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7th Asia Conference on Power and Electrical Engineering, ACPEE 2022

作者： Li, Yanmei Li, Xiaoxue Shi, Chaoyu Li, Yan Li, Man Li, Lifeng Li, Yunpeng Xin, Ya Kunlun Digital Technology Co. Ltd. Business Department Beijing China Beijing Aerospace Data Co. Ltd. Big Data Center Beijing China China Electric Power Research Institute Artificial Intelligence Department Beijing China National Research Center for Rehabilitation and Technical Aids Testing Department Beijing China National Research Center for Rehabilitation and Technical Aids Ai Application Research Department Beijing China Beijing Aerospace Data Co. Ltd. General Headquarters Beijing China

ISBN: (纸本)9781665418195

Regionally distributed energy supply system is not only an important energy Internet physical carrier, but also the prototype and foundation of energy Internet. It focuses on physical technologies such as collaborative optimization between different energy sources. Distributed energy supply system has important research significance for exploring the internal operation mechanism of promoting advanced energy technology and different energy sources. In view of the special position of regionally distributed energy supply system in the transformation of energy system, it is particularly important to realize the scientific and reasonable coordinated operation and optimal dispatching of multiple energy in regionally distributed energy supply system, meet the demand for cooling and heating and power, and maximize the comprehensive economic benefits such as emission reduction and energy conservation. The coordinated operation and optimal scheduling of energy supply equipment in regionally distributed energy supply system is the core technology to ensure the safe, stable and economic operation of distributed energy supply system. Comprehensively considering the complex coupling characteristics of thermoelectricity and the random characteristics of renewable energy and load, coordinating the multi-directional energy flow in distributed energy supply system, studying the optimal operation mode of distributed energy supply system and optimal scheduling strategy will be the key research direction of energy Internet in the future. Based on the conventional cogeneration system, renewable energy generation is introduced. Firstly, the coupling interaction characteristics of photovoltaic power generation systems, wind power and other random power sources in the regionally distributed energy supply system and cogeneration system are considered, and the steady-state model is constructed. Then, combining the characteristics of operation of external energy supply conditions and energy su

关键词： Internet of Energy

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Network analysis and spatial agglomeration of China’s high-speed rail: A dual network approach

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Chinese Physics B 2021年第1期30卷 612-622页

作者： Wei Wang Wen-Bo Du Wei-Han Li Lu(Carol)Tong Jiao-E Wang School of Electronic and Information Engineering Beihang UniversityBeijing 100191China National Engineering Laboratory for Big Data Application Technologies for Comprehensive Traffic Beijing 100191China School of Cyber Science and Technology Beihang UniversityBeijing 100191China Research Institute of Frontier Science Beihang UniversityBeijing 100191China Institute of Geographic Sciences and Natural Resources Research Chinese Academy of SciencesBeijing 100101China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049China

China has the largest high-speed railway(HSR) system in the world, and it has gradually reshaped the urban *** HSR system can be represented as different types of networks in terms of the nodes and various relationships(i.e.,linkages) between them. In this paper, we first introduce a general dual network model, including a physical network(PN)and a logical network(LN) to provide a comparative analysis for China’s high-speed rail network via complex network theory. The PN represents a layout of stations and rail tracks, and forms the basis for operating all trains. The LN is a network composed of the origin and destination stations of each high-speed train and the train flows between them. China’s high-speed railway(CHSR) has different topological structures and link strengths for PN in comparison with the LN. In the study, the community detection is used to analyze China’s high-speed rail networks and several communities are found to be similar to the layout of planned urban agglomerations in China. Furthermore, the hierarchies of urban agglomerations are different from each other according to the strength of inter-regional interaction and intra-regional interaction, which are respectively related to location and spatial development strategies. Moreover, a case study of the Yangtze River Delta shows that the hub stations have different resource divisions and are major contributors to the gap between train departure and arrival flows.

关键词： China’s high-speed rail dual network network analysis urban agglomeration

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Pushing the Performance Limit of Scene Text Recognizer without Human Annotation

arXiv

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arXiv 2022年

作者： Zheng, Caiyuan Li, Hui Rhee, Seon-Min Han, Seungju Han, Jae-Joon Wang, Peng School of Computer Science Ningbo Institute Northwestern Polytechnical University China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology China China Korea Republic of

Scene text recognition (STR) attracts much attention over the years because of its wide application. Most methods train STR model in a fully supervised manner which requires large amounts of labeled data. Although synthetic data contributes a lot to STR, it suffers from the real-to-synthetic domain gap that restricts model performance. In this work, we aim to boost STR models by leveraging both synthetic data and the numerous real unlabeled images, exempting human annotation cost thoroughly. A robust consistency regularization based semi-supervised framework is proposed for STR, which can effectively solve the instability issue due to domain inconsistency between synthetic and real images. A character-level consistency regularization is designed to mitigate the misalignment between characters in sequence recognition. Extensive experiments on standard text recognition benchmarks demonstrate the effectiveness of the proposed method. It can steadily improve existing STR models, and boost an STR model to achieve new state-of-the-art results. To our best knowledge, this is the first consistency regularization based framework that applies successfully to STR. © 2022, CC BY.

关键词： Character recognition

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Boosting the Electrochemical Performance of Li-and Mn-Rich Cathodes by a Three-in-One Strategy

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Nano-Micro Letters 2021年第12期13卷 311-321页

作者： Wei He Fangjun Ye Jie Lin Qian Wang Qingshui Xie Fei Pei Chenying Zhang Pengfei Liu Xiuwan Li Laisen Wang Baihua Qu Dong-Liang Peng State Key Lab of Physical Chemistry of Solid Surface Collaborative Innovation Center of Chemistry for Energy MaterialsCollege of Materials and Pen-Tung Sah Institute of Micro-Nano Science and TechnologyXiamen UniversityXiamen 361005People’s Republic of China College of Chemistry and Chemical Engineering Xiamen UniversityXiamen 361005People’s Republic of China Zhengzhou Key Laboratory of Big Data Analysis and Application Henan Academy of Big DataZhengzhou UniversityZhengzhou 450002People’s Republic of China Fujian Provincial Key Laboratory of Light Propagation and Transformation College of Information Science and EngineeringHuaqiao UniversityXiamen 361021People’s Republic of China Shenzhen Research Institute of Xiamen University Shenzhen 518000People’s Republic of China

There are plenty of issues need to be solved before the practi-cal application of Li-and Mn-rich cathodes,including the detrimental voltage decay and mediocre rate capability,*** doping can e ectively solve the above problems,but cause the loss of *** introduction of appropriate defects can compensate the capacity loss;however,it will lead to structural mismatch and stress ***,a three-in-one method that combines cation–polyanion co-doping,defect construction,and stress engineering is *** co-doped Na^(+)/SO_(4)^(2-)can stabilize the layer framework and enhance the capacity and voltage *** induced defects would activate more reac-tion sites and promote the electrochemical ***,the unique alternately distributed defect bands and crystal bands structure can alleviate the stress accumulation caused by changes of cell parameters upon ***,the modified sample retains a capacity of 273 mAh g^(-1)with a high-capacity retention of 94.1%after 100 cycles at 0.2 C,and 152 mAh g^(-1)after 1000 cycles at 2 C,the corresponding voltage attenuation is less than 0.907 mV per cycle.

关键词： Li-and Mn-rich cathodes Cation–polyanion co-doping Defect and stress engineering Good structure stability Electrochemical performance

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Identifying stepping-stones within small wetlands in highly urbanized areas and under network construction: A case study of the Guangdong–Hong Kong–Macao greater Bay Area, China

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Ecological Indicators 2025年 176卷

作者： Ye, Ying Chen, Caixia Yu, Chunxue Sun, Caige Geng, Shoubao Guangdong Provincial Key Laboratory of Remote Sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and Application Guangdong Province Engineering Laboratory for Geographic Spatio-Temporal Big Data Guangzhou Institute of Geography Guangdong Academy of Sciences Guangzhou510070 China School of Geography South China Normal University Guangzhou510631 China Research Center for Eco-environmental Engineering Dongguan University of Technology Dongguan523808 China

In highly urbanized areas, small wetlands can provide multiple ecosystem services while benefiting the well-being of citizens. Although existing studies on wetland ecological networks have prioritized large wetland conservation measures, insufficient attention has been paid to the distribution patterns of small wetlands and their role in ecological networks. Utilizing the Guangdong–Hong Kong–Macao Greater Bay Area as a case study, we constructed a wetland ecological network to identify ecological pinch points while identifying small wetlands suitable to function as stepping-stones. This approach aims to establish potential corridors within the network and to assess the connectivity and robustness of the network under various scenarios. Our findings identified 297 ecological pinch points within the wetland ecological network alongside 53 small wetlands designated as stepping-stones, predominantly located in Foshan and Zhongshan cities in the central and western regions of the study area. The stepping-stone network comprised of 241 ecological corridors, with enhancements observed in the α, β, and γ indices, thereby significantly expanding the network's connectivity. Robustness index alterations in the stepping-stone network were moderated in relation to the ecological network, demonstrating that small wetlands can effectively bolster ecological network stability. It is recommended that, considering the distribution of ecological stepping stones of small wetlands, priority be given to the conservation and restoration of small wetlands in Foshan and Zhongshan within the central and western regions of the Guangdong–Hong Kong–Macao Greater Bay Area. This includes delineating conservation zones for small wetlands or establishing clusters of wetland parks centered on small wetlands, thereby maximizing their ecosystem value in supporting the urban agglomeration of the Guangdong–Hong Kong–Macao Greater Bay Area. © 2025 The Author(s)

关键词： Biotic

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Interpretable text-to-sql generation with joint optimization 1

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17th International Conference on Web Information Systems and applications, WISA 2020

作者： Zhu, Mingdong Wang, Xianfang Zhang, Yang School of Computer Science and Technology Henan Institute of Technology Xinxiang China Intelligent Industrial Big Data Application Engineering Technology Research Center of Xinxiang Xinxiang China

ISBN: (数字)9783030600297

ISBN: (纸本)9783030600280

The purpose of Text-to-SQL is to obtain the correct answer for a textual question from the database, which can take advantage of advanced database system to provide reliable and efficient response. Existing Text-to-SQL methods generally focus on accuracy by designing complex deep neural network models, and hardly consider interpretability, which is very important for serious applications. To address this, in this paper we propose a novel framework for Interpretable Text-to-SQL Generation (ITSG) with joint optimization, which achieves state-of-the-art accuracy and possesses two-level interpretability at the same time. The framework mainly consists of three layers: a sequence encoder which encodes questions, table headers and significant table contents, an attention-based LSTM layer which generates SQL queries and a reinforcement learning layer which boosts the execution accuracy. Comparing with state-of-the-art methods on benchmark datasets, the experimental results show the effectiveness and interpretability of our ITSG framework. © Springer Nature Switzerland AG 2020.

关键词： Reinforcement learning

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Perceptive self-supervised learning network for noisy image watermark removal

arXiv

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arXiv 2024年

作者： Tian, Chunwei Zheng, Menghua Li, Bo Zhang, Yanning Zhang, Shichao Zhang, David School of Software Northwestern Polytechnical University Xi’an710129 China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Xi’an710129 China School of Electronics and Information Northwestern Polytechnical University Xi’an710129 China School of Computer Science Northwestern Polytechnical University National Engineering Laboratory for Integrated AeroSpace-Ground-Ocean Big Data Application Technology Xi’an710129 China Guangxi Key Lab of Multisource Information Mining & Security College of Computer Science & Engineering Guangxi Normal University Guilin541004 China Shenzhen518172 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518172 China

Popular methods usually use a degradation model in a supervised way to learn a watermark removal model. However, it is true that reference images are difficult to obtain in the real world, as well as collected images by cameras suffer from noise. To overcome these drawbacks, we propose a perceptive self-supervised learning network for noisy image watermark removal (PSLNet) in this paper. PSLNet depends on a parallel network to remove noise and watermarks. The upper network uses task decomposition ideas to remove noise and watermarks in sequence. The lower network utilizes the degradation model idea to simultaneously remove noise and watermarks. Specifically, mentioned paired watermark images are obtained in a self-supervised way, and paired noisy images (i.e., noisy and reference images) are obtained in a supervised way. To enhance the clarity of obtained images, interacting two sub-networks and fusing obtained clean images are used to improve the effects of image watermark removal in terms of structural information and pixel enhancement. Taking into texture information account, a mixed loss uses obtained images and features to achieve a robust model of noisy image watermark removal. Comprehensive experiments show that our proposed method is very effective in comparison with popular convolutional neural networks (CNNs) for noisy image watermark removal. Codes can be obtained at https://***/hellloxiaotian/PSLNet. Copyright © 2024, The Authors. All rights reserved.

关键词： Image denoising

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A Robust Distance Regularized Potential Function for Level Set Image Segmentation 17th

A Robust Distance Regularized Potential Function for Level S...

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17th International Conference on Intelligent Computing, ICIC 2021

作者： Zou, Le Huang, Qian-Jing Wu, Zhi-Ze Song, Liang-Tu Wang, Xiao-Feng Anhui Provincial Engineering Laboratory of Big Data Technology Application for Urban Infrastructure School of Artificial Intelligence and Big Data Hefei University Anhui Hefei230601 China Hefei Institutes of Physical Science Chinese Academy of Sciences P. O. Box 1130 Anhui Hefei230031 China University of Science and Technology of China Anhui Hefei230026 China College of Bioengineering Food and Environmental Sciences Hefei University Anhui Hefei230601 China Institute of Applied Optimization School of Artificial Intelligence and Big Data Hefei University Anhui Hefei230601 China

ISBN: (纸本)9783030845216

The level set is a classical image segmentation method, but during the evolution of the level set, it can produce evolutionary problems such as local spikes and deep valleys, or overly flat regions, making the iterative process of final segmentation unstable and segmentation results inaccurate. In order to ensure the stability and validity of the level set evolution during the evolution process, the level set function must be periodically initialized so that the level set is always kept as a signed distance function. We construct a new distance regularization potential function based on logarithmic and power function and give a specific analysis. During the evolution process, the level set function always approximates the signed distance function, which is stable and efficient for level set image segmentation. Experimental analyses are conducted to compare the segmentation performance of various distance regularization potential functions when combining with the classical Chan Vese model. © 2021, Springer Nature Switzerland AG.

关键词： Image segmentation

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MedUniSeg: 2D and 3D Medical Image Segmentation via a Prompt-driven Universal Model

arXiv

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arXiv 2024年

作者： Ye, Yiwen Chen, Ziyang Zhang, Jianpeng Xie, Yutong Xia, Yong The National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi’an710072 China The College of Computer Science and Technology Zhejiang University Zhejiang China The University of Adelaide Australia Research & Development Institute of Northwestern Polytechnical University in Shenzhen Shenzhen518057 China The Ningbo Institute of Northwestern Polytechnical University Ningbo315048 China

Universal segmentation models offer significant potential in addressing a wide range of tasks by effectively leveraging discrete annotations. As the scope of tasks and modalities expands, it becomes increasingly important to generate and strategically position task- and modal-specific priors within the universal model. However, existing universal models often overlook the correlations between different priors, and the optimal placement and frequency of these priors remain underexplored. In this paper, we introduce MedUniSeg, a prompt-driven universal segmentation model designed for 2D and 3D multi-task segmentation across diverse modalities and domains. MedUniSeg employs multiple modal-specific prompts alongside a universal task prompt to accurately characterize the modalities and tasks. To generate the related priors, we propose the modal map (MMap) and the fusion and selection (FUSE) modules, which transform modal and task prompts into corresponding priors. These modal and task priors are systematically introduced at the start and end of the encoding process. We evaluate MedUniSeg on a comprehensive multi-modal upstream dataset consisting of 17 sub-datasets. The results demonstrate that MedUniSeg achieves superior multi-task segmentation performance, attaining a 1.2% improvement in the mean Dice score across the 17 upstream tasks compared to nnUNet baselines, while using less than 1/10 of the parameters. For tasks that underperform during the initial multi-task joint training, we freeze MedUniSeg and introduce new modules to re-learn these tasks. This approach yields an enhanced version, MedUniSeg*, which consistently outperforms MedUniSeg across all tasks. Moreover, MedUniSeg surpasses advanced self-supervised and supervised pre-trained models on six downstream tasks, establishing itself as a high-quality, highly generalizable pre-trained segmentation model. The code and model will be available at https://***/yeerwen/UniSeg. Copyright © 2024, The Authors.

关键词： Image segmentation

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Evaluating the Impact of Special Characters on Password Security: a Comparative Analysis

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IEEE Network 2025年

作者： He, Daojing Liu, Zhiyong Chan, Sammy Zhou, Beibei Guizani, Mohsen Harbin Institute of Technology School of Computer Science and Technology Shenzhen China Guizhou University State Key Laboratory of Public Big Data Guizhou China Research and Development Center Guangzhou Jingyuan Security Technology Co. Ltd Guangzhou China City University of Hong Kong Kowloon Department of Electrical Engineering Hong Kong Hong Kong Shanghai Urban Construction Vocational College School of Artificial Intelligence Application Shanghai China Machine Learning Department Abu Dhabi United Arab Emirates

Text-based password authentication remains essential for identity verification on internet platforms and blockchain systems. However, as computational power advances, security threats to user passwords have intensified, raising concerns about their effectiveness. While special characters (i.e., non-alphanumeric symbols, which include punctuation marks, mathematical symbols, and other non-letter/number characters like '.', '@', '#', '$', and similar) are often recommended to enhance password strength, the National institute of Standards and technology (NIST) prioritizes length over complexity, challenging their necessity. This study fills a critical gap in understanding user behavior regarding special character usage. By analyzing 15 datasets from Chinese, English, and German languages, we examined patterns of special character incorporation and their impact on password strength. Our findings indicate that users frequently employ predictable methods for including special characters, potentially compromising security, especially under stringent policies. We present three key contributions: (1) an analysis of special character usage patterns, (2) a quantitative assessment of strength differences using the PCFGv4.1 model, and (3) actionable recommendations for stakeholders to enhance password security practices. This research further advocates for aligning password policies with user behavior for more effective security. © 1986-2012 IEEE.

关键词： Authentication Protocol

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