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17th Asian Conference on computer Vision, ACCV 2024

作者： Li, Siqi Chen, Xiaoxue Cheng, Haoyu Zhou, Guyue Zhao, Hao Tian, Guanzhong Ningbo innovation Center Zhejiang University Hangzhou China College of Control Science and Engineering Zhejiang University Hangzhou China Institute for AI Industry Research Tsinghua University Beijing China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9789819609628

Detecting the openable parts of articulated objects is crucial for downstream applications in intelligent robotics, such as pulling a drawer. This task poses a multitasking challenge due to the necessity of understanding object categories and motion. Most existing methods are either category-specific or trained on specific datasets, lacking generalization to unseen environments and objects. In this paper, we propose a Transformer-based Openable Part Detection (OPD) framework named Multi-feature Openable Part Detection (MOPD) that incorporates perceptual grouping and geometric priors, outperforming previous methods in performance. In the first stage of the framework, we introduce a perceptual grouping feature model that provides perceptual grouping feature priors for openable part detection, enhancing detection results through a cross-attention mechanism. In the second stage, a geometric understanding feature model offers geometric feature priors for predicting motion parameters. Compared to existing methods, our proposed approach shows better performance in both detection and motion parameter prediction. Codes and models are publicly available at https://***/lisiqi-zju/MOPD. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Intelligent robots

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A network-based bioinformatic analysis for identifying potential repurposable drugs for obesity avoiding hepatic steatosis side-effect

A network-based bioinformatic analysis for identifying poten...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Brunetti, Martina Fiscon, Giulia Costanzo, Alessia Di Arca, Marcello Paci, Paola Sapienza University of Rome Department of Experimental Medicine Rome Italy Sapienza University of Rome Institute for Systems Analysis and Computer Science "a. Ruberti" National Research Council of Rome Department of Computer Control and Management Engineering "a. Ruberti" Rome Italy Sapienza University of Rome Policlinico Umberto I Department of Translational and Precision Medicine Rome Italy Sapienza University of Rome Department of Computer Control and Management Engineering "a. Ruberti" Rome Italy Karolinska Institutet Stockholm Sweden

ISBN: (纸本)9798350386226

Obesity is a complex multifactorial disorder characterized by the excess accumulation of body fat that impairs human health due to the risk of developing other diseases, including cardiovascular and hepatic diseases, hypertension, diabetes, hyperlipidemia. Its spread has been progressively accelerating, resulting in an unprecedented epidemic with no significant signs of slowing down any time soon. Drug therapy via the proposal repurposing solutions can represent an actionable treatment strategy, even if the emergence of drug-induced adverse effects can affect the treatment of this pathology. In this study, we propose a network-based analysis to identify a list of drug candidates predicted to be repurposable for obesity that are unlikely to produce specific adverse side-effect, such as hepatic steatosis. © 2024 IEEE.

关键词： Nutrition

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Differential gene correlation analysis to investigate evolutionary divergence between Cardamine hirsuta and Arabidopsis thaliana

Differential gene correlation analysis to investigate evolut...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： D'Annunzio, Federica Fiscon, Giulia Bertolotti, Gaia Dello Ioio, Raffaele Paci, Paola Sapienza University of Rome Department of Translational and Precision Medicine Rome Italy Sapienza University of Rome Institute for Systems Analysis and Computer Science 'A. Ruberti' National Research Council of Rome Department of Computer Control and Management Engineering 'A. Ruberti' Rome Italy Sapienza University of Rome Department of Biology and Biotechnology 'Charles Darwin' Rome Italy Department of Computer Control and Management Engineering 'A. Ruberti' Sapienza University of Rome Rome Italy Karolinska Institutet Stockholm Sweden

ISBN: (纸本)9798350386226

Dissecting the intricate regulatory dynamics between genes stands as a critical step towards the development of precise predictive models within biological systems. A highly effective strategy in this pursuit involves an examination of variations in correlation among gene pairs across different conditions trough differential gene correlation analysis. We anticipated that the application of this method to phylogenetically close plant species could reveal powerful insights on how genes' relationships have a fundamental role in evolutionary dynamics. Building upon this principle, our investigation focused primarily on conducting a comprehensive differential correlation analysis of the roots' orthologous genes of two closely related plant species: Cardamine hirsuta and Arabidopsis thaliana. By leveraging their shared phylogenetic proximity, we were able to draw comparisons that shed light on how evolutionary pressures might have shaped their gene regulatory networks. By integrating differential expression analysis, differential correlation analysis and functional enrichment analysis, we offer a robust framework for future studies aiming to unravel the complexities of adaptation and evolution across a wide range of biological systems. © 2024 IEEE.

关键词： Plant diseases

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Towards a real-time control of robotic ultrasound using haptic force feedback

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Current Directions in Biomedical engineering 2022年第1期8卷 81-84页

作者： Schreiter, J. Semshchikov, V. Hanses, M. Elkmann, N. Hansen, C. University of Magdeburg Faculty of Computer Science & Research Campus Stimulate Magdeburg Germany University of Magdeburg Faculty of Electrical Engineering and Information Technology Magdeburg Germany Fraunhofer Institute for Factory Operation and Automation Iff Magdeburg Germany

Ultrasound is a widely used imaging technique and is appreciated for its non-invasiveness, absence of radiation, widespread availability, and compact equipment. Ergonomic difficulties in manual handling of the probe could be enhanced by a robotic controlled ultrasound. The paper addresses the development of such a system which enables remote operation of a ultrasound probe and includes haptic force feedback as well as video conferencing components for visual feedback. The development process followed a user-centered approach by investigating needs of potential end-users. Preliminary results demonstrated the functionality of the developed system for generating medical image data under laboratory conditions. © 2022 by Walter de Gruyter Berlin/Boston.

关键词： Probes

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Multi-objective Optimization of the Interior Permanent Magnet Synchronous Motor for Electric Vehicles

Multi-objective Optimization of the Interior Permanent Magne...

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China International Electrical and Energy Conference (CIEEC)

作者： Changchuang Huang Baoqaun Kou Xiaokun Zhao Electrical Engineering and Automation Harbin Institute of Technology Heilongjiang China Computer and Control Engineering Northeast Forestry University Heilongjiang China

Permanent magnet synchronous motors (PMSMs) are widely used in various fields due to their high efficiency, high power factor and small volume. In this paper, a segmented permanent magnet interior permanent magnet synchronous motor (IPMSM) is proposed and optimized. First, the topology of the IPMSM is introduced. Second, multi-objective optimization is performed by non-dominated sorting genetic algorithm-II (NSGA-II) using rotor structure parameters as optimization variables, saliency ratio as constraint, electromagnetic torque and constant-power speed range as objective functions. Then, the electromagnetic characteristics of the initial IPMSM and the optimized IPMSM are analyzed and compared. The results show that the torque and constant-power speed range of the optimized motor are improved, which verifies the validity of the optimization method. The proposed motor is suitable for electric vehicles, which require large torque at low speeds and wide constant-power speed range at high speeds.

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automation 5.0: The Key to Systems Intelligence and Industry 5.0

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1723-1727页

作者： Ljubo Vlacic Hailong Huang Mariagrazia Dotoli Yutong Wang Petros A.Ioannou Lili Fan Xingxia Wang Raffaele Carli Chen Lv Lingxi Li Xiaoxiang Na Qing-Long Han Fei-Yue Wang Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith UniversityNathanQLD 4111Australia Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190and also with the Qingdao Academy of Intelligent IndustriesQingdao 266114China Department of Electrical Engineering-Systems University of Southern CaliforniaLos AngelesCA 90007 USA School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 Beijing Huairou Academy of Parallel Sensing Beijing 101499China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University IndianapolisIndianapolisIN 46202 USA Department of Engineering University of CambridgeCB21TN CambridgeU.K. School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Dazhou Artificial Intelligence Institute Dazhouand the Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

automation has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with *** rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:***,***,***,***,***,***,***,***,***,***,***,Q.-***,and F.-***,“automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA ***,vol.11,no.8,pp.1723-1727,Aug.2024.

关键词： automation machinery intelligence

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High-Entropy Oxide of (BiZrMoWCeLa)O2 as a Novel Catalyst for Vanadium Redox Flow Batteries

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ACS Applied Materials and Interfaces 2024年第8期16卷 10019-10032页

作者： Demeku, Aknachew Mebreku Kabtamu, Daniel Manaye Chen, Guan-Cheng Ou, Yun-Ting Huang, Zih-Jhong Hsu, Ning-Yih Ku, Hung-Hsien Wang, Yao-Ming Wang, Chen-Hao Department of Materials Science and Engineering National Taiwan University of Science and Technology Taipei106335 Taiwan Department of Chemistry Debre Berhan University Debre Berhan000000 Ethiopia Chemistry Division National Atomic Research Institute Taoyuan325207 Taiwan Maritime Innovation & Industry Promotion Department Metal Industries Research & Development Centre Kaohsiung811160 Taiwan Research Center National Cheng Kung University Tainan701401 Taiwan Center of Automation and Control National Taiwan University of Science and Technology Taipei106335 Taiwan

In this study, new fluorite high-entropy oxide (HEO), (BiZrMoWCeLa)O2, nanoparticles were produced using a surfactant-assisted hydrothermal technique followed by calcination and were used as novel catalytic materials for vanadium redox flow batteries (VRFBs). The HEO calcined at 750 °C (HEO-750) demonstrates superior electrocatalytic activity toward V3+/V2+ and VO2+/VO2+ redox couples compared to those of cells assembled with other samples. The charge-discharge tests further confirm that VRFBs using the HEO-750 catalyst demonstrate excellent Coulombic efficiency, voltage efficiency, and energy efficiency of 97.22, 87.47, and 85.04% at a current density of 80 mA cm-2 and 98.10, 74.76, and 73.34% at a higher current density of 160 mA cm-2, respectively. Moreover, with 500 charge-discharge cycles, there is no discernible degradation. These results are attributed to the calcination heat treatment, which induces the formation of a new single-phase fluorite structure, which facilitates the redox reactions of the vanadium redox couples. Furthermore, a high surface area, wettability, and plenty of oxygen vacancies can give more surface electroactive sites, improving the electrochemical performance, the charge transfer of the redox processes, and the stability of the VRFBs’ electrode. This is the first report on the development of fluorite structure HEO nanoparticles in VRFBs, and it opens the door to further research into other HEOs. © 2024 The Authors. Published by American Chemical Society.

关键词： Entropy

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research on Identification and Refactoring Approach of Event-driven Architecture Based on Ontology 34

Research on Identification and Refactoring Approach of Event...

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34th International Conference on Software engineering and Knowledge engineering, SEKE 2022

作者： Wang, Li Kong, Xiang-Long Wang, Xiao-Fei Li, Bi-Xin School of Computer Science and Engineering Southeast University Nanjing China Jiangsu Automation Research Institute Lianyungang China NARI Group Corporation Nanjing China

ISBN: (纸本)1891706543

Event-driven architecture is one of the common software architecture patterns. In the process of software evolution, the deviation and corrosion often occur to architecture, which leads to larger deviation between actual software architecture and design architecture. Therefore, it is of great significance to study the approach of software architecture identification and refactoring. To solve this problem, we propose an identification and refactoring approach of event-driven based on ontology, i.e., IRABO. We evaluated IRABO on 50 open-source projects and the results show that it performs effectively and efficiently. © 2022 Knowledge Systems institute Graduate School. All rights reserved.

关键词： Software architecture

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Experimental Implementation of Single-shot Joint Parity Measurement for Quantum State Tomography of Phonon Modes of a Trapped Ion

Experimental Implementation of Single-shot Joint Parity Meas...

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2024 Conference on Lasers and Electro-Optics/Pacific Rim, CLEO-PR 2024

作者： Jeon, Honggi Kang, Jiyong Kim, Jaeun Choi, Wonhyeong Kim, Kyunghye You, Jaehun Kim, Taehyun Department of Computer Science and Engineering Seoul National University Seoul08826 Korea Republic of Automation and System Research Institute Seoul National University Seoul08826 Korea Republic of Inter-university Semiconductor Research Center Seoul National University Seoul08826 Korea Republic of Institute of Computer Technology Seoul National University Seoul08826 Korea Republic of Institute of Applied Physics Seoul National University Seoul08826 Korea Republic of

We implemented a single-shot joint parity measurement of two motional modes using spin dependent beam splitter interaction. The joint Wigner function of a two-mode entangled coherent state is then measured. © 202... 详细信息

关键词： Trapped ions

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Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced control Applications

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 18-36页

作者： Ding Wang Ning Gao Derong Liu Jinna Li Frank L.Lewis IEEE the Faculty of Information Technology Beijing Key Laboratory of Computational Intelligence and Intelligent SystemBeijing Laboratory of Smart Environmental Protectionand Beijing Institute of Artificial IntelligenceBeijing University of TechnologyBeijing 100124China the School of System Design and Intelligent Manufacturing Southern University of Science and TechnologyShenzhen 518055China the Department of Electrical and Computer Engineering University of Illinois at ChicagoChicago IL 60607 USA the School of Information and Control Engineering Liaoning Petrochemical UniversityFushun 113001China the UTA Research Institute the University of Texas at ArlingtonArlington TX 76118 USA

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, ***, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation ***, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

关键词： Adaptive dynamic programming(ADP) advanced control complex environment data-driven control event-triggered design intelligent control neural networks nonlinear systems optimal control reinforcement learning(RL)

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