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Computer, control and Robotics (ICCCR), International Conference on

作者： Jian Han Jiahui Tong Cheng Tang Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

The following topics are dealt with: mobile robots; feature extraction; learning (artificial intelligence); motion control; neural nets; path planning; optimisation; object detection; fault diagnosis; design engineering.

ISBN: (数字)9781728190358

ISBN: (纸本)9781728190365

关键词： Strips Gray-scale Reconstruction algorithms Position measurement Image reconstruction Robots Next generation networking

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Size-invariance matters: rethinking metrics and losses for imbalanced multi-object salient object detection 24

Size-invariance matters: rethinking metrics and losses for i...

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Proceedings of the 41st International Conference on Machine Learning

作者： Feiran Li Qianqian Xu Shilong Bao Zhiyong Yang Runmin Cong Xiaochun Cao Qingming Huang Institute of Information Engineering Chinese Academy of Sciences Beijing China and School of Cyber Security University of Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Institute of Information Science Beijing Jiaotong University Beijing China and School of Control Science and Engineering Shandong University Jinan China and Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China School of Cyber Science and Tech. Shenzhen Campus Sun Yat-sen University School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China and Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China and Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China

This paper explores the size-invariance of evaluation metrics in Salient Object Detection (SOD), especially when multiple targets of diverse sizes co-exist in the same image. We observe that current metrics are size-sensitive, where larger objects are focused, and smaller ones tend to be ignored. We argue that the evaluation should be size-invariant because bias based on size is unjustified without additional semantic information. In pursuit of this, we propose a generic approach that evaluates each salient object separately and then combines the results, effectively alleviating the imbalance. We further develop an optimization framework tailored to this goal, achieving considerable improvements in detecting objects of different sizes. Theoretically, we provide evidence supporting the validity of our new metrics and present the generalization analysis of SOD. Extensive experiments demonstrate the effectiveness of our method. The code is available at https://***/Ferry-Li/SI-SOD.

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Unlocking the Secrets Behind Advanced Artificial Intelligence Language Models in Deidentifying Chinese-English Mixed Clinical Text: Development and Validation Study

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Journal of Medical Internet Research 2024年第1期26卷 e48443页

作者： Lee, You-Qian Chen, Ching-Tai Chen, Chien-Chang Lee, Chung-Hong Chen, Peitsz Wu, Chi-Shin Dai, Hong-Jie Dialogue System Technical Department Asustek Computer Inc Taipei Taiwan Intelligent System Laboratory Department of Electrical Engineering College of Electrical Engineering and Computer Science National Kaohsiung University of Science and Technology Kaohsiung Taiwan Department of Bioinformatics and Medical Engineering Asia University Taichung Taiwan Center for Precision Health Research Asia University Taichung Taiwan Electromagnetic Sensing Control and AI Computing System Laboratory Department of Electrical Engineering College of Electrical Engineering and Computer Science National Kaohsiung University of Science and Technology Kaohsiung Taiwan Knowledge Discovery and Data Mining Lab Department of Electrical Engineering College of Electrical Engineering and Computer Science National Kaohsiung University of Science and Technology Kaohsiung Taiwan Department of Chemical Engineering Feng Chia University Taichung Taiwan National Center for Geriatrics and Welfare Research National Health Research Institutes Zhunan Taiwan National Institute of Cancer Research National Health Research Institutes Tainan Taiwan School of Post-Baccalaureate Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Center for Big Data Research Kaohsiung Medical University Kaohsiung Taiwan

Background: The widespread use of electronic health records in the clinical and biomedical fields makes the removal of protected health information (PHI) essential to maintain privacy. However, a significant portion of information is recorded in unstructured textual forms, posing a challenge for deidentification. In multilingual countries, medical records could be written in a mixture of more than one language, referred to as code mixing. Most current clinical natural language processing techniques are designed for monolingual text, and there is a need to address the deidentification of code-mixed text. Objective: The aim of this study was to investigate the effectiveness and underlying mechanism of fine-tuned pretrained language models (PLMs) in identifying PHI in the code-mixed context. Additionally, we aimed to evaluate the potential of prompting large language models (LLMs) for recognizing PHI in a zero-shot manner. Methods: We compiled the first clinical code-mixed deidentification data set consisting of text written in Chinese and English. We explored the effectiveness of fine-tuned PLMs for recognizing PHI in code-mixed content, with a focus on whether PLMs exploit naming regularity and mention coverage to achieve superior performance, by probing the developed models’ outputs to examine their decision-making process. Furthermore, we investigated the potential of prompt-based in-context learning of LLMs for recognizing PHI in code-mixed text. Results: The developed methods were evaluated on a code-mixed deidentification corpus of 1700 discharge summaries. We observed that different PHI types had preferences in their occurrences within the different types of language-mixed sentences, and PLMs could effectively recognize PHI by exploiting the learned name regularity. However, the models may exhibit suboptimal results when regularity is weak or mentions contain unknown words that the representations cannot generate well. We also found that the availability of cod

关键词： ChatGPT code mixing deidentification electronic health record large language model pretrained language model

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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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Quick identification of ABC trilayer graphene at nanoscale resolution via a near-field optical route

材料展望（英文）

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材料展望（英文） 2023年第1期 148-156页

作者： Peiyue Shen Xianliang Zhou Jiajun Chen Aolin Deng Bosai Lyu Zhichun Zhang Shuo Lou Saiqun Ma Binbin Wei Zhiwen Shi Key Laboratory of Artificial Structures and Quantum Control(Ministry of Education) Shenyang National Laboratory for Materials ScienceSchool of Physics and AstronomyShanghai Jiao Tong UniversityShanghai 200240People's Republic of China Collaborative Innovation Center of Advanced Microstructures Nanjing UniversityNanjing 210093People's Republic of China Institute of System Engineering Beijing 100191People's Republic of China

ABC-stacked trilayer graphene has exhibited a variety of correlated phenomena owing to its relatively flat bands and gate-tunable ***,convenient methods are still lacking for identifying ABC graphene with nanometer-scale *** we demonstrate that the scanning near-field optical microscope working in ambient conditions can provide quick recognition of ABC trilayer graphene with no ambiguity and excellent resolution(～20 nm).The recognition is based on the difference in their near-field infrared(IR)responses between the ABA and ABC *** show that in most frequencies,the response of the ABC trilayer is weaker than the ABA ***,near the graphene phonon frequency(～1585 cm-1),ABC's response increases dramatically when gated and exhibits a narrow and sharp Fano-shape resonant line,whereas the ABA trilayer is largely ***,the IR contrast between ABC and ABA becomes reversed and can even be striking(ABC/ABA～3)near the graphene phonon *** observed near-field IR features can serve as a golden rule to quickly distinguish ABA and ABC trilayers with no ambiguity,which could largely advance the exploration of correlation physics in ABC-stacked trilayer graphene.

关键词： ABC trilayer graphene identification SNOM nanoscale Fano resonance

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Quantitative evaluation modeling of mobile Ad Hoc networkcommunication service availability under failure|

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International Journal of Modeling, Simulation, and Scientific Computing 2020年第6期11卷 250-267页

作者： Yanfang Fu Yichang Su Zan Wang Dengdeng Guo Fei Dai Lianjiong Zhong Jianing Wei Xi’an Technological University State and Provincial Joint Engineering Lab.of Advanced Network Monitoring and Control Xi’an 710021P.R.China Beijing Electromechanical Engineering Institute Beijing 100074 P.R.China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing 100074 P.R.China

The availability of network communication services is an important evaluation standard to measure the ability of the network to meet the user’s business *** current related research mostly focuses on the evaluation of network reliability,which cannot reflect the logical relationship between failure/maintenance and network performance *** Ad Hoc Network is a multi-hop,centerless and energy-constrained distributed *** to the dynamic change of communication environment and the instability of wireless link,Ad Hoc Network is facing great challenges in service avail*** this thesis,a fault-based quantitative evaluation model of traffic availability in Ad Hoc networks is *** studying the multi-state Markov fault model of communication networks and the performance analysis of delay index based on CSMA\CA protocol,the quantitative evaluation of traffic availability in Ad Hoc networks is *** the availability of tactical unit network under different typical network configuration conditions is analyzed through experiments.

关键词： Network reliability service availability fault model quantitative evaluation

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A Risk-Averse Just-In-Time Scheme for Learning-Based Operation of Microgrids With Coupled Electricity-Hydrogen-Ammonia Under Uncertainties

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IEEE Transactions on Sustainable Energy 2025年

作者： Li, Longyan Ning, Chao Pan, Guangsheng Zhang, Leiqi Gu, Wei Zhao, Liang Du, Wenli Shahidehpour, Mohammad Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China School of Electrical Engineering Southeast University Nanjing210096 China Zhejiang Key Laboratory of Distributed Generations and Microgrid Technology State Grid Zhejiang Electric Power Research Institute Hangzhou310014 China Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology China Department of Electrical and Computer Engineering Illinois Institute of Technology ChicagoIL60616 United States

This paper proposes a Risk-Averse Just-In-Time (RAJIT) operation scheme for Ammonia-Hydrogen-based Micro-Grids (AHMGs) to boost electricity-hydrogen-ammonia coupling under uncertainties. First, an off-grid AHMG model is developed, featuring a novel multi-mode ammonia synthesis process and a hydrogen-ammonia dual gas turbine with tunable feed-in ratios. Subsequently, a state-behavior mapping strategy linking hydrogen storage levels with the operation modes of ammonia synthesis is established to prevent cost-ineffective shutdowns. The proposed model substantially improves operational flexibility but results in a challenging nonlinear fractional program. Based upon this model, a data-driven RAJIT scheme is developed for the real-time rolling optimization of AHMGs. Unlike conventional one-size-fits-all schemes using one optimization method throughout, the data-driven RAJIT intelligently switches between cost-effective deterministic optimization and risk-averse online-learning distributionally robust optimization depending on actual risk profiles, thus capitalizing on the respective strengths of these two optimization methods. To facilitate the solution of the resulting nonlinear program, we develop an equivalent-reformulation-based solution methodology by leveraging a constraint-tightening technique. Numerical simulations demonstrate that the proposed scheme guarantees safety and yields an overall cost reduction up to 14.6% compared with several state-of-the-art methods. © 2025 IEEE.

关键词： Ammonia

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Co2 and H2o as Sweep Gases Elevated Carbon Stability and Decreased Phytotoxicity Of Biochars Produced from Sawdust and Pig Manure

SSRN

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SSRN 2023年

作者： Pan, Xin Wang, Xiao Liu, Liuqingqing Kuang, Shaoping Zheng, Hao College of Environment and Safety Engineering Qingdao University of Science and Technology Qingdao266042 China Marine Agriculture Research Center Tobacco Research Institute Chinese Academy of Agricultural Sciences Qingdao266101 China Institute of Coastal Environmental Pollution Control College of Environmental Science and Engineering Key Laboratory of Marine Environment and Ecology Ministry of Education Frontiers Science Center for Deep Ocean Multispheres and Earth System Ocean University of China Qingdao266100 China Sanya Oceanographic Institution Ocean University of China Sanya572000 China

As a crucial pyrolysis factor for biochar production, the mechanistically effect of different sweep gases on the inherent multi-level chemical structure of biochars is poorly understood, impeding the widespread use of biochars as sustainable carbon-negative materials. This study investigated the effect of CO2 and H2O as sweep gases relative to N2 on the physic-chemical properties of biochars derived from sawdust (SBC-N/C/H) and pig manure (PBC-N/C/H) at 300–700ºC. Meanwhile, carbon sequestration potential and potential environmental risks of SBC-N/C/H and PBC-N/C/H were comprehensively evaluated. Unlike N2, CO2 showed a superior effect on biochar (especially SBCs with more carbonaceous substances), decreased the oxygenated-functional groups content in SBC-C (4.6%–28.1%) relative to SBC-N (25.5%–37.4%) via cracking reaction. Besides, CO2 stimulated the formation of pore structure in biochar (surface area increased from 9.38 m2/g in SBC500-N to 15.0 m2/g in SBC500-C) by boudouard reaction. H2O exhibited a similar but less pronounced effect with CO2, leading to a lower H/C ratio in biochar by aggravated demethylation of methoxyl groups and facilitating a more developed pore structure with water-gas reaction. Both CO2 and H2O enhanced the carbon stability of biochar and carbon sequestration potential in SBC500-C (30.1%) and SBC500-H (28.7%) was higher than SBC500-N (25.6%). Moreover, CO2 and H2O exhibited excellent performance in mitigating phytotoxicity of biochars (especially for PBCs) to radish and cucumber seeds via the reduced release of polycyclic aromatic hydrocarbons and heavy metals. These results proposed an effective approach to improve long-term carbon sequestration and environmental safety of biochars. © 2023, The Authors. All rights reserved.

关键词： Carbon dioxide

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Dual Role of Pulmonary Surfactant Corona in Modulating Carbon Nanotube Toxicity and Benzo[A]Pyrene Bioaccessibility

SSRN

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SSRN 2023年

作者： Luo, Zhen Xu, Dongfang Xu, Yan Zhao, Jian Hu, Guoqing Yue, Tongtao Department of Engineering Mechanics State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou310027 China Institute of Coastal Environmental Pollution Control Key Laboratory of Marine Environment and Ecology Ministry of Education Frontiers Science Center for Deep Ocean Multispheres and Earth System Ocean University of China Qingdao266100 China College of Electronic Engineering and Automation Shandong University of Science and Technology Qingdao266590 China

Inhaled carbon nanotubes (CNTs) can deposit in the deep lung, where they interact with pulmonary surfactant (PS) to form coronas, potentially altering the fate and toxicity profile of CNTs. However, the presence of other contaminants in combination with CNTs may affect these interactions. In this study, we investigated the effects of coexisting contaminants, specifically benzo[a]pyrene (BaP), on the interaction between CNTs and PS. We used passive dosing and fluorescence-based techniques to demonstrate that PS increases the solubility of BaP pre-adsorbed on CNTs. Subsequently, molecular dynamics simulations were performed to gain insight into the intricate interactions between CNTs, BaP, and PS. Our results suggest that the PS corona plays a dual role in modulating the toxicity of CNTs. First, it mitigates toxicity by reducing the hydrophobicity and apparent aspect ratio of CNTs. Second, it exacerbates toxicity due to energetically dominant PS-BaP interactions, which increase the solubility and thus bioaccessibility of BaPs. Importantly, these interactions are strongly influenced by the size and aggregation state of the CNTs. Our findings highlight the need to consider the bioaccessibility of coexisting contaminants when assessing the inhalation toxicity of PS-modified CNTs. © 2023, The Authors. All rights reserved.

关键词： Toxicity

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S$^{\text{4}}$TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehicles

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2023年第2期9卷 3220-3231页

作者： Xiao Wang Ke Tang Xingyuan Dai Jintao Xu Quancheng Du Rui Ai Yuxiao Wang Weihao Gu Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education Anhui University Hefei China Haomo Technology Company Ltd. Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing 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 (S $^{\text{4}}$ TP) framework. Specifically, S $^{\text{4}}$ TP 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. S $^{\text{4}}$ TP employs an optimization-based approach for motion planning, utilizing the predicted HDVs' trajectories as input. With the integration of SADRF, S $^{\text{4}}$ TP 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 S $^{\text{4}}$ TP in terms of safety and rationality. S $^{\text{4}}$ TP 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%.

关键词： Trajectory Safety Vehicles Trajectory planning Autonomous vehicles Risk management Behavioral sciences

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