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arXiv 2024年

作者： Wei, Qikai Yang, Mingzhi Wang, Jinqiang Mao, Wenwei Xu, Jiabo Ning, Huansheng School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China Key Laboratory of Xinjiang Coal Resources Green Mining Ministry of Education Xinjiang Institute of Engineering Urumqi830023 China Beijing Engineering Research Center for Cyberspace Data Analysis and Applications Beijing100083 China Guangxi Tourism Development One-Click Tour Digital Cultural Tourism Industry Co. Ltd. Guangxi530012 China

Recently, large language models (LLMs) have demonstrated their effectiveness in various natural language processing (NLP) tasks. However, the lack of tourism knowledge limits the performance of LLMs in tourist attraction presentations and travel planning. To address this challenge, we constructed a supervised fine-tuning dataset for the culture and tourism domain, named Cultour. This dataset consists of three parts: tourism knowledge base QA data, travelogues data, and tourism diversity QA data. Additionally, we propose TourLLM, a Qwen-based model supervised fine-tuned with Cultour, to improve the quality of the information provided about attractions and travel planning. To evaluate the performance of TourLLM, we employed both automatic and human evaluation, and we proposed a human evaluation criterion named CRA (Consistency, Readability, Availability). The experimental results demonstrate the effectiveness of the responses generated by the TourLLM. Our proposed Cultour is accessible at https://***/mrweiqk/Cultour. Copyright © 2024, The Authors. All rights reserved.

关键词： Natural language processing systems

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Accelerating exploitation and integration of global renewable energy

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Innovation 2025年

作者： Wang, Jianxiao Chen, Xinjiang Zhuang, Minghao Li, Yan Ruan, Ziwen Wang, Yuhan Zhang, Ning Song, Jie He, Kebin Lu, Xi National Engineering Laboratory for Big Data Analysis and Applications Peking University Beijing100871 China Department of Industrial Engineering and Management College of Engineering Peking University Beijing100871 China Peking University Ordos Research Institute of Energy Ordos017000 China State Key Laboratory of Nutrient Use and Management College of Resources and Environmental Sciences China Agricultural University Beijing100193 China College of Environmental Science and Engineering Tongji University Shanghai200092 China School of Environment State Key Joint Laboratory of Environment Simulation and Pollution Control Tsinghua University Beijing100084 China State Key Lab of Power Systems Department of Electrical Engineering Tsinghua University Beijing100084 China Institute for Carbon Neutrality Tsinghua University Beijing100084 China

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Power Grid Critical State Search Based on Improved Particle Swarm Optimization 6th

Power Grid Critical State Search Based on Improved Particle ...

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6th International Conference on Advanced Intelligent Systems and Informatics, AISI 2020

作者： Luo, Jie Deng, Hui-Qiong Li, Qin-Bin Zheng, Rong-Jin Li, Pei-Qiang Chang, Kuo-Chi School of Information Science and Engineering Fujian University of Technology Fuzhou350108 China Fujian Provincial University Engineering Research Center of Smart Grid Simulation Analysis and Integrated Control Fuzhou350108 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)9783030586683

This article proposes a method to find the closest critical initial running state of power grid, aiming at the possible chain reaction failure caused by branch fault in power system. First of all, assuming the initial failure of power grid, considering the specific performance of relay protection, analyze the critical state of the branch in cascading trip in detail, the electrical distance between the current running state and the interlocking fault expressed in the form of nodal injection power is given. Secondly, on the basic of the relationship between the nodal injections power and the system safety, a safety level model that the system will not trigger cascading failures is established. Finally, the improved simplified mean particle swarm optimization algorithm is used to solve the model, and an example is analyzed on IEEE-14 node system. An example shows the effectiveness and feasibility of the proposed method, which provides a reference for further prevention of cascading trip accidents. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Outages

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Attribution-guided planning for renewable energy generation bases: Synergistic design of ammonia co-firing and renewable energy integration

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Energy 2025年 330卷

作者： Han, Yiting Zhang, Tiance Li, Gengyin Zhou, Ming Wang, Jianxiao State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China National Engineering Laboratory for Big Data Analysis and Applications Peking University Beijing100871 China

To balance the economic viability, operational stability, and carbon reduction objectives in renewable energy generation bases (REGB), the retrofitting strategy for thermal power units (TPUs) has garnered significant research attention. Ammonia co-firing in TPUs has emerged as an effective transitional solution. Recognizing the limitations of traditional optimization-based planning in fully explaining planning results and providing guidance, an attribution-guided low-carbon planning framework for integrated thermal-renewable energy systems is proposed in this paper. A high-fidelity CO2 emission model is developed, which incorporates the impacts of ammonia co-firing on turbine/boiler efficiency and auxiliary power consumption under flexible operations. Then, a path-integration-based attribution analysis method is proposed to quantifying technology contributions, enabling targeted optimization guidance for REGB. On this basis, self-consistent renewable energy management strategy with green electricity-driven ammonia production/power generation synergy is proposed in this paper. Case studies based on a realistic REGB in Northwest China shows that the proposed strategy achieves 2.48 % CO2 emission reduction while maintaining operational costs 2.20 % lower than the original optimal scheme. © 2025 Elsevier Ltd

关键词： Strategic planning

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LDoS attack detection method based on traffic time-frequency characteristics

arXiv

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arXiv 2022年

作者： Fu, Yu Duan, Xueyuan Wang, Kun Li, Bin Department of Information Security Naval University of Engineering Wuhan430033 China College of Computer and Information Technology Xinyang Normal University Xinyang464000 China Henan Key Laboratory of Analysis and Applications of Education Big Data Xinyang464000 China School of Mathematics and Information Engineering Xinyang Vocational and Technical College Xinyang464000 China

For the traditional denial-of-service attack detection methods have complex algorithms and high computational overhead, which are difficult to meet the demand of online detection;and the experimental environment is mostly a simulation platform, which is difficult to deploy in real network environment, we propose a real network environment-oriented LDoS attack detection method based on the time-frequency characteristics of traffic data. All the traffic data flowing through the Web server is obtained through the acquisition storage system, and the detection data set is constructed using pre-processing;the simple features of the flow fragments are used as input, and the deep neural network is used to learn the time-frequency domain features of normal traffic features and generate reconstructed sequences, and the LDoS attack is discriminated based on the differences between the reconstructed sequences and the input data in the time-frequency domain. The experimental results show that the proposed method can accurately detect the attack features in the flow fragments in a very short time and achieve high detection accuracy for complex and diverse LDoS attacks;since only the statistical features of the packets are used, there is no need to parse the packet data, which can be adapted to different network environments. Copyright © 2022, The Authors. All rights reserved.

关键词： Denial-of-service attack

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CATIRI:An Efficient Method for Content-and-Text Based Image Retrieval

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Journal of Computer Science & Technology 2019年第2期34卷 287-304页

作者： Mengqi Zeng Bin Yao Zhi-Jie Wang Yanyan Shen Feifei Li Jianfeng Zhang Hao Lin Minyi Guo Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China School of Data and Computer Science Sun Yat-sen University Guangzhou 510006 China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou 510006 China National Engineering Laboratory for Big Data Analysis and Applications Beijing 100871 China School of Computing University of Utah Salt Lake City 84112 U.S.A. Alibaba Group Hangzhou 311121 China

The combination of visual and textual information in image retrieval remarkably alleviates the semantic gap of traditional image retrieval methods,and thus it has attracted much attention *** retrieval based on such a combination is usually called the content-and-text based image retrieval(CTBIR).Nevertheless,existing studies in CTBIR mainly make efforts on improving the retrieval *** the best of our knowledge,little attention has been focused on how to enhance the retrieval ***,image data is widespread and expanding rapidly in our daily ***,it is important and interesting to investigate the retrieval *** this end,this paper presents an efficient image retrieval method named CATIRI(content-and-text based image retrieval using indexing).CATIRI follows a three-phase solution framework that develops a new indexing structure called *** MHIM-tree seamlessly integrates several elements including Manhattan Hashing,Inverted index,and *** use our MHIM-tree wisely in the query,we present a set of important metrics and reveal their inherent *** on them,we develop a top-k query algorithm for *** results based on benchmark image datasets demonstrate that CATIRI outperforms the competitors by an order of magnitude.

关键词： image retrieval text-and-visual feature indexing top-k

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Cascading Fault Prevention of Power Grid Based on key Power Generation Nodes 1

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16th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2020 in conjunction with the 13th International Conference on Frontiers of Information Technology, applications and Tools, FITAT 2020

作者： Chang, Kuo-Chi Luo, Jie Deng, Hui-Qiong Li, Qin-Bin Zheng, Rong-Jin Li, Pei-Qiang School of Information Science and Engineering Fujian University of Technology Fuzhou350108 China Fujian Provincial University Engineering Research Genter of Smart Grid Simulation Analysis and Integrated Control Fuzhou350108 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Business Administration North Borneo University College Sabah Malaysia

ISBN: (数字)9789813364202

ISBN: (纸本)9789813364196

In the case of power grid cascading trip, this study puts forward a strategy to prevent cascading trip by changing the output of generator set. Firstly, according to the specific performance of the power grid under the cascade tripping, combined with the action behavior of the line current-type backup protection, and an expression equation for measuring the safety level index between the power grid and the cascading trip failure is given. Secondly, the vulnerable branch is found out through the safety level index, the output of the key power generation nodes on the branch is taken as the optimization variable, and the optimization model is established to improve the safety level index under the chain trip of the power grid. Finally, a combination of sensitivity analysis and particle swarm optimization(PSO) was used to analyze an example on the IEEE-39 node system. The results demonstrate the feasibility and effectiveness of the model and method, and provide a reference for preventing chain trip accidents. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Sensitivity analysis

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Optimal Power Generation Output Considering Cascading Failure 1

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作者： Deng, Hui-Qiong Luo, Jie Li, Qin-Bin Zheng, Rong-Jin Li, Pei-Qiang Chang, Kuo-Chi School of Information Science and Engineering Fujian University of Technology Fuzhou350108 China Fujian Provincial University Engineering Research Genter of Smart Grid Simulation Analysis and Integrated Control Fuzhou350108 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Business Administration North Borneo University College Sabah Malaysia

ISBN: (数字)9789813364202

ISBN: (纸本)9789813364196

Aiming at the cascading fault phenomenon of power system, this paper analyzes the disturbed branches involved in the initial fault and their relationship with the power generating nodes. Firstly, according to the performance of the initial fault branch in the cascading fault phenomenon and the action of relay protection, an expression form of evaluating the severity of the initial fault branch is given. Secondly, the relationship between the current of the residual system branch and the injection power of the nodes after the initial fault removal is analyzed. Then, on the basis of synthesizing the severity of the disturbed branch and its correlation with the power generating nodes, the key power generating nodes on the seriously disturbed branch are selected by clustering analysis. Finally, based on the key power generation nodes, the optimal power generation output model considering the power generation operation cost was established, the model was solved by particle swarm optimization (PSO), the model was simulated by IEEE39 bus system in MATLAB environment, and the correctness of the established model and method was verified. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Particle swarm optimization (PSO)

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Design of Leakage Current Monitoring System for Low Voltage Power Grid Based on NB-IoT 6th

Design of Leakage Current Monitoring System for Low Voltage ...

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6th International Conference on Advanced Machine Learning Technologies and applications, AMLTA 2021

作者： Xu, GuanWei Zheng, RongJin Chang, Kuo-Chi School of Information Science and Engineering Fujian University of Technology Fuzhou China Fujian Institute of Engineering Smart Grid Simulation Analysis and Integrated Control of Fujian University Engineering Research Center Fuzhou Fujian China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Business Administration North Borneo University College Sabah Malaysia

ISBN: (纸本)9783030697167

Leakage current of low-voltage power grid lines will cause major safety hazards such as personal electric shock and electrical fire. Traditional leakage current protectors can not play their due protection role due to their quality problems and aging, and other reasons. When leakage current accidents occur, traditional manual troubleshooting is inefficient. Aiming at the safety of leakage current in a low-voltage power grid, a new leakage current monitoring system is designed based on NB-IoT technology. The system includes the detection and transmission of leakage current and the construction of the cloud platform, which can realize the real-time monitoring of leakage current in low-voltage power grid and prevent and solve the leakage current safety problems. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Leakage currents

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MF-CLIP: Leveraging CLIP as Surrogate Models for No-box Adversarial Attacks

arXiv

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arXiv 2023年

作者： Zhang, Jiaming Qiu, Lingyu Yi, Qi Li, Yige Sang, Jitao Xu, Changsheng Yeung, Dit-Yan Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong Department of Mathematics and Applications University of Naples Federico II Naples Italy School of Computing and Information Systems Singapore Management University Singapore School of Computer and Information Technology Beijing Key Laboratory of Traffic Data Analysis and Mining Beijing Jiaotong University Beijing China National Lab of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing100190 China

The vulnerability of Deep Neural Networks (DNNs) to adversarial attacks poses a significant challenge to their deployment in safety-critical applications. While extensive research has addressed various attack scenarios, the no-box attack setting—where adversaries have no prior knowledge, including access to training data of the target model—remains relatively underexplored despite its practical relevance. This work presents a systematic investigation into leveraging large-scale Vision-Language Models (VLMs), particularly CLIP, as surrogate models for executing no-box attacks. Our theoretical and empirical analyses reveal a key limitation in the execution of no-box attacks stemming from insufficient discriminative capabilities for direct application of vanilla CLIP as a surrogate model . To address this limitation, we propose MF-CLIP (Margin-based Fine-tuned CLIP), a novel framework that enhances CLIP’s effectiveness as a surrogate model through margin-aware feature space optimization. Comprehensive evaluations across diverse architectures and datasets demonstrate that MF-CLIP substantially advances the state-of-the-art in no-box attacks, surpassing existing baselines by 15.23% on standard models and achieving a 9.52% improvement on adversarially trained models. Our code (attached in the supplement) will be made publicly available to facilitate reproducibility and future research in this direction. Copyright © 2023, The Authors. All rights reserved.

关键词： Visual languages

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