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A Decomposition and Reconstruction Based Hybrid Time Series Model for Short-Term Wind Power Forecasting

Journal of advanced Computational Intelligence and intelligent Informatics 2025年第3期29卷 592-605页

作者： Ding, Min Lv, Ji Zhou, Sibei Li, Junhao Fang, Zhijian Yokoyama, Ryuichi School of Automation China University of Geosciences No.388 Lumo Road Hongshan District Hubei Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems No.388 Lumo Road Hongshan District Hubei Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education No 388 Lumo Road Hongshan District Hubei Wuhan430074 China School of Environment and Energy Engineering Waseda University 3-4-1 Okubo Shinjuku-ku Tokyo169-8555 Japan

The intermittency, uncontrollability, and variability of wind power affect the economical operation and reliable delivery of the power system. To ensure the smooth integration of wind power into the grid, an accurate wind power forecast is essential. In this paper, we propose a short-term wind power prediction model based on decomposition and reconstruction to improve the accuracy of wind power forecasts. This model has the following characteristics: (i) wind power time series are decomposition into multiple components through the application of a decomposition method that combines fully integrated empirical mode decomposition with adaptive noise algorithm;(ii) the components are clustered using ķ-means clustering based on dynamic time warping. According to the similarity of the complexity and lag of components, they are divided into three classes;(iii) three different prediction models, including seasonal autoregressive integrated moving average model (SARIMA), long short-term memory network (LSTM) and Bi-directional long short-term memory network (BiLSTM), predict three types of components respectively. Finally, to illustrate the capability of the model, we compare its performance with three typical models. The results demonstrate that the proposed method exceeds the baseline models in regard to prediction performance. © Fuji Technology Press Ltd.

关键词： Electric power transmission networks

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Development and Implementation of a Wisdom Course Utilizing the "teaching-Innovation-Competition" Model within the Virtual Teaching and Research Section of Mechatronic Engineering Major in China 3

Development and Implementation of a Wisdom Course Utilizing ...

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3rd International Conference on Artificial Intelligence and Education, ICAIE 2024

作者： Chen, Wei Ma, Wenpeng Hu, Wenhua Liu, Fulong Zhang, Xiaotao Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education (Tianjin University of Technology) Tianjin University of Technology Tianjin China

ISBN: (纸本)9798400712692

A new teaching model of teaching-innovation-competition is presented and a wisdom course based on this model is developed for mechatronics engineering majors, mainly to deal with several existing problems such as limited experimentation and lack of innovative inspiration in Chinese universities. This study elaborates the course objectives and structure of curriculum system, including digitalized teaching content, project-driven teaching means, innovation platform, web-based resource support, team competition and diversified evaluation method. Through a teaching case study within mechatronic engineering major, the teaching mechanism and achievements are demonstrated. The study results indicate that the proposed teaching mode based on the virtual teaching and research section, significantly improves students' innovation ability and the teaching effects, compared to traditional teaching methods. This teaching mode can also be extended to other majors for reference. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Construction and Practice of Wisdom Course Mechatronic Engineering Major Teaching-Innovation-Competition Mode Virtual Teaching and Research Section

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Task Assignment Scheme Designed for Online Urban Sensing Based on Sparse Mobile Crowdsensing

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IEEE Internet of Things Journal 2025年第11期12卷 17791-17806页

作者： Hongjian Zeng Yonghua Xiong Jinhua She Anjun Yu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Engineering Tokyo University of Technology Hachioji Tokyo Japan Operation Management Department Jiangxi Ganyue Expressway Company Ltd. Nanchang Jiangxi China

Sparse mobile crowdsensing (SMCS) achieves urban-scale environmental sensing by assigning tasks to workers in specific subareas and inferring global data from the collected information. However, the effectiveness of SMCS is often limited because many studies overlook workers’ mobility and data collection time during subarea selection, as well as the time constraints of the sensing cycle in task assignment. This may affect the task completion timeliness and data quality. To address these issues, we develop a subarea evaluation method based on deep reinforcement learning, considering both the temporal effectiveness of sensing tasks and the importance of subarea selection for data inference. Using the subarea evaluation values derived from this method, we establish an online urban sensing task assignment model which is subject to constraints of sensing cycle time and cost budget. This model aims to find the task assignment result that minimizes data inference error by maximizing the comprehensive utility value. Considering the characteristics of the task assignment model, we propose an evolutionary algorithm named OTA-EA, which is based on an improved genetic algorithm. Its enhanced evolutionary operators can avoid generating infeasible solutions while maintaining robust search and optimization performance. Lastly, we conduct experimental evaluations of these methods on the real-world datasets. The results demonstrate that our subarea evaluation method can significantly reduce the data inference error, and our evolutionary task assignment algorithm can achieve better task assignment results than the baseline algorithms.

关键词： Sensors Costs Time factors Data collection Crowdsensing Evolutionary computation Data integrity Optimization Inference algorithms Mobile computing

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Thickness Measurement of Single-Mode Fiber Coating Layer Based on Forward Brillouin Scattering

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IEEE Sensors Journal 2025年第11期25卷 19332-19340页

作者： Zhang, Yongqi Wang, Tao Liu, Yijia Liu, Li Zhang, Mingjiang Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education College of Physics and Optoelectronic Engineering Taiyuan030024 China Taiyuan University of Technology Shanxi Key Laboratory of Precision Measurement Physics College of Physics and Optoelectronic Engineering Taiyuan030024 China

The coating layer is essential for protecting and applying optical fibers. Nowadays, the thickness measurement of the coating layer relies on point measurement schemes such as the side-looking light distribution method and mechanical method. However, there are some problems with the above methods, such as the trade-off between resolution and field of view, the cutting of the measurement position and the long measurement time. To overcome these problems, we propose a new method based on forward Brillouin scattering, which measures the coating layer thickness of single-mode fibers. The physical properties of the transverse acoustic field involved in forward Brillouin scattering make it possible to measure the thickness of the fiber coating. The corresponding relationship between the transverse acoustic mode frequency and the diameter of the coating layer can be calculated. The coating layer thickness can be measured with high precision by measuring the frequency spectrum of forward Brillouin scattering corresponding to multiple transverse acoustic modes at a given temperature. In the verification experiment, three types of single-mode fibers coated with polyimide are used as the sensing fiber to measure the thickness of the coating layer at multiple temperatures. The experimental results show that the error in the coating layer thickness obtained is less than 0.05 μm. To the best of our knowledge, this is the first demonstration of non-destructive, high-precision monitoring of fiber coating thickness. © 2001-2012 IEEE.

关键词： Acoustic field measurement

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Hand Gesture Recognition from an Open-Set Perspective

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IEEE Transactions on Multimedia 2025年

作者： Zhou, Jun Xu, Chi Cheng, Li China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Vision and Learning Laboratory Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada

Existing hand gesture recognition methods predominantly rely on a close-set assumption, which in essence limits the viewpoints, gesture categories, and hand shapes at test time to closely resemble those seen during training. This requirement is however rarely met in practice, as images are often captured from unconstrained viewpoints, with novel gestures and unseen hand shapes that can differ significantly from the training data. This motivates us to investigate an open-set hand gesture recognition problem, where hand gestures are still recognizable from unconstrained viewpoints, and novel gesture classes and hand shapes can be incrementally learned with just a few examples. To address this, we propose a viewpoint influence elimination network that extracts view-independent features, significantly improving performance in scenarios with unconstrained viewpoints. Moreover, a joint-weighted classification scheme is introduced to augment the cosine similarity metric for evaluating few-shot incremental learning of novel gestures and shapes. Finally, as existing hand gesture recognition datasets primarily adhere to the close-set assumption, a new hand gesture recognition dataset, OHG, is introduced in this paper, that includes a wide range of viewpoints, diverse gesture classes, and distinct hand shapes. Experimental hand gesture recognition results demonstrate the superior performance of our approach in both unconstrained viewpoint and few-shot incremental learning scenarios. The source code and the OHG dataset are to be made available at https://***/zhoujun-7/OSHGR. © 1999-2012 IEEE.

关键词： Palmprint recognition

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3D bioprinting of a dermal scaffold for full-thickness skin tissue regeneration

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Bio-Design and Manufacturing 2025年第1期8卷 68-84,I0039-I0041页

作者： Lu Han Zixian Liu Meng Li Zhizhong Shen Jianming Wang Shengbo Sang Shanxi Key Laboratory of Micro Nano Sensors&Artificial Intelligence Perception College of Electronic Information and Optical EngineeringTaiyuan University of TechnologyTaiyuan 030024China Key Laboratory of Advanced Transducers and Intelligent Control System of the Ministry of Education Taiyuan University of TechnologyTaiyuan 030024China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan 030024China Shanxi Research Institute of 6D Artificial Intelligence Biomedical Science Taiyuan 030031China General Hospital of TISCO Taiyuan 030809China

Dermal substitutes have provided a template for the regeneration and reconstruction of the ***,the healed skin tissue often exhibits abnormal morphology and functionality,including scarring and *** this study,a composite bioink composed of methacrylated gelatin(GelMA)and chitosan oligosaccharide(COS)was proposed for printing a dermal scaffold using digital light processing(DLP)*** GelMA/COS bioink exhibited suitable porosity,swelling,degradation rate,and mechanical *** inclusion of COS demonstrated antibacterial effects against both Gram positive and Gram-negative bacteria,while simultaneously fostering the proliferation of human dermal fibroblasts(HDFs).Additionally,the application of COS could effectively reduce the expression levels of fibrosis-related genes,such as collagen I,collagen III,and fibronectin *** three-dimensionally printed cell-laden dermal scaffold exhibited excellent shape fidelity and high cellular viability,facilitating the extension of HDFs along the scaffold and the simultaneous secretion of extracellular matrix ***,the HDF-laden dermal scaffold transplanted into full-thickness skin defect sites in nude mice was shown to accelerate wound closure,reduce inflammation,and improve wound ***,the DLP-printed dermal scaffold provides an appealing approach for effectively treating full-thickness skin defects in clinical settings.

关键词： 3D printing Dermal scaffold Photo-cross-linking Skin tissue regeneration

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Research on Early Warning of Drug Crime Behaviors Based on Data-driven Method 24

Research on Early Warning of Drug Crime Behaviors Based on D...

引用

Proceedings of the 2024 4th International Conference on Big Data, Artificial Intelligence and Risk Management

作者： Shaobing Wu Changmei Wang Institute of Information Security Key Laboratory of Intelligent Drug Control Yunnan Police College Kunming Yunnan China Education Ministry Key Laboratory of Advanced Technology and Preparation for Renewable Energy Materials Yunnan Normal University Kunming Yunnan China

ISBN: (纸本)9798400709753

The identification of target suspects in images and videos from multi-source heterogeneous data is a difficult task in criminal investigation. In criminal scene analysis during law enforcement, images and videos from surveillance applications and security systems play an important role in providing visual files for the scene. With the rise of big data, artificial intelligence, the Internet of Things, blockchain, and cyberspace security, it is particularly important to improve the application of computer technology in drug crime cases and achieve data-driven drug crime behavior prediction. This paper builds police subject-specific databases such as drug addicts, drug traffickers, key personnel, and fugitives, and achieves drug crime behavior prediction and warning based on identity information, facial recognition and storage and picture comparison using a combination of Python and OpenCV. It provides a useful exploration for combating Drug Crime.

关键词： data-driven

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A Stable RTK/MEMS-IMU Tightly-Coupled Algorithm under Differential Corrections Outage

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IEEE Transactions on Vehicular Technology 2025年

作者： Bian, Yougang Cao, Shipeng Wang, Guangcai Qin, Xiaohui Hu, Manjiang Qin, Hongmao Hunan University State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle College of Mechanical and Vehicle Engineering Changsha410082 China Hunan University Wuxi Intelligent Control Research Institute Wuxi214115 China

The GNSS-RTK and MEMS-IMU integrated navigation system is a commonly used high-precision, low-cost solution for outdoor positioning. However, the significant measurement error of MEMS-IMU can rapidly lead to divergence in navigation state predictions based on inertial error propagation models. To overcome this limitation and enhance accuracy, maintaining the continuity of RTK measurement information is crucial. Nevertheless, due to the instability of wireless transmission links and communication equipment, or disruptions in base station observations, differential corrections often experience outages, resulting in a decline in measurement information quality and affecting the accuracy of integrated navigation. Therefore, this paper proposes a stable RTK/MEMS-IMU tightly coupled algorithm. During outages of differential corrections, the proposed algorithm utilizes historical differential corrections from the base station along with real-time rover station information to construct a stable double-difference carrier phase vector. This approach ensures the stability of measurement information and enhances positioning accuracy. Simulation results have verified the effectiveness of this method, and land tests have demonstrated that, compared to the traditional RTK/MEMS-IMU tightly coupled algorithm, the position and velocity accuracy of this algorithm during outages of differential corrections have been improved by 29.5% and 18.4%, respectively. © 1967-2012 IEEE.

关键词： Base stations

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Phase-gain Dual-parametric Spectrum Measurement in Chaotic Brillouin Optical Correlation Domain Analysis

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IEEE Sensors Journal 2025年

作者： Chen, Jing Wang, Yahui Ma, Jinglian Huang, Haochen Zhang, Mingjiang Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan030024 China Taiyuan University of Technology College of Physics and Optoelectronics Taiyuan China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan030024 China

In this paper, the chaotic Brillouin phase-gain dual-parametric spectrum (BDS) is measured for the first time, which can realize high-accuracy and large-range dynamic strain demodulation in chaotic Brillouin optical correlation domain analysis (CBOCDA). The phase of the chaotic probe wave is measured by a Sagnac interferometer (SI) combined with an optical bandpass filter (OBPF) and a beat frequency locking technique. The Brillouin gain spectrum (BGS), Brillouin phase-shift spectrum (BPS), and BDS are measured in the chaotic BOCDA system through both simulation and experiment, and the feasibility of their demodulation with high-accuracy and large-range dynamic strain is verified. The chaotic BPS exhibits good linearity at the Brillouin frequency shift (BFS) and can be used to demodulate high-accuracy tiny strains. The measurement error of a 1 μΕ strain is only 0.0446 μΕ. The linear range of the chaotic BDS is extended to 150 MHz, and more than 10 mΕ dynamic strain measurements can be enabled by incorporating the slope-assisted method. © 2001-2012 IEEE.

关键词： Ultraviolet spectroscopy

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Differentially Private Opinion Dynamics of Influence Networks

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IEEE Transactions on control of Network Systems 2025年

作者： Wu, Guanglei Zhang, Wenbing Mao, Shuai Wu, Xiaotai Tang, Yang Yangzhou University School of Mathematical Sciences Jiangsu225002 China Nantong University Department of Electrical Engineering Nantong226019 China Anhui Polytechnic University Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment Ministry of Education Wuhu241000 China East China University of Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Shanghai200237 China

In this paper, a unified influence networks model incorporating differential privacy mechanisms (DPMs), called the differentially private opinion dynamics (DPODs) model is proposed. In this model, each individual uses protected opinions rather than the private opinions of his/her neighbors to update his/her private opinions, where the protected opinion of an individual is a blend of private opinions and random noise following Laplace distribution. Building on stochastic analysis techniques and matrix theory, we show that the influence network under consideration converges under specific conditions governing individual sensitivities and interaction weights. In addition, the statistical properties related to convergence accuracy are established by utilizing the Markov inequality to estimate a lower bound on the probability of all individuals' final opinions converging to a neighborhood formed by their initial opinions' convex hull. We further conduct a differential privacy analysis to validate the efficacy of the proposed DPMs in safeguarding the private opinions of all individuals. Finally, two examples including one of the Karate-Club networks are provided to shed new light on the effectiveness of the theoretical results. © 2014 IEEE.

关键词： Differential privacy

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