9798331527549

Digital Twin (DT) technology has emerged as a cornerstone in modern engineering, enabling real-time digital replication of physical assets for monitoring, diagnostics, and optimization. However, as DTs become increasingly integrated into critical infrastructure, their security has become a paramount concern. This paper presents a comprehensive survey on the integration of Explainable Artificial Intelligence (XAI) into Digital Twin security, highlighting the potential of XAI in enhancing the transparency, interpretability, and trustworthiness of AI - driven security mechanisms in DTs. We explore various XAI techniques, including model- agnostic approaches, interpretable neural networks, and rule-based systems, detailing their potential applications in bolstering the security of Digital Twins. Furthermore, we identify several key challenges in implementing XAI for DT security, such as the need for standardized metrics for interpretability, the trade-offs between model complexity and explainability, and the potential for adversarial attacks on explainable models. Through our analysis, we highlight the critical research gaps, including the security of Digital Twin (DT) systems and explores the integration of Explainable AI (XAI) to enhance transparency, interpretability, and trustworthiness. Outcomes include detailed XAI applications for DT security, identification of limitations, and a roadmap for future research. We discuss various XAI techniques, their applications, and the current challenges in implementing XAI for DT security. Our survey identifies key research gaps and offers a roadmap for future research in this emerging field. © 2025 IEEE.

关键词： Artificial intelligence

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Cybersecurity Threat Detection in Smart Cities using Box Plot Sampling Isolation Forest 1

Cybersecurity Threat Detection in Smart Cities using Box Plo...

引用

1st international conference on Intelligent Systems and Computational Networks, ICISCN 2025

作者： Shankari, S. Uma Mohameed, Haeedir Kulkarni, Megha Aravindh, S. Purushotham, N. Srm Institute of Science and Technology Department of Computer Science and Applications Ramapuram India The Islamic University of Al Diwaniyah College of Technical Engineering Department of Computers Techniques Engineering Al Diwaniyah Iraq Nitte Meenakshi Institute of Technology Department of Civil Engineering Bengaluru India New Prince Shri Bhavani College of Engineering and Technology Department of Mechanical Engineering Chennai India Mohan Babu University Department of Computer Science and Engineering Tirupati India

ISBN: (纸本)9798331529246

Now a days, the standard of living in urban areas is advanced by leveraging technologies such as Cyber-physical Systems (CPS) and Internet of Things (IoT) with physical infrastructures. However, smart cities highly rely on digital ecosystems, which makes them vulnerable to various cyber threats such as Distributed Denial of Service (DDoS) which leads in violations of privacy and threats to safety of citizens. To develop an effective and efficient system for detection of cybersecurity threats, Box plot Sampling Isolation Forest (BSIF) is proposed. Initially, the data was collected from the Botnet Traffic attack in Internet of Things (BoT-IoT) dataset which contains various normal traffic and Botnet traffic data. After that, Label Encoding (LE) was used for preprocessing the data, which assigns numerical labels to each category in the dataset. Furthermore, Recursive Feature Elimination (RFE) technique was utilized for iterative extraction and selection of features based on their weights is performed by Decision Tree (DT). Finally, the proposed BSIF model is used for detection of cybersecurity threats associated with smart cities, by leveraging box plot sampling method. The proposed obtain better results with 99.74% Precision, 99.92% Accuracy, 99.87% Recall and 99.84% F1-score, compared with Smart Attacks Learning Machine Advisor (SALMA) respectively. © 2025 IEEE.

关键词： Bot (Internet)

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Exploring Hand Gesture Recognition: Trends, technologies, and Application 3

Exploring Hand Gesture Recognition: Trends, Technologies, an...

引用

3rd international conference on Intelligent Data Communication technologies and Internet of Things, IDCIoT 2025

作者： Pohekar, Ayesha Pundge, Ajitkumar Shirsath, Vishal School of Engineering Ajeenkya DY Patil University Maharashtra Pune India

ISBN: (纸本)9798331527549

Hand Gesture Recognition (HGR) systems have garnered significant attention due to their applications in human-computer interaction, virtual reality, and assistive technologies. However, achieving adaptable, accurate, and user-friendly HGR solutions remains a challenge due to issues such as environmental variability and user adaptability. This survey explores state-of-the-art HGR techniques, encompassing traditional methods and advanced deep learning-based methodologies. Classification techniques are analyzed based on sensory-based, vision-based, and hybrid input approaches, highlighting their respective strengths and limitations. The impact of feature extraction methods, dataset quality, and real-time processing on the performance of classification algorithms is discussed. By addressing these challenges, this work identifies potential pathways for advancing HGR systems to enhance their usability and reliability across diverse applications. © 2025 IEEE.

关键词： Palmprint recognition

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Advancing Deep Learning on Edge Devices: Fine-Tuning and Deployment of YOLOv7 Model for Efficient Object Detection in AI based computer Vision applications 3

Advancing Deep Learning on Edge Devices: Fine-Tuning and Dep...

引用

3rd international conference on Intelligent Data Communication technologies and Internet of Things, IDCIoT 2025

作者： Shekhar, Sudhanshu Sathwik, T.S. Pritwani, Mayank Mohana Ramakanth Kumar, P. Sreelakshmi, K. RV College of Engineering® Bengaluru India

ISBN: (纸本)9798331527549

This paper investigates the optimization and deployment of YOLOv7 deep learning model on NVIDIA Jetson Nano, an AI-focused edge computing platform for object detection in various computer vision applications. The work leverages TensorRT and quantization techniques for model acceleration for good detection accuracy. Further it examines performance metrics such as speed, accuracy, and resource utilization for image dataset. The model is trained using 80 different classes of objects and demonstrates the use of 6 classes. The average detection accuracy obtained 92.35% and the average processing time is 117.8ms. This work supports AI by demonstrating the feasibility of running deep learning models on edge devices and provides insight into the challenges and opportunities of optimizing AI models for energy-efficient, real-time operations on edge devices for various computer vision applications. © 2025 IEEE.

关键词： Adversarial machine learning

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SMS Spam Detection using Advance Naive-Bayes Approach

SMS Spam Detection using Advance Naive-Bayes Approach

引用

2025 international conference on Pervasive Computational technologies, ICPCT 2025

作者： Arora, Yojna Gupta, Neha Rathore, Yogesh Singh Bansal, Nidhi Mehta, Aina Chadha, Shikha Kumar, Ashwani Sharda University Department of Computer Science and Engineering Greater Noida India Symbiosis University of Applied Sciences School of Computer Science & Information Technology Madhya Pradesh Indore India Sharda University School of Engineering and Technology Department of Computer Science and Applications Uttar Pradesh Greater Noida India School of Engineering and Technology Department of Computer Science & Engineering Haryana Faridabad India Bennett University School of Computer Science Engineering and Technology India

ISBN: (纸本)9798331508685

Recently, with increased use of mobile phones, it has transformed into a multibillion-dollar Short Message Service or SMS. However, the drop in the cost of messaging services has led to an increased number of unsolicited commercial messages, or spam, being delivered to mobile phones. Several reasons exist for which traditional algorithms used in email filtering may not efficiently classify the spam in SMS such as the absence of strong SMS spam databases, with the short length and features of the message, the informal language used, etc. This paper uses a real SMS spam database After preprocessing the data and extraction of relevant features, Naïve Bayes machine learning techniques is applied to get the results. Then it is analyzed using confusion matrix, accuracy, precision and recall values. A learning curve with clearly defined relationship between the training and testing data set and overall error at the end. © 2025 IEEE.

关键词： Adversarial machine learning

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Chatbot and its Impact on the Retail Industry 3

Chatbot and its Impact on the Retail Industry

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3rd international conference on Intelligent Data Communication technologies and Internet of Things, IDCIoT 2025

作者： Tatikonda, Reshmi Kempanna, M. Thatikonda, Ramya Bhuvanesh, A. Thota, Ragupathi Keerthanadevi, R. Department of Computer Information Systems University of the Central Missouri Warrensburg United States Department of AI and ML Bangalore Institute of Technology Bengaluru India Department of Information Technology University of the Cumberlands Williamsburg United States Department of Electrical and Electronics Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli India Department of Information Technology Jawaharlal Technological University Hyderbad India Department of Computer Science and Engineering PSN College of Engineering and Technology Tirunelveli India

ISBN: (纸本)9798331527549

This study explores the transformative potential of chatbots in the retail industry, highlighting their role in enhancing customer engagement, optimizing business processes, and revolutionizing the nature of retail interactions. Through a comprehensive review of existing literature and case studies, the paper delves into the cognitive processes underlying human-chatbot interactions and examines their impact on customer experience, satisfaction, and loyalty. Chatbots serve a wide array of operational functions, including inventory management, automated order processing, data-driven analytics, and employee training. These functionalities streamline workflows, improve efficiency, and maximize resource utilization. The paper further explores the innovative applications of chatbots, including AI-driven personalization, conversational commerce, and seamless integration with emerging technologies. By analyzing both the current applications and challenges of chatbot technology in retail, the study uncovers the exciting opportunities they present for shaping the future of retail by fostering more personalized, efficient, and interactive customer experiences. © 2025 IEEE.

关键词： Inventory control

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Computational Modeling of Thermal Effects on MoS2 Electrodes in KOH Electrolyte for Energy Storage applications 3

Computational Modeling of Thermal Effects on MoS2 Electrodes...

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3rd international conference on Intelligent and Innovative technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Singh, Iqbal Kaur, Amardeep Hamza, Muhammad Sharma, Rohit Southern Illinois University Edwardsville Electrical and Computer Engineering EdwardsvilleIL United States Beijing Institute of Technology School of Mechanical Engineering Beijing China Satyam Institute of Engineering & Technology Punjab Amritsar India

ISBN: (纸本)9798331515911

An axisymmetric two-dimensional model of a supercapacitor using molybdenum disulfide electrodes and 1M KOH electrolyte is simulated under different operating cell currents involving charge-discharge process using COMSOL Multiphysics to analyze different temperatures, inner temperature distribution field, electric current density, ion concentration and various types of heat transfers. In this paper, the influence of different current values on the thermal behavior of the supercapacitor is investigated and key thermal trends are identified showing the effects of increasing current on the supercapacitor. © 2025 IEEE.

关键词： Potassium hydroxide

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Innovative Construction technologies for Smart Villages: Case Study Karabakh 2nd

Innovative Construction Technologies for Smart Villages: Cas...

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2nd international conference on Information technologies and Their applications

作者： Mammadova, Gulchohra Akbarova, Samira Azerbaijan Univ Architecture & Construct 11 A Sultanova AZ-1073 Baku Azerbaijan

ISBN: (纸本)9783031734199;9783031734205

Currently, Azerbaijan is rebuilding the once-destroyed settlements of Karabakh, implementing the concept of a "smart" village. Despite a significant number of such projects around the world, the level of their theoretical and methodological validity is not sufficient. This paper examines the construction technologies for sustainable smart villages, focusing on innovative energy-efficient engineering systems and measures. The subject of the study is a set of theoretical and practical aspects of the realization of the smart village concept to justify the effectiveness of the applied innovative construction technologies in the realized pilot project of smart village Agali in Karabakh. The methodological basis of the work was the comparative, statistical, and logical analysis of foreign academic studies on the problems of rural development. The main conceptual components of the Azerbaijani model of a smart village are described, the effectiveness of applied innovative construction technologies is substantiated, and scientific-practical recommendations for further realization of the smart village concept in the socioeconomic realities of Azerbaijan are developed. It is proposed to create a catalog of energy-saving and energy-efficient innovative technologies adaptive for the region;a map of the village competencies with the indication of economic specialization;and a model concept of integrated development of the village with the help of advanced IT solutions and green energy sources, taking into account the availability of resources, specific features, and the historical development path of a village.

关键词： Green Energy Efficient Systems Scientific-practical Recommendations Catalog of Energy-Saving technologies Map of Competencies Economic Specialization

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