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12th International Symposium on Project Management, ISPM 2024

作者： Chen, Shan Fang, Meiqi Wang, Linlin Su, Jiafu Chongqing Industrial Big Data Innovation Center Co. Ltd. Chongqing China National Research Base of Intelligent Manufacturing Service Chongqing Technology and Business University Chongqing China School of Management Science and Engineering Chongqing Technology and Business University Chongqing China Western Branch of China Academy of Information and Communications Technology Chongqing China International College Krirk University Bangkok Thailand

ISBN: (纸本)9798331302344

In order to examine the impact of the withdrawal of government green subsidies on the green market, this paper formulates a two-period model to examine a green supply chain composed of a government and two manufacturers. We construct a basic model of government green subsidies in the first period, and formulate four scenarios in the second period considering the market expansion effect, green preference effect, price reference effect, and quality reference effect. We examine the impacts of the above effects on equilibrium decision-making and profits of the green supply chain through comparing and numerical analysis. We find that: 1) Only the market size enlarges to a certain degree, the profit of green manufacturer would increase after subsidy withdrawal. 2) Both green and traditional manufacturers can benefit from the consumers’ green preference, but it will hinder some traditional manufacturers from investing in green production. 3) The consumer price reference effect will damage green manufacturers' profits and reduce the greenness of products, while the traditional manufacturer could benefit from it under certain conditions. 4) Appropriate consumer green quality preferences are beneficial to the green market and can increase the profits of green manufacturers, but they will also provide free-riding opportunities for traditional manufacturers. © 2024 ISPM. All Rights Reserved.

关键词： Green manufacturing

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Lower Limb Muscle State Transition Control Based on Complex Network

Lower Limb Muscle State Transition Control Based on Complex ...

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第42届中国控制会议

作者： Junjie Geng Lingling Chen Xin Guo Rui Chen Mengge Wang School of Artificial Intelligence and Data Science Hebei University of Technology Control Engineering Technology Innovation Center of Hebei Province Hebei University of Technology School of Electrical Engineering Hebei University of Technology

Muscle activation cannot achieve the activation state experienced during normal activity throughout the rehabilitation process,and effectiveness of rehabilitation will be enhanced if the muscle state can be controlled from the "zero EMG" state to the normal motion *** is challenging to precisely regulate the muscle state during the model establishment process because the lower limb muscle group is a highly interconnected complicated ***,this study provides a muscle state transfer control method based on complex network control theory.A linear time-invariant functional myoelectric network model is modeled,and the structural controllability of the network is demonstrated using the PBH rank criterion to determine the optimal set of control *** Electrical Stimulation is used as an exogenous input to drive state transfer between *** results suggest that the method we propose is effective in controlling muscle state transitions.

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Optimization of Fracture Reduction Robot Controller

Optimization of Fracture Reduction Robot Controller

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International Symposium on Computer science and Intelligent Controls (ISCSIC)

作者： Baichuan An Jianwen Chen Minghe Liu Minghuan Yin Zicheng Song Chao Zhuang Cheng Chang Hao Sun School of Artificial Intelligence and Data Science Hebei University of Technology Tianjin China Limb Deformity Correction and Function Reconstruction Department Southern University of Science and Technology Hospital Shenzhen China School of Artificial Intelligence and Data Science Engineering Research Center of Intelligent Rehabilitation Device and Detection Technology Ministry of Education Control Engineering Technology Innovation Center of Hebei Province Hebei University of Technology Tianjin China

ISBN: (数字)9798350380286

ISBN: (纸本)9798350380293

To improve the accuracy of fracture reduction, combining inverse kinematic analysis with robot dynamics modelling might lead to a more effective controller for the fracture reduction process. The trajectory of the actuator driving rod’s motion and any deviations from it are calculated using Simulink simulation. The Levy-SSA-optimized fracture reduction robot’s positioning inaccuracy is two orders of magnitude lower than the PID adjustment approach. Using this method also improves the reduction trajectory’s accuracy and speeds up the convergence of the fracture-resetting robot control system to the ideal solution.

关键词： Actuators Accuracy Torque Software packages Robot control Process control Muscles Reliability engineering Trajectory Optimization

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An overview on the designs of distributed observers in LTI multi-agent systems

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science China(Technological sciences) 2021年第11期64卷 2337-2346页

作者： PEI YingQing GU HaiBo LIU KeXin LU JinHu Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain ComputingBeihang UniversityBeijing 100191China

With the rapid development of information technologies and cloud computing, sensor networks play an increasingly important role in our society. Over the past few decades, distributed observer theory has attracted unprecedented attention due to its wide potential applications in different areas. Meanwhile, various approaches and algorithms have been proposed and investigated. The design of distributed observers is one of the frontier topics of system and control research, which has the significant theoretical values and broad application prospects. This paper attempts to review the representative models and the corresponding approaches for distributed observer design in linear time-invariant(LTI) systems. Firstly, the research backgrounds and main advances of distributed observer designs are briefly reviewed. Then, recent results of distributed observer designs for discrete-time and continuous-time LTI multi-agent systems(MASs) are introduced in detail, respectively. Finally, the prospects and the future work directions of the design of distributed observers are put forward. The main purpose of this paper is to promote the emerging topic on the designs of distributed observers, with focuses on the interdisciplinary interest from technological sciences.

关键词： multi-agent system linear time-invarient system distributed observer consensus

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An improved multi-objective whale optimization algorithm to solve weapon-target assignment problems 2

An improved multi-objective whale optimization algorithm to ...

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2nd International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2022

作者： She, Wei Wang, Yeteng Liu, Wei Tian, Zhao Zhong, Lihong School of Cyber Science and Engineering Zhengzhou University Zhengzhou450000 China Zhengzhou Key Laboratory of Blockchain and Data Intelligence Zhengzhou450000 China Henan Collaborative Innovation Center for Internet Medical and Health Services Zhengzhou University Zhengzhou450000 China

ISBN: (纸本)9781510660571

In the process of traditional weapon-target assignment, there are two critical issues that have not been well-studied: (1) the waste of firepower resources and (2) the lack of description of the relationship between targets. Towards this end, we propose an improved weapon-target assignment model, which combines the damage probability, the weapon resource consumption and the relationship coefficient between the targets. On this basic, we design a multi-objective whale optimization algorithm based on grid division (GDMOWOA). Specifically, the algorithm uses the grid partitioning method to sort the population non-dominated, selects the optimal individual by calculating the grid number and density, and introduces an external Pareto archive to maintain the population diversity. Simulation experiments are conducted to verify the rationality and effectiveness of our solution. The results show that our algorithm has better effectiveness and superiority compared with other classical algorithms, and can effectively solve the problem of weapon-target assignment. © 2022 SPIE.

关键词： Combinatorial optimization

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Does graph distillation see like vision dataset counterpart? 23

Does graph distillation see like vision dataset counterpart?

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Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Beining Yang Kai Wang Qingyun Sun Cheng Ji Xingcheng Fu Hao Tang Yang You Jianxin Li School of Computer Science and Engineering Beihang University and Advanced Innovation Center for Big Data and Brain Computing Beihang University National University of Singapore Carnegie Mellon University

Training on large-scale graphs has achieved remarkable results in graph representation learning, but its cost and storage have attracted increasing concerns. Existing graph condensation methods primarily focus on optimizing the feature matrices of condensed graphs while overlooking the impact of the structure information from the original graphs. To investigate the impact of the structure information, we conduct analysis from the spectral domain and empirically identify substantial Laplacian Energy Distribution (LED) shifts in previous works. Such shifts lead to poor performance in cross-architecture generalization and specific tasks, including anomaly detection and link prediction. In this paper, we propose a novel Structure-broadcasting Graph dataset Distillation (SGDD) scheme for broadcasting the original structure information to the generation of the synthetic one, which explicitly prevents overlooking the original structure information. Theoretically, the synthetic graphs by SGDD are expected to have smaller LED shifts than previous works, leading to superior performance in both cross-architecture settings and specific tasks. We validate the proposed SGDD across 9 datasets and achieve state-of-the-art results on all of them: for example, on the YelpChi dataset, our approach maintains 98.6% test accuracy of training on the original graph dataset with 1,000 times saving on the scale of the graph. Moreover, we empirically evaluate there exist 17.6% ~ 31.4% reductions in LED shift crossing 9 datasets. Extensive experiments and analysis verify the effectiveness and necessity of the proposed designs. The code is available in the https://***/RingBDStack/SGDD.

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Preliminary Studies for Cracking Sound Identification During Coffee Roasting

Preliminary Studies for Cracking Sound Identification During...

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International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA)

作者： Jony Winaryo Wibowo Muhammad Ilham Rizqyawan Hanif Fakhrurroja Ulfah Nadiya Aris Munandar Oka Mahendra Artha Ivonita Simbolon Irfan Asfy Fakhry Anto Annida Rahmawati Research Center for Smart Mechatronic National Research and Innovation Agency Bandung Indonesia School Of Industrial Engineering Telkom University Bandung Indonesia Research Center for Smart Mechatronics National Research and Innovation Agency Bandung Indonesia Research Center for Data and Information Science National Research and Innovation Agency Bandung Indonesia

A coffee roasting plays an important role in determining the taste of coffee. The process consists of drying, browning, first crack, roast development, and second crack. The first crack is a beginning to form the characteristics of coffee beans. At this stage, a professional coffee roaster must ensure the spesific temperature and time, hence the beans are not getting burn. In manual coffee roasters, this causes inconsistency, because it really depends on the ability and experience of the coffee bean roaster. Therefore, in this study, we conducted a machine learning-based preliminary study to detect the cracking sound of coffee beans. The preliminary study was conducted by collecting videos of the roasting process from the internet. The videos are converted into audio format and separated between audio containing the sound of coffee beans cracking and audio that does not contain the sound of coffee beans cracking. The audios are then converted into an image format using the Mel-frequency cepstral coefficients (MFCC) method and modeled using convolutional neural network (CNN). From the 216 dataset files, we obtained an accuracy value of 89.7% with data lost during the testing process as much as 34.9% with 50 epochs of training and validation processes.

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Research on Hand-oriented Tactile Evoked Brain-Computer Interface Rehabilitation Method

Research on Hand-oriented Tactile Evoked Brain-Computer Inte...

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第42届中国控制会议

作者： Wanmeng Cai Lingling Chen Xin Guo Mengge Wang School of Artificial Intelligence and Data Science Hebei University of Technology Control Engineering Technology Innovation Center of Hebei Province Hebei University of Technology School of Electrical Engineering Hebei University of Technology

In recent years,the incidence of stroke has increased due to the growing issue of aging,significantly affecting the quality of life of *** hand rehabilitation is one of the common ***,in most cases,mechanical repetitive rehabilitation methods are used clinically,lacking patient's autonomous intention and *** interface(BCI) can be used as a solution to overcome such problems by proposing a hand rehabilitation protocol utilizing vibration stimulation induced ***,the vibration stimulation module was designed to be placed at the fingertip,with the amplitude adjusted to solve the problems of patient fatigue and low tactile sensation during the ***,the optimal channel was selected using the P300 characteristics evoked by different stimuli,and the classification accuracy was improved to more than 80% by cross-subject ***,the soft actuator chamber air pressure and bending angle are analyzed to establish the soft braking P300-BCI online *** results indicate that the actuator to a soft robotic hand based on BCI is valid in *** work can further promote neuroplasticity of patients and achieve closed-loop neuromotor rehabilitation for the in-loop population.

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NEHand: Enhancing Hand Pose Estimation in the Wild through Synthetic and Motion Capture datasets

NEHand: Enhancing Hand Pose Estimation in the Wild through S...

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WRC Symposium on Advanced Robotics and Automation (WRC SARA)

作者： Xiuzhen Jiao Xiangnan Li Haonan Wen Dianke Data (Beijing) Information Technology Services Co. Ltd China Yantai Science and Technology Innovation Promotion Center Yantai China School of Computer and Control Engineering Yantai University Yantai China

ISBN: (数字)9798331506100

ISBN: (纸本)9798331506117

Recovering interacting hand poses in natural environments poses a highly challenging task. Current datasets for interacting hands are relatively simple, lacking complex textures or background interference, allowing models to focus more on hand interaction behaviors. However, the diversity of backgrounds and textures in natural environments can significantly interfere with hand pose estimation, affecting the model’s generalization ability. Therefore, we propose an approach named NEHand, which combines synthetic datasets with publicly available datasets, including those based on motion capture, to achieve the recovery of interacting hand gestures in natural environments. To simplify the model, reduce complexity, and enhance generalization, we employ a strategy of flipping the left hand to the right hand to effectively achieve the recovery of both hands. Additionally, we introduce constraints from the mano model, including adjustments to joint angles, finger bending, and overall hand shape. This ensures that the generated hand poses not only conform to anatomical structures but also represent common, spontaneously occurring postures in our daily lives. By restricting and adjusting these parameters within specified ranges, we consider the natural motion relationships between hand joints, ensuring that the generated hand poses are physiologically reasonable. The method undergoes quantitative and qualitative evaluations, showcasing state-of-the-art robustness, generalization, and accuracy across multiple diverse datasets. This indicates that our approach has achieved significant success in addressing the challenge of recovering interacting hand poses in natural environments.

关键词： Solid modeling Accuracy Three-dimensional displays Shape Pose estimation Feature extraction Motion capture

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FM-FCN:A Neural Network with Filtering Modules for Accurate Vital Signs Extraction

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Research 2025年第1期2024卷 92-106页

作者： Fangfang Zhu Qichao Niu Xiang Li Qi Zhao Honghong Su Jianwei Shuai Department of Physics and Fujian Provincial Key Laboratory for Soft Functional Materials ResearchXiamen UniversityXiamen 361005China National Institute for Data Science in Health and Medicine and State Key Laboratory of Cellular Stress BiologyInnovation Center for Cell Signaling NetworkXiamen UniversityXiamen 361005China Vitalsilicon Technology Co.Ltd. JiaxingZhejiang 314006China School of Computer Science and Software Engineering University of Science and Technology LiaoningAnshan 114051China Yangtze Delta Region Institute of Tsinghua University ZhejiangJiaxing 314006China Wenzhou Institute University of Chinese Academy of SciencesWenzhou 325001China Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine Vision and Brain Health)Wenzhou 325001China

Neural networks excel at capturing local spatial patterns through convolutional modules,but they may struggle to identify and effectively utilize the morphological and amplitude periodic nature of physiological *** this work,we propose a novel network named filtering module fully convolutional network(FM-FCN),which fuses traditional filtering techniques with neural networks to amplify physiological signals and suppress ***,instead of using a fully connected layer,we use an FCN to preserve the time-dimensional correlation information of physiological signals,enabling multiple cycles of signals in the network and providing a basis for signal ***,we introduce the FM as a network module that adapts to eliminate unwanted interference,leveraging the structure of the *** approach builds a bridge between deep learning and signal processing ***,we evaluate the performance of FM-FCN using remote *** results demonstrate that FM-FCN outperforms the second-ranked method in terms of both blood volume pulse(BVP)signal and heart rate(HR)*** substantially improves the quality of BVP waveform reconstruction,with a decrease of 20.23%in mean absolute error(MAE)and an increase of 79.95%in signal-to-noise ratio(SNR).Regarding HR estimation accuracy,FM-FCN achieves a decrease of 35.85%in MAE,29.65%in error standard deviation,and 32.88%decrease in 95%limits of agreement width,meeting clinical standards for HR accuracy *** results highlight its potential in improving the accuracy and reliability of vital sign measurement through high-quality BVP signal *** codes and datasets are available online at https://***/zhaoqi106/FM-FCN.

关键词： physiological signalsin filtering module fully convolutional network fm fcn which vital signs extraction amplify physiological signals convolutional modulesbut neural networks filtering module capturing local spatial patterns

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