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Exploiting comments information to improve legal public opinion news abstractive summarization

Frontiers of Computer science 2022年第6期16卷 31-40页

作者： Yuxin HUANG Zhengtao YU Yan XIANG Zhiqiang YU Junjun GUO Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650500China Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and TechnologyKunming650500China

Automatically generating a brief summary for legal-related public opinion news(LPO-news,which contains legal words or phrases)plays an important role in rapid and effective public opinion *** LPO-news,the critical case elements which are significant parts of the summary may be mentioned several times in the reader ***,we investigate the task of comment-aware abstractive text summarization for LPO-news,which can generate salient summary by learning pivotal case elements from the reader *** this paper,we present a hierarchical comment-aware encoder(HCAE),which contains four components:1)a traditional sequenceto-sequence framework as our baseline;2)a selective denoising module to filter the noisy of comments and distinguish the case elements;3)a merge module by coupling the source article and comments to yield comment-aware context representation;4)a recoding module to capture the interaction among the source article words conditioned on the *** experiments are conducted on a large dataset of legal public opinion news collected from micro-blog,and results show that the proposed model outperforms several existing state-of-the-art baseline models under the ROUGE metrics.

关键词： legal public opinion news abstractive summarization comment comment-aware context case elements bidirectional attention

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Laser ranging and reflectance discrimination based on stretched noise-like pulse

Laser ranging and reflectance discrimination based on stretc...

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2024 Asia Communications and Photonics Conference, ACP 2024 and International Conference on information Photonics and Optical Communications, IPOC 2024

作者： Yao, Yao Sun, Yixiang Liu, Haoguang Lu, Long An, Yu Luo, Yiyang Sun, Qizhen Shum, Ping Perry Key Laboratory of Optoelectronic Technology and Systems Ministry of Education Chongqing University Chongqing China School of Optics and Electronic Information Huazhong University of Science and Technology Wuhan China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China

ISBN: (纸本)9798350379266

We propose a chaotic ultrafast laser-based ranging scheme. Employing the noise-like pulse stretched by the time-stretch dispersive Fourier transform technique, the distance and surface reflectance information can be obtained through a cross-correlation operation. It is demonstrated that this approach has a range resolution of 6 mm and can identify the relative reflectance information of the target. © 2024 IEEE.

关键词： laser ranging noise-like pulse reflectance discrimination

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Cluster-preserving sampling algorithm for large-scale graphs

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science China(information sciences) 2023年第1期66卷 60-76页

作者： Jianpeng ZHANG Hongchang CHEN Dingjiu YU Yulong PEI Yingjun DENG National Digital Switching System E&T Research Center Information Engineering University Network Systems Department of the Strategic Support Force School of Computer Science and Technology Eindhoven University of Technology Center for Applied Mathematics Tianjin University

Graph sampling is a very effective method to deal with scalability issues when analyzing largescale graphs. Lots of sampling algorithms have been proposed, and sampling qualities have been quantified using explicit properties(e.g., degree distribution) of the sample. However, the existing sampling techniques are inadequate for the current sampling task: sampling the clustering structure, which is a crucial property of the current networks. In this paper, using different expansion strategies, two novel top-leader sampling methods(i.e., TLS-e and TLS-i) are proposed to obtain representative samples, and they are capable of effectively preserving the clustering structure. The rationale behind them is to select top-leader nodes of most clusters into the sample and then heuristically incorporate peripheral nodes into the sample using specific expansion strategies. Extensive experiments are conducted to investigate how well sampling techniques preserve the clustering structure of graphs. Our empirical results show that the proposed sampling algorithms can preserve the population's clustering structure well and provide feasible solutions to sample the clustering structure from large-scale graphs.

关键词： graph sampling clustering structure top-leader nodes expansion strategies large-scale graphs

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Machine Learning-Based Calibration Approaches for Single-Beam and Multiple-Beam Distance Sensors

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IEEE Sensors Journal 2024年第1期24卷 975-983页

作者： Syu, Jia-Hao Lin, Jerry Chun-Wei Biernacki, Piotr Ziebinski, Adam National Taiwan University Department of Computer Science and Information Engineering Taipei10617 Taiwan Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Department of Distributed Systems and Informatics Devices Gliwice44-100 Poland Silesian University of Technology Department of Distributed Systems and Informatic Devices Gliwice44-100 Poland

Sensors are the foundation to facilitate smart cities, smart grids, and smart transportation, and distance sensors are especially important for sensing the environment and gathering information. Researchers have developed various methods to calibrate distance sensors;however, they mainly focus on using external information for calibration, which is inefficient and computationally expensive. To alleviate the above problems, we propose machine learning (ML)-based calibration approaches for distance sensors. We develop two calibration mechanisms, where the naive mechanism directly predicts the true distance, while the residual mechanism predicts the residual for calibration. The conventional ML regression algorithms are then adopted to predict the true distance or calibration residual. Experimental results show that the designed residual calibration mechanism outperforms the naive mechanism by reducing the root mean square error (RMSE) by 92.2% and mean absolute error (MAE) by 93.3% in the fitting task. In prediction, the proposed 2-D-residual mechanism achieves an improvement of 78.6% and 65.7% compared to the state-of-the-art method. The experimental results show the effectiveness and generalization of the proposed ML-based calibration method, especially for the 2-D mechanism, which achieves the highest robustness in all fitting and prediction tasks. © 2001-2012 IEEE.

关键词： Calibration

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MMH-FE:AMulti-Precision and Multi-Sourced Heterogeneous Privacy-Preserving Neural Network Training Based on Functional Encryption

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Computers, Materials & Continua 2025年第3期82卷 5387-5405页

作者： Hao Li Kuan Shao Xin Wang Mufeng Wang Zhenyong Zhang The State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China Key Laboratory of Computing Power Network and Information Security Ministry of EducationShandong Computer Science CenterQilu University of Technology(Shandong Academy of Sciences)Jinan250014China China Industrial Control Systems Cyber Emergency Response Team Beijing100040China

Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model ***,dishonest clouds may infer user data,resulting in user data *** schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing *** address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training ***,we design a multi-precision functional encryption computation based on Euclidean ***,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced ***,we conduct experiments on three *** results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×2^(24) times compared to the previous best approach.

关键词： Functional encryption multi-sourced heterogeneous data privacy preservation neural networks

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INNSE: Invertible neural network-based DNA image storage with self-correction encoding

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Computational and Structural Biotechnology Journal 2025年 27卷 2492-2502页

作者： Zheng, Yanfen Zhang, Xiaokang Sun, Lijun Cao, Ben Wang, Bin Zhang, Qiang Zheng, Pan School of Computer Science and Technology Dalian University of Technology Liaoning Dalian116024 China The Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Liaoning Dalian116622 China Department of Accounting and Information Systems University of Canterbury Upper Riccarton Christchurch8140 New Zealand

DNA storage has become an alternative to silicon-based storage of media. However, when used to store multimodal data such as images, it fails to take full advantage of the characteristics of high correlation and variability present in such data, and currently remains inferior in terms of encoding density and time complexity. It also has the shortcoming of weak performance in terms of error correction methods to address insertion and deletion errors caused by error crosstalk. Therefore, we proposed an invertible neural network-based DNA image storage self-correction encoding method (INNSE) that uses the invertibility of network to perform up-down sampling processing on image and video data, thereby greatly reducing the number of DNA sequences required for data storage. A codebook generator was then designed to encode low-dimensional vectors into DNA sequences that meet various constraints. Finally, a self-correction method was constructed to achieve DNA sequence error correction at the base level without adding any redundant information. Our experimental results showed that, compared to the Yin-Yang algorithm, the encoding density of INNSE was increased by 3×, encoding time complexity was reduced by 95.26%. Under a simulated error rate of 2%, PSNR and SSIM were raised by 80.88% and 63.82%, respectively, proving that INNSE has significant advantages in encoding performance and error correction ability. © 2025

关键词： Network coding

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Multi-Criteria Decision-Making Model to Achieve Sustainable Developmental Goals in Industry 4.0 for Smart City Infrastructure

HighTech and Innovation Journal

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HighTech and Innovation Journal 2024年第4期5卷 1135-1153页

作者： Akila, D. Pal, Souvik Sarkar, Bikramjit Jayalaksshmi, S. Muthaiyah, Saravanan Anbananthen, Kalaiarasi Sonai Muthu Department of Computer Applications Saveetha College of Liberal Arts and Sciences Saveetha Institute of Medical and Technical Sciences India Department of Management Information Systems Saveethas College of Liberal Arts and Sciences Saveetha Institute of Medical and Technical Sciences India Department of Computer Science and Engineering JIS College of Engineering Kalyani India Department of Information Technology Vels Institute of Science Technology and Advanced Studies India School of Business and Technology International Medical University Kuala Lumpur57000 Malaysia Faculty of Information Science and Technology Multimedia University Melaka75450 Malaysia

Due to a shortage of funding and other market challenges, Small and Medium-sized Enterprises (SMEs) face difficulties in adopting new technologies. Numerous technological obstacles negatively impact the long-term commercial achievement of SMEs. The deployment of Industry 4.0hopes to resolve these technological challenges. A sustainable city is a complex structure where economic, societal, and ecological components interact and compete. There is a scarcity of l methodologies for measuring interactions in this complex structure. Industry 4.0 aims to obtain higher performance effectiveness, profitability, and automation. The main goal is to develop a reliable method of evaluating small and medium-sized enterprises (SMEs) adopting Industry 4.0 technologies, particularly concerning smart city applications. This paper aims to determine the influence of Industry 4.0 in fostering economic efficiency and sustainability amongst these SMEs. The study introduces a multi-criteria decision-making (SC-MCDM) system designed to test an SME’s achievement of their targeted sustainable developmental goals. A technique for computing the interaction between various standards, i.e., (static interactions and dynamical pattern resemblance), as well as the weightage of variables of every indicator generated by the connection, is included within SC-MCDM. Furthermore, applying the suggested technique is validated by assessing the sustainable development goals of twelve Chinese cities within the Triple Bottom Line (TBL) paradigm. From a geographic-temporal viewpoint, spatial variations in city sustainability reveal regional sustainable inequalities. Indicator scores suggest that the most significant factors for most communities are the lack of research spending, falling financing in stationary assets, shortage of financial development, and inadequate shared transit. Furthermore, the growth of tertiary industries, improvement of energy performance, expansion of green areas, and reduction of poll

关键词： Sustainable city

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Detection of Oscillations in Process Control Loops From Visual Image Space Using Deep Convolutional Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 982-995页

作者： Tao Wang Qiming Chen Xun Lang Lei Xie Peng Li Hongye Su the Department of Electronic Engineering the School of InformationYunnan UniversityKunming 650091China DAMO Academy Alibaba GroupHangzhou 311100China the State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou 310027China

Oscillation detection has been a hot research topic in industries due to the high incidence of oscillation loops and their negative impact on plant *** numerous automatic detection techniques have been proposed,most of them can only address part of the practical *** oscillation is heuristically defined as a visually apparent periodic ***,manual visual inspection is labor-intensive and prone to missed *** neural networks(CNNs),inspired by animal visual systems,have been raised with powerful feature extraction *** this work,an exploration of the typical CNN models for visual oscillation detection is ***,we tested MobileNet-V1,ShuffleNet-V2,Efficient Net-B0,and GhostNet models,and found that such a visual framework is well-suited for oscillation *** feasibility and validity of this framework are verified utilizing extensive numerical and industrial *** with state-of-theart oscillation detectors,the suggested framework is more straightforward and more robust to noise and *** addition,this framework generalizes well and is capable of handling features that are not present in the training data,such as multiple oscillations and outliers.

关键词： Convolutional neural networks(CNNs) deep learning image processing oscillation detection process industries

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Numerical studies of the voltage amplitude effect on plasma characteristics in atmospheric pressure driven by dual LF-RF frequency discharge

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Plasma science and technology 2025年第3期27卷 45-54页

作者： Yilin YU Zhibo ZHAO Qiuyue NIE Shu CHEN Zhonglin ZHANG School of Electrical Engineering and Automation Harbin Institute of TechnologyHarbin 150001People’s Republic of China Laboratory for Space Environment and Physical Sciences Harbin Institute of TechnologyHarbin 150001People’s Republic of China Institute of Scientific and Technical Information Beijing Academy of Science and TechnologyBeijing 100044People’s Republic of China

Dielectric barrier discharges(DBDs)are primarily utilized as efficient sources of large-volume diffuse ***,the synergistic interaction of certain key plasma factors limits their broader *** the present paper,we report numerical investigations of the effects of voltage amplitude in dual-frequency excitation on atmospheric DBDs using a 50 kHz/5 MHz frequency *** results indicate that varying the voltages for low frequency(LF)and radio frequency(RF)significantly influences the electron dynamics during discharge,resulting in distinct spatio-temporal distributions of electron and metastable particle *** findings contribute to the regulation of discharges under atmospheric pressure conditions and facilitate the attainment of non-equilibrium and nonlinear plasma parameters.

关键词： dielectric barrier discharge atmospheric pressure plasma electron dynamics behavior

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Efficient acetoin production from pyruvate by engineered Halomonas bluephagenesis whole-cell biocatalysis

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Frontiers of Chemical science and engineering 2023年第4期17卷 425-436页

作者： Meiyu Zheng Zhenzhen Cui Jing Zhang Jing Fu Zhiwen Wang Tao Chen Department of Biochemical Engineering School of Chemical Engineering and TechnologyTianjin UniversityTianjin 300350China Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering(Ministry of Education) School of Chemical Engineering and TechnologyTianjin UniversityTianjin 300350China Department of Biology and Biological Engineering Chalmers University of TechnologyGothenburg 41296Sweden

Acetoin is an important platform chemical,which has a wide range of applications in many *** bluephagenesis,a chassis for next generation of industrial biotechnology,has advantages of fast growth and high tolerance to organic acid salts and alkaline ***,α-acetolactate synthase andα-acetolactate decarboxylase from Bacillus subtilis 168 were co-expressed in *** to produce acetoin from *** reaction condition optimization and further increase ofα-acetolactate decarboxylase expression,acetoin production and yield were significantly enhanced to 223.4 mmol·L^(-1) and 0.491 mol·mol^(-1) from 125.4 mmol·L^(-1) and 0.333 mol·mol^(-1),***,the highest titer of 974.3 mmol·L^(-1)(85.84 g·L^(-1))of acetoin was accumulated from 2143.4 mmol·L^(-1)(188.6 g·L^(-1))of pyruvic acid within 8 h in fed-batch bioconversion under optimal reaction ***,the reusability of the cell catalysis was also tested,and the result illustrated that the whole-cell catalysis obtained 433.3,440.2,379.0,442.8 and 339.4 mmol·L^(-1)(38.2,38.8,33.4,39.0 and 29.9 g·L^(-1))acetoin in five repeated cycles under the same *** work therefore provided an efficient *** whole-cell catalysis with a broad development prospect in biosynthesis of acetoin.

关键词： acetoin pyruvate α-acetolactate synthetase α-acetolactate decarboxylase Halomonas bluephagenesis whole-cell biocatalysis

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