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20th International computer Conference on Wavelet Active media technology and information Processing, ICCWAMTIP 2023

作者： Zeeshan, Hafiz Muhammad Bin Heyat, Md Belal Bin Hayat, Mohd Ammar Parveen, Saba Akhtar, Faijan Sayeed, Eram Akhtar, Soha Singh, Priya Mohsin, Mohd Parveen, Saima Singh, Bandana Iqbal, Abid Li, Jian Ping Abdelgeliel, Asmaa Sayed National College of Business Administration and Economics Department of Computer Science Lahore Pakistan CenBRAIN Neurotech Center of Excellence School of Engineering Westlake University Hangzhou China M.A.H. Inter College Laxmipur Deoria India College of Electronics and Information Engineering Shenzhen University Shenzhen China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Government Co-ed Sarvodaya Vidyalaya New Delhi India Hamdard Public School New Delhi India Dreamvessels Technology UP India Meerut Institute of Engineering and Technology Department of Electronics and Communication Engineering Meerut India Shah Abdul Latif University Department of Mathematics Khairpur Pakistan School of Media and Communication Shenzhen University Shenzhen China Central Library Prince Sultan University Riyadh Saudi Arabia South Valley University Botany & Microbiology Department Qena83523 Egypt

ISBN: (纸本)9798350318982

COVID-19's control hinges on precise virus identification in healthcare. The Internet of Medical Things (IoMT) denotes the online network of medical devices and apps facilitating data exchange. IoMT's recent rapid expansion indicates a rising use of internet-linked medical tools in healthcare. However, concerns about security and timely healthcare delivery impede IoMT-based application adoption. Safeguarding patient information and averting unauthorized access to medical systems remain paramount. Digital Clinical Trials (DCTs) are gaining significance, offering participation avenues regardless of time or location constraints. For their widespread adoption, IoMT and IoHT-based medical device development is crucial. The Internet of Health Things (IoHT), interlinking medical devices and apps, simplifies health data sharing. Scopus, a comprehensive academic database, was searched for IoMT-related papers between January 2017 and December 2022. Utilizing statistical tools like R, Biblioshiny, Bibliometrix, VOSviewer, and Microsoft Excel 365, 578 pertinent publications were analyzed, offering valuable insights. Additionally, 500 relevant papers were found in the Web of Science (WoS) database, contributing to this field's understanding and advancement. © 2023 IEEE.

关键词： Intelligent systems

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Optical Wavelength Tunability of Negative Refractive Index Transmission Line Phase Shifter

Optical Wavelength Tunability of Negative Refractive Index T...

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Antennas and Propagation & USNC/URSI National Radio Science Meeting

作者： Asif Bilal Abdul Quddious Atsushi Kanno Tetsuya Kawanishi Marco A. Antoniades Stavros Iezekiel EMPHASIS Research Centre University of Cyprus Nicosia Cyprus Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Chair for RF and Photonics Engineering Technische Universität Dresden Dresden Germany Nagoya Institute of Technology Aichi Japan National Institute of Information and Communications Technology Tokyo Japan Waseda University Tokyo Japan Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University Toronto ON Canada

ISBN: (数字)9798350369908

ISBN: (纸本)9798350369915

An optically reconfigurable phase shifter based on negative-refractive-index transmission line (NRI-TL) metamaterials is presented; the design is suitable for 5G antenna beam steering. Continuous tuning of the transmitted signal's phase is achieved by using varactor diodes for which the biasing is provided via an array of photodiodes placed on the back of the substrate. These are illuminated by a remote optical source whose wavelength can be tuned in the visible range, thus enabling indirect control of the varactor capacitance (and hence the phase shift) while also eliminating the need for a complex biasing network. Three different phases are achieved by illuminating the photodiode array with three different wavelengths (blue, green, and red). The compact size along with simplified biasing network introduced by the inclusion of the optical wavelength tunability has numerous applications in antenna and phased array technology, making the design a suitable candidate for 5G beam steering applications.

关键词： Phased arrays Varactors Beam steering Optical design Phase shifters Optical fiber networks Optical variables control

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Enhancing Older Adults’ Gesture Typing Experience Using the T9 Keyboard on Small Touchscreen Devices

arXiv

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arXiv 2023年

作者： Kuang, Emily Chen, Ruihuan Fan, Mingming Golisano College of Computing and Information Sciences Rochester Institute of Technology United States School of Information Rochester Institute of Technology United States Computational Media and Arts Thrust The Hong Kong University of Science and Technology Guangzhou China Division of Integrative Systems and Design Department of Computer Science and Engineering The Hong Kong University of Science and Technology China

Older adults increasingly adopt small-screen devices, but limited motor dexterity hinders their ability to type effectively. While a 9-key (T9) keyboard allocates larger space to each key, it is shared by multiple consecutive letters. Consequently, users must interrupt their gestures when typing consecutive letters, leading to inefficiencies and poor user experience. Thus, we proposed a novel keyboard that leverages the currently unused key 1 to duplicate letters from the previous key, allowing the entry of consecutive letters without interruptions. A user study with 12 older adults showed that it significantly outperformed the T9 with wiggle gesture in typing speed, KSPC, insertion errors, and deletes per word while achieving comparable performance as the conventional T9. Repeating the typing tasks with 12 young adults found that the advantages of the novel T9 were consistent or enhanced. We also provide error analysis and design considerations for improving gesture typing on T9 for older adults. © 2023, CC BY-NC-ND.

关键词： Touch screens

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Improving IoT Security Using Elliptic Curve Integrated Encryption Scheme with Primary Structure-Based Block Chain technology 4th

Improving IoT Security Using Elliptic Curve Integrated Encry...

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4th International Conference on Innovative Data Communication Technologies and Application, ICIDCA 2022

作者： Chauhan, Chetan Ramaiya, Manoj Kumar Rajawat, Anand Singh Goyal, S.B. Verma, Chaman Raboaca, Maria Simona Faculty of Engineering and Technology SAGE University Indore India School of Computer Science and Engineering Sandip University Maharshtra Nashik India Faculty of Information Technology City University Malaysia Department of Media and Educational Informatics Faculty of Informatics Eötvös Loránd University Budapest1053 Hungary ICSI Energy Department National Research and Development Institute for Cryogenics and Isotopic Technolog Ramnicu Valcea240050 Romania

Security and privacy remain as a significant challenge in the distributed Internet of Things (IoT) framework. IoT has already demonstrated that it can significantly impact our daily lives. The internet sends and receives a large volume of data from different devices present worldwide. IoT comprises of heterogeneous units present across a wide variety of networks to communicate sensitive and non-critical data, resulting in significant challenges in terms of protecting and ownership of the data collected from users. The Internet security architecture developed in a constrained location, such as healthcare, is presented in this research work. Across a range of networks and PCs, the system offers safe data sharing and authentication mechanism. The proposed design is based on the blockchain technology's underlying structure and the usage of secure hazarding. This research study has attempted to propose a technique for improving IoT security using elliptic curve integrated encryption scheme with primary structure based blockchain technology. © 2023 The Authors. Published by Elsevier B.V.

关键词： Blockchain

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Cultural-aware Machine Learning based Analysis of COVID-19 Vaccine Hesitancy

Cultural-aware Machine Learning based Analysis of COVID-19 V...

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IEEE International Conference on Communications (ICC)

作者： Raed Alharbi Sylvia Chan-Olmsted Huan Chen My T. Thai Computer and Information Science and Engineering Department University of Florida Gainesville FL USA Department of Media Production Management and Technology University of Florida Gainesville FL USA Department of Advertising University of Florida Gainesville FL USA

Understanding the COVID-19 vaccine hesitancy, such as who and why, is very crucial since a large-scale vaccine adoption remains as one of the most efficient methods of controlling the pandemic. Such an understanding also provides insights into designing successful vaccination campaigns for future pandemics. Unfortunately, there are many factors involving in deciding whether to take the vaccine, especially from the cultural point of view. To obtain these goals, we design a novel culture-aware machine learning (ML) model, based on our new data collection, for predicting vaccination willingness. We further analyze the most important features which contribute to the ML model's predictions using advanced AI explainers such as the Probabilistic Graphical Model (PGM) and Shapley Additive Explanations (SHAP). These analyses reveal the key factors that most likely impact the vaccine adoption decisions. Our findings show that Hispanic and African American are most likely impacted by cultural characteristics such as religions and ethnic affiliation, whereas the vaccine trust and approval influence the Asian communities the most. Our results also show that cultural characteristics, rumors, and political affiliation are associated with increased vaccine rejection.

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Nonasymptotic Performance Limits of Low-Latency Secure Integrated Sensing and Communication Systems

Nonasymptotic Performance Limits of Low-Latency Secure Integ...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Onur Günlü Matthieu Bloch Rafael F. Schaefer Aylin Yener Electrical Engineering Department Linköping University Sweden School of Electrical and Computer Engineering Georgia Institute of Technology USA Chair of Information Theory and Machine Learning TU Dresden Germany BMBF Research Hub 6G-Life & Cluster of Excellence CeTI Dresden Germany Department of Electrical and Computer Engineering The Ohio State University USA

This paper considers an information theoretic model for secure integrated sensing and communication (ISAC) with the goal of establishing fundamental limits in low-latency scenarios. In this secure ISAC model, a message is transmitted through a state-dependent wiretap channel with decoder-side state availability. The model is studied under a strong secrecy constraint when only a part of the transmitted message should be kept secret. First, the secrecy-distortion rate region is established for a degraded channel by treating the model as a special case of a feed-backed secure ISAC model. Finite-length inner bounds are then proved by applying nonasymptotic random binning techniques. Bounds on the rates have a similar form to common finite-length bounds, and the distortion bound follows from a bound for letter-typical sequences.

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Residue super-resolution convolutional neural network based complexity reduction for H.266 VVC intra-coding

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ICT Express 2025年第3期11卷 460-466页

作者： Dhanalakshmi, A. Balaji, L. Raja, C. Giri, Jayant Alrashoud, Mubarak Department of ECE Panimalar Engineering College Chennai India Department of ECE Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India Department of Mechanical Engineering Yeshwantrao Chavan College of Engineering Nagpur India Division of Research and Development Lovely Professional University Phagwara India Chair of Smart Technologies College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia

Versatile Video Coding (VVC) promised to provide the same video quality as HEVC with 50 % bitrate reduction, which was introduced in 2020. Our suggested method for VVC Intra-coding is residue super-resolution convolutional neural network (RSR-CNN) utilizing downsampling and upsampling procedures. We present an effective complexity reduced VVC intra-coding scheme based on residue SR-CNN. Reducing an original video's resolution in both the vertical and horizontal directions is all that is required to execute down sampling. Increasing the video dimensions for improved visual quality, convolutional neural networks are utilized in the upsampling process to create residue super-resolution. Specifically, for every block, we train a CNN model to perform residue SR after downsampling and compressing the residue at low resolution, and then we carry out motion estimation (ME) and motion compensation (MC) to extract the residue. Using the MC prediction signal, a new residue SR-CNN is designed. Additionally, this work comprehensively examines the complexity and performance of VVC intra-coding tools and integrates them with the residue SR-CNN method. The experiments demonstrate a substantial time savings of 40 % in encoding with BDBR coding gains of 4.2 %, and 2.9 % in AI and RA configurations respectively. © 2025 The Author(s)

关键词： Intra-coding Low complexity PSNR Residue super-resolution convolutional neural network VVC

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Analyzing the Impact of Scene Transitions on Indoor Camera Localization through Scene Change Detection in Real-Time

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Intelligent Automation & Soft Computing 2024年第3期39卷 417-436页

作者： Muhammad S.Alam Farhan B.Mohamed Ali Selamat Faruk Ahmed AKM B.Hossain Department of Emergent Computing School of ComputingUniversiti Teknologi MalaysiaJohor Bahru81310Malaysia Malaysia-Japan International Institute of Technology(MJIIT) Universiti Teknologi MalaysiaKuala Lumpur54100Malaysia Media and Game Innovation Centre of Excellence(MaGICX) Universiti Teknologi MalaysiaJohor Bahru81310Malaysia Department of Engineering Technology University of MemphisMemphisTN38152USA Department of Computer Science and Artificial Intelligence College of Computing and Information TechnologyUniversity of BishaBisha61922Saudi Arabia School of Computing Faculty of EngineeringUniversiti Teknologi MalaysiaJohor Bahru81310Malaysia Department of Information System and Cyber Security College of Computing and Information TechnologyUniversity of BishaBisha61922Saudi Arabia

Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance *** scene can change during the image sequence and plays a vital role in the localization performance of robotic applications in terms of accuracy and *** research proposed a real-time indoor camera localization system based on a recurrent neural network that detects scene change during the image *** annotated image dataset trains the proposed system and predicts the camera pose in *** system mainly improved the localization performance of indoor cameras by more accurately predicting the camera *** also recognizes the scene changes during the sequence and evaluates the effects of these *** system achieved high accuracy and real-time *** scene change detection process was performed using visual rhythm and the proposed recurrent deep architecture,which performed camera pose prediction and scene change impact ***,this study proposed a novel real-time localization system for indoor cameras that detects scene changes and shows how they affect localization performance.

关键词： Camera pose estimation indoor camera localization real-time localization scene change detection simultaneous localization and mapping(SLAM)

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Beamforming Design with Partial Channel Estimation and Feedback for FDD RIS-Assisted Systems

arXiv

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arXiv 2023年

作者： Ge, Xiaochun Yu, Shanping Shen, Wenqian Xing, Chengwen Shim, Byonghyo School of Information and Electronics Beijing Institute of Technology Beijing100081 China The School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China The Institute of New Media and Communications Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of

Beamforming design with partial channel estimation and feedback for frequency-division duplexing (FDD) reconfigurable intelligent surface (RIS) assisted systems is considered in this paper. We leverage the observation that path angle information (PAI) varies more slowly than path gain information (PGI). Then, several dominant paths are selected among all the cascaded paths according to the known PAI for maximizing the spectral efficiency of downlink data transmission. To acquire the dominating path gain information (DPGI, also regarded as the path gains of selected dominant paths) at the base station (BS), we propose a DPGI estimation and feedback scheme by jointly beamforming design at BS and RIS. Both the required number of downlink pilot signals and the length of uplink feedback vector are reduced to the number of dominant paths, and thus we achieve a great reduction of the pilot overhead and feedback overhead. Furthermore, we optimize the active BS beamformer and passive RIS beamformer by exploiting the feedback DPGI to further improve the spectral efficiency. From numerical results, we demonstrate the superiority of our proposed algorithms over the conventional schemes. Copyright © 2023, The Authors. All rights reserved.

关键词： Beamforming

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Risk-Sensitive Inhibitory Control for Safe Reinforcement Learning

Risk-Sensitive Inhibitory Control for Safe Reinforcement Lea...

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IEEE Conference on Decision and Control

作者： Armin Lederer Erfaun Noorani John S. Baras Sandra Hirche Chair of Information-oriented Control (ITR) School of Computation Information and Technology Technical University of Munich Munich Germany Department of Electrical and Computer Engineering Institute for Systems Research (ISR) at the University of Maryland College Park MD USA

Humans have the ability to deviate from their natural behavior when necessary, which is a cognitive process called response inhibition. Similar approaches have independently received increasing attention in recent years for ensuring the safety of control. Realized using control barrier functions or predictive safety filters, these approaches can effectively ensure the satisfaction of state constraints through an online adaptation of nominal control laws, e.g., obtained through reinforcement learning. While the focus of these realizations of inhibitory control has been on risk-neutral formulations, human studies have shown a tight link between response inhibition and risk attitude. Inspired by this insight, we propose a flexible, risk-sensitive method for inhibitory control. Our method is based on a risk-aware condition for value functions, which guarantees the satisfaction of state constraints. We propose a method for learning these value functions using common techniques from reinforcement learning and derive sufficient conditions for its success. By enforcing the derived safety conditions online using the learned value function, risk-sensitive inhibitory control is effectively achieved. The effectiveness of the developed control scheme is demonstrated in simulations.

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