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Computational Intelligence, Communication Technology and Networking (CICTN), International Conference on

作者： A. Anitha Lis Maria Saju Balakrishnan Kamaraj School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore Tamil Nadu India Madurai Medical College Madurai Tamilnadu India

ISBN: (数字)9798331530389

ISBN: (纸本)9798331530396

Deepfake technology has rapidly evolved, posing a serious threat to the authenticity of digital media and contributing to the spread of misinformation. The manipulation of media content raises significant concerns across sectors like politics, entertainment, and social media, undermining public trust in digital information. In response, this research proposes an advanced deepfake detection model that integrates Explainable Artificial Intelligence (XAI) techniques within a hybrid deep learning architecture. The proposed model combines ResNet50 and Vision Transformer (ViT) to capture spatial and contextual features effectively. While exploring additional methods such as facial landmark detection and frequency domain analysis, the final model focuses on the ResNet50-ViT combination for its superior performance to fusion model. To ensure transparency, the model employs XAI techniques such as LIME (Local Interpretable Model-agnostic Explanations) and SHAP (SHapley Additive exPlanations), offering interpretability by revealing the key factors that influence its predictions. This dual focus on high detection accuracy and interpretability ensures that the model not only detects deepfakes effectively but also builds trust in automated decision-making processes. By leveraging cutting-edge deep learning and XAI methods, this framework offers a more reliable, transparent, and adaptable solution for preserving digital media authenticity across various applications, ultimately contributing to combating misinformation and fostering trust in digital content.

关键词： Deep learning Deepfakes computer vision Analytical models Adaptation models Explainable AI Frequency-domain analysis Predictive models Transformers Residual neural networks

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Optimizing Security Protocols for IoT in Healthcare to Ensure Privacy in Smart Patient Monitoring Systems

Optimizing Security Protocols for IoT in Healthcare to Ensur...

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2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Karthiyayini, J. Bhargavi, Y. Krishna Lakhanpal, Sorabh Sharma, Amit Kumar Saeed, Ali Kumari, E.N. Vijaya New Horizon College of Engineering Department of Information Science Engineering Bangalore India Griet Department of Cse Bachupally Telangana Hyderabad India Lovely Professional University Phagwara India Galgotias university Department of Electrical Electronics & Communication Engineering Uttar Pradesh Gerater Noida203201 India College of Medical Technology The Islamic University Radiology Techniques Department Najaf Iraq Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India

ISBN: (纸本)9798331527495

The Internet of Things (IoT) might improve healthcare. Smart patient tracking systems may benefit. There are many networked gadgets, creating new security risks. Privacy and accessibility of patient data require strong security measures. This paper addresses this requirement by proposing a comprehensive hospital IoT security approach for patient-tracking smart devices. Our solution's stringent methodology uses contemporary encryption, blockchain, and machine learning-based anomalous detection. This combination aims to provide a full security system for all assaults. Healthcare IoT is complicated and ever-changing;hence, this is essential. The introduction emphasizes the need for patient data security in smart tracking systems to set the stage for constructing and evaluating the recommended security design. The study's security design outperforms current techniques in several key aspects. The recommended approach outperforms Triple DES (88%), RSA (85%), AES (90%), and SHA-256 (88%), with a security level of 95%. This new approach computes in 4 milliseconds, much faster than Triple DES (7 milliseconds), RSA (5 milliseconds), AES (6 milliseconds), and SHA-256 (8 milliseconds). These data demonstrate that the proposed security architecture is superior and can secure hospital IoT. In the ever-changing world of healthcare IoT, the recommended response protects patient data safety and accuracy in smart patient monitoring systems. © 2025 IEEE.

关键词： Sensitive data

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Federated Learning for Privacy-Preserving medical Data Analytics in Big Data

Federated Learning for Privacy-Preserving Medical Data Analy...

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2024 International Conference on Communication, computer sciences and engineering, IC3SE 2024

作者： Madavarapu, Jhansi Bharathi Nainwal, Ankita Shnain, Ammar Hameed Shrivastava, Anurag Yadav, Kanchan Rao, A.L.N. University Of Cumberlands Department Of Information Technology 6178 College Station Drive WilliamsburgKY40769 United States Graphic Era Deemed To Be University Department Of Computer Science & Engineering Dehradun India College Of Technical Engineering The Islamic University Department Of Computers Techniques Engineering Najaf Iraq Saveetha School Of Engineering Saveetha Institute Of Medical And Technical Sciences Tamilnadu Chennai India Gla University Department Of Electrical Engineering Mathura India Lloyd Institute Of Engineering & Technology Greater Noida India

ISBN: (纸本)9798350366846

This examination investigates the application of Federated Learning (FedAvg, FedSGD, FedProx, HEFL) for security safeguarding medical data analytics about big data. Utilizing a different dataset containing electronic well-being records, medical imaging, and wearable gadget data, our review means to work out some kind of harmony between tackling the experiences implanted in broad medical care data and defending patient protection. Through thorough trials, it looked at the exhibition of federated learning calculations, taking into account measurements, for example, intermingling rate, exactness, and correspondence above. Results uncovered that FedSGD displayed the quickest combination (50 rounds) while keeping a high exactness of 89%. FedAvg, described by straightforwardness, exhibited combination in 100 rounds with an exactness of 87%. FedProx accomplished a harmony between combination speed (75 adjusts) and model precision (88%). The application of Homomorphic Encryption for Federated Learning (HEFL) showed promising outcomes, meeting in 50 rounds with a precision of 85%, despite the higher correspondence above because of encryption. The near examination with related work featured the predominance of federated learning in security safeguarding and productive medical data analytics. This examination contributes significant experiences to the talk on secure and cooperative medical care analytics in the period of big data. © 2024 IEEE.

关键词： Data Analytics

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Detection of Osteoporosis with DEXA Scan Images using Deep Learning Models

Detection of Osteoporosis with DEXA Scan Images using Deep L...

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2022 IEEE International Conference on Advances in Computing, Communication and Applied informatics, ACCAI 2022

作者： Varalakshmi, P. Sathyamoorthy, Smruthi Darshan, V. Ramanujan, V. Rajasekar, Sakthi Jaya Sundar Madras Institute of Technology Anna University Department of Computer Technology Chennai India College of Engineering Guindy Anna University Department of Information Science and Technology India Melmaruvathur Adhiparasakthi Institute of Medical Sciences and Research India

ISBN: (纸本)9781665495295

Osteoporosis is a chronic degenerative disease. Postmenopausal women and people over 50 years of age are at the highest risk of developing osteoporosis. If left untreated, osteoporosis can prove to be debilitating and might require hospitalization. So it is crucial to identify the risk of osteoporosis and take appropriate measures before the disease can negatively impact the quality of human life. Many existing osteoporosis classification models are computationally expensive and suffer from low accuracy due to inefficient processing of scan images. In this paper, the best model for predicting the risk of osteoporosis using DEXA scan images is identified. To improve the accuracy and specificity of the diagnosis, the scan images are pre-processed using denoising, image enhancement, and thresholding. Different CNN and hybrid models are trained, tested and the performance of the models is charted to infer the best model that gives promising results. Experimental results show that the proposed approach of pre-processing the images, data augmentation, sampling with Synthetic Minority Over Sampling Technique (SMOTE) and Inception v3 CNN model achieves the highest accuracy of 92.05%, specificity of 90.37%, the sensitivity of 93.87%, Precision of 89.97%, and F1 score of 91.88%. © 2022 IEEE.

关键词： Image enhancement

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Cloud-Driven Collaborative Filtering and Waiter Robots Transforming Customer Experiences in Restaurants

Cloud-Driven Collaborative Filtering and Waiter Robots Trans...

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2024 International Conference on Advances in Modern Age Technologies for Health and engineering science, AMATHE 2024

作者： Srinivasan, V. Prasanna Mohankumar, N. Prabakaran, T. Sairam, A. Elangovan, K. Velmurugan, S. R.M.D. Engineering College Department Of Information Technology Tamil Nadu Chennai India Maharashtra Nagpur India Joginpally B.R. Engineering College Department Of Computer Science And Engineering Telangana Hyderabad India Saveetha School Of Engineering Saveetha Institute Of Medical And Technical Sciences Department Of Computer Science And Engineering Thandalam Tamil Nadu Chennai India Dhanalakshmi Srinivasan Engineering College Department Of Mechanical Engineering Tamil Nadu Chennai India T.J.S. Engineering College Department Of Electronics And Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350371567

To improve customer relations, this research investigates the possibility of using cloud-enabled collaborative filtering with robot waiters in restaurant environments. With the use of innovation, to revolutionize the way people eat out. It suggests using smart robots that can interact with customers and help the wait staff out. Customer preferences are analyzed, order suggestions are streamlined, and service is personalized using cloud-based collaborative filtering algorithms. Test this novel approach in a real-world restaurant setting to view how it changes things for the better in terms of customer happiness, service efficiency, and employee output. It seems that the combination of autonomous waiters and collaborative filtering on the cloud might completely change the way people dine out by making everything more streamlined and personalized to each individual's preferences. To the existing conversation about how robots, cloud computing, and customer service intersect in the restaurant industry, which is important since technology is still playing a major influence on how businesses engage with their customers. © 2024 IEEE.

关键词： Collaborative filtering

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Rehearse With User: Personalized Opinion Summarization via Role-Playing based on Large Language Models

arXiv

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arXiv 2025年

作者： Zhang, Yanyue He, Yulan Zhou, Deyu School of Computer Science and Engineering Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University China Department of Informatics King’s College London United Kingdom The Alan Turing Institute

Personalized opinion summarization is crucial as it considers individual user interests while generating product summaries. Recent studies show that although large language models demonstrate powerful text summarization and evaluation capabilities without the need for training data, they face difficulties in personalized tasks involving long texts. To address this, Rehearsal, a personalized opinion summarization framework via LLMs-based role-playing is proposed. Having the model act as the user, the model can better understand the user’s personalized needs. Additionally, a role-playing supervisor and practice process are introduced to improve the role-playing ability of the LLMs, leading to a better expression of user needs. Furthermore, through suggestions from virtual users, the summary generation is intervened, ensuring that the generated summary includes information of interest to the user, thus achieving personalized summary generation. Experiment results demonstrate that our method can effectively improve the level of personalization in large model-generated summaries. Copyright © 2025, The Authors. All rights reserved.

关键词： Economic and social effects

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Dual-Band Planar Microstrip Monopole Antenna Design Using Multi-Objective Hybrid Optimization Algorithm

Dual-Band Planar Microstrip Monopole Antenna Design Using Mu...

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2023 Photonics and Electromagnetics Research Symposium, PIERS 2023

作者： Hosseini, V. Shapour, F. Pinho, P. Farhang, Y. Majidzadeh, K. Ghobadi, Ch. Nourinia, J. Barshandeh, S. Shokri, M. Amiri, Zh. Jalilirad, M. Kaboutari, K. Payame Noor University Department of Computer Engineering and Information Technology Tehran Iran Islamic Azad University Urmia Branch Computer Engineering Department Urmia Iran Instituto de Telecomunicações Aveiro Portugal University of Aveiro Department of Electronics Telecommunications and Informatics Aveiro Portugal Islamic Azad University Khoy Branch Department of Computer Engineering Khoy Iran Urmia University Department of Electrical Engineering Urmia Iran School of Engineering Department of Computer Science Afagh Higher Education Institute Urmia Iran

ISBN: (纸本)9798350312843

This research uses a new proposed multi-objective optimization algorithm that utilizes an untested combined chaotic map to integrate Customized Mutated PSO (CM-PSO) with a Modified Genetic Algorithm (MGA) to design an antenna with specific electromagnetic characteristics. The hybrid approach achieves preferred outcomes faster than PSO, CM-PSO, GA, and MGA by avoiding being trapped in local minimums. The proposed Metaheuristic Algorithm (MA) functionality has been authenticated successfully using Benchmark Functions (BFs) like Rastrigin Function (RaF), Ackley Function (AF), Rosenbrock Function (RoF), and Booth Function (BoF). Finally, the validity of the offered approach for electromagnetic applications is demonstrated by optimizing a dual-band planar microstrip monopole antenna with a simple structure, such that its optimized S11 be less than -10 dB at two frequency bands encompasses 2.4 to 2.484 and 5.15 to 5.825 GHz for Wireless Local Area Network (WLAN) with IEEE 802.11 standards. The proposed algorithm allows the optimization criteria to be customized. The optimization algorithm developed in MATLAB is used to determine the necessary parameter adjustments in order to achieve expected frequency bands using CM-PSO or an innovative MGA, while high-frequency and electromagnetic simulations are performed using computer Simulation Technology (CST) Studio Suite. The dimensions of the proposed antenna's elements are critical input parameters of the algorithm, named decision variables. © 2023 IEEE.

关键词： Monopole antennas

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Was Wuhan the early epicenter of the COVID-19 pandemic?——a critique

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National science Review 2023年第4期10卷 19-21页

作者： Yanan Cao Lingling Chen Hua Chen Yupeng Cun Xiaofeng Dai Hongli Du Feng Gao Fengbiao Guo Yalong Guo Pei Hao Shunmin He Shunping He XiongLei He Zheng Hu Boon-Peng Hoh Xin Jin Qian Jiang Qinghua Jiang Asifullah Khan Hong-Zhi Kong Jinchen Li Shuai Cheng Li Ying Li Qiang Lin Jianquan Liu Qi Liu Jian Lu Xuemei Lu Shujin Luo Qinghua Nie Zilong Qiu Tieliu Shi Xiaofeng Song Jianzhong Su Sheng-ce Tao Chaolong Wang Chuan-Chao Wang Guo-Dong Wang Jiguang Wang Qi Wu Shaoyuan Wu Shuhua Xu Yu Xue Wenjun Yang Zhaohui Yang Kai Ye Yuan-Nong Ye Li Yu Fangqing Zhao Yiqiang Zhao Weiwei Zhai Dandan Zhang Liye Zhang Houfeng Zheng Qi Zhou Tianqi Zhu Ya-ping Zhang Ruijin Hospital Shanghai Jiao Tong University College of Life Science and Technology Guangxi University Beijing Institute of Genomics Chinese Academy of Sciences Children's Hospital of Chongqing Medical University Wuxi School of Medicine Jiangnan University School of Biology and Biological Engineering South China University of Technology Department of Physics School of ScienceTianjin University School of Pharmaceutical Sciences Wuhan University Institute of Botany Chinese Academy of Sciences Institut Pasteur of Shanghai Chinese Academy of Sciences Institute of Biophysics Chinese Academy of Sciences Institute of Hydrobiology Chinese Academy of Sciences School of Life Sciences Sun Yat-sen University Institute of Synthetic Biology Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences Faculty of Medicine and Health Sciences University College Sedaya International School of Medicine South China University of Technology Department of Medical Genetics Capital Institute of Pediatrics School of Life Science and Technology Harbin Institute of Technology Department of Biochemistry Abdul Wali Khan University Xiangya Hospital Central South University Department of Computer Science City University of Hong Kong College of Life Science and Technology Foshan University South China Sea Institute of Oceanology Chinese Academy of Sciences College of Ecology Lanzhou University School of Life Sciences and Technology Tongji University School of Life Sciences Peking University Kunming Institute of Zoology Chinese Academy of Sciences College of Animal Science South China Agricultural University Institute of Neuroscience Chinese Academy of Sciences School of Life Sciences East China Normal University Nanjing University of Aeronautics and Astronautics Wenzhou Institute University of Chinese Academy of Sciences Institute of Systems Biomedicine Shanghai Jiao Tong University Tongji Medical College Huazhong University of Science and Technology School of Life Sciences Xiamen University Division of Life Science and Department of

Recently, Worobey et al.(2022) published a report entitled ‘The Huanan Seafood Wholesale Market in Wuhan was the early epicenter of the COVID-19 pandemic' that succinctly summarizes their study [1]. A pre-print version of this study had earlier elicited a series of highprofile media coverages [2,3]. All these reports deliver a social-political message that the Huanan market is the epicenter of COVID-19.

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Comprehensive Exploration of Acute Febrile Illnesses with Low Platelet Count Syndrome: From Epidemiology to AI-Driven Solutions

Comprehensive Exploration of Acute Febrile Illnesses with Lo...

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2025 International Conference on Artificial Intelligence and Data engineering, AIDE 2025

作者： Rao, Abhishek S. Karthik Pai, B.H. Poojary, Ramaprasad Adithi, K. Shenoy, Rathika Nayak, Sneha Visvesvaraya Technological University Belagavi India NMAM Institute of Technology Nitte Dept. of Information Science & Engineering Nitte India Canara Engineering College Department of Computer Science and Engineering Benjanapadavu India Manipal Academy of Higher Education School of Engineering and IT Dubai campus PO Box no Dubai345050 United Arab Emirates K S Hegde Medical Academy Department of General Medicine Karnataka Mangaluru India American University of Antigua Department of Clinical Medicine University Park Antigua NMAM Institute of Technology Nitte Department of Biotechnology Engineering Karnataka India

ISBN: (纸本)9798331527518

This narrative review provides an in-depth examination of acute febrile illnesses with thrombocytopenia. Utilizing a robust and systematic literature search strategy, the study has identified and analyzed relevant studies to comprehensively understand these conditions. The review addresses the epidemiology of these syndromes, detailing their incidence, prevalence, and geographic distribution. The study explores a wide range of etiologies and the pathophysiological mechanisms that result in low platelet counts. Insights into the clinical presentation and diagnostic criteria are offered, highlighting the symptomatic spectrum and methods for accurate diagnosis. The discussion extends to management and treatment options specific to different etiologies, as well as potential complications and their prognostic implications. Preventive and control measures are also examined to emphasize the significance of public health interventions. Furthermore, the review investigates the promising role of artificial intelligence in the early prediction and diagnosis of these diseases, suggesting pathways for enhanced patient outcomes and more efficient healthcare strategies. © 2025 IEEE.

关键词： Epidemiology

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The Realization Factors of Taiwan's Low Altitude Airspace Economy and UAM: Analysis and Evaluation 20

The Realization Factors of Taiwan's Low Altitude Airspace Ec...

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20th IEEE International Conference on e-Business engineering, ICEBE 2024

作者： Wu, Tung-Ling Kung, Chih-Ming Lin, Guan-Ting Tsai, Kuen-Yu Meng, Guang-Yun Huang, Yu-Che Cheng, Wan-Shu Institute of Transportation at Ministry of Transportation and Communications Taiwan Shin Chin Univeristy Kaohsiung Campus Dep. of Information Technology&Communication Taiwan Providence University Dep. of Computer Science and Information Management Taichung Taiwan National Taiwan Univeristy Department of Electrical Engineering Taipei Taiwan Executive Officer Center for Research on High-Performance Remote Sensing and Urban Informatics Ntu Taiwan

ISBN: (纸本)9798350365856

Low altitude airspace economy applications will be of highly effective in a wide range of civil activities and will be a critical element in the smart cities of the future. In view of the main features of unmanned aerial vehicle (UAV), such as automatic piloting system, access to uninhabited areas, low cost compared to road and manned aircraft, shorter delivery time, and the ability to carry heavy payloads, it is important to recognize that UAVs can be used for a wide range of civil activities. With the development of these applications in full swing around the world, in addition to advanced communications technology and other related infrastructure, business demand and a favorable investment climate, clarity, definiteness and feasible regulations in the Taiwanese environment are also essential. Based on the premise of local economic strength, the technical level of the telecommunication industry, and commercial demands, Taiwan should establish a rational standard for the UAV regulatory system as soon as possible, so as to facilitate the development of UAM and to ensure the international competitiveness of the related technologies for market development © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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