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International Conference on Inventive Computation Technologies (ICICT)

作者： Bharathi R.B. G.K. Prabhu Ramesh S. Ve Meenakshi S. Sundaram Department of Electrical & Electronics Engineering Manipal Institute of Technology MAHE Manipal India Department of Electronics and Communication Engineering Manipal University Jaipur Rajasthan India Department of Optometry MAHE Manipal India Department of Instrumentation & Control Engineering Manipal Institute of Technology MAHE Manipal

ISBN: (数字)9781728146850

ISBN: (纸本)9781728146867

A 3D model of human eye is developed by using Finite Element based software to determine the influence of variation in Intra Ocular Pressure (IOP) of eye on the magnitude of applanation force applied during tonometry test procedure. The standard tonometer experiences deformation from 0.5mm to 3mm of the cornea is adopted during the simulation work. The study about the applanation force during tonometry plays a major role while designing new prototype of tonometer. The results demonstrate that higher IOP of eye will tend to reduce the magnitude of force of applanation required during tonometry test and vice versa. To provide maximum of up-to 3mm displacement of cornea along the direction of cornea towards retina, the amount of applanation force provided through tonometer is 2.8N and to provide 0.5mm displacement of cornea along the direction towards the retina, the amount of applanation force is 0.5N.

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Unsupervised Domain Adaptation on Person Re-Identification via Dual-level Asymmetric Mutual Learning

arXiv

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arXiv 2023年

作者： Wu, Qiong Li, Jiahan Dai, Pingyang Ye, Qixiang Cao, Liujuan Wu, Yongjian Ji, Rongrong Institute of Artificial Intelligence The Media Analytics and Computing Laboratory Department of Artificial Intelligence School of Informatics Xiamen University Xiamen361005 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221000 China The Media Analytics and Computing Laboratory Department of Artificial Intelligence School of Informatics Xiamen University Xiamen361005 China The Peng Cheng Laboratory Shenzhen518066 China The School of Electronics Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China The Media Analytics and Computing Lab Department of Computer Science School of Informatics Xiamen University Xiamen361005 China The Youtu Laboratory Tencent Shanghai200233 China The Fujian Engineering Research Center of Trusted Artificial Intelligence Analysis and Application Institute of Artificial Intelligence Xiamen University Xiamen361005 China

Unsupervised domain adaptation person re-identification (Re-ID) aims to identify pedestrian images within an unlabeled target domain with an auxiliary labeled source-domain dataset. Many existing works attempt to recover reliable identity information by considering multiple homogeneous networks. And take these generated labels to train the model in the target domain. However, these homogeneous networks identify people in approximate subspaces and equally exchange their knowledge with others or their mean net to improve their ability, inevitably limiting the scope of available knowledge and putting them into the same mistake. This paper proposes a Dual-level Asymmetric Mutual Learning method (DAML) to learn discriminative representations from a broader knowledge scope with diverse embedding spaces. Specifically, two heterogeneous networks mutually learn knowledge from asymmetric subspaces through the pseudo label generation in a hard distillation manner. The knowledge transfer between two networks is based on an asymmetric mutual learning manner. The teacher network learns to identify both the target and source domain while adapting to the target domain distribution based on the knowledge of the student. Meanwhile, the student network is trained on the target dataset and employs the ground-truth label through the knowledge of the teacher. Extensive experiments in Market-1501, CUHK-SYSU, and MSMT17 public datasets verified the superiority of DAML over state-of-the-arts. Copyright © 2023, The Authors. All rights reserved.

关键词： Distillation

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Contactless and passive humidity measurement by using ultra-thin GO nanosheet coated SAW sensor

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Sensors and Actuators A: Physical 2025年 393卷

作者： Baile Cui Xu Gao Zheng Zhao Xufeng Xue Qiming Yang Jing Jin Wen Wang Yong Liang Dongliang Guo Institute of Acoustics Chinese Academy of Sciences Beijing 100190 PR China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing 100049 China Tianjin Key Laboratory of Quantum Precision Measurement Technology Tianjin Navigation Instruments Research Institute Tianjin 300131 PR China State Grid Jiangsu Electric Power Co. Ltd. Research Institute Nanjing Jiangsu 211103 PR China

The contractless humidity sensing technology with far distance, high sensitivity and fast response is a favorable method to realize humidity measurement in complex environments. Herein, an ultra-thin 1 nm Graphene oxide (GO) film is deposited on the surface of a reflective delay linear SAW device to construct a SAW humidity sensor for wireless signal excitation and passive sensing. A radio frequency (RF) reader with low noise < ±0.003 dB has been successfully designed and manufactured for stable wireless sensing. The hydrogen bond between GO and water molecules, and the viscoelastic-acoustoelectric coupling effect improved the humidity sensitivity. Remarkably, the prepared SAW humidity sensor achieved high humidity sensitivity (0.46 dB/%RH), low detection limit (0.37 % RH), fast response and recovery speed (T 90 =15.5 s, T 10 =16.1 s) and excellent repeatability at 150 cm contractless distance. Practically, the contractless and passive SAW humidity sensor prepared in this study has the potential to realize high-precision and real-time humidity measurement in complex environments.

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Lateral Trajectory Stabilization of an Articulated Truck during Reverse Driving Maneuvers

Lateral Trajectory Stabilization of an Articulated Truck dur...

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IEEE Symposium on Intelligent Vehicle

作者： Mohit Kumar Arne-Christoph Hildebrandt Peter Strauss Sven Kraus Christoph Stiller Andreas Zimmermann Mobile Perception System Forschungszentrum Informatik Karlsruhe Germany Engineering Central Research MAN Truck & Bus SE. Munich Germany Institute of Measurement and Control Systems Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (数字)9781728166735

ISBN: (纸本)9781728166742

The stabilization of articulated truck i.e. truck-semitrailer is a complex problem due to the instable dynamics. In this paper, a lateral trajectory stabilization algorithm for reverse driving of truck-semitrailer is proposed. A cascade control is presented for lateral trajectory stabilization of truck-semitrailer. A high-level path tracking algorithm handles the path tracking of a virtual vehicle which is an equivalent model for the semitrailer. A low-level Linear Quadratic Regulator (LQR) stabilizes the hitch angle. The path tracking problem is formulated as a linear time-varying differential dynamic programming problem subjective to virtual vehicle dynamics in a receding horizon fashion. The virtual vehicle dynamics are defined by the single track kinematic vehicle model and the hitch angle dynamics is used for formulating the Linear Quadratic Regulator problem. The approach is demonstrated with replays of real-world path tracking scenarios on a full-scale truck-semitrailer prototype.

关键词： Vehicle dynamics Trajectory Level control Dynamic programming Wheels Regulators Predictive models

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Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface Assisted NOMA Networks

arXiv

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arXiv 2021年

作者： Yue, Xinwei Xie, Jin Liu, Yuanwei Han, Zhihao Liu, Rongke Ding, Zhiguo The Key Laboratory of Information and Communication Systems Ministry of Information Industry China The Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom The School of Electronic and Information Engineering Beihang University Beijing100191 China The Department of Electrical Engineering Princeton University Princeton United States The School of Electrical and Electronic Engineering The University of Manchester Manchester United Kingdom

Simultaneously transmitting/refracting and reflecting reconfigurable intelligent surface (STAR-RIS) has been introduced to achieve full coverage area. This paper investigate the performance of STAR-RIS assisted non-orthogonal multiple access (NOMA) networks over Rician fading channels, where the incidence signals sent by base station are reflected and transmitted to the nearby user and distant user, respectively. To evaluate the performance of STAR-RIS-NOMA networks, we derive new approximate expressions of outage probability and ergodic rate for a pair of users, in which the imperfect successive interference cancellation (ipSIC) and perfect SIC (pSIC) schemes are taken into consideration. Based on the asymptotic expressions, the diversity orders of the nearby user with ipSIC/pSIC and distant user are achieved carefully. The high signal-to-noise ratio slopes of ergodic rates for nearby user with pSIC and distant user are equal to one and zero, respectively. In addition, the system throughput of STAR-RIS-NOMA is discussed in delay-limited and delay-tolerant modes. Simulation results are provided to verify the accuracy of the theoretical analyses and demonstrate that: 1) The outage probability of STAR-RIS-NOMA outperforms that of STAR-RIS assisted orthogonal multiple access (OMA) and conventional cooperative communication systems;2) With the increasing of reflecting elements K and Rician factor κ, the STAR-RIS-NOMA networks are capable of attaining the enhanced performance;and 3) The ergodic rates of STAR-RIS-NOMA are superior to that of STAR-RIS-OMA. Copyright © 2021, The Authors. All rights reserved.

关键词： Signal to noise ratio

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An Optimal Lateral Trajectory Stabilization of Vehicle using Differential Dynamic Programming

An Optimal Lateral Trajectory Stabilization of Vehicle using...

引用

IEEE Symposium on Intelligent Vehicle

ISBN: (数字)9781728166735

ISBN: (纸本)9781728166742

Vehicles nowadays are equipped with several assistance functions for e.g. Cruise control and Lane Keeping Assist. Classical lateral control approaches such as pure pursuit, Stanley used for lane keeping assist provide good path tracking precision. However the operational domain for these approaches is limited i.e. highway driving. An adaptation of control parameters can increase the operational domain, but its difficult to tune classical approaches for the whole range of automated driving maneuvers. Apart from these classical approaches, optimization approaches are also used for lateral trajectory stabilization. The optimization based approaches have a wider operational domain, but the feasibility and real time execution remain some open issues. In this paper, we combine a classical approach and an optimization method for lateral trajectory stabilization. We present a method to optimize the control input calculated using a classical control approach i.e. pure pursuit based on a performance criteria. The performance criteria weighs the precision and comfort requirements. A non- linear optimization based on Differential Dynamic Programming (DDP) is used to solve the optimization problem. The calculated optimal trajectory is finally evaluated using a line search method to ensure the convergence and to verify the optimization policy. The approach is demonstrated on a full scale automated truck prototype and the experimental results are discussed.

关键词： Optimization Trajectory Dynamic programming Predictive models Optimal control Vehicle dynamics Trajectory optimization

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Co-Saliency Detection Using Collaborative Feature Extraction And High-To-Low Feature Integration

Co-Saliency Detection Using Collaborative Feature Extraction...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Jingru Ren Zhi Liu Gongyang Li Xiaofei Zhou Cong Bai Guangling Sun Shanghai Institute for Advanced Communication and Data Science Shanghai University China Institute of Information and Control Hangzhou Dianzi University China College of Computer Science Zhejiang University of Technology China School of Communication and Information Engineering Shanghai University China

ISBN: (数字)9781728113319

ISBN: (纸本)9781728113326

Co-saliency detection, as a developing research branch of saliency detection, devotes to identify the common salient objects in a group of related images. The major challenge of co-saliency detection is how to effectively represent features considering both intra-image and inter-image information. In this paper, we propose a co-saliency detection model using collaborative feature extraction and high-to-low feature integration. We first feed the target image and its co-images into the Individual Feature Extraction Module (IFEM) to produce multi-level individual features. Then, to capture the collaborative inter-image information, the Collaborative Feature Extraction Module (CFEM) is applied to all highest-level individual features, generating the collaborative feature. Finally, we build a High-to-low Feature Integration Module (HFIM), which integrates the collaborative feature and multi-level individual features of the target image, to enrich the collaborative feature with individual intra-image information. Extensive experiments on two public datasets demonstrate that the proposed model achieves the state-of-the-art performance.

关键词： Feature extraction Collaboration Correlation Cats Computational modeling Task analysis Visualization

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Correction to: Utilizing social media and machine learning for personality and emotion recognition using PERS

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Neural Computing and Applications 2023年第10期36卷 5649-5649页

作者： Talaat, Fatma M. El-Gendy, Eman M. Saafan, Mahmoud M. Gamel, Samah A. Faculty of Artificial Intelligence Kafrelsheikh University Kafrelsheikh Egypt Faculty of Computer Science and Engineering New Mansoura University Gamasa Egypt Nile Higher Institute for Engineering and Technology Mansoura Egypt Computers and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura Egypt Electronics and Communication Engineering Department Faculty of Engineering Horus University Damietta Egypt

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Author Correction: Inferring time-varying generation time, serial interval, and incubation period distributions for COVID-19 ( doi 10.1038/s41467-022-35496-8, 13 dec 2022 )

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NATURE communicationS 2023年第1期14卷 1页

作者： Chen, Dongxuan Lau, Yiu-Chung Xu, Xiao-Ke Wang, Lin Du, Zhanwei Tsang, Tim K. Wu, Peng Lau, Eric H. Y. Wallinga, Jacco Cowling, Benjamin J. Ali, Sheikh Taslim WHO Collaborating Centre for Infectious Disease Epidemiology and Control School of Public Health Li Ka Shing Faculty of Medicine The University of Hong Kong Hong Kong Special Administrative Region China Laboratory of Data Discovery for Health Limited Hong Kong Science and Technology Park New Territories Hong Kong Special Administrative Region China College of Information and Communication Engineering Dalian Minzu University Dalian 116600 China Department of Genetics University of Cambridge Cambridge CB2 3EH UK Center for Infectious Disease Control National Institute for Public Health and the Environment (RIVM) Bilthoven The Netherlands Department of Biomedical Data Sciences Leiden University Medical Center Leiden The Netherlands

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Fault Detection and Correction in Omni Bundle Robot Using EKF

Fault Detection and Correction in Omni Bundle Robot Using EK...

引用

International Conference on Manufacturing, Advanced Computing, Renewable Energy and communication, MARC 2018

作者： Rana, Rohit Agarwal, Vijyant Gaur, Prerna Parthasarathy, Harish Instrumentation and Control Engineering Division Netaji Subhas Institute of Technology Sec-03 Dwarka110078 India Manufacturing Process and Automation Engineering Division Netaji Subhas Institute of Technology Sec-03 Dwarka110078 India Electronics and Communication Engineering Division Netaji Subhas Institute of Technology Sec-03 Dwarka110078 India

ISBN: (纸本)9789811367717

In this paper, the entire focus is on fault detection and correction using extended Kalman filter (EKF) on industrially used omni bundle robot. Here, the authors considered a problem where a robot does monotonous job and repetitively traverse the same trajectory every time. Due to wear and tear or any fluctuation in input signals, the robot may not track the desired trajectory. Faults may arise at various levels in robots, for example, in actuator, encoder, and dynamical parameters. Actuator fault detection using encoder sensor will be the main focus in this research paper. The dynamics of robotic arm link is modeled using a DC motor attached with the link, and the encoder attached with the motor will provide position feedback. The fault is detected using EKF state estimation, and the fault is corrected using a PID controller feedback into the motor input torque. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Extended Kalman filters

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