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Iranian Conference on electrical engineering (ICEE)

作者： Arash Akbari Arman Akbari Mehdi Tale Masouleh Department of Computer Science University of Tehran Tehran Iran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Tehran Iran

Robot grasping is of paramount importance in industrial and service robotics. In recent years, various data-driven algorithms have been proposed to solve the problem of grasp detection and a part of them are based on reinforcement learning (RL) approaches. In a variety of proposed algorithms, random key points are being employed which will make the learning process inefficient and time-consuming. In this paper, a geometry-based algorithm is presented which can find grasp poses based on the geometry of the unknown object and propose the ones which may lead to successful grasping. For the grasp contacts computation part, the presented algorithm produces a finite number of key points based on the 2D shape of the object from a specific point of view. Afterward, it will narrow down the candidate points and output a finite number of successful grasp poses based on three grasp quality metrics for various unknown objects. Three approaches are proposed in order to achieve center points which can describe different parts of a 2D shape. Then, the obtained points are used as the center of circles which are tangent to the 2D shape contour. Also, a new grasp quality metric is proposed. The time of the grasp and the amount of object disorientation after grasping are considered as a metric to evaluate the successfulness of the grasp. Simulation results demonstrate that the proposed algorithm for unknown object grasping can find a finite number of successful grasp poses for different seen or unseen objects without using any random point,

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Calculation Method of Switch Machine Health Index Based on Long-Term and Short-Term Neural Network 1

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5th International Symposium for Intelligent Transportation and Smart City, ITASC 2022

作者： Shen, Tuo Zheng, Zhi Zeng, Xiaoqing Ying, Peiran Zhang, Xuanxiong School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China Shanghai Key Laboratory of Rail Infrastructure Durability and System Safety School of Transportation Engineering Tongji University Shanghai China The Key Laboratory of Road and Traffic Engineering Ministry of Education Tongji University No. 4800 Cao’an Road Shanghai201804 China

ISBN: (数字)9789819922529

ISBN: (纸本)9789819922512

With the continuous development of urban rail, it has become one of the main ways for people to travel. How to ensure the safe and efficient operation of urban rail transit is the focus of attention. The switch machine is one of the important equipment of the signal system. During the long-term service, the performance of the device gradually deteriorates or sudden failure, which will have a significant impact on the operation of the train. For this reason, it is necessary to evaluate the health status of the point machine to predict the life of the point machine. Therefore, a continuously distributed health index (HI) is proposed to characterize the health status of the switch machine in service throughout its life cycle. The operation state of Switch machine is related to the characteristics of its working current. Based on this assumption, this paper monitor the operation state of Switch machine by applying artificial intelligence technology. In this paper, Long-Short Term Memory is trained to predict the health index of the Switch machine. The result shows that the model used by this paper can achieve high accuracy and the prediction accuracy rate reaches 84.9%.It is reliable in predicting the health index of Switch machine. Finally, the HI can be used not only to evaluate the health status of switch machines, but also to predict the health status of other key rail equipment, and promote the development of smart rail transit operation and maintenance. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Life cycle

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Grid of Near Future: Impact on (N-1) Contingency Analysis in Presence of Droop-Controlled Grid-Forming Converter-Interfaced Generations

Grid of Near Future: Impact on (N-1) Contingency Analysis in...

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2022 IEEE Power and Energy Society General Meeting, PESGM 2022

作者： Karunaratne, Lilan Yogarathnam, Amirthagunaraj Ray Chaudhuri, Nilanjan Yue, Meng Pennsylvania State University School of Electrical Engineering and Computer Science University ParkPA United States Brookhaven National Laboratory Interdisciplinary Science Department UptonNY United States

ISBN: (数字)9781665408233

ISBN: (纸本)9781665408233

Similar to the traditional ac grids, a secure operation of near future grids with high penetration of converter-interfaced generations (CIGs) including grid-forming converters (GFCs) following a single-point failure, i.e., an (N-1) contingency, is a fundamental problem during the contingency screening and ranking. The increasing CIGs introduce dynamics of different time scales and may change the dynamic behaviors of the grid under (N-1) contingencies. This paper focuses on the contingency analysis of such grids following synchronous generator (SG) outages i.e., the impact of GFCs following a SG outage on such analysis due to their dc-side current limits. To this end, an averaged model of GFCs is developed, and the dc side dynamics and the current limits are also modeled. Then, a revised online/offline generator outage contingency screening and ranking approach to take into account the effect of dc-link voltage collapse of GFCs is proposed. Finally, the proposed approach is validated using the time-domain simulation on a modified 2-area 4-machine test system with a GFC. © 2022 IEEE.

关键词： Time domain analysis

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Multi-dimensional multiplexing optical secret sharing framework with cascaded liquid crystal holograms

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Opto-Electronic Advances 2024年第1期7卷 28-35页

作者： Keyao Li Yiming Wang Dapu Pi Baoli Li Haitao Luan Xinyuan Fang Peng Chen Yanqing Lu Min Gu Institute of Photonic Chips University of Shanghai for Science and TechnologyShanghai 200093China Centre for Artificial-Intelligence Nanophotonics School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and TechnologyShanghai 200093China National Laboratory of Solid State Microstructures and College of Engineering and Applied SciencesNanjing UniversityNanjing 210093China

Secret sharing is a promising technology for information encryption by splitting the secret information into different ***,the traditional scheme suffers from information leakage in decryption process since the amount of available information channels is ***,we propose and demonstrate an optical secret sharing framework based on the multi-dimensional multiplexing liquid crystal(LC)*** LC holograms are used as spatially separated shares to carry secret *** polarization of the incident light and the distance between different shares are served as secret keys,which can significantly improve the information security and ***,the decryption condition is also restricted by the applied external voltage due to the variant diffraction efficiency,which further increases the information *** implementation,an artificial neural network(ANN)model is developed to carefully design the phase distribution of each LC *** the advantage of high security,high capacity and simple configuration,our optical secret sharing framework has great potentials in optical encryption and dynamic holographic display.

关键词： holographic encryption optical secret sharing cascaded liquid crystal hologram multi-dimensional multiplexing

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基于语音识别的电磁调控智能超表面

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engineering 2023年第3期22卷 185-190页

作者：柏林刘元可徐亮张政王强蒋卫祥仇成伟崔铁军 State Key Laboratory of Millimeter Waves School of Information Science and EngineeringSoutheast UniversityNanjing 210096China Purple Mountain Laboratories Nanjing 211111China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore

本文提出并实现了一种基于人类语音识别的智能超表面,用于对电磁波束进行可编程调控。该智能超表面平台由数字编码超表面、语音识别模块、单片机和数模转换器(DAC)电路组成,可根据预先存储的语音指令对电磁波进行智能控制。所构建的数... 详细信息

本文提出并实现了一种基于人类语音识别的智能超表面,用于对电磁波束进行可编程调控。该智能超表面平台由数字编码超表面、语音识别模块、单片机和数模转换器(DAC)电路组成,可根据预先存储的语音指令对电磁波进行智能控制。所构建的数字编码超表面包含6×6个超级子单元,每个超级子单元由4×4个嵌入了变容二极管的有源数字单元组成。语音识别模块配合DAC和单片机对语音指令进行识别,并生成对应的电压序列来控制超表面。此外,在超表面的设计过程中引入遗传算法,可有效优化超表面相位分布。为了验证智能超表面平台的性能,演示了雷达散射截面积缩减、涡旋波束生成和波束分裂三种典型功能。所提出的方案为调控电磁波提供了一种新的途径,并在电磁和声学通信之间架起了连接桥梁。

关键词： Speech recognition Programmable metasurface Genetic algorithm Smart electromagnetic manipulation

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A short review on infrared thermography: history, philosophy, approaches, standards and application examples 45

A short review on infrared thermography: history, philosophy...

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Thermosense: Thermal Infrared Applications XLV 2023

作者： Plastropoulos, Angelos Adiuku, Ndidiamaka Avdelidis, Nicolas P. Ibarra-Castanedo, Clemente Maldague, Xavier P.V. Servais, Pierre Integrated Vehicle Health Management Centre School of Aerospace Transport and Manufacturing Cranfield University United Kingdom Computer Vision & Systems Laboratory Department of Electrical & Computer Engineering Laval University Quebec CityG1V 0A6 Canada NDT PRO Srl Le grand enclos 18 LibramontB6800 Belgium

ISBN: (纸本)9781510661868

Infrared thermography is a condition monitoring technique that, from a measurement of the radiant heat pattern emitted by a material, is able to determine regions or points of increased or reduced heat emission that can indicate the presence of an imperfection in the investigated material. The result of an infrared thermographic investigation is a sequence of thermograms or thermal images, in other words a picture of temperature, that can be further processed for qualitative and quantitative purposes. Such images can be presented in either false color or black and white format. In the present work, the philosophy and history of thermal–infrared imaging are reviewed. Moreover, the different evaluation approaches (passive and active), as well as many standards related to infrared thermography are discussed. Finally, various applications of the transient thermography approach are briefly presented. © 2023 SPIE.

关键词： Thermography (imaging)

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Application of Explainable Ai in Predicting Symptomatic Influenza a Infection

SSRN

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SSRN 2024年

作者： Lin, Tsung-Hsien Cheng, Zhi-Jian Xie, Zhong-Ru Chang, Kuan Y. Biomedical AI Laboratory Department of Computer Science & Engineering National Taiwan Ocean University Keelung Taiwan Computational Drug Discovery Laboratory School of Electrical and Computer Engineering College of Engineering University of Georgia AthensGA United States

DeepFlu predicts the onset of symptomatic influenza infection from pre-exposure gene expression, yet the role of individual genes in the model is unclear. This study uses SHapley Additive exPlanations (SHAP), an explainable artificial intelligence method, to assess individual gene impacts on Deep Flu for H1N1 and H3N2 influenza virus infections. The analysis is based on two gene expression datasets: GSE52428 and GSE73072. Five common key genes across different datasets are identified: HLA-DQA1, HLA-DQB1, XIST, RPS4Y1, and KDM5D. These genes are linked to immunity and sex, with higher expression of XIST and lower expression of RPS4Y1 or KDM5D suggesting increased fe male susceptibility to influenza. This integration of SHAP with this deep learning model offers early predictive insights and interpretability for influenza susceptibility. © 2024, The Authors. All rights reserved.

关键词： Gene expression

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In situ impulse-rotation nanomotors on microfibers driven by photothermal gradient forces

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Physical Review Applied 2024年第5期22卷 054066-054066页

作者： Zhaoqi Gu Lin Dou Shuangyi Linghu Runlin Zhu Fuxing Gu Laboratory of Integrated Opto-Mechanics and Electronics School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai 200093 China Department of Physics Guizhou University Guiyang 550025 China

With the development of nanotechnology, there has been great interest in manipulating nanomaterials. However, the development of manipulating techniques still faces challenges and is slower than that of nanomaterial fabrication techniques. The key to solving this problem is to develop universal nanomotors that can provide energy to overcome the large interfacial resistance caused by the high surface-to-volume ratio at the nanoscale. Photothermal gradient forces generated by photothermal shock have been demonstrated to drive nanomaterials on dry, flat substrates. Yet, the driving mechanism for the motion of semisuspended nanomaterials with a single-point contact remains unclear. In this work, we demonstrate metal nanowire rotation motors that operate on the curved surfaces of silica microfibers. The theoretical analysis proves the unified principle of body and surface forces and confirms that the direct driving power source is the internal stress, a generalized surface force. Experimentally, we achieve pure and stable in situ rotation of single nanowires without axial translation and rotation of multinanowire assemblies. Our work provides a firm foundation for using transient photothermal gradient forces to manipulate nanomaterials at the nanoscale and broadens the potential applications of nanomotors.

关键词： Adhesion Friction Optical fibers Optical forces Surface & interfacial phenomena Thermoelasticity Tribology Nanomechanical devices

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Design and Implementation of Braille Learning Machine Based on Internet of Things Technology 3

Design and Implementation of Braille Learning Machine Based ...

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3rd International Conference on Internet of Things and Smart City, IoTSC 2023

作者： Liu, Weipu Wu, Fengjie Li, Shenghui Mo, Guangpeng Luo, Wenjun Liu, Qingkun School of Electronics and Communication Engineering Guangzhou University Guangdong Guangzhou510006 China Laboratory Center of Guangzhou University Guangzhou University Guangdong Guangzhou510006 China School of Mechanical and Electrical Engineering Guangzhou University Guangdong Guangzhou510006 China School of Computer Science and Cyber Engineering Guangzhou University Guangdong Guangzhou510006 China

ISBN: (纸本)9781510666375

In order to meet the needs of the visually impaired to learn Braille and improve the efficiency of teachers teaching Braille, this paper uses Internet of Things technology and embedded technology to design a new type of Braille learning machine to optimize the existing Braille teaching. The Braille teaching system is designed through the MQTT protocol to realize the network control of multiple Braille learning machines. A micro motor is used to control the lifting of a single braille bump, and a dual CPU control architecture is used to control the lifting of the braille bump, which improves its reusability compared with traditional braille boards. We tested the accuracy of Braille conversion, and the experimental results were in line with expectations. This research can better serve the visually impaired and bring convenience to their Braille learning. © 2023 SPIE.

关键词： Reusability

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Instance-Level Panoramic Audio-Visual Saliency Detection and Ranking 24

Instance-Level Panoramic Audio-Visual Saliency Detection and...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Guo, Ruohao Niu, Dantong Qu, Liao Qi, Yanyu Shi, Ji Yue, Wenzhen Xing, Bowei Chen, Taiyan Ying, Xianghua National Key Laboratory of General Artificial Intelligence School of Intelligence Science and Technology Peking University Beijing China Berkeley AI Research University of California Berkeley BerkeleyCA United States Department of Electrical and Computer Engineering Carnegie Mellon University PittsburghPA United States College of Information and Electrical Engineering China Agricultural University Beijing China

ISBN: (纸本)9798400706868

Panoramic audio-visual saliency detection is to segment the most attention-attractive regions in 360° panoramic videos with sound. To meticulously delineate the detected salient regions and effectively model human attention shift, we extend this task to more fine-grained instance scenarios: identifying salient object instances and inferring their saliency ranks. In this paper, we propose the first instance-level framework that can simultaneously be applied to segmentation and ranking of multiple salient objects in panoramic videos. Specifically, it consists of a distortion-aware pixel decoder to overcome panoramic distortions, a sequential audio-visual fusion module to integrate audio-visual information, and a spatio-temporal object decoder to separate individual instances and predict their saliency scores. Moreover, owing to the absence of such annotations, we create the ground-truth saliency ranks for the PAVS10K benchmark. Extensive experiments demonstrate that our model is capable of achieving state-of-the-art performance on the PAVS10K for both saliency detection and ranking tasks. The code is available at https://***/ruohaoguo/pavsodr. © 2024 ACM.

关键词： Contrastive Learning

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