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Society 5.0: Metaverse Facilitated Human-centric “5H” Services Across Cyber-Physical-Social Spaces

IFAC-PapersOnLine 2024年第3期58卷 159-164页

作者： Xiao Wang Jun Huang QingHua Ni Zhe Wan HuaDan Xue Larry Stapleton Fei-Yue Wang Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education Anhui University Hefei 230601 China Macau University of Science and Technology Macau 999078 China Beijing Normal University Beijing 100875 China Department of Radiology Peking Union Medical College Hospital Shuaifuyuan Beijing 100730 Dongcheng District China Brownsbarn Thomastown Co. Kilkenny Ireland R95D8P2 Qingdao Academy of Intelligent Industries Qingdao 266109 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

Cyber-Physical-Social systems bridge the gap between social resource organization and distribution, and give birth to Society 5.0, which represents a transformative vision aimed at realizing the human-centric paradigm for more efficient and effective sustainable development. In this paper, we discuss the decentralized paradigm in fostering human needs-driven smart services, in line with Maslow’s hierarchy of needs theory. Societies 5.0 is committed to optimizing the use of natural, artificial, and social resources by enhancing democratic participation and ensuring that decision-making processes are more transparent, reliable, and aligned with the needs of the populace in sustainable ways. Moreover, our discussion extends to how Society 5.0’s principles correlate with the United Nations Sustainable Development Goals (SDGs), providing a framework that supports health, education, and poverty reduction, among other targets. This approach also aligns with the Human Development Index (HDI), reinforcing the notion that technological progress in Society 5.0 does not overshadow but rather complements and enhances human values, paving a synergistic path towards sustainable development that is both advanced and fundamentally human-centric.

关键词： Cyber-Physical-Social systems Society 5.0 Human-Centric Services Socio-technical synergistic sustainable development

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Zero-shot Learning Based on Semantic Embedding for Ship Detection

Zero-shot Learning Based on Semantic Embedding for Ship Dete...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Zihan Zhang Jiajia Zhoa Xinkai Liang School of Electronics and Information Northwestern Polytechnical University Xi’an Shaanxi China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Bejing China

ISBN: (数字)9781728180250

ISBN: (纸本)9781728180267

Zero-shot detection (ZSD) is a hot topic, which can detect unseen object without training on it. This new approach rises several challenges, e.g., the imbalance between positive and negative data, ambiguity between background and unseen classes, and how to align visual feature and semantic concept. In this paper, we apply an end-to-end zero-shot network to fulfil ZSD, where polarity loss is utilized to train detection model. polarity loss puts more importance on difficult data to reduce class imbalance and can maximize the difference between positive and negative predictions. Then, we use a semantic embedding method that use word vectors in both classification and regression subnets to better align visual features and semantic features. Finally, we use MS-COCO dataset as seen classes to train detection model, then we transfer the model for our own to detect warship object. Our model performs good on unseen classes and test accuracy of using polarity loss is apparently higher than that of using focal loss.

关键词： Semantics Visualization Vocabulary Training Feature extraction Object detection Measurement

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Task-irrelevant Auditory Event-related Potentials as Mental Workload Indicators: A Between-task Comparison Study*

Task-irrelevant Auditory Event-related Potentials as Mental ...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Jinzhao Xu Yufeng Ke Shuang Liu Xizi Song Cheng Xu Guchuan Zhou Dong Ming Academy of Medical Engineering and Translational Medicine Tianjin University Tianjin China Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing China

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

Real-time monitoring of mental workload (MWL) is a crucial step to build closed-loop adaptive aiding systems for human-machine systems. MWL estimators based on spontaneous electroencephalography (EEG) and event-related potentials (ERPs) have shown great potentials to achieve this goal. However, the previous studies show that the between-task robustness of these EEG/ERP-based MWL estimators is still an unsolved intractable question. This study attempts to examine the task-irrelevant auditory event-related potentials (tir-aERPs) as MWL indicators. A working memory task (verbal n-back) and a visuo-motor task (multi-attribute task battery, MATB), both with two difficulty levels (easy and hard), were used in the experiment, along with task-irrelevant auditory probes that did not need any response from the participants. EEG was recorded from ten participants when they were performing the tasks. The tir-aERPs elicited by the auditory probes were extracted and analyzed. The results show that the amplitudes of N1, early P3a (eP3a) and the late reorienting negativity (RON) significantly decreased with the increasing MWL in both n-back and MATB. Task type has no obvious influence on the amplitudes and topological layout of the MWL-sensitive tir-aERPs features. These results suggest that the tir-aERPs are potentially more constant MWL indicators across very different task types. Therefore, the tir-aERPs should be taken into consideration in future task-independent MWL monitoring studies.

关键词： Task analysis Electroencephalography Monitoring Electric potential Probes Resource management Feature extraction

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Prediction of exosomal piRNAs based on deep learning for sequence embedding with attention mechanism

Prediction of exosomal piRNAs based on deep learning for seq...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yajun Liu Yulian Ding Aimin Li Rong Fei Xie Guo Fangxiang Wu Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an University of Technology Xi'an China Division of Biomedical Engineering University of Saskatchewan Saskatoon Canada Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China Department of Computer Science Department of Mechanical Engineering Division of Biomedical Engineering University of Saskatchewan Saskatoon Canada

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

PIWI-interacting RNAs (piRNAs) are a type of small non-coding RNAs which bind with the PIWI proteins to exert biological effects in various regulatory mechanisms. A growing amount of evidence reveals that exosomal piRNAs are potential biomarkers for diagnosis and treatment of complex diseases. Effective methods for the prediction of exosomal piRNAs are the foundation of piRNA functional research. In this study, we propose an end-to-end deep network for identifying exosomal piRNAs based on features learned from natural language processing (NLP) models for sequence embedding with attention mechanism. First, a benchmark dataset is constructed by processing piRNA subcellular localization annotated data and sequence data. Moreover, bagging positive unlabeled learning is applied to get the reliable negative set. Finally, we treat a piRNA sequence as a sentence and its k-mer subsequence as a token. Sequence embedding models with self-attention mechanism is designed to extract features from exosome piRNA sequences, which are used for the prediction task. Compared with three competing methods, our model achieves the best performance and reveals the key factors of exosomal piRNA sequences by the attention mechanism. Our model characterizes exosomal piRNAs and could be beneficial for researchers to investigate exosomal piRNAs’ functions.

关键词： Proteins Location awareness RNA Biological system modeling Predictive models Feature extraction Natural language processing

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S4TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehicles

arXiv

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arXiv 2024年

作者： Wang, Xiao Tang, Ke Dai, Xingyuan Xu, Jintao Du, Quancheng Ai, Rui Wang, Yuxiao Gu, Weihao Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education Anhui University Hefei230031 China Haomo Technology Co. Ltd. Beijing100192 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Qingdao Academy of Intelligent Industries Qingdao266114 China The School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China

In public roads, autonomous vehicles (AVs) face the challenge of frequent interactions with human-driven vehicles (HDVs), which render uncertain driving behavior due to varying social characteristics among humans. To effectively assess the risks prevailing in the vicinity of AVs in social interactive traffic scenarios and achieve safe autonomous driving, this article proposes a social-suitable and safety-sensitive trajectory planning (S4TP) framework. Specifically, S4TP integrates the Social-Aware Trajectory Prediction (SATP) and Social-Aware Driving Risk Field (SADRF) modules. SATP utilizes Transformers to effectively encode the driving scene and incorporates an AV’s planned trajectory during the prediction decoding process. SADRF assesses the expected surrounding risk degrees during AVs-HDVs interactions, each with different social characteristics, visualized as two-dimensional heat maps centered on the AV. SADRF models the driving intentions of the surrounding HDVs and predicts trajectories based on the representation of vehicular interactions. S4TP employs an optimization-based approach for motion planning, utilizing the predicted HDVs’ trajectories as input. With the integration of SADRF, S4TP executes real-time online optimization of the planned trajectory of AV within low-risk regions, thus improving the safety and the interpretability of the planned trajectory. We have conducted comprehensive tests of the proposed method using the SMARTS simulator. Experimental results in complex social scenarios, such as unprotected left-turn intersections, merging, cruising, and overtaking, validate the superiority of our proposed S4TP in terms of safety and rationality. S4TP achieves a pass rate of 100% across all scenarios, surpassing the current state-of-the-art methods Fanta of 98.25% and Predictive-Decision of 94.75%. Copyright © 2024, The Authors. All rights reserved.

关键词： Autonomous vehicles

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Suppression of Actuator Nonlinearities Based on the Cascade Active Disturbance Rejection Approach

Suppression of Actuator Nonlinearities Based on the Cascade ...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Mingjun, Wei Cheng, Xu Wanhai, Hu Hua, Ji Feng, Gao Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Aviation Institute of Technology of CASIC Beijing China

ISBN: (纸本)9781728137926

In this paper, influences of actuator nonlinearities and their suppression methods are studied. Firstly, the influences of the dead zone and backlash characteristics of the actuator on the control performance of statically unstable missiles are analyzed in detail. Then based on the cascade control method and the active disturbance rejection control (ADRC) theory, a nonlinear "double-layer compensation" suppression method for the actuator nonlinearities is proposed. Finally, the simulation verification is carried out. Simulation results show that the "double-layer compensation" suppression method based on the cascade ADRC approach can significantly suppress the adverse effects such as system self-sustaining oscillation caused by actuator nonlinearities, and effectively improve the control performance of the statically unstable missile. © 2019 IEEE.

关键词： Disturbance rejection

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Generating infrared image from visible image using Generative Adversarial Networks

Generating infrared image from visible image using Generativ...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： An, Lei Zhao, Jiajia Di, Huijun Beijing Institute of Technology School of Computer Science and Technology Beijing China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Coorperation Laboratory Beijing China

ISBN: (纸本)9781728137926

Infrared images have properties that are unaffected by illumination compared to visible images, object can be clearly recognized at day or night. Therefore, it is a better choice to use infrared images when training deep learning algorithms in unmanned systems. However, how to obtain a large number of infrared images makes it possible to train deep learning algorithm, which is the focus of our attention. In contrast to difficulties in direct shooting, computer simulations can generate large infrared images from visible images. But models that are trained on simulated data usually do not translate well to real scenarios. To bridge the domain gap between simulated and real infrared images, we exploit recent advances in paired image-to-image translation. We extend Pixel2Pixel to generate infrared image from visible image and propose a novel way of multilayer semantic information fusion, which significantly improves the quality of generated images. Finally, the image generated by our proposed PixelPro network is almost consistent with the real image distribution, achieved the purpose of expanding the dataset. © 2019 IEEE.

关键词： Generative adversarial networks

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An initial alignment approach for improving the accuracy of azimuth setting

An initial alignment approach for improving the accuracy of ...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Guan, Xujun Wang, Xing Guo, Jianzhong Fu, Wenxing Meng, Lingbao Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China China Aerospace Science and Industry Corporation Beijing China

ISBN: (纸本)9781728137926

Considering the azimuth discrepancy between the main and sub-inertial navigation systems (INS) for a platform-carried unmanned aerial vehicles(UAV) in case of tilted launching at a large pitch angle, an initial alignment method for improving the accuracy of the azimuth setting is proposed. First, an algorithm for computing the azimuth discrepancy is derived. Then, a mathematical model for initial alignment is established based on azimuth setting. The simulation results show that correcting the azimuth discrepancy between the main and sub-INS can greatly improve the accuracy of azimuth setting, and therefore the initial alignment accuracy of the sub-INS. Meanwhile, the drift for the gyros in three directions can be effectively estimated. © 2019 IEEE.

关键词： Inertial navigation systems

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Point Cloud Preprocessing on 3D LiDAR data for Unmanned Surface Vehicle in Marine Environment

Point Cloud Preprocessing on 3D LiDAR data for Unmanned Surf...

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Information technology,Big Data and Artificial Intelligence (ICIBA), International Conference on IEEE International Conference on

作者： Xianzhi Qi Wenxing Fu Pei An Bingli Wu Jie Ma National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9781728152240

ISBN: (纸本)9781728152257

Point cloud preprocessing is still a challenging task in the marine environment, for it is difficult to filter out non-obstacle points while avoiding damage to the obstacle completeness. In this paper, we propose a novel data preprocessing method on 3D LiDAR data for the unmanned surface vehicle in the marine environment. It consists of two tasks: outlier removal and wake filtering. As the spatial resolution of LiDAR changes with distance, we exploit distance normalization on statistical outlier filter for robust outlier removal. Considering the gradient difference between wave wake and obstacle surface near the water, we define and calculate the vertical state of point cloud on the range image to obtain the pre-filtering point set, and then use the RANSAC method to filter out the wake points. Experiments on real data has demonstrated the effectiveness of the proposed algorithm both in terms of feasibility and accuracy.

关键词： Three-dimensional displays Laser radar Filtering Filtering algorithms Spatial resolution Task analysis Measurement by laser beam

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Applications of MXenes in human-like sensors and actuators

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Nano Research 2023年第4期16卷 5767-5795页

作者： Jinbo Pang Songang Peng Chongyang Hou Xiao Wang Ting Wang Yu Cao Weijia Zhou Ding Sun Kai Wang Mark H.Rümmeli Gianaurelio Cuniberti Hong Liu Institute for Advanced Interdisciplinary Research(iAIR) Collaborative Innovation Center of Technology and Equipment for Biological Diagnosis and Therapy in Universities of ShandongUniversity of JinanJinan 250022China Institute for Materials Science and Max Bergmann Center of Biomaterials Technische Universität DresdenDresden 01069Germany Center for Advancing Electronics Dresden Technische Universität DresdenDresden 01069Germany Dresden Center for Computational Materials Science Technische Universität DresdenDresden 01062Germany Dresden Center for Intelligent Materials(GCL DCIM) Technische Universität DresdenDresden 01062Germany High-Frequency High-Voltage Device and Integrated Circuits R&D Center Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China Key Laboratory of Microelectronic Devices&Integrated Technology Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China Shenzhen Key Laboratory of Nanobiomechanics Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China State Key Laboratory of Biobased Material and Green Papermaking Qilu University of TechnologyShandong Academy of SciencesJinan 250353China School of Bioengineering Qilu University of TechnologyShandong Academy of ScienceJinan 250353China Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology(Ministry of Education) Northeast Electric Power UniversityJilin 132012China School of Electrical Engineering Northeast Electric Power UniversityJilin 132012China School of Electrical Engineering Weihai Innovation Research InstituteQingdao UniversityQingdao 266000China School of Electrical and Computer Engineering Jilin Jianzhu UniversityChangchun 130118China Institute for Complex Materials Leibniz Institute for Solid State and Materials Research Dresden(IFW Dresden)20 Helmholtz StrasseDresden 01069Germany College of Energy Soochow Institute for Energy and Materials Innovations Soochow UniversitySuzhou 215006China Key L

Human beings perceive the world through the senses of sight,hearing,smell,taste,touch,space,and *** first five senses are prerequisites for people to *** sensing organs upload information to the nervous systems,including the brain,for interpreting the surrounding ***,the brain sends commands to muscles reflexively to react to stimuli,including light,gas,chemicals,sound,and ***,as an emerging two-dimensional material,has been intensively adopted in the applications of various sensors and *** this review,we update the sensors to mimic five primary senses and actuators for stimulating muscles,which employ MXene-based film,membrane,and composite with other functional ***,a brief introduction is delivered for the structure,properties,and synthesis methods of ***,we feed the readers the recent reports on the MXene-derived image sensors as artificial retinas,gas sensors,chemical biosensors,acoustic devices,and tactile sensors for electronic ***,the actuators of MXene-based composite are ***,future opportunities are given to MXene research based on the requirements of artificial intelligence and humanoid robot,which may induce prospects in accompanying healthcare and biomedical engineering applications.

关键词： MXenes sensors actuators gas sensors biosensors tactile sensors sound sensors artificial retina

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