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Telecommunications Conference (ITC-Egypt), International

作者： Rana M. NourEldeen Rahma A. Elshshtawy Omnia A. Elgohary Fatma Alzahraa A. Wahba Marco K. Attia Zeinab B. Abo elazm Mohamed G. Khattap Hend Galal Eldeen Mohamed Ali Hassan Mariam Mostafa Nayra Ibrahim Reem Ramadan Yomna Refaat Mennatallah Khaled Ali Maher Mohamed Abd Elaziz Ahmed Gamal Abdellatif Ibrahim Radiology and Medical Imaging Faculty of Applied Health Sciences Galala University Suez Egypt Biomedical Informatics Faculty of Computer Science and Engineering Galala University Suez Egypt Artificial Intelligence Science Program Faculty of Computer Science and Engineering Galala University Suez Egypt Department of Electronics and Electrical Communications Engineering Air Defense College Alexandria Egypt

ISBN: (数字)9798350351408

ISBN: (纸本)9798350351415

This paper proposes an alternative detection frame-work for multiple sclerosis (MS) and idiopathic acute transverse myelitis (ATM) within the 6G-enabled Internet of Medical Things (IoMT) environment. The developed framework relies on the implementation of a deep learning technique known as Dense Convolutional Networks (DenseNets) in the 6G-enabled IoMT to enhance prediction performance. To validate the performance of DenseNets, we compared it with other deep learning techniques, including Convolutional Neural Networks (CNN) and MobileNet, using real-world datasets. The experimental results show the high performance of DenseNets in predicting MS and ATM compared to other methods, achieving an accuracy of nearly 90 %.

关键词： 6G mobile communication Deep learning Multiple sclerosis Accuracy Internet of Medical Things Telecommunications Convolutional neural networks

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Sample Complexity of Kernel-Based Q-Learning

arXiv

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arXiv 2023年

作者： Yeh, Sing-Yuan Chang, Fu-Chieh Yueh, Chang-Wei Wu, Pei-Yuan Bernacchia, Alberto Vakili, Sattar MediaTek Research Graduate Program of Data Science National Taiwan University Academia Sinica Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Department of Electrical Engineering National Taiwan University Taiwan

Modern reinforcement learning (RL) often faces an enormous state-action space. Existing analytical results are typically for settings with a small number of state-actions, or simple models such as linearly modeled Q-functions. To derive statistically efficient RL policies handling large state-action spaces, with more general Q-functions, some recent works have considered nonlinear function approximation using kernel ridge regression. In this work, we derive sample complexities for kernel based Q-learning when a generative model exists. We propose a nonparametric Q-learning algorithm which finds an ǫ-optimal policy in an arbitrarily large scale discounted MDP. The sample complexity of the proposed algorithm is order optimal with respect to ǫ and the complexity of the kernel (in terms of its information gain). To the best of our knowledge, this is the first result showing a finite sample complexity under such a general model. © 2023, CC BY.

关键词： Reinforcement learning

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Unbiased Parameter Estimation for Partially Observed Diffusions

arXiv

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arXiv 2023年

作者： Awadelkarim, Elsiddig Jasra, Ajay Ruzayqat, Hamza Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this article we consider the estimation of static parameters for partially observed diffusion process with discrete-time observations over a fixed time interval. In particular, we assume that one must time-discretize the partially observed diffusion process and work with the model with bias and consider maximizing the resulting log-likelihood. Using a novel double randomization scheme, based upon Markovian stochastic approximation we develop a new method to unbiasedly estimate the static parameters, that is, to obtain the maximum likelihood estimator with no time discretization bias. Under assumptions we prove that our estimator is unbiased and investigate the method in several numerical examples, showing that it can empirically out-perform existing unbiased *** Codes 60J22, 62M05, 65C40, 62M20 © 2023, CC BY.

关键词： Parameter estimation

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Implementation and Evaluation of 0.6 µm CMOS Complex RCPF for Accurate Frequency Response Measurement

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and Systems 2025年第1期145卷 25-37页

作者： Sato, Lina Fukagawa, Kanta Shouno, Kazuhiro Tanimoto, Hiroshi Muto, Cosy Moriyama, Seijiro Takahashi, Chikau Yoshino, Michitaka Graduate School of Science and Technology Degree Programs in Systems and Information Engineering Master’s Program in Computer Science University of Tsukuba Japan Division of Information Engineering University of Tsukuba 1-1-1 Tennoudai Ibaraki Tsukuba305-8573 Japan Kitami Institute of Technology 165 Koen-cho Hokkaido Kitami090-8507 Japan Faculty of Education Nagasaki University 1-14 Bunkyo-machi Nagasaki852-8521 Japan Anagix Corporation 3-22-27 Numama Kanagawa Zushi249-0004 Japan Takamori Corporation Japan Research Center for Micro-Nano Technology Hosei University 3-11-15 Midori-cho Koganei Tokyo184-0003 Japan

This paper describes the implementation and evaluation of an RC polyphase filter (RCPF) and circuitry for measuring its frequency characteristics. The integrated circuit is fabricated on a 0.6 µm CMOS process and its supply voltage is 5 V. The integrated circuit includes a filter under test (FUT), a four-phase square wave generator, several analog switches and differential amplifiers to amplify the high-impedance signals of the RCPF. This FUT is a third-order complex RCPF whose passband is 8 − 40 MHz. This paper describes the design of these circuits in detail. This integrated circuit can select two measurement methods by means of external control signals. The first method uses a four-phase square wave. The frequency characteristics are measured by using an on-chip four-phase square wave generator driven by an external clock generator and by a spectrum analyzer tuned to the fundamental frequency. The second method uses an external network analyzer. Furthermore, this integrated circuit is equipped with a calibration circuit to measure the frequency characteristics of the circuitry except FUT by passing through the input / output signals of the FUT. As a result, the frequency characteristics of the FUT itself can be accurately measured. The effectiveness is confirmed through evaluation of the fabricated integrated circuit. © 2025 The Institute of electrical Engineers of Japan.

关键词： Differential amplifiers

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A Comprehensive Review Analysis of Supervised Machine Learning Techniques 5

A Comprehensive Review Analysis of Supervised Machine Learni...

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5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Ghildiyal, Shivangi Garg, Raghav Dhanik, Saurabh Sarkar, Argya Sharma, Gayatry Kharayat, Pushpendra Singh Invertis University Deptt. of Computer Application Uttar Pradesh Bareilly India Tula's Institute Deptt. of Computer Sci. & Engg U.K. Dehradun India Graphic Era Hill University School of Computing Bhimtal India Tula's Institute Graduate School of Business U.K. Dehradun India Miet Kumaun Department of Computer Science Uttarakhand Haldwani India Graphic Era Deemed to be university Department of Electrical Engineering Dehradun248002 India

ISBN: (纸本)9798331504403

This study presents an exhaustive review analysis of the supervised machine learning techniques. The different types of supervised machine learning methods which are discussed in this study are linear Regression, Logistic Regression, Decision Trees, Random Forest, Support Vector Machines (SVM), k-Nearest Neighbors (k-NN), Naive Bayes, Gradient Boosting Machines (GBM) and Neural Networks. All these methods are showing its relevance and utility in the various domain of engineering and bio medical engineering. Using supervised machine learning methods, review evaluation involves assessing and deriving insight from evaluations, frequently in order to categorize them, identify themes, or forecast scores. © 2024 IEEE.

关键词： Adversarial machine learning

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SBS-FD: Fault Diagnosis of Harmonic Reducers Based on Symmetrized Dot Pattern, Bag of Visual Word, and Support Vector Machine Jointed Method 13

SBS-FD: Fault Diagnosis of Harmonic Reducers Based on Symmet...

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13th IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2023

作者： Han, Xinming Long, Zhuo Ma, Xiaoguang Jia, Jie Chen, Wenjie Lin, Wenjie School of Computer Science and Engineering Northeastern University Shenyang110167 China School of Electrical and Information Engineering Changsha University of Science and Technology Changsha410076 China Foshan Graduate School Northeastern University Foshan528000 China College of Information and Engineering Northeastern University Shenyang110819 China Midea Group Lancheng Lab Foshan528000 China Guangdong Jiya Precision Machinery Technology Co. Ltd Foshan528000 China

ISBN: (纸本)9798350315196

In order to realize fault diagnosis of harmonic reducers in real industrial scenarios, a fault diagnosis method based on image visual information, i.e., SBS-FD is proposed. Firstly, Symmetrized Dot Pattern images are obtained based on vibration signals, and Scale Invariant Feature Transform method is used to extract image information, wherein the mappings between fault signals and visual information are achieved. Then the bag of visual word and space pyramid matching method are used to process the visual information. Finally, the support vector machine is used for fault diagnosis. Comprehensive experimental results show that the diagnostic accuracy of four fault states can be up to 98% at all speeds, using proposed SBS-FD method, illustrating superior performance over other machine learning methods. © 2023 IEEE.

关键词： Failure analysis

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Joint Design of Spirograph Method and Reconfigurable Intelligent Surface for Future Communication Systems

Joint Design of Spirograph Method and Reconfigurable Intelli...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Balqis Yafis Jane-Hwa Huang Chih-Min Yu Li-Chun Wang EECS Int’l Graduate Program National Yang Ming Chiao Tung University Hsinchu Taiwan Dept. of Electrical Engineering National Chi Nan University Taiwan Department of Information and Computer Engineering Chung Yuan Christian University Taiwan Dept. of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Reconfigurable Intelligent Surface (RIS) is a transformative technology using the passive beamforming capabilities to create the programmable wireless environments. However, the control overhead is a challenging issue. The system needs to deliver the high-precision reflection coefficients to the RIS controller, for adjusting the phase shifts of the numerous RIS elements. Therefore, we propose a Spirograph-based discrete beamdirection strategy, which selects a set of non-uniformly distributed beam directions based on the generic patterns generated by the Spirograph (SG). We evaluate the achievable data rate and the number of controlling bits of SG-based method. We compare the SG-based method, the ideal continuous phase-shift method, and the SISO method. Simulation results show that with the properly-selected discrete beam directions, the SG-based method can achieve a comparable data rate as the ideal method, while having a lower control overhead.

关键词： Wireless communication Quantization (signal) Array signal processing Simulation Design methodology Reconfigurable intelligent surfaces Reflection coefficient Global communication

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Plasmonic BICs as Biosensors with Better Detectivity

Plasmonic BICs as Biosensors with Better Detectivity

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Conference on Lasers and Electro-Optics (CLEO)

作者： Zhichao Li Ciril S. Prasad Xielin Wang Gururaj V. Naik Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston TX USA Department of Electrical and Computer Engineering Rice University Houston TX USA

Plasmonic sensors exhibit high sensitivity due to enhanced local fields. But, their detectivity is poor because of their poor Q-factors. Using a plasmonic BIC, we experimentally demonstrate enhanced Q-factors in a pla... 详细信息

ISBN: (纸本)9781957171258

关键词： Absorption spectroscopy Field enhancement Optical sensing Plasmonic sensors Q factor Sensor performance

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CRISP - DM Process in Smart Building Management

CRISP - DM Process in Smart Building Management

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International Conf on electrical and Electronic engineering (ICEEE)

作者： Mahir Dursun Moldir Sabyrzhan Dept. of Electrical and Electronics Engineering Faculty of Technology Gazi University Ankara Türkiye Department of Computer Science Graduate School of Informatics Gazi University Ankara Türkiye

ISBN: (数字)9798350362541

ISBN: (纸本)9798350362558

Smart Buildings are buildings that integrate and combine intelligence, management, control, materials, and construction as a single system to meet all the needs of the building, such as comfort, energy efficiency, and durability. In universities, laboratories are used less frequently than other facilities and classrooms. Courses and students may change in the same classroom, and the period of use of such classrooms is much more extended than in laboratories. However, classrooms may only be used for classes during long breaks or for short periods of non-use between exams. In addition, there is no provision for when the heating system will start to heat up before classes or when it will be turned off after classes. By planning heating and lightning, energy and costs will be saved. This paper presents data acquisition methods for preparing a dataset to create a machine learning (ML) model to save energy loss in university laboratories. The developed model will predict energy consumption in classrooms and laboratories based on weather conditions. The study is being conducted in two stages. The first stage describes how to collect data using electronic devices such as Internet of Things (IoT) controllers of Smart Building Management Systems. The second stage gave possibilities for data analysis and preparation using the phases of the Cross-Industry Standard Process for Data Mining (CRISP-DM).

关键词： Heating systems Smart buildings Laboratories Energy conservation Decision making Process control Data models Planning Internet of Things Data mining

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Towards cross-modal causal structure and representation learning 2

Towards cross-modal causal structure and representation lear...

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2nd Machine Learning for Health Symposium, ML4H 2022

作者： Mao, Haiyi Liu, Hongfu Xiaotian Dou, Jason Benos, Panayiotis V. Joint CMU-Pitt PhD Program in Computational Biology University of Pittsburgh United States Michtom School of Computer Science Brandeis University United States Department of Electrical and Computer Engineering University of Pittsburgh United States Department of Epidemiology University of Florida United States

Does the SARS-CoV-2 virus cause patients' chest X-Rays ground-glass opacities? Does an IDH-mutation cause differences in patients' MRI images? Conventional causal discovery algorithms, although well developed to uncover the cause-effect relationships on structured data, cannot elucidate causal relations between unstructured images and structured scalar variables due to the complexity of the former. In this paper, we consider causal discovery between images and structured (scalar) variables. Specifically, we derive low dimensional image representations to analyze with structured variables. We propose a two-module amortized variational algorithm named Cross-Modal Variational Causal representation and structure Learning (CMCL). CMCL jointly learns identifiable representations given a set of independent structured variables and causal relations via formulating latent representations and structured variables into a direct acyclic graph. Moreover, we further enforce counterfactual invariance/variance onto representations. We demonstrate that CMCL outperforms other related methods on synthetic datasets and validate causal relations on semi-synthetic datasets by visualization. © 2022 P.N. Argaw, E. Healey & I.S. Kohane.

关键词： Coronavirus

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