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Guest editorial: Progress on computational techniques for electromagnetic fields and applications

COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic engineering 2023年第1期42卷 1-1页

作者： Yang, Shiyou Sykulski, Jan Qingxin, Yang Cui, Xiang Department of Electrical Engineering Zhejiang University Hangzhou China Department of Electronics and Computer Science Southampton University Southampton United Kingdom Tianjin Key Laboratory of Advanced Electrical Engineering and Energy Technology Tianjin Polytechnic University Tianjin China State Key Laboratory for Alternate Electrical Power System with Renewable Energy Sources Research Center for Electromagnetism and Superconduction Beijing China

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Dimensional inconsistency measures and postulates in spatio-temporal databases

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Journal of Artificial Intelligence Research 2021年 71卷 733-780页

作者： Grant, John Martinez, Maria Vanina Molinaro, Cristian Parisi, Francesco Department of Computer Science UMIACS University of Maryland College Park United States Department of Computer Science FCEyN University of Buenos Aires Argentina Department of Informatics Modeling Electronics and System Engineering University of Calabria Italy

The problem of managing spatio-temporal data arises in many applications, such as location-based services, environmental monitoring, geographic information systems, and many others. Often spatio-temporal data arising from such applications turn out to be inconsistent, i.e., representing an impossible situation in the real world. Though several inconsistency measures have been proposed to quantify in a principled way inconsistency in propositional knowledge bases, little effort has been done so far on inconsistency measures tailored for the spatio-temporal setting. In this paper, we define and investigate new measures that are particularly suitable for dealing with inconsistent spatio-temporal information, because they explicitly take into account the spatial and temporal dimensions, as well as the dimension concerning the identifiers of the monitored objects. Specifically, we first define natural measures that look at individual dimensions (time, space, and objects), and then propose measures based on the notion of a repair. We then analyze their behavior w.r.t. common postulates defined for classical propositional knowledge bases, and find that the latter are not suitable for spatio-temporal databases, in that the proposed inconsistency measures do not often satisfy them. In light of this, we argue that also postulates should explicitly take into account the spatial, temporal, and object dimensions and thus define "dimension-aware" counterparts of common postulates, which are indeed often satisfied by the new inconsistency measures. Finally, we study the complexity of the proposed inconsistency measures. © 2021 AI Access Foundation. All rights reserved.

关键词： Location based services

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Quantum noise of dark pulse microcombs

Quantum noise of dark pulse microcombs

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Conference on Lasers and Electro-Optics (CLEO)

作者： Chenghao Lao Xing Jin Lin Chang Weiqiang Xie Haowen Shu Xingjun Wang John E. Bowers Qi-Fan Yang School of Physics State Key Laboratory for Artificial Microstructure and Mesoscopic Physics and Frontiers Science Center for Nano-Optoelectronics Peking University Beijing China Department of Electrical and Computer Engineering University of California Santa Barbara CA USA Department of Electronics School of Electronics Engineering and Computer Science State Key Laboratory of Advanced Optical Communications System and Networks Peking University Beijing China

We investigate the fundamental timing jitter of dark pulse microcombs generated in an AlGaAs microresonator, where the quantum-limited frequency noise of the 91-GHz repetition rate is measured to be 0.5 Hz 2 /Hz.

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

关键词： Timing jitter Pulse measurements Laser noise Measurement by laser beam Solitons Lasers and electrooptics Microcavities

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Review of the Ionospheric Error Correction Techniques in Satellite Navigation

Review of the Ionospheric Error Correction Techniques in Sat...

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第十四届中国卫星导航年会

作者： Xihao Han Jianlei Yang Shuaiyong Zheng Mengzhi Gao Zhigang Huang Xiaoqin Jin Kun Li Peng Yang Zhonghao Zuo Department School of Integrated Circuit Science and Engineering Tianjin University of Technology The 54th Research Institute of China Electronics Technology Group Corporation State Key Laboratory of Satellite Navigation System and Equipment Technology School of Electronic and Information Engineering Beihang University College of Artificial Intelligence Nankai University School of Computer Science and Engineering Tianjin University of Technology

Ionospheric error seriously affects the positioning accuracy of the global navigation satellite ***,BDS,Galileo and GLONASS all adopt different ionospheric error correction *** ionospheric error correction methods in satellite navigation are introduced,and the principle and development of single frequency ionospheric error correction,dual-frequency ionospheric error correction and multi-frequency ionospheric error correction are summarized in this *** the single frequency correction,the grid ionospheric model,Klobuchar model,IRI constraint model and Ne Quick model are summarized,the BDGIM model further improves the ionospheric error correction accuracy on the base of the grid ionospheric model correction by ameliorating spherical harmonics,the Kriging interpolation method improves the interpolation accuracy of the grid ionospheric model correction;In the dualfrequency correction,the ionosphere-free model and the ionospheric error correction methods in the PPP-RTK technology are summarized;In the multifrequency correction,the optimization and improvement of ionospheric error correction technique with the high order correction and geomagnetic field model are ***,the ionospheric error correction techniques and their derivative are analyzed and encapsulated,the development trend and future hotspots of ionospheric error correction technology in satellite navigation are listed and analyzed.

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Autonomous Power Supply Development for Hydrometeorological Monitoring Station

Autonomous Power Supply Development for Hydrometeorological ...

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IEEE International Energy Conference and Exhibition (EnergyCon)

作者： Anatoliy Prystupa Volodymyr Kazymyr Anatolijs Zabaš ta Anatoliy Revko Serhii Stepenko Kateryna Novyk Electrical Engineering Information and Measurement Technologies Department Chernihiv Polytechnic National University Chernihiv Ukraine Information and Computer system Department Chernihiv Polytechnic National University Chernihiv Ukraine Institute of Industrial Electronics and Electrical Engineering Riga Technical University Riga Latvia Electronics Automation Robotics and Mechatronics Department Chernihiv Polytechnic National University Chernihiv Ukraine

This paper presents the results of the investigation of the power supply system of the autonomous monitoring system. In particular, calculations of the system’s daily balance of energy consumption were performed. Also, the question of the influence of the angle of inclination of solar converters on energy generation is considered and the necessity of collecting solar radiation during the whole daylight, not focusing on the maximum amount of energy, is substantiated. This research aimed to develop an algorithm for calculating the power supply system for autonomous monitoring systems. The proposed algorithm takes into account the coordination of diagrams of generation and consumption of energy within the autonomous monitoring station and statistical analysis of information from the NASA website. Experiments have shown the effectiveness of this method. It can be used in future design of power supply systems for autonomous monitoring stations.

关键词： Power measurement Power supplies Statistical analysis NASA Energy measurement Reliability theory Battery charge measurement

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Next-generation machine vision systems incorporating two-dimensional materials: Progress and perspectives

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InfoMat 2022年第1期4卷 23-39页

作者： Peisong Wu Ting He He Zhu Yang Wang Qing Li Zhen Wang Xiao Fu Fang Wang Peng Wang Chongxin Shan Zhiyong Fan Lei Liao Peng Zhou Weida Hu State Key Laboratory of Infrared Physics Shanghai Institute of Technical PhysicsChinese Academy of SciencesShanghaiChina University of Chinese Academy of Sciences BeijingChina Hangzhou Institute for Advanced Study University of Chinese Academy of SciencesHangzhouChina State Key Laboratory of ASIC and System School of MicroelectronicsFudan UniversityShanghaiChina Henan Key Laboratory of Diamond Optoelectronic Materials and Devices School of Physics and EngineeringZhengzhou UniversityZhengzhouChina Department of Electronic and Computer Engineering The Hong Kong University of Science and TechnologyClear Water BayKowloonHong Kong SARChina School of Physics and Electronics Hunan UniversityChangshaChina

Machine vision systems(MVSs)are an important component of intelligent systems,such as autonomous vehicles and ***,with the continuous increase in data and new application scenarios,new requirements are put forward for the next generation of *** is an urgent need to find new material systems to complement the existing semiconductor technology based on thin-film materials,and new architectures must be explored to improve *** of their unique physical properties,two-dimensional(2D)materials have received extensive attention for use in MVSs,especially in biomimetic ones:the human visual system,which can process complex visual information with low power consumption,provides a model for next-generation *** review paper summarizes the progress and challenges of applying 2D material photodetectors in sense-memory-computational integration and biomimetic image sensors for machine vision.

关键词： in-sensor computing machine vision systems photodetectors two-dimensional materials

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Dynamic Task Sequence Allocation Based on Natural Language Instruction

Dynamic Task Sequence Allocation Based on Natural Language I...

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Automation, Robotics and computer engineering (ICARCE), International Conference on

作者： Yongchang Li Jianhang Feng Zhigang Tao Lumeng Ma Yanzhi Dong Xiaohu Yuan School of Physics and Electronic Information Yantai University Yantai China Key Lab of Information System Requirement Nanjing Research Institute of Electronics Engineering Nanjing China The 28th Research Institute of China Elecchonics Technology Group Corporation Nanjing China School of Electrical and Electronic Engineering Shanghai Institute of Technology Shanghai China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (数字)9798331529505

ISBN: (纸本)9798331529512

In recent years, with the development of technology, robots have become more prominent in the public eye. Service robots are now being used in some smart hotels to decrease manual transportation costs. However, these service robots operate according to set instructions, and humans usually apply fixed operating instructions to control the robots. Whether in daily life or at work, humans are more likely to use natural language to communicate and give task instructions. Moreover, in the field of multi-robotics, most of the existing researches on multi-task assignment have been conducted in simulation environments on a list of pre-set tasks, and seldom update the task sequences in real time in conjunction with the real environmental information and time. In this paper, we propose a method for assigning dynamic navigation task sequences based on natural language instruction and verify its effectiveness in a real scenario.

关键词： Service robots Navigation Human-robot interaction Transportation Transforms Oral communication Real-time systems Natural language processing Resource management Robots

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A Model Predictive Current Control for a Three-Phase Modular Matrix Converter

A Model Predictive Current Control for a Three-Phase Modular...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Maryam Sarebanzadeh Mohammad Ali Hosseinzadeh Ralph Kennel Ebrahim Babaei Marco Rivera Patrick Wheeler Chair of High-Power Converters System Technical University of Munich Munich Germany Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran Department of Electrical and Electronic Engineering Faculty of Engineering Chair of Power Electronics Machines and Control (PEMC) Research Group University of Nottingham Nottingham UK Laboratorio de Conversión de Energías y Electrónica de Potencia (LCEEP) Vicerrectoría Academica Universidad de Talca Talca Chile

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

The modular matrix converter (MMC) integrates a multi-winding transformer with a three-phase-to-single-phase matrix converter for each phase, making it suitable for high-power, high-voltage applications. Predictive control is an advanced control technique widely applied to power converters due to its numerous advantages, including fast dynamic response, the elimination of the need for proportional gain, and straightforward implementation. This study proposes a model predictive control (MPC) strategy to regulate load currents, reactive power, and common-mode voltage in a three-phase modular matrix converter. The proposed MPC algorithm selects the optimal switching states from all valid options for the modular matrix converter to apply in the next control step. A cost function is then used to minimize the error between the predicted system variables and their reference values, ensuring that the best states are applied to the modular matrix converter. The proposed MPC technique effectively controls the load currents to follow the desired reference signals, maintains sinusoidal source current waveforms by regulating reactive power, and reduces the magnitude of the common-mode voltage. The performance of the proposed approach is demonstrated through simulation results obtained in the MATLAB/Simulink environment.

关键词： Current control Reactive power Total harmonic distortion Simulation Switches Cost function Transformers Matrix converters Voltage control Predictive control

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Driver Fatigue Detection Using OpenCV and Dlib Library

Driver Fatigue Detection Using OpenCV and Dlib Library

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computer Science and Data engineering (CSDE), IEEE Asia-Pacific Conference on

作者： Kuang Shen Rusyaizila Ramli Joong Huang Chuah Grace Mei Ting Chai School of Electronics and Computer Science University of Southampton Southampton United kingdom Carbon Neutrality Research Group University of Southampton Malaysia Iskandar Puteri Johor Malaysia Department of Electrical Engineering Faculty of Engineering University of Malaya Kuala Lumpur Malaysia Smart Manufacturing System Reasearch Group University of Southampton Malaysia Iskandar Puteri Johor Malaysia

Driver fatigue and distraction are major contributors to fatal road accidents worldwide. To enhance vehicle safety, this article proposes a fatigue detection system using EAR and MAR algorithms to identify signs of fatigue, such as eye closure and yawning. When prolonged eye closure or yawning is detected, the system issues an alert to the driver. It leverages OpenCV and Dlib libraries for implementation. Additionally, the system detects driver distraction by monitoring head swivels, counting left and right movements. It's worth noting that Dlib may yield facial landmark deviations for non-frontal faces. To mitigate this, the study selected 69 videos from the YawDD database, focusing on near-frontal face views, achieving a 91.3% accuracy rate.

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Deep Learning in Smart Healthcare: A GAN-based Approach for Imbalanced Alzheimer's Disease Classification

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Procedia computer Science 2024年 241卷 146-153页

作者： Hina Tufail Abdul Ahad Ira Puspitasari Ibraheem Shayea Paulo Jorge Coelho Ivan Miguel Pires Department of Computer Science University of Management and Technology Sialkot Pakistan Information System Study Program Faculty of Science and Technology Universitas Airlangga School of Software Northwestern Polytechnical University Xian Shaanxi P.R. China Department of Electronics and Communication Engineering Istanbul Technical University(ITU) Turkey Polytechnic University of Leiria Leiria Portugal Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra) Coimbra Portugal Instituto de Telecomunicações Escola Superior de Tecnologia e Gestão de Águeda Universidade de Aveiro Águeda Portugal

Alzheimer's disease (AD) is a type of dementia that leads to memory loss and impairment, which afects patients’ lives badly. It is not curable yet, but its progression can be slowed down if detected at earlier stages. In this research study, we propose a transfer learning-based convolutional neural network (CNN) model to classify magnetic resonance imaging (MRI) into one of four stages of Alzheimer's disease. One of the major limitations of the deep learning-based classification model is the non-availability of healthcare datasets related to AD. The widely used Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset has a major class imbalance issue. We propose a generative adversarial network (GAN) based data augmentation technique to overcome the data imbalance. This promotes the investigation of applying GANs to generate synthetic samples for minority classes in Alzheimer's disease datasets to enhance classification performance. The results show the progression in the overall classification process of AD.

关键词： Alzheimer disease (AD) Deep learning Convolutional Neural Network (CNN) computer-aided diagnosis (CAD)

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