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Communication and Information technology (AICCIT), Al-Sadiq International Conference on

作者： Mohammed S. Khalaf Aeizaal Azman A. Wahab Haider A Al-Wzwazy Ahmed Salih Al-Khaleefa Murtadha A. Alazzawi Mohammed Almohamadi School of Electrical & Electronic Engineering Universiti Sains Malaysia Pulau Pinang Malaysia Halfaya Oilfield Division Maysan Iraq Department of Physics Faculty of Education University of Misan Maysan Iraq Department of Computer Techniques Engineering Imam Al-Kadhum College (IKC) Baghdad Iraq Department of Computer Technical Engineering College of Information Technology Imam Ja’afar Al-Sadiq University Al-Muthanna Iraq

Here, we depict the ongoing 3GPP Delivery 16 particularly for situating in 5G organizations, which is currently being developed. To address the issues of an extensive variety of administrative, business, and modern use cases, the detail indicates situating signals, estimations, methods, and framework engineering. Accordingly, when contrasted with what was beforehand conceivable with LTE, 5G essentially advances situating capacities. Utilizing 3GPP reenactment situations that have been settled upon, the demonstrative situating execution is assessed, and it is found that the 90 percentile precision goes from a couple of meters to a couple of decimeters, contingent upon the procedures and suppositions utilized.

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A transformer-based model for effective and exportable IoMT-based stress detection

A transformer-based model for effective and exportable IoMT-...

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GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Moudy Sharaf Alshareef Badraddin Alturki Mona Jaber School of Electronic Engineering and Computer Science Queen Mary University of London London UK Department of Computer Science Umm Al-Qura University Makkah Saudi Arabia Department of Information Technology Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia

ISBN: (纸本)9781665435413

Pervasive e-healthcare services have evolved rapidly in the recent years with the surge of the Internet of Medical Things (IoMT). Intelligent stress monitoring assistant is such an example that uses affective computing to detect stress levels based on biological signals. Existing works use different forms of machine learning and deep learning methods to successfully detect stress in pre-defined individuals. However, such models fail to recognise stress in unseen people, a problem that is harder to solve but of critical importance when three quarters of people in our society feel unable to cope due to stress. In this work, we propose a deep learning method that leverages self-attention to compute representations of the network's input and output layers and yields a generic stress detection model. We present a comparative analysis in which we examine the efficacy of Random Forest with handcrafted features, CNN-based deep learning, and transformer network with multi-modal data. Our results show that the proposed transformer solution outperforms the state of the art in all scenarios with accuracy of 96% and F1 score of 97%. More importantly, the model is validated using a leave-one-subject-out (LOSO) approach, hence is exportable and can successfully detect the stress condition of any unseen person.

关键词： Deep learning Performance evaluation Analytical models Art Computational modeling Internet of Medical Things Transformers

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Retraction Note: Resnet-based deep learning multilayer fault detection model-based fault diagnosis

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Multimedia Tools and Applications 2024年第38期83卷 86323-86324页

作者： Jaber, Mustafa Musa Ali, Mohammed Hasan Abd, Sura Khalil Jassim, Mustafa Mohammed Alkhayyat, Ahmed Majid, Mohammed Sh. Alkhuwaylidee, Ahmed Rashid Alyousif, Shahad Informatics Institute for Postgraduate Studies Iraqi Commission for Computers and Informatics Baghdad Iraq Department of Computer Science Al-Turath University College Baghdad Iraq Computer Techniques Engineering Department Faculty of Information Technology Imam Ja’afar Al-Sadiq University Najaf Iraq Directorate of Research and development Ministry of Higher Education and Scientific Research Baghdad Iraq Department of Medical Instruments Engineering Techniques Al-Farahidi University Baghdad Iraq College of Technical Engineering The Islamic University Najaf Iraq Medical Instrumentation Techniques Engineering Department Al-Mustaqbal University College Babylon Iraq Computer Technical Engineering Mazaya University College Thi Qar Iraq Department of Electrical and Electronic Engineering College of Engineering Gulf University Sanad Kingdom of Bahrain Research Centre University of Mashreq Baghdad Iraq

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Design of Wideband Transmitarray with 1-Bit Beam-Deflection

Design of Wideband Transmitarray with 1-Bit Beam-Deflection

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IEEE International Conference on electronic Information and Communication technology (ICEICT)

作者： Liwei Rao Botao Feng Xiao Ding Wenzhe Gu Sanshan Sun Qingsheng Zeng College of Electronics and Information Engineering Shenzhen University Shenzhen China Faculty of Humanities and Arts Macau University of Science and Technology Macau China School of Computer Science and Engineering Huizhou University Huizhou China College of Physics and Electronic Engineering Sichuan Normal University Sichuan China College of Astronautics Nanjing University of Aeronautics and Astronautics Nanjing China

This paper introduces a linearly polarized beam-deflection array that operates in the X-band and has a phase resolution of 1 bit. The transmission unit consists of three media layers and three metal layers. Its metal layers include metal strips with specific arrangements are used to twist the polarization of electromagnetic waves by $\boldsymbol{\pm 90^{\circ}}$ , and then the middle metal layer is rotated by 90° to form a phase difference of 0°/180°. A $\boldsymbol{20\times 20}$ transmission array with beam deflection is designed using this unit. The designed antenna array shows good electrical characteristics including gain of 16 dBi at 11GHz and stable radiation patterns at both H- and V-planes.

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Maximal Quantum Interaction between Free Electrons and Photons

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Physical Review Letters 2025年第4期134卷 043803-043803页

作者： Zetao Xie Zeling Chen Hao Li Qinghui Yan Hongsheng Chen Xiao Lin Ido Kaminer Owen D. Miller Yi Yang Department of Physics and HK Institute of Quantum Science and Technology The University of Hong Kong Pokfulam Hong Kong China Z. X. and Z. C. contributed equally to this Letter. Department of Applied Physics and Energy Sciences Institute Yale University New Haven Connecticut 06520 USA Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation College of Information Science and Electronic Engineering Zhejiang University Hangzhou 310027 China Solid State Institute and Faculty of Electrical and Computer Engineering Technion—Israel Institute of Technology 32000 Haifa Israel

The emerging field of free-electron quantum optics enables electron-photon entanglement and holds the potential for generating nontrivial photon states for quantum information processing. Although recent experimental studies have entered the quantum regime, rapid theoretical developments predict that qualitatively unique phenomena only emerge beyond a certain interaction strength. It is thus pertinent to identify the maximal electron-photon interaction strength and the materials, geometries, and particle energies that enable one to approach it. We derive an upper limit to the quantum vacuum interaction strength between free electrons and single-mode photons, which illuminates the conditions for the strongest interaction. Crucially, we obtain an explicit energy selection recipe for electrons and photons to achieve maximal interaction at arbitrary separations and identify two optimal regimes favoring either fast or slow electrons over those with intermediate velocities. We validate the limit by analytical and numerical calculations on canonical geometries and provide near-optimal designs indicating the feasibility of strong quantum interactions. Our findings offer fundamental intuition for maximizing the quantum interaction between free electrons and photons and provide practical design rules for future experiments on electron-photon and electron-mediated photon-photon entanglement. They should also enable the evaluation of key metrics for applications such as the maximum power of free-electron radiation sources and the maximum acceleration gradient of dielectric laser accelerators.

关键词： Quantum optics

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Deep learning based DeepFake video detection

Deep learning based DeepFake video detection

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Smart Computing and Application (ICSCA), International Conference on

作者： Sarra Guefrachi Marwa Ben Jabra Naif A. Alsharabi Mohamed Tahar Ben Othman Yasser O. Alharabi Abdulsalam Alkholidi Habib Hammam Faculty of Engineering Université de Moncton) Moncton NB Canada Spectrum of Knowledge Production & Skills Development Sfax Tunisia Computer Engineering University of Ha'il Computer Science Amran University Yemen Ha'il KSA Department of Computer Science College of Computer) Qassim University Buraydah Saudi Arabia line Computer Science and Information College of computer sc. & engneering Ha'il University Ha'il KSA College Department of Software Engineering Canadian Institute of Technology Tirana Canada International Institute of Technology and Management Commune d'Akanda Libreville BP Ga-bon Dept of Electrical and Electronic Eng. Science School of Electrical Engineering University of Johannes-burg Tirana Canada

Recent advances in DeepFake face-swapping technology have made it simple to create fake videos that appear remarkably real. Since it has been employed in numerous instances for deceit, extortion, and the falsification of facts, its widespread use has generated a huge social, security, and political risk. Its use on websites and social media has become more widespread. Detecting this crime is becoming more and more important due to the potential harm false videos may inflict on a global scale. This research offers a method for building a deep learning model that really can tell the difference between authentic and false videos. The article describes how to create new models based on the VGG16 neural network, a previously created neural network that does image categorization, using transfer learning in the computer vision field. Deep learning is still becoming better at both producing and spotting DeepFakes. DeepFake detection algorithms are developed using dated public datasets, and as a result, they may become obsolete with time. and require continual updating. The research findings are encouraging, and our results reached an accuracy rate of over 90%.

关键词： Deep learning Deepfakes computer vision Social networking (online) Computational modeling Neural networks Transfer learning

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A complete and open Simulink model of the Tennessee Eastman process (COSTEP)

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SoftwareX 2025年 31卷

作者： Johandri Vosloo Kenneth R. Uren George van Schoor School of Electrical Electronic and Computer Engineering Faculty of Engineering North-West University South Africa Unit for Energy and Technology Systems Faculty of Engineering North-West University South Africa

The Tennessee Eastman process serves as a benchmark system for the evaluation of fault diagnosis techniques. Current simulator implementations are available in FORTRAN and in a C-mex S-function in MATLAB. The C-mex file is a conversion of the FORTRAN code to C for implementation in MATLAB. Both implementations have the limitation that not all the variables and parameters are directly accessible. Hence, a complete and open Tennessee Eastman process simulator was developed in Simulink to allow for total access to all parameters and variables and better Simulink integration. This implementation will give researchers more freedom towards the design of control and fault diagnosis techniques.

关键词： Tennessee Eastman process Chemical process simulation Fault diagnosis Simulink

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The state-of-the-art review on resource allocation problem using artificial intelligence methods on various computing paradigms

arXiv

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arXiv 2022年

作者： Joloudari, Javad Hassannataj Mojrian, Sanaz Saadatfar, Hamid Nodehi, Issa Fazl, Fatemeh Shirkharkolaie, Sahar Khanjani Alizadehsani, Roohallah Dipu Kabir, H.M. Tan, Ru-San Rajendra Acharya, U. Department of Computer Engineering Faculty of Engineering University of Birjand Birjand*** Iran Department of Information Technology Mazandaran University of Science and Technology Babol Iran Department of Computer Engineering Qom University of Technology Qom Iran Department of Electronic Engineering Faculty of Electrical and Computer Engineering University of Birjand Birjand Iran Institute for Intelligent Systems Research and Innovation Deakin University GeelongVIC3216 Australia School of Science and Technology Singapore University of Social Sciences Singapore Ngee Ann Polytechnic Singapore599489 Singapore Dept. of Biomedical Informatics and Medical Engineering Asia University Taichung Taiwan

With the increasing growth of information through smart devices, increasing the quality level of human life requires various computational paradigms presentation including the Internet of Things, fog, and cloud. Between these three paradigms, the cloud computing paradigm as an emerging technology adds cloud layer services to the edge of the network so that resource allocation operations occur close to the end-user to reduce resource processing time and network traffic overhead. Hence, the resource allocation problem for its providers in terms of presenting a suitable platform, by using computational paradigms is considered a challenge. In general, resource allocation approaches are divided into two methods, including auction-based methods (goal, increase profits for service providers-increase user satisfaction and usability) and optimization-based methods (energy, cost, network exploitation, Runtime, reduction of time delay). In this paper, according to the latest scientific achievements, a comprehensive literature study (CLS) on artificial intelligence methods based on resource allocation optimization without considering auction-based methods in various computing environments are provided such as cloud computing, Vehicular Fog Computing, wireless, IoT, vehicular networks, 5G networks, vehicular cloud architecture, machine-to-machine communication (M2M), Train-to-Train(T2T) communication network, Peer-to-Peer (P2P) network. Since deep learning methods based on artificial intelligence are used as the most important methods in resource allocation problems;Therefore, in this paper, resource allocation approaches based on deep learning are also used in the mentioned computational environments such as deep reinforcement learning, Q-learning technique, reinforcement learning, online learning, and also Classical learning methods such as Bayesian learning, Cummins clustering, Markov decision process. © 2022, CC BY-SA.

关键词： Reinforcement learning

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Evaluating deep neural network for automated sleep staging in real-life scenarios

Evaluating deep neural network for automated sleep staging i...

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2022 International Conference on computer Network Security and Software engineering, CNSSE 2022

作者： Cao, Dingbang Hu, Congjia Hu, Jiaming Li, Dailun Li, Wenkang School of Computer Engineering and Science Shanghai University Shanghai200444 China School of International Education Guangxi University of Science and Technology Guangxi Liuzhou545000 China Electronic and Electrical Engineering University College London Gower Street LondonWC1E6BT United Kingdom Faculty of Computer Science McGill University MontrealQCH3A0G4 Canada School of Computing University of Leeds West Yorkshire LeedsLS2 9JT United Kingdom

ISBN: (纸本)9781510655980

Using artificial intelligence in automated sleep staging has become very popular. In this paper, we evaluate a deep learning model, Tiny Sleep Net, to illustrate the limitations of the deep learning model in the task of sleep staging predication. During the experiment, we changed the hyperparameter to achieve various study rates, changed the number of epochs and the balance of datasets. The results showed that the actual result of this model is quite acceptable, which is 82.3%. In contrast, the whole model is relatively fragile when some parameters are changed, witnessing an incredibly low accuracy when predicting. In addition, compared with the overall accuracy, the difference in the per-class accuracy can be drastic. Therefore, these results showed that the neural network is susceptible to the hyperparameter and the exact number of epochs generated. Therefore, in exact situations when the input dataset is not balanced or hyperparameters have minus changes, the final prediction accuracy will decrease dramatically. © 2022 SPIE.

关键词： Sleep research

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Pairs in Nested Steiner Quadruple Systems

arXiv

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arXiv 2024年

作者： Chee, Yeow Meng Dau, Son Hoang Etzion, Tuvi Kiah, Han Mao Zhang, Wenqin Dept. of Industrial Systems Engineering and Management National University of Singapore Singapore School of Computing Technologies RMIT University MelbourneVIC3000 Australia Computer Science Faculty TechnionIsrael Institute of Technology Haifa3200003 Israel School of Physical and Mathematical Sciences Nanyang Technological University Singapore School of Electronic Information and Engineering Shanghai Jiao tong University China

Motivated by a repair problem for fractional repetition codes in distributed storage, each block of any Steiner quadruple system (SQS) of order v is partitioned into two pairs. Each pair in such a partition is called a nested design pair and its multiplicity is the number of times it is a pair in this partition. Such a partition of each block is considered as a new block design called a nested Steiner quadruple system. Several related questions on this type of design are considered in this paper: What is the maximum multiplicity of the nested design pair with minimum multiplicity? What is the minimum multiplicity of the nested design pair with maximum multiplicity? Are there nested quadruple systems in which all the nested design pairs have the same multiplicity? Of special interest are nested quadruple systems in which all the (v2) pairs are nested design pairs with the same multiplicity. Several constructions of nested quadruple systems are considered and in particular classic constructions of SQS are examined. © 2024, CC BY.

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