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2021 Ural Symposium on Biomedical engineering, Radioelectronics and Information Technology, USBEREIT 2021

作者： Sozykin, Andrey Koshelev, Anton Bersenev, Alexander Shadrin, Denis Aksenov, Alexander Kuklin, Evgeniy N.N. Krasovskii Institute of Mathematics and Mechanics Department of Computing Systems Ekaterinburg Russia Engineering School of IT Telecom. and Control Systems Ural Federal University Ekaterinburg Russia Institute of Natural Sciences and Mathematics Ural Federal University Ekaterinburg Russia

ISBN: (纸本)9781728176918

The paper presents an approach to developing new educational programs for information technologies (IT) specialists using job market analysis. We developed a set of innovative software tools for collecting data from job sites and analyzing the data using machine learning algorithms. The tools were used to create a dataset of job advertisements from popular Russian job site HeadHunter for a period from 2006 until 2020. Both tools and dataset are freely available on the Internet. In order to develop the educational programs, we analyzed the demand for IT professions and programming languages, as well as joint occurrence of skills in job descriptions. To demonstrate the possibilities of our approach, two educational programs were created: A JavaScript-based program for Web Development and a Python-based program for Data Science. Developing the educational programs based on the requirements of the job market allows graduates to increase their employability. During the programs, students not only study the foundation of the profession such as programming languages, but also acquire a complete set of skills required to work in demanded positions. © 2021 IEEE.

关键词： Employment

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Parallel intelligence method for timetable rescheduling of high-speed railways under disturbances 1

Parallel intelligence method for timetable rescheduling of h...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Liu, Xuan Zhou, Min Song, Haifeng Gao, Shigen Jin, Chenkun Dong, Hairong Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing100044 China School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China Institute of Computing Technology Academy of Railway Sciences Beijing100081 China

ISBN: (纸本)9781665433372

This paper focuses on solving the real-time timetable rescheduling problem for dispatching systems of high-speed railway systems (HSRs) in case of temporary speed restriction by utilizing the parallel intelligence method. We construct a parallel intelligent system framework, which combines the actual and artificial dispatching systems through computational experiments and parallel execution. Then a rescheduling model includes retiming, recording and rerouting, and a solution method based on rolling horizon optimization are both proposed. Finally, a timetable of Beijing-Shanghai HSR within the jurisdiction of the Beijing Railway Bureau based case study indicates that the proposed parallel intelligence method can effectively decrease the total delay. © 2021 IEEE.

关键词： Intelligent systems

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Decentralized Goal Function-Based Primary control of Microgrids

SSRN

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SSRN 2022年

作者： Isakov, Ivana Vekić, Marko Rapaić, Milan Todorović, Ivan Grabić, Stevan University of Novi Sad Department of Power Electronic and Telecommunication Engineering Trg Dositeja Obradovica 6 Novi Sad21000 Serbia University of Novi Sad Department of Computing and Control Engineering Trg Dositeja Obradovica 6 Novi Sad21000 Serbia

The usage of distributed generation sources and segmentation of the power systems into the microgrids brings several advantageous features, such as energy independency, lower transmission losses, higher flexibility, etc. Still, the expected steady abolition of traditional centralized networks and their centralized control schemes will introduce several operational difficulties, that can compromise (micro)grid’s stability and reliability. Consequently, several approaches to how microgrids should be operated have been proposed, albeit with several salient deficiencies, such as power-sharing, control of frequency and voltage excursions, applicability on different grids, etc. This paper proposes a novel, goal function-based, decentralized control that addresses the mentioned problems and guarantees the microgrid’s stability by constraining the frequency and node voltage deviations, simultaneously supporting the desired active power exchange between prosumers. Unlike droop-based control schemes, the proposed approach aims to inherently preserve the frequency and voltage levels within the limits defined by the grid operator or future microgrid codes, thus preventing the generation unit’s unwanted disconnection during transients and disturbances. In addition, the control algorithm is independent of network topology. To confirm the effectiveness of the proposed control strategy, simulation results are presented and discussed. © 2022, The Authors. All rights reserved.

关键词： Electric power transmission networks

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UAV-miniUGV Hybrid System for Hidden Area Exploration and Manipulation

arXiv

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arXiv 2022年

作者： Pushp, Durgakant Kalhapure, Swapnil Das, Kaushik Liu, Lantao School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Automatic Control and Systems Engineering Department University of Sheffield Mappin St SheffieldS1 3JD United Kingdom TCS Research India

— We propose a novel hybrid system (both hardware and software) of an Unmanned Aerial Vehicle (UAV) carrying a miniature Unmanned Ground Vehicle (miniUGV) to perform a complex search and manipulation task. This system leverages heterogeneous robots to accomplish a task that cannot be done using a single robot system. It enables the UAV to explore a hidden space with a narrow opening through which the miniUGV can easily enter and escape. The hidden space is assumed to be navigable for the miniUGV. The miniUGV uses Infrared (IR) sensors and a monocular camera search for an object in the hidden space. The proposed system takes advantage of a wider field of view (fov) of the camera as well as the stochastic nature of the object detection algorithms to guide the miniUGV in the hidden space to find the object. Upon finding the object the miniUGV grabs it using visual servoing and then returns back to its start point from where the UAV retracts it back and transports the object to a safe place. In case there is no object found in the hidden space, UAV continues the aerial search. The tethered miniUGV gives the UAV an ability to act beyond its reach and perform a search and manipulation task which was not possible before for any of the robots individually. The system has a wide range of applications and we have demonstrated its feasibility through repetitive experiments. Copyright © 2022, The Authors. All rights reserved.

关键词： Antennas

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Two Enhanced-rate Power Allocation Strategies for Active IRS-assisted Wireless Network

arXiv

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arXiv 2023年

作者： Cheng, Qiankun Dong, Rongen Cai, Wenlong Liu, Ruiqi Shu, Feng Wang, Jiangzhou The School of Information and Communication Engineering Hainan University Haikou570228 China The School of Information and Communication Engineering Collaborative Innovation Center of Information Technology Hainan University Haikou570228 China The School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing210094 China National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing Aerospace Automatic Control Institute Beijing China The Wireless and Computing Research Institute ZTE Corporation Beijing100029 China The School of Engineering University of Kent CanterburyCT2 7NT United Kingdom

Due to its ability of overcoming the impact of double-fading effect, active intelligent reflecting surface (IRS) has attracted a lot of attention. Unlike passive IRS, active IRS should be supplied by power, thus adjusting power between base station (BS) and IRS having a direct impact on the system rate performance. In this paper, the active IRS-aided network under a total power constraint is modeled with an ability of adjusting power between BS and IRS. Given the transmit beamforming at BS and reflecting beamforming at IRS, the SNR expression is derived to be a function of power allocation (PA) factor, and the optimization of maximizing the SNR is given. Subsequently, two high-performance PA strategies, enhanced multiple random initialization Newton's (EMRIN) and Taylor polynomial approximation (TPA), are proposed. The former is to improve the rate performance of classic Netwon's method to avoid involving a local optimal point by using multiple random initializations. To reduce its high computational complexity, the latter provides a closed-form solution by making use of the first-order Taylor polynomial approximation to the original SNR function. Actually, using TPA, the original optimization problem is transformed into a problem of finding a root for a third-order polynomial. Simulation results are as follows: the first-order TPA of SNR fit its exact expression well, the proposed two PA methods performs much better than fixed PA in accordance with rate, and appoaches exhaustive search as the number of IRS reflecting elements goes to large-scale. Copyright © 2023, The Authors. All rights reserved.

关键词： Polynomial approximation

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Segmentation Model Approaches using Cardiac Magnetic Resonance Images: A Review

TechRxiv

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TechRxiv 2022年

作者： Khan, Amjad Nfai, Dayang Wang, Yin Chai Lim, P.C. Ullah, Faheem Javid Ahmad, Tariq Deapartment of Computing Abasyn University Islamabad Campus Pakistan UNIMAS Sarawak Malaysia School of Automation and Control Engineering SCUT China Department of Computer Science University of Science and Technology Bannu Pakistan School of Information and Communications Engineering Guilin University China

Automatic segmentation solution is the process of detecting and extracting information to simplify the representation of Cardiac Magnetic Resonance images (CMRI) of Left Ventricle (LV) contour. This segmented information, using CMR images, helps to reduce the segmentation error between expert and automatic segmented contours. The error represents missing region values calculated in percentages after segmenting a cardiac LV contour. This review paper will discuss the major three segmentation approaches, namely manual approach, semiautomatic, and fully automatic, along with the segmentation models, namely image-based models, region-based models, edge-based models, deformable-based models, active shape-based models (ASM), active contour-based models (ACM), level set-based models (LSM), and variational LSM (VLSM). The review deeply explains the performance of segmentation models using different techniques. Furthermore, the review compares 122 studies on segmentation model approaches, i.e., 16 from 2004 to 2010, 40 from 2011 to 2016, and 63 from 2017 to 2021, and 3 other related studies were conducted for LV contour segmentation, cardiac function, area-at-risk (AAR) identification, scar tissue classification, oedema tissue classification, and identification via presence, size, and location. Given the large number of articles on CMR-LV images that have been published, this review conducted a critical analysis and found a gap for researchers in the areas of LV localization, LV contour segmentation, cardiac function, and oedoema tissue classification and segmentation. Regarding critical analysis, this paper summarised a research gap and made useful suggestions for new CMR-LV researchers. although a timely reviewed study can lead to cardiac segmentation challenges, which will be discussed in each review section. © 2022, CC BY.

关键词： Magnetic resonance imaging

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Performance Analysis of Quaternion vs Euler-based Approaches in Reduced INS/GNSS Fusion Techniques

Performance Analysis of Quaternion vs Euler-based Approaches...

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Telecommunications Conference (ITC-Egypt), International

作者： Maher Tarek Shady Zahran Ahmed Radi Sherif F Nafea Eyad S. Oda Alaa El-Din Sayed Hafez Control and Navigation Departement Technical Researches and Development Center Cairo Egypt College of Computing and Information technology Arab academy for Science Technology and Maritime Transport Cairo Egypt Technical Researches Center Cairo Egypt Electrical Engineering Department Suez Canal University Cairo Egypt Electrical Engineering Affiliate Instructor Alexandria University Cairo Egypt

Unmanned vehicle navigation using various combination of sensors in different fields, civilian or military, has always known to be a challenging and nontrivial task. Bayesian filter algorithms are usually being used for combining and optimally processing measurements provided by such sensors, considering the available knowledge such as the uncertainty in measurements. Since the performance of any navigation system mainly depends on the efficiency of the chosen filter algorithm associated with the utilized sensors’ quality, the choice of suitable filtering approach (according to the demand application) can be considered as a critical and essential designing point. In this paper, the performance of two different attitudes representation filtering approaches (Quaternion and Euler angles-based) is investigated, when applied in Multiplicative Extended Kalman Filter (MEKF) design. The overall performance and accuracy of both approaches were analyzed and compared during various GNSS signal outages for a self-driving cars application in straight and curved trajectory paths. Multiple in-filed experiments were conducted using a special setup that includes a MEMS-based SPATIAL Advanced Navigation INS/GNSS system where the output of both approaches was compared to the ground truth of a utilized reference navigation system. The comparison includes 1) Position, Velocity and Attitude (PVA) estimation accuracy, 2) processing time and computational complexity. Results concluded that each approach has its own merits in demerits where the Quaternion-based approach outperforms the Euler one in terms of PVA navigation solution estimation accuracy. On the other hand, a faster calculation for the Euler-based approach associated with lower computational complexity was significantly noticeable.

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Multistability Analysis and Adaptive Feedback control on a New Financial Risk System

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International Journal of Applied and Computational Mathematics 2023年第5期9卷 1-16页

作者： Johansyah, Muhamad Deni Sambas, Aceng Vaidyanathan, Sundarapandian Benkouider, Khaled Sulaiman, Ibrahim Mohammed Department of Mathematics Universitas Padjadjaran Jatinangor Sumedang 45363 Indonesia Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Campus Besut Terengganu Besut 22200 Malaysia Department of Mechanical Engineering Universitas Muhammadiyah Tasikmalaya Tamansari Gobras Tasikmalaya 46196 Indonesia Center for Control System Vel Tech University Avaddi Chennai 60062 India Department of Non-Destructive Automatic Testing Laboratory Jijel University Rue Rouikha Mokhta Jijel 1800 Algeria School of Quantitative Science University Utara Malaysia Sintok Kedah Bukit Kayu Hitam 06010 Malaysia

This study presents the findings of a new financial risk system with one absolute function and two quadratic nonlinearities. The rich dynamic behaviors of the new financial risk system are discussed analytically and numerically through stability analysis, phase portrait, bifurcation diagram, Lyapunov exponent, multistability and coexisting attractors. In addition, a new financial risk system with two quadratic nonlinearities and one absolute function shows multistability and coexistence of chaotic attractors. Using adaptive feedback control, we established a new control law for fully synchronising the proposed chaotic financial systems with itself. To conclude, some numerical simulation was presented using MATLAB to illustrate the efficiency of the designed method. © 2023, The Author(s), under exclusive licence to Springer Nature India Private Limited.

关键词： Backstepping control Chaos Financial chaotic system Synchronisation

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Deepkernel: 2d-Kernels Clustering Based Mutant Reduction for Cost-Effective Deep Learning Software Testing

SSRN

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SSRN 2023年

作者： Zhang, Shiyu Wang, Xingya Feng, Lichao Huang, Song Chen, Zhenyu Zhao, Zhihong Nanjing Tech University Jiangsu Nanjing211816 China College of Command and Control Engineering Army Engineering University of PLA Jiangsu Nanjing210001 China State Key Laboratory for Novel Software Technology Nanjing University Jiangsu Nanjing210092 China College of Computing Science and Artificial Intelligence Suzhou City University Jiangsu Suzhou215104 China

Mutation testing has been demonstrated as a practical approach for evaluating the quality of deep learning (DL) testing datasets. However, the enormous mutants during testing lead to significant testing overhead. Feature clustering is a conventional method that reduces the number of mutants while preserving the mutants' distribution diversity. This distribution diversity is considered crucial for maintaining the effectiveness of testing assessment ability. DL software relies on convolutional kernels to extract data features and construct logic. Thus, using kernels to measure the differences among DL mutants is a feasible approach. This paper proposes DeepKernel, a convolutional kernel features clustering based reduction method. Specifically, it considers 2D-Kernel sparsity and 2D-Kernel entropy as kernel features. The features are clustered to construct a subset with equivalent testing assessment capability to the original set. Empirical studies on three classical DL models demonstrate that: (1) there is a significant correlation between the distribution diversity of the mutants and their testing assessment ability, as indicated by a Spearman Correlation Coefficient of 0.9689. (2) the reduced set maintains a similar distribution diversity and testing effectiveness as the original set. (3) when preserving the effectiveness of the mutation testing, our method reduces 63.47% of mutants and outperforms random selection. © 2023, The Authors. All rights reserved.

关键词： Software testing

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High-Order Discontinuous Galerkin Schemes for Radiation Hydrodynamics Equations in the Equilibrium-Diffusion Limit

SSRN

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SSRN 2023年

作者： Peng, Gang Luo, Dongmi Qiu, Jianxian Chen, Yibing Command and Control Engineering College Army Engineering University of PLA Nanjing210007 China Institute of Applied Physics and Computational Mathematics National Key Laboratory of Computational Physics Beijing100088 China School of Mathematical Sciences Fujian Provincial Key Laboratory of Mathematical Modeling and High-Performance Scientific Computing Xiamen University Fujian Xiamen361005 China

In this paper, the high-order discontinuous Galerkin (DG) schemes are presented for radiation hydrodynamics equations in the equilibrium-diffusion limit. The governor equations contain two parts, one part is a hyperbolic system of conservation laws and another part is a radiative heat transfer term. The discrete schemes are constructed in three parts and possess characteristics of the high-order, oscillation-free and efficient. Firstly, the DG method and local DG (LDG) method are respectively used to discretize the hyperbolic system and radiative heat transfer term to achieve high-order spatial accuracy. Secondly, the combination of the KXRCF shock detector, Hermite WENO limiter, and positivity-preserving limiter is utilized to enhance the robustness of the discretization schemes. Finally, the implicit-explicit schemes are employed for time discretization to enable the schemes suitable for larger time steps. Numerical experiments have verified that the new schemes are high-order accuracy, oscillation-free and efficiency. © 2023, The Authors. All rights reserved.

关键词： Hydrodynamics

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