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arXiv 2023年

作者： Chakravarty, Abhiruph Tripathy, Jatin Karthik Sibi Chakkaravarthy, S. Cherukuri, Aswani Kumar Anitha, S. Kamalov, Firuz Jonnalagadda, Annapurna Cognitive Systems University of Potsdam Germany School of Electronics Engineering VIT-AP University Andhra Pradesh India School of Information Technology Vellore Institute of Technology Vellore India Dept. of Electrical Engineering Canadian University Dubai United Arab Emirates School of Computer Science and Engineering Vellore Institute of Technology Vellore India

Quadruped robots are currently used in industrial robotics as mechanical aid to automate several routine tasks. However, presently, the usage of such a robot in a domestic setting is still very much a part of the research. This paper discusses the understanding and virtual simulation of such a robot capable of detecting and understanding human emotions, generating its gait, and responding via sounds and expression on a screen. To this end, we use a combination of reinforcement learning and software engineering concepts to simulate a quadruped robot that can understand emotions, navigate through various terrains and detect sound sources, and respond to emotions using audio-visual feedback. This paper aims to establish the framework of simulating a quadruped robot that is emotionally intelligent and can primarily respond to audio-visual stimuli using motor or audio response. The emotion detection from the speech was not as performant as ERANNs or Zeta Policy learning, still managing an accuracy of 63.5%. The video emotion detection system produced results that are almost at par with the state of the art, with an accuracy of 99.66%. Due to its "on-policy" learning process, the PPO algorithm was extremely rapid to learn, allowing the simulated dog to demonstrate a remarkably seamless gait across the different cadences and variations. This enabled the quadruped robot to respond to generated stimuli, allowing us to conclude that it functions as predicted and satisfies the aim of this work. © 2023, CC BY-SA.

关键词： Reinforcement learning

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Wind Turbine Instrumentation System using Labview 3

Wind Turbine Instrumentation System using Labview

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3rd International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2022

作者： Sudharsan, G. Srinivasa Vishnupriyan, J. Anand, K. Vijay Chidambarathanu, K. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Dept. of Ece Chennai India Chennai Institute of Technology Center for Energy Research Chennai India R.M.K. Engineering College Department of Electronics and Instrumentation Engineering Chennai India R.M.K. Engineering College Department of Computer Science and Business Systems Chennai India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

This work proposes an electronics circuit-based monitoring and control panel for wind turbines. In the wind business, wind turbine monitoring is a critical task. This work describes the process of building a monitoring and control panel system that uses LabVIEW to record and analyze various metrics such as wind speed, wind direction, tip speed ratio, energy generated, power and current power using LabVIEW and buzzer indication. The measuring equipment must function properly in order to produce the highly qualified data required for an accurate wind gust prediction. This work aims to create a promising measuring and monitoring system for wind parameter measurement. The graphical user interface makes even the most critical processes much easier to control and monitor. © 2022 IEEE.

关键词： Wind turbines

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An Overview of Medical Implant Antennas

An Overview of Medical Implant Antennas

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European Conference on Antennas and Propagation, EuCAP

作者： Ali Khaleghi Sema Dumanli Ilangko Balasingham Institute for Electronic Systems Norwegian University of Science and Technology (NTNU) Trondheim Norway Intervention Center Oslo University Hospital (OUS) Oslo Norway Electrical and Electronics Engineering Dept. Bogazici University Istanbul Turkey

Antenna miniaturization for integration with small implants for sensing, wireless powering, and communication is a multi-parameter design task. The implanted antenna performance is governed by the antenna size, operating frequency, antenna surrounding tissues, subsequent biological tissues, antenna encapsulation, the electronics and metal objects nearby the antenna, implant dept., and the electromagnetic radiation source defined by the antenna geometry. The antenna performance can be characterized by impedance matching, bandwidth, antenna near-field, far-field radiation pattern, efficiency and gain, and the specific absorption rate (SAR). This paper reviews the design steps for miniaturized implant antennas, the frequency dependency of biological tissues, and EM modeling and simulation tools to support the design. Examples of miniaturized implant antennas are provided for application in the cardiac, gastric, and brain.

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Stroke Risk Assessment Through Sparse AM-FM Decompositions of Carotid Plaque Ultrasound Images

Stroke Risk Assessment Through Sparse AM-FM Decompositions o...

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IEEE Southwest Symposium on Image Analysis and Interpretation

作者： Kyriacos P. Constantinou Ioannis P. Constantinou Efthyvoulos Kyriacou Christos P. Loizou Constantinos S. Pattichis Andreas Panayides Marios S. Pattichis University of Cyprus Nicosia Cyprus Istognosis Ltd Nicosia Cyprus Cyprus University of Technology Limassol Cyprus CYENS Center of Excellence University of Cyprus Nicosia Cyprus Center of Excellence CYENS Nicosia Cyprus Dept. of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA

The objective of this work was to investigate a new sparse multiscale Amplitude Modulation - Frequency Modulation (AM-FM) analysis based on multiple Gabor filterbanks representations where component selection was carried out using the elastic net regularization equation. The AM-FM histogram features sets of instantaneous amplitude, instantaneous phase and the magnitude of instantaneous frequency were computed from carotid plaque ultrasound images to assess the risk of stroke. A total of 100 carotid plaque ultrasound images (50 asymptomatic and 50 symptomatic) were analyzed following manual segmentation by an expert. Classification modelling was carried out using the Support Vectors Machine to classify asymptomatic versus symptomatic plaques. An overall classification accuracy of 74% was achieved, demonstrating that the new sparse multiscale AM-FM analysis provided robust features. These findings are comparable with classification models trained with traditional AM-FM feature sets as well as classical texture feature sets. Moreover, the proposed analysis provides new sparse image representations that allow us to reduce the number of AM-FM components needed to explain the local spatial-frequency content and can further facilitate the desired explanatory interpretation in stroke risk assessment.

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Assessment of IT Governance Maturity Level for Yemeni Telecom Sector Using COBIT 2019 Framewor006B

Assessment of IT Governance Maturity Level for Yemeni Teleco...

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Emerging Technologies for Dependable Internet of Things (ICETI), International Conference on

作者： Abdullatif Ghallab Tahani Alswari Saleh Alhazbi Belal Al-Fuhaidi Mohammed Hadwan Farouk Al-Fahaidy Mohammed Al-Dowail Naseebah Maqtary Department of Computer Science University of Science and Technology Sana'a Yemen Department of IT Open University Malaysia Sana'a Yemen Dept. of Computer Science & Eng Qatar University Doha Qatar Department of IT Qassim University Buraydah Saudi Arabia Department of Electrical Engineering Ibb University Ibb Yemen Department of Information Systems University of Science and Technology Sana’a Yemen

ISBN: (数字)9798331533557

ISBN: (纸本)9798331533564

Information technology (IT) plays a crucial role in business operations most organizations rely on IT resources for gaining competitive advantages and creating innovative and continuous values. This increased the importance of enterprise IT governance (EGIT) and developed the recent version of the control objectives for information and related technology (COBIT), COBIT 2019 framework. It identifies the seven components of an effective EGIT system: processes, organizational structures, information flows and items, people, skills and competencies, policies and procedures, culture, ethics and behavior, services, infrastructure, and applications. The EGIT maturity level (ITGML) assessment helps to align the EGIT with strategic objectives. This study aims to assess the ITGML of the Yemeni telecom sector using COBIT 2019 framework. A quantitative method was applied, with a 73.6% response rate (148 out of 201 questionnaires collected). The study revealed that the current ITGML is 3.48, reflecting a defined maturity level. The findings suggested that IT governance practices based on COBIT 2019 are well documented and standardized within the Yemeni telecom sector.

关键词： Ethics Standards organizations Process control Focusing Companies Documentation Telecommunications Stakeholders Internet of Things Information technology

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Toward ultrahigh efficiency GaN nano and micro full-color LEDs 27

Toward ultrahigh efficiency GaN nano and micro full-color LE...

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27th International Display Workshops, IDW 2020

作者： Mi, Zetian Liu, Xianhe Wu, Yuanpeng Sun, Yi Malhotra, Yakshita Ra, Yong-Ho Dept. of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109 United States Optic and Electronic Component Material Center Korea Institute of Ceramic Engineering and Technology Jinju52851 Korea Republic of

Using the selective area epitaxy technique, we have demonstrated nanowire emitters with controlled diameter, position, and emission wavelength. Furthermore, monolithic integration of multicolor emission and photonic crystal structure are realized, which allows for ultimately small multicolor nano-LEDs and micro-LEDs with emission properties tailored by the photonic crystal, as well as surface emitting lasers. © 2020 ITE and SID.

关键词： Crystal structure

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Myoelectric Pattern Recognition Performance Enhancement Using Nonlinear Features

arXiv

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arXiv 2022年

作者： Islam, Md Johirul Ahmad, Shamim Haque, Fahmida Reaz, Md Mamun Bin Ibne Bhuiyan, Mohammad A.S. Islam, Md Rezaul Dept. of Electrical and Electronic Engineering University of Rajshahi Rajshahi6205 Bangladesh Dept. of Physics Rajshahi University of Engineering and Technology Rajshahi6204 Bangladesh Dept. of Computer Science and Engineering University of Rajshahi Rajshahi6205 Bangladesh Dept. of Electrical Electronic and Systems Engineering Universiti Kebangsaan Malaysia UKM Selangor Bangi43600 Malaysia Dept. of Electrical and Electronic Engineering Xiamen University Malaysia Bandar Sunsuria Sepang Selangor 43900 Malaysia

The multichannel electrode array used for electromyogram (EMG) pattern recognition provides good performance, but it has a high cost, is computationally expensive, and is inconvenient to wear. Therefore, researchers try to use as few channels as possible while maintaining improved pattern recognition performance. However, minimizing the number of channels affects the performance due to the least separable margin among the movements possessing weak signal strengths. To meet these challenges, two time-domain features based on nonlinear scaling, the log of the mean absolute value (LMAV) and the nonlinear scaled value (NSV), are proposed. In this study, we validate the proposed features on two datasets, existing four feature extraction methods, variable window size and various signal to noise ratios (SNR). In addition, we also propose a feature extraction method where the LMAV and NSV are grouped with the existing 11 time-domain features. The proposed feature extraction method enhances accuracy, sensitivity, specificity, precision, and F1 score by 1.00%, 5.01%, 0.55%, 4.71%, and 5.06% for dataset 1, and 1.18%, 5.90%, 0.66%, 5.63%, and 6.04% for dataset 2, respectively. Therefore, the experimental results strongly suggest the proposed feature extraction method, for taking a step forward with regard to improved myoelectric pattern recognition performance. © 2022, CC BY.

关键词： Feature extraction

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Survey on LED lamps for residential applications: characterization of performance

Survey on LED lamps for residential applications: characteri...

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International Scientific Conference on Electric Power engineering (EPE)

作者： Tomáš Hudač Jiri Drapela Leoš Kukačka Jan Meyer Robert Stiegler Dept. of Electrical Power Engineering Faculty of Elect. Eng. and Communication Brno University of Technology Brno Czech Republic Institute of Mechatronics and Computer Engineering Technical University of Liberec Liberec Czech Republic Institute of Electrical Power Systems and High Voltage Engineering Technische Universität Dresden Dresden Germany

Aim of the paper is to conduct a survey of the present market, focusing on the best-selling retrofit LED lamps and to analyze experimentally their fundamental EMC performance for subsequent classification of the LED drivers. Two stage experimental characterization testing approach is adopted. First, input current and output luminous flux in steady-state under nominal supply conditions is acquired. Next, transfer of input supply voltage interharmonics to output visible flicker components in terms of gain factor curves is obtained. Based on the achieved and discussed testing results, classification of the LED lamps is developed.

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Convergence Analysis of the Feedforward Hybrid Active Noise Control

Convergence Analysis of the Feedforward Hybrid Active Noise ...

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2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023

作者： Ma, Y. Xiao, Y. Ma, L. Khorasani, K. Hasegawa, K. Jiangnan University Wuxi214122 China Jiangsu University Zhenjiang212013 China Wuxi Heshuofeng Technology Co. Ltd. China Prefectural University of Hiroshima Hiroshima734âÂÄa"8558 Japan Concordia University Dept. of Electrical and Computer Engineering MontrealH3G 1M8 Canada Western Region Industrial Research Center Hiroshima Prefectural Technology Research Institute Hiroshima737-0004 Japan

ISBN: (纸本)9798350316728

The conventional feedforward broadband active noise control (ANC, BANC, FFBANC) generates 'firework noise' if it is set to converge fast and its reference signal contains both a broadband and a low-frequency sinusoidal component. The feedforward hybrid ANC (FFHANC) converges fast without producing any firework noise in the presence of such a reference signal. In this paper, statistical convergence analysis is conducted for the original FFHANC system. Difference equations are derived for the mean errors of the sinusoidal noise canceller (SNC) coefficients, the FFBANC and feedforward narrowband ANC (FFNANC) subcontroller filter weights. The mean residual error expression is also derived for the FFHANC system. Extensive simulations are performed to verify the validity of the analytical results. © 2023 IEEE.

关键词： Signal processing

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Performance Evaluation of District Energy Microgrids Planning Tool for Non-Technical Users

Performance Evaluation of District Energy Microgrids Plannin...

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IEEE Texas Power and Energy Conference (TPEC)

作者： Fatima Ezzahra El Aidos Simon Abongmbo Safae Bourhnane Driss Benhaddou Fan Lei Lennart Johnsson Carlos Gamarra Tianrun Zhang Muhammad Anan Mohamed Riduan Abid Dept. of Computer Science University of Houston Houston TX USA Dept. of Electrical and Computer Engineering University of Houston Houston TX USA School of Science and Engineering Al Akhawayn University in Ifrane Ifrane Morocco Technology Division University of Houston Houston TX USA Houston Advanced Research Center Houston TX USA College of Engineering Al Fayssal University Riyadh Saudi Arabia TSYS School of Computer Science Columbus State University Columbus GA USA

Community Microgrids are increasingly gaining popularity worldwide for their efficiency, cost-effectiveness, and local resilience improvement. Microgrid planning tools play a crucial role in their deployment. In the process, tentative designs of the microgrid are simulated, analyzed, and optimized. Due to the complexity of the problem, planning tools must carefully balance computational efficiency while seeking the most optimal solutions. This paper investigates the impact of algorithm selection on CPU and memory utilization of a Community Microgrid planning tool that is specifically designed for non-technical users. We compare two version of the code with two alternatives for Community Microgrid planning tools: a Greedy Algorithm, and a Linear Programming Approach. This comparison examines scenarios spanning from 2 to 50 buildings. Our findings revealed a significant difference in performance between the two algorithms, underscoring the critical role of algorithm selection in optimizing the efficiency of Community Microgrid Planning Tools.

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