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作者： Yang, Bin Wu, Bin You, Yuwen Guo, Chunmei Qiao, Liang Lv, Zhihan School of Energy and Safety Engineering Tianjin Chengjian University Tianjin China Information and Educational Technology Center Zhejiang A & F University Zhejiang Hangzhou China College of Computer Science & Technology Qingdao University Qingdao China Department of Game Design Faculty of Arts Uppsala University Uppsala Sweden

It aims to explore the efficient and reliable wireless transmission and cooperative communication mechanism of Internet of Vehicles (IoV) based on edge intelligence technology. It first proposes an intelligent network architecture for IoV services by combining network slicing and deep learning (DL) technology, and then began to study the key technologies needed to achieve the architecture. It designs the cooperative control mechanism of unmanned vehicle network based on the full study of wireless resource allocation algorithm from the micro level. Second, in order to improve the safety of vehicle driving, deep reinforcement learning is used to configure the wireless resources of IoV network to meet the needs of various IoV services. The research results show that the accuracy rate of the improved AlexNet algorithm model can reach 99.64%, the accuracy rate is more than 80%, the data transmission delay is less than 0.02 ms, and the data transmission packet loss rate is less than 0.05. The algorithm model has practical application value for solving the data transmission related problems of vehicular internet communication, providing an important reference value for the intelligent development of unmanned vehicle internet. © 2022 John Wiley & Sons Ltd.

关键词： Network architecture

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Diagnostic Framework for Mumps Based on Deep Learning with Enhanced Mayfly Optimization Algorithm 1

Diagnostic Framework for Mumps Based on Deep Learning with E...

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1st IEEE International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics, AIKIIE 2023

作者： Mercy, S. Sudha Madhavi, S. Keerthika, A. Prathima, Ch Prabhu, R.T. R.M.K Engineering College Department of Computer Science & Design Chennai India Vel Tech Multi Tech Dr.Rangarajan Dr Sakunthala Engineering College Department of It Chennai India Aarupadai Veedu Institute of Technology Department of Ece Chennai India Department of Data Science Tirupati India Saveetha School of Engineering Simats Department of Ece Chennai India

ISBN: (纸本)9798350316469

The mumps virus causes a very infectious sickness. The enlargement of the parotid salivary glands can be quite uncomfortable. Mumps treatment centers on symptom management. The illness must take its natural course. While most people experience very moderate symptoms, some develop severe consequences. The mumps virus can be avoided with the use of the MMR vaccination. In this research, we employ a convolutional neural network (CNN) technique to better automate mumps detection. In order to automate mumps detection, the authors of this research suggest a convolutional neural network (CNN) trained using XGBoost Classifier data. Incorporating machine learning (ML) technique comparisons. A mumps dataset consisting of 50×50 RGB picture patches served as the basis for all the models. Quantitative findings from each approach were put through validation testing based on their respective effectiveness metrics. To improve the efficiency of the model, the Mayfly Optimization Algorithm is implemented. Results show that the suggested method is effective, with 97% accuracy, suggesting that it might help decrease diagnostic errors caused by human error. And the suggested system we've developed is so precise that it outperforms the CNN model, which only gets around 92% of the time. Consequently, the suggested method is 5% more accurate than the CNN Model. © 2023 IEEE.

关键词： Convolutional Neural Network Mayfly Optimization Algorithm Mumps Classification XGBoost Classifier

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Implementation of an Automatic Incinerator in Real Time for Safe Disposal of Sanitary Waste

Implementation of an Automatic Incinerator in Real Time for ...

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International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES)

作者： Mariaraja P L. Murali Rajesh Sharma R Akey Sungheetha GS Pradeep Ghandasala Rajiv Gandhi K P.A. College of Engineering and Technology Pollachi India Department of CSE Alliance University Bangalore India Department of Computer Science Alagappa University India

ISBN: (数字)9798331506452

ISBN: (纸本)9798331506469

This research work describes the establishment of an automated incineration scheme in real-time for the safe disposal of sanitary waste. Proper sanitary waste disposal is critical for public health and environmental sustainability. Although burning has shown to be an effective way for dealing with such garbage, manual incineration operations are sometimes time-consuming, inefficient, and possibly toxic to workers. The regular disposal methods are dustbin 25%, disposal in open space 23%, common burning method 15% and burying 25%. To overcome these issues, an automated incineration system provides safe and efficient sanitary waste disposal. The proposed system established a complete and dependable waste management system that improves public health and the environment by integrating trash segregation, real-time sensing and control, and safety measures. This gadget is suitable for usage in a variety of environments, including schools, universities, hospitals, and offices. With a current rating of 3 ampere, the real-time implemented model takes 120 seconds to burn the napkin and reaches a temperature of 300°C.

关键词： Temperature sensors Temperature measurement Hospitals Incineration Signal processing Real-time systems Sensors Safety Land surface temperature Public healthcare

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Toward Democratized Generative AI in Next-Generation Mobile Edge Networks

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IEEE Network 2025年

作者： Zhang, Ruichen He, Jiayi Luo, Xiaofeng Niyato, Dusit Kang, Jiawen Xiong, Zehui Li, Yonghui Sikdar, Biplab Nanyang Technological University College of Computing and Data Science Singapore Guangdong University of Technology School of Automation Guangzhou510006 China Singapore University of Technology and Design Pillar of Information Systems Technology and Design Singapore University of Sydney School of Electrical and Information Engineering SydneyNSW2006 Australia National University of Singapore College of Design and Engineering Department of Electrical and Computer Engineering Singapore

The rapid development of generative artificial intelligence (AI) technologies, including large language models (LLMs), has brought transformative changes to various fields. However, deploying such advanced models on mobile and edge devices remains challenging due to their high computational, memory, communication, and energy requirements. To address these challenges, we propose a model-centric framework for democratizing generative AI deployment on mobile and edge networks. First, we comprehensively review key compact model strategies, such as quantization, model pruning, and knowledge distillation, and present key performance metrics to optimize generative AI for mobile deployment. Next, we provide a focused review of mobile and edge networks, emphasizing the specific challenges and requirements of these environments. We further conduct a case study demonstrating the effectiveness of these strategies by deploying LLMs on real mobile edge devices. Experimental results highlight the practicality of democratized LLMs, with significant improvements in generalization accuracy, hallucination rate, accessibility, and resource consumption. Finally, we discuss potential research directions to further advance the deployment of generative AI in resource-constrained environments. © 1986-2012 IEEE.

关键词： Generative adversarial networks

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Measuring the Interaction of Conflict-Minimizing and Goal-Seeking Motor Imperatives in Autism Spectrum Disorder 1

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53rd International Simulation and Gaming Association Conference, ISAGA 2022

作者： Rengarajan, Sundararaman Cannon, Jonathan Baron, Brendan Mohan, Naren Chukoskie, Leanne Department of Physical Therapy Movement and Rehabilitation Sciences Northeastern University Boston United States Department of Brain and Cognitive Sciences Massachusetts Institute of Technology Cambridge United States Khoury College of Computer Sciences Northeastern University Boston United States Department of Mechanical and Industrial Engineering College of Engineering Northeastern University Boston United States Art + Design College of Arts Media and Design Northeastern University Boston United States

ISBN: (数字)9783031371714

ISBN: (纸本)9783031371707

When subjected to sensory conflict, our bodies respond spontaneously and unconsciously to reduce or resolve it. We developed a Virtual Reality (VR) phase-matching task to establish a framework for explaining behaviors under conflict using hand-tracking, eye-tracking and pupillometry. We also describe a computational model of this behavior that was designed to help us understand differences in observed behavior from autistic individuals and non-autistic peers. We expect that known differences in prediction and attention mechanisms in autism will be important for accounting for behavioral differences observed in the task, highlighting these mechanisms as targets for future intervention. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Eye tracking

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Enhancing healthcare data security using RFE and CRHSM for big data

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computers in Biology and Medicine 2025年 190卷 110063-110063页

作者： Sreedhar, C. Mahesh babu, K. Kallam, Suresh Ghantasala, G.S. Pradeep Anthoniraj, S. Kumarganesh, S. Martin Sagayam, K. Pandey, Binay Kumar Pandey, Digvijay Department of CSE G. Pulla Reddy Engineering College Andhra Pradesh Kurnool India Department of CSE Ravindra College of Engineering for Women AP Kurnool India Karnataka India Department of CSE Alliance College of Engineering and Design Faculty of Science & Technology Alliance University Bengaluru India Bangalore India Department of ECE Knowledge Institute of Technology Tamil Nadu Salem India Department of ECE Karunya Institute of Technology and Sciences Tamil Nadu Coimbatore India Department of Information Technology College of Technology Govind Ballabh Pant University of Agriculture and Technology Pantnagar Udham Singh Nagar Uttarakhand India Lucknow India

Providing security to the medical big data stored in healthcare cloud systems is the most exciting and demanding task in the present day. Many researchers use cryptographic techniques to protect big data against malicious users/attacks in cloud environments. Still, they face the problems of high complexity in operations, increased time consumption, storage overhead, and lack of efficiency. Hence, this paper aims to develop a new extensive data security framework for improving the reliability of healthcare systems. The main contribution of this work is to introduce a novel Cohesive Random-Hash based Security Model (CRHSM) for securing both user authentication and medical records. Here, the hospital environment is considered with the entities of patients, healthcare professionals, and hospital servers. In this environment, the registered entities can only participate in communication, including system initialization, registration, login, authentication, encryption, and decryption modules. First, the entities must register with the hospital server to obtain the smart card for further communications. Here, the Squirrel Search Optimization (SSO) technique generates the random number used for the registration phase. During the login and authentication module, the legitimacy of patients and healthcare professionals is validated based on the authentication parameters. Moreover, the medical records are encrypted before storing them in the cloud systems using an efficient Reformist Feistel Encryption (RFE) mechanism. Moreover, various evaluation parameters are considered for assessing the performance of the proposed model, and the evaluated values are compared with security approaches to validate the effectiveness of the proposed scheme. © 2025 Elsevier Ltd

关键词： Electronic health record

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User Persona Mapping Technique for Human Interaction with Augmented and Virtual Reality Environments

User Persona Mapping Technique for Human Interaction with Au...

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2023 International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023

作者： Nandhini Devi, S. Shiny, A. Sureshbabu, J. Mahalakshmi, S. Sundara Bala Murugan, P. Priya, R. Sri Sairam Engineering College Department of MTECH-C.S.E. Chennai Tambaram India Nanjappa Polytechnic College Department of E.C.E. Tamilnadu Coimbatore India R.M.K. Engineering College Department of Computer Science and Design Tamilnadu Chennai India St. Joseph's Institute of Technology Department of Management Studies Tamil Nadu Chennai India Mohamed Sathak A.J.College of Engineering Department of Information Technology Tamilnadu Chennai India

ISBN: (纸本)9798350300857

An in-depth analysis of user-centered design's function in the context of augmented and virtual reality demonstrates how 'User Persona Mapping' can help satisfy the target audience's requirements. As shown by this study, it is crucial to consider user needs and preferences throughout the design phase of augmented and virtual reality (AR/VR) interfaces. Essential to this analysis is the 'User Persona Mapping' technique, which entails the construction of detailed user personas based on extensive user research. By synthesizing user attributes, behaviors, and preferences, designers can better meet the expectations of their end users if they first construct a concrete representation of that demographic. Through real-world examples, this article demonstrates how this strategy can be used to improve the usability of augmented and virtual reality interfaces. This study contends that in the future of interactive technology, empathic design will be essential for ensuring that extended and virtual reality experiences are not only innovative but also authentically user-centric and engaging. © 2023 IEEE.

关键词： Augmented reality

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Remaining Useful Life Estimation of Lenses for an Ion Beam Etching Tool in Semiconductor Manufacturing Using Deep Convolutional Neural Networks 13

Remaining Useful Life Estimation of Lenses for an Ion Beam E...

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13th International Conference on Electronics, Communications and Networks, CECNet 2023

作者： Wan, Jian McLoone, Seán Department of Mechanical Biomedical and Design Engineering School of Engineering and Technology College of Engineering and Physical Sciences Aston University BirminghamB4 7ET United Kingdom School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast BelfastBT9 5BN United Kingdom

ISBN: (纸本)9781643684802

Maintenance plays a significant role in semiconductor manufacturing as plant yield, factory downtime and operation cost are all closely related to maintenance efficiency. Accordingly, maintenance strategies in semiconductor manufacturing industries are increasingly shifting from traditional preventive maintenance (PM) to more efficient predictive maintenance (PdM). PdM uses manufacturing process data to develop predictive models for remaining useful life (RUL) estimation of key equipment components. Traditional approaches to building predictive models for RUL estimation involve manual selection of features from manufacturing process data. This paper proposes to use deep convolutional neural networks (CNN) for the task of estimating RUL of lenses for an ion beam etch tool in semiconductor manufacturing. The proposed approach has the advantage of automatic feature extraction through the use of convolution and pool filters along the temporal dimension of the optical emission spectroscopy (OES) data from the endpoint detection system. Simulation studies demonstrate the feasibility and the effectiveness of the proposed approach. © 2024 The authors and IOS Press.

关键词： Optical emission spectroscopy

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Retraction Note: Enhancing low latency and high performance in clustered-based wireless sensor network routing using genetic algorithm for 5G networks

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Optical and Quantum Electronics 2024年第11期56卷 1-2页

作者： Banu, Firdouse Udhayamoorthi, M. Ramana Gupta Nallagattla, Venkata Phaneendra Maguluri, Lakshmana Mahesh Kumar, N. B. Jayachitra, S. Department of Applied Information System Applied College King Khalid University Khamis Mushaiyt Saudi Arabia Department of Computer Science and Design Karpagam College of Engineering (Autonomous) Coimbatore India Department of CSE Prasad V. Potluri Siddhartha Institute of Technology Vijayawada India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram India Department of Computer Science and Engineering Hindusthan Institute of Technology Coimbatore India Department of Electronics and Communication Engineering PSNA College of Engineering and Technology Dindigul India

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Smart Alert Fencing System for Crop Protection Against Wild Animals

Smart Alert Fencing System for Crop Protection Against Wild ...

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International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES)

作者： K.Anish Pon Yamini Priscilla Whitin Jeba Singh. O K. Suthendran Sheila Mahapatra Rajesh Sharma R Department of ECE Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Chennai India Department of EEE Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Chennai India Centre for Academic Research Alliance University Bengaluru India Department of IT Kalasalingam Academy of Research and Education Krishnankoil Tamilnadu India Department of EEE Alliance College of Engineering and Design Alliance University Bengaluru India Department of CSE Alliance College of Engineering and Design Alliance University Bengaluru India

ISBN: (数字)9798331506452

ISBN: (纸本)9798331506469

India, with massive agricultural and has different plants starting from paddy to tomato. However, few plants are destroyed due to animal risk and therefore protection is required to shop the vegetation from animals. digital fencing that functions much like bodily fencing for animals the usage of the GSM era. Digital fencing for wild animals is meant to restrict animals to the best few regions. This helps the proprietors to reveal their farms remotely from anywhere in the international. This comprises of a microcontroller-based tracking together with IR (Infrared) sensors. When an un-legal entry is detected, the sends SMS signals/calls to the farm/subject proprietor mechanically and presents audible indicators using a buzzer inside the prototype and the usage of the siren in actual time applications. This allows us to keep away such wild animals from the farmlands in addition to offering surveillance capability.

关键词： GSM Animals Surveillance Crops Vegetation mapping Signal processing Message services Security Protection Videos

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