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2023 International Conference on Artificial Intelligence of Things and Systems, AIoTSys 2023

作者： Cao, Xiaoya Chen, Zhenya Liu, Weisheng Liu, Yuanlong Wang, Wenting Wang, Xin Yang, Ming Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China State Grid Shandong Electric Power Company Jinan China State Grid Shandong Electric Power Research Institute Jinan China

ISBN: (纸本)9798350312270

This paper presents a novel controller design for dealing with the challenges posed by Denial-of-Service (DoS) attacks in the context of Artificial Intelligence of Things (AIOT). The proposed design employs a prediction approach that utilizes uniform quantization for both encoder and decoder, aiming to effectively mitigate data loss during data transmission in scenarios involving DoS attacks. Furthermore, the study investigates the application of dynamic system design as a means to enhance the security defense mechanisms of AIOT, consequently bolstering the overall resilience of the system. The effectiveness and practicality of the proposed approach are validated through comprehensive simulations, providing empirical evidence of its efficacy. © 2023 IEEE.

关键词： System stability

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Application of quantum genetic algorithm in high noise laser image security

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Optoelectronics Letters 2022年第1期18卷 59-64页

作者： MAN Zhenlong LI Jinqing DI Xiaoqiang MU Yining School of Computer Science and Technology Changchun University of Science and TechnologyChangchun 130022China Jilin Province Key Laboratory of Network and Information Security Changchun 130022China Information Center of Changchun University of Science and Technology Changchun 130022China School of Science Changchun University of Science and TechnologyChangchun 130022China

Aiming at the security problem of range gated laser imaging in high noise background,a range gated laser image encryption scheme based on the quantum genetic algorithm(QGA)is *** to the fuzziness of the laser image itself,the randomness and security of the key become more and more important in *** this paper,the chaotic sequence is used as the parent chromosome of the QGA,and the random number satisfying the encryption algorithm is obtained by an iterative genetic *** further improve the security of laser images,some random pixels are stochastically inserted around the laser image before *** random pixels are scrambled together with the ***,an adaptive diffusion method is designed to completely change the original statistical information of the *** simulation and performance analysis show that the scheme has high security.

关键词： image algorithm quantum

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Demand Response Scheme: Achieving Sustainability in Distributed Data Processing 9

Demand Response Scheme: Achieving Sustainability in Distribu...

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9th IEEE International Conference on Data Science in Cyberspace, DSC 2024

作者： Zhai, Xueying Peng, Yunfeng Guo, Xiuping Zhang, Liang Zhang, Wei University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China Beijing University of Posts and Telecommunications School of Economics and Management Beijing China Guizhou Institute of Technology Guizhou Key Laboratory of Electric Power Big Data Guizhou China Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Jinan China

ISBN: (纸本)9798350391367

The rapid development of Internet of Things (IoT) technology has driven the intelligent transformation of various industries, including manufacturing, agriculture, and healthcare, etc., significantly enhancing their management capabilities and decision-making efficiency. Data analysis is crucial, serving as both the core technology of this transformation and a major driving force for advancing industry intelligence. However, the increasing volume of data has led to high energy consumption during data analysis, posing significant challenges to environmental and economic sustainability. Integrating renewable energy sources (RESs) is an effective way to reduce greenhouse gas emissions due to their low-carbon and renewable nature. Additionally, the spatiotemporal variability and complementarity of RES generation and grid electricity prices provide favorable conditions for distributed data processing. Therefore, a two-stage demand response scheme is proposed to reduce carbon emissions and electricity costs by prioritizing data processing in data centers (DCs) where RES is abundant or electricity prices are low, based on RES generation and electricity price signals. Simulation results show that the proposed scheme reduces 36.37% carbon emissions and 20.49% electricity costs compared to the benchmark algorithm, indicating its potential for both environmental and economic optimization. © 2024 IEEE.

关键词： Low emission

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Wrong-of-Thought: An Integrated Reasoning Framework with Multi-Perspective Verification and Wrong information

Wrong-of-Thought: An Integrated Reasoning Framework with Mul...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Zhang, Yongheng Chen, Qiguang Zhou, Jingxuan Wang, Peng Si, Jiasheng Wang, Jin Lu, Wenpeng Qin, Libo School of Computer Science and Engineering Central South University China Research Center for SCIR Harbin Institute of Technology Harbin China Key Laboratory of Computing Power Network and Information Security Ministry of Education Qilu University of Technology Shandong Academy of Sciences China Yunnan University Kunming China

ISBN: (纸本)9798891761681

Chain-of-Thought (CoT) has become a vital technique for enhancing the performance of Large Language Models (LLMs), attracting increasing attention from researchers. One stream of approaches focuses on the iterative enhancement of LLMs by continuously verifying and refining their reasoning outputs for desired quality. Despite its impressive results, this paradigm faces two critical issues: (1) Single verification method: The current paradigm relies solely on a single verification method. (2) Wrong information Ignorance: The traditional paradigm directly ignores wrong information during reasoning and refines the logic paths from scratch each time. To address these challenges, we propose Wrong-of-Thought (WoT), which includes two core modules: (1) Multi-Perspective Verification: A multi-perspective verification method for accurately refining the reasoning process and result, and (2) Wrong information Utilization: Utilizing wrong information to alert LLMs and reduce the probability of LLMs making same mistakes. Experiments on 8 popular datasets and 5 LLMs demonstrate that WoT surpasses all previous baselines. In addition, WoT exhibits powerful capabilities in difficult computation tasks. © 2024 Association for Computational Linguistics.

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A Constructive Method Based on Dynamic Solution Space for Travelling Salesman Problem

A Constructive Method Based on Dynamic Solution Space for Tr...

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International Conference on Advanced Cloud and Big Data (CBD)

作者： Xiaoxin Bai LuLi LuLi Hanqian Wu School of Computer Science and Engineering Southeast University China School of Cyber Science and Engineering Southeast University China Suzhou Centennail College China Key Laboratory of Computer Network and Information Integration of Ministry of Education Southeast University China

Neural combinatorial optimization (NCO) has emerged as a promising field to solve the combinatorial optimization problem (COP) as automatically learning the solvers less relying on domain-specific expert knowledge. Constructive Method (ConsM) is the most widely used approach in NCO for solving various COPs and their variations. However, few literature elucidates the underlying principles of ConsM, hindering further optimization. In this paper, we analyze the efficiency principle of ConsM for COPs from the perspective of discrete solution space and summarize its design principles. These principles can serve as guidelines for designing novel constructive policy. Based on these principles, we reviewed the existing ConsM models and identified that the design of existing decoder introduced certain noises, which negatively impacted the policy performance. Therefore, we designed a novel decoder in line with the aforementioned principles. Notably, our method can be applied to all ConsM models and yielded significant improvements compared to the original. We evaluated our method on Traveling Salesman Problem(TSP) and the experimental results verified the effectiveness and efficiency of our method, supporting our analysis of ConsM. In particular, we reduced the average optimality gap from 1.16% to 0.62% for TSP100 compared to Sym-NCOs, keeping the hyperparameters constant.

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Cross-chain Transaction Tracking Protocol based on Multi-dimensional Digital Watermarking Fingerprints

Cross-chain Transaction Tracking Protocol based on Multi-dim...

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Frontiers Technology of information and computer (ICFTIC), IEEE International Conference on

作者： Duanzhen Li Shujiang Xu Haochen He Hongrui Xue Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan PR China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan PR China

ISBN: (数字)9798331541750

ISBN: (纸本)9798331541767

Cross-chain technology plays a critical role in the process of interconnecting blockchains. However, all attention has been focused on how to achieve efficient cross-chain interoperability protocols, thus neglecting the most important security issues in cross-chain data interaction. Frequent network attacks and data privacy leaks have sounded the alarm for the safety of cross-chain data transactions. How to solve the problem of data ownership tracking in cross-chain transactions has become the top priority. This paper designs a cross-chain transaction tracking protocol based on multi-dimensional digital watermark fingerprints, using robust watermark, fragile watermark, and user identity key to achieve multi-dimensional tracking and supervision of cross-chain data transactions. Finally, this paper analyzes the feasibility and efficiency of the proposed protocol through experiments.

关键词： Data privacy Protocols Watermarking Fingerprint recognition Blockchains Safety Discrete wavelet transforms Interoperability

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Semantic recommendation through Reinforcement Learning and weighted meta-paths

Semantic recommendation through Reinforcement Learning and w...

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2022 International Conference on Electronic information Engineering, Big Data, and computer Technology, EIBDCT 2022

作者： Yu, Jing Lang, Yue Li, Xuewen Zhang, Jin Zheng, Shaojie Gong, Jibing School of Information Science and Engineering Yanshan University Qinhuangdao066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University Qinhuangdao066004 China Key Laboratory for Software Engineering of Hebei Province Yanshan University Qinhuangdao066004 China

ISBN: (纸本)9781510655133

Explainable recommendation systems, which can produce high-accuracy recommendations and help users make quick decisions, have become a hotspot in research field. Most of existing research algorithms committed to improving the accuracy of recommendation, but ignored the interpretability of recommendation. We propose a semantic recommendation algorithm through Reinforcement Learning and weighted meta-paths which analyzes and selects the meta-path, and uses Reinforcement Learning network to train the weight of meta-path. This method can effectively solve data sparsity, improve the accuracy of recommendation, and increase interpretability. Compared with the baseline method, indicators of the recommended methods for integrating Reinforcement Learning with Heterogeneous information networks have been greatly improved, as verified and compared on a real MovieLens 1M dataset. Experimental results prove that the algorithm can effectively improve the accuracy and interpretability of the recommendation. © 2022 SPIE.

关键词： Reinforcement learning

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Prior Knowledge Enhanced Topic Model For Research Topic Evolution Analysis

Prior Knowledge Enhanced Topic Model For Research Topic Evol...

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International Conference on Advanced Cloud and Big Data (CBD)

作者： Zhongyuan Kang Lu Zhang Zheng Chen Haiting Zhu Gaofeng He Mingwei Tang School of Computer Science Nanjing Audit University Nanjing China Key Laboratory of Computer Network and Information Integration (Southeast University) Ministry of Education School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing China School of Engineering Audit Nanjing Audit University Nanjing China

ISBN: (数字)9798331511074

ISBN: (纸本)9798331511081

Extracting and analyzing topics from the scientific literature is crucial for identifying the research hotspots, under-standing the developmental trajectory, and further revealing and predicting the evolutionary trends of a research field. Existing topic models like LDA and ETM can effectively extract topics from large text corpora. However, they struggle with incor-porating the domain-specific prior knowledge that is inherent and can be easily obtained in the scientific literature (e.g., the keywords in the paper), causing weekly targeted but over generic topic extraction and representation. To address this problem, we propose a Prior Attention Topic Model (PATM), which leverages inherent keywords in the scientific literature as prior knowledge for more targeted topic extracting and representation. Specifically, we first construct a prior attention weight matrix to guide the document embedding to pay more attention on the keywords, and then, a multi-view Variational Autoencoder (VAE) is utilized to separately encode different literature types, combining their unique characteristics while sharing one latent space. At last, the topic-word probability martix learned from the VAE are regarded as the topic representations. The experimental results and case study demonstrate that the proposed PATM is effective in extracting topics in the scientific literature, including papers and patents, and by analyzing these topics, we clearly reveal the thematic evolution of the research about emerging information technologies empowering auditing.

关键词： Patents Analytical models Solid modeling Big Data Solids Market research Data models Trajectory Data mining information technology

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Open-vocabulary 3D Semantic Understanding via Affinity Neural Radiance Fields

Open-vocabulary 3D Semantic Understanding via Affinity Neura...

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Next Generation Data-driven networks (NGDN), International Conference on

作者： Yujie Fan Huan Luo Computer and Data Science Fuzhou University Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China

ISBN: (数字)9798350388374

ISBN: (纸本)9798350388381

Three-dimensional semantic understanding using only several multi-view images can largely reduce the communication burden on the network. In addition, while point clouds are extensively studied for 3D scene understanding, utilization of multi-view image data offers rich visual details and texture information. However, challenges persist in lifting 2D semantic features to 3D space and leveraging language for segmentation. Inspired by recent advancements, this paper proposes a method that combines CLIP features and SAM masks to create a feature field capable of segmenting objects via natural language text across 2D multi-view and 3D Gaussian splatting. It offers a promising function for extracting 3D assets for game engines and the metaverse. Our method involves mask generation from video frames, extracting physical scales via RGB Nerf with masks, and organizing hierarchical information for semantic comprehension. In the training process, affinity features maintain scale properties and guide CLIP feature generation with auto weights blending for semantic robustness. A straightforward 3D splatting CLIP feature approach and canonical text methodology enhance query robustness across 2D multi-view and 3D splatting through relevance score calculation based on text CLIP features for inference. Experimental results demonstrate promising improvements in semantic understanding of 3D scenes.

关键词： Training Image segmentation Vocabulary Visualization Three-dimensional displays Semantics Natural languages Neural radiance field Feature extraction Robustness

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A Harmonic Current Self-Compensation Control Strategy of DC Active Power Filter

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IEEE Journal of Emerging and Selected Topics in Power Electronics 2025年

作者： Li, Gaoxiang Wu, Huanchao Chen, Jining Liu, Xiao Guangxi University Guangxi Key Laboratory of Power System Optimization and Energy Technology School of Electrical En-gineering Nanning530004 China Guangxi Zhuang Autonomous Region Information Center Guangxi Key Laboratory of Digital Infrastructure Nanning530200 China Guangxi Key Laboratory of Multimedia Communications and Network Technology Guangxi Colleges and Universities Key Laboratory of Multimedia Communications and Information Processing School of Computer Electronics and Information Guangxi Uni-versity Nanning530004 China

Due to the diversity of nonlinear loads, the harmonic frequency of the DC microgrid is unpredictable, which poses a challenge to traditional DC active power filters (DC-APF). Firstly, the harmonic compensation mechanism and characteristics of the DC-APF with classical control strategy are analyzed. For the classical DC-APF, the voltage control and harmonic extraction are independent of each other, which may lead to their conflict and reduce the harmonic compensation performance. To address this issue, a harmonic current self-compensation control strategy of DC-APF is proposed, which uses a first-order inertia controller in the voltage loop and can simultaneously achieve voltage control and harmonic extraction. Then, the mechanism, characteristics, and parametric design method of the proposed harmonic current self-compensation control are introduced in detail. Compared with the classical DC-APF, the proposed DC-APF does not require any harmonic extraction filter and has better harmonic current compensation performance. Finally, the proposed control strategy and theoretical analysis are verified by simulation and experiment. © 2025 IEEE. All rights reserved.

关键词： Active filters

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