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ACS/IEEE International Conference on computer systems and Applications

作者： Heba Helal Mohamed A. Sharaf College of Information Technology United Arab Emirates University UAE Dept. of Computer Engineering and Systems College of Engineering Mansoura University Egypt

Dealing with high-dimensional time series data makes the process of recommending visualizations with "interesting" insights difficult. The challenge originates from finding a way to obtain the recommended visualizations efficiently without compromising their quality. Identifying such visualizations manually is considered a labor-intensive and time-consuming process. In response, this paper introduces different techniques designed to optimize the automated recommendation process. These techniques are entirely based on the concept of computation sharing and pruning. Furthermore, we provide a glimpse into our future research works in PhD thesis. The objective is to broaden the scope of our current work and enhance the generality of our problem statement.

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Fractional Exponential Reaching Law Sliding Mode control for a Robot Manipulator Tracking Application

Fractional Exponential Reaching Law Sliding Mode Control for...

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International Conference on systems and control (ICSC)

作者： Sana Stihi Abdelhadi Aouaichia Omar Gad Raouf Fareh Sofiane Khadraoui Maamar Bettayeb Research Institute of Sciences and Engineering (RISE) University of Sharjah Sharjah UAE Laboratory of Electrical Systems and Remote Control University of Blida 1 Algeria Dept. of Electrical Engineering University of Sharjah

ISBN: (数字)9798331531812

ISBN: (纸本)9798331531829

This paper proposes a control strategy for a robot manipulator with four Degrees Of Freedom (DOF) that takes advantage of sliding mode control theory, exponential reaching law, and fractional calculus. Tracking the joint space trajec-tories with precision is the goal of the proposed Fractional Exponential reaching law Sliding Mode control (FrExpSMC). Utilizing fractional calculus in the sliding surface enhances the robustness of the exponential reaching mode against external disturbances. The fractional calculus expression of the sliding surface ensures a finite time convergence of the controller and provides the controller with a fast response in the transient phase. The proposed control approach's efficiency and performances are demonstrated by simulation on a model of a 4-DOF robot manipulator and compared to the conventional sliding mode control. The stability of the closed-loop system is proved using Lyapunov theory. The results indicate that the recommended control outperforms the conventional sliding mode control in both tracking performance and robustness against step disturbances.

关键词： Trajectory tracking Manipulators Stability analysis Robustness Steady-state Closed loop systems Transient analysis Sliding mode control Fractional calculus Convergence

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control of Deterministic Chaotic Modes in Power systems

Control of Deterministic Chaotic Modes in Power Systems

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Smart Information systems and Technologies (SIST), IEEE International Conference on

作者： Mamyrbek Beisenbi Ainur Satpayeva Shugla Mussabayeva Gulnara Mussina Meruert Tlegen Dept. of System Analysis and Control L.N. Gumilyov Eurasian National University Astana Kazakhstan Dept. of Computer Engineering Astana IT University Astana Kazakhstan

The paper examines a new approach to controlling deterministic dynamical chaotic mode of power system with two electric generate-sources. A control law is synthesized in the class of one-parameter structurally stable mappings from catastrophe theory. Analytical calculations and a numerical experiment in MatLab showed that the proposed system excludes the generation of a deterministic chaotic mode for any changes in the uncertain system parameters. The study of the control system is carried out by the gradient-velocity method Lyapunov vector functions

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Empirical Characterization of Doppler in Industrial Wireless Channels

Empirical Characterization of Doppler in Industrial Wireless...

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European Conference on Antennas and Propagation, EuCAP

作者： Dreyelian Morejón Jon Montalbán Eneko Iradier Mohamed Kashef Hany Richard Candell Pablo Angueira Dept. Communication Engineering UPV/EHU Bilbao Spain Dept. Electronics Technology UPV/EHU Bilbao Spain Dept. Computer Languages and Systems UPV/EHU Bilbao Spain NIST: National Institute of Standards and Technology Gaithersburg USA

This paper analyzes the temporal variation of the radio propagation channel in industrial environments. The results have been obtained by processing empirical data from the National Institute of Standards and Technology (NIST) in a field measurement campaign, at different industrial premises, with various dimensions and clutter densities. The paper analyzes the shape of the Doppler spectra and related parameters such as Doppler bandwidth and coherence time. The results are supplemented with maximum Delay Times and RMS Delay Spread data. The influence of factors such as the operational frequency band, environment, and polarization is also analyzed.

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Enabling A Network AI Gym for Autonomous Cyber Agents

arXiv

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arXiv 2023年

作者： Li, Li El Rami, Jean-Pierre S. Taylor, Adrian Rao, James Hailing Kunz, Thomas Defence Research & Development Canada Ottawa Canada Dept of Electrical and Computer Engineering Queen's University Kingston Canada Dept. of Systems & Computer Engineering Carleton University Ottawa Canada

This work aims to enable autonomous agents for network cyber operations (CyOps) by applying reinforcement and deep reinforcement learning (RL/DRL). The required RL training environment is particularly challenging, as it must balance the need for high fidelity, best achieved through real network emulation, with the need for running large numbers of training episodes, best achieved using simulation. A unified training environment, namely the Cyber Gym for Intelligent Learning (CyGIL), is developed where an emulated CyGIL-E automatically generates a simulated CyGIL-S. From preliminary experimental results, CyGIL-S can train agents in minutes compared with the days required in CyGIL-E. The agents trained in CyGIL-S are transferrable directly to CyGIL-E, showing full decision proficiency in the emulated "real" network. Enabling offline RL, the CyGIL solution presents a promising direction towards simto-real in leveraging RL agents in real-world cyber networks. © 2023, CC BY.

关键词： Reinforcement learning

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Speaker's Emotions Recognition Module Based on the GoogleLeNet Neural Network

Speaker's Emotions Recognition Module Based on the GoogleLeN...

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2022 International Conference on Smart Information systems and Technologies, SIST 2022

作者： Tereikovskyi, Ihor Tereikovska, Liudmyla Kryvoruchko, Olena Tereikovskyi, Oleh Tyshchenko, Dmytro Franchuk, Tamara National Technical University Of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Dept. Of System Programming And Specialized Computer Systems Kyiv Ukraine Kyiv National University Of Construction And Architecture Dept. Of Information Technology For Design And Applied Mathematics Kyiv Ukraine Kyiv National University Of Trade And Economics Dept. Of Software Engineering And Cyber Security Kyiv Ukraine National Technical University Of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Dept. Of Department Of Computer Engineering Kyiv Ukraine

ISBN: (数字)9781665467902

ISBN: (纸本)9781665467902

The article is devoted to the development of means for recognition of the emotions of the speaker, based on the neural network analysis of fixed fragments of the voice signal. The possibility of improving recognition tools through the use of a convolutional neural network of the GoogLeNet type is shown. The expediency of training the network on the examples of the TESS database is determined. A procedure for representing a voice signal in the form of a square grayscale image has been developed. Based on the use of the specified database, the modification of the GoogLeNet network was carried out. The architecture and software implementation of the recognition module have been developed. With the help of computer experiments, it has been established that after 150 epochs of training on a fairly limited training sample, the modified GoogLeNet makes it possible to achieve an accuracy of recognition of the speaker's emotions of approximately 0.97 on test examples. The obtained accuracy is comparable to the accuracy of the best modern systems of this purpose and confirms the promise of using neural network models like GoogLeNet for emotion recognition based on voice signal analysis. The need for further research aimed at reducing the resource intensity of the neural network model is shown. © 2022 IEEE.

关键词： Emotion Recognition

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Wobble control of a pendulum actuated spherical robot

arXiv

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arXiv 2023年

作者： Singhal, Animesh Modi, Sahil Gupta, Abhishek Vachhani, Leena Systems and Control Engineering Dept. Indian Institute of Technology Bombay Mumbai India General Electric Research Bangalore India Mechanical Engineering Dept. Indian Institute of Technology Bombay Mumbai India

Spherical robots can conduct surveillance in hostile, cluttered environments without being damaged, as their protective shell can safely house sensors such as cameras. However, lateral oscillations, also known as wobble, occur when these sphere-shaped robots operate at low speeds, leading to shaky camera feedback. These oscillations in a pendulum-actuated spherical robot are caused by the coupling between the forward and steering motions due to nonholonomic constraints. Designing a controller to limit wobbling in these robots is challenging due to their underactuated nature. We propose a model-based controller to navigate a pendulum-actuated spherical robot using wobble-free turning maneuvers consisting of circular arcs and straight lines. The model is developed using Lagrange-D’Alembert equations and accounts for the coupled forward and steering motions. The model is further analyzed to derive expressions for radius of curvature, precession rate, wobble amplitude, and wobble frequency during circular motions. Finally, we design an input-output feedback linearization-based controller to control the robot’s heading direction and wobble. Overall, the proposed controller enables a teleoperator to command a specific forward velocity and pendulum angle as per the desired turning radius while limiting the robot’s lateral oscillations to enhance the quality of camera feedback. © 2023, CC BY.

关键词： Robots

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Self-Reported Learning Strategies and Preferences in Health Informatics

Self-Reported Learning Strategies and Preferences in Health ...

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34th Medical Informatics Europe Conference, MIE 2024

作者： Rohani, Narjes Gallagher, Michael Gal, Kobi Banas, Kasia Manataki, Areti Usher institute University of Edinburgh United Kingdom Moray House School of Education and Sport University of Edinburgh United Kingdom School of Informatics University of Edinburgh United Kingdom Dept. of Software and Information Systems Engineering Ben-Gurion University Israel School of Computer Science University of St Andrews United Kingdom

ISBN: (纸本)9781643685335

Despite the proliferation of educational programmes in Health Informatics (HI) worldwide, there is limited knowledge regarding students' preferences and learning strategies in HI courses. To address this gap, we conducted a study to gather and analyse data from three HI courses. Employing the Motivated Strategies for Learning Questionnaire (MSLQ) and theories of deep and surface learning, we designed a questionnaire to collect data. The analysis of students' responses indicates that machine learning emerges as one of the most interesting topics, while certain topics such as data wrangling of genomics data were more challenging for students. Students expressed a preference for sequential learning. They exhibited multimodal tendencies regarding the type of learning resources, with tendency to prefer learning resources that have more visual contents. In all three courses, learners reported using deep learning strategy rather than surface learning, yet they appear to struggle with employing organisation, elaboration, and peer learning tactics. This study provides valuable insights into HI education, offering recommendations for educators, learners, and researchers to enhance HI education. © 2024 The Authors.

关键词： Contrastive Learning

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Path-Integral Formula for Computing Koopman Eigenfunctions

Path-Integral Formula for Computing Koopman Eigenfunctions

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IEEE Conference on Decision and control

作者： Shankar A. Deka Sriram S.K.S. Narayanan Umesh Vaidya Dept. of Electrical Engr. and Computer Science Decision and Control Systems division KTH Royal Institute of Technology Sweden Dept. of Mechanical Engr. Clemson University Clemson SC

The paper is about the computation of the principal spectrum of the Koopman operator (i.e., eigenvalues and eigenfunctions). The principal eigenfunctions of the Koopman operator are the ones with the corresponding eigenvalues equal to the eigenvalues of the linearization of the nonlinear system at an equilibrium point. The main contribution of this paper is to provide a novel approach for computing the principal eigenfunctions using a path-integral formula. Furthermore, we provide conditions based on the stability property of the dynamical system and the eigenvalues of the linearization towards computing the principal eigenfunction using the path-integral formula. Further, we provide a Deep Neural Network framework that utilizes our proposed path-integral approach for eigenfunction computation in high-dimension systems. Finally, we present simulation results for the computation of principal eigenfunction and demonstrate their application for determining the stable and unstable manifolds and constructing the Lyapunov function.

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Design of Lowpass Filter and Wavelet Analysis for Electroretinogram in Dogs

Design of Lowpass Filter and Wavelet Analysis for Electroret...

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IEEE Region 10 International Conference TENCON

作者： Tunyawat Tuntrik Nalinee Tuntivanich David Banjerdpongchai Dept. of Electrical Engineering Center of Excellence in Intelligent Control Automation of Process Systems Faculty of Engineering Chulalongkorn University Bangkok Thailand Dept. of Veterinary Surgery Faculty of Veterinary Science Bangkok Thailand

In frequency domain, wavelet coefficient is one of the characteristics of ERG signal which is hidden in frequency-domain. This paper aims to develop a tool for analyzing the constituent frequencies and time of interest in the dog's ERG signal using wavelet analysis. We design a lowpass filter to reduce noise during the measurement of ERG response. ERG dataset was obtained for the light intensity series and their constituent frequencies are analyzed by using the continuous wavelet transform (CWT). The results show that, in time-domain, as light intensity increases, both amplitudes of a-wave and b-wave are higher. We can visualize the noise interference in the ERG signals. Then a lowpass filter is designed to attenuate the noise effect. The filtered signals have lower a-, and b-waves' amplitude which affect the important characteristics in time domain. Therefore, we choose to filter signal from 26ms onward, the main components are recovered, and the filtered signal becomes smoother. In frequency-domain, the peak magnitude of wavelet coefficients is increased as light intensity increases.

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