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CDCAT: A Multi-Language Cross-Document Entity and Event Coreference Annotation Tool

Tsinghua science and Technology 2022年第3期27卷 589-598页

作者： Yang Xu Boming Xia Yueliang Wan Fan Zhang Jiabo Xu Huansheng Ning School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Beijing Engineering Research Center for Cyberspace Data Analysis and Applications Beijing 100083China Research Institute with Run Technologies Company Ltd.Beijing 100192China School of Information Engineering Xinjiang Institute of EngineeringUrumqi 830091China

A tool for the manual annotation of cross-document entity and event coreferences that helps annotators to label mention coreference relations in text is essential for the annotation of coreference corpora. To the best of our knowledge, CROss-document Main Events and entities Recognition(CROMER) is the only open-source manual annotation tool available for cross-document entity and event coreferences. However, CROMER lacks multi-language support and extensibility. Moreover, to label cross-document mention coreference relations, CROMER requires the support of another intra-document coreference annotation tool known as Content Annotation Tool, which is now unavailable. To address these problems, we introduce Cross-Document Coreference Annotation Tool(CDCAT), a new multi-language open-source manual annotation tool for cross-document entity and event coreference, which can handle different input/output formats, preprocessing functions, languages, and annotation systems. Using this new tool, annotators can label a reference relation with only two mouse clicks. Best practice analyses reveal that annotators can reach an annotation speed of 0.025 coreference relations per second on a corpus with a coreference density of 0.076 coreference relations per word. As the first multi-language open-source cross-document entity and event coreference annotation tool, CDCAT can theoretically achieve higher annotation efficiency than CROMER.

关键词： event coreference entity coreference manual annotation tool natural language processing

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Matrix of Fused Features-based Approach for Tor Application Classification 26

Matrix of Fused Features-based Approach for Tor Application ...

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26th International Conference on computer Supported Cooperative Work in Design, CSCWD 2023

作者： Liu, Dong Wang, Can Zhang, Weidong Wu, Xuangou Anhui University of Technology School of Computer Science and Technology Ma'anshan China Anhui Engineering Research Center for Intelligent Applications and Security of Industrial Internet Ma'anshan China

ISBN: (纸本)9798350331684

Encrypted traffic identification is critical for detecting network attacks and improving the quality of service, making it an essential aspect of cyberspace security. However, existing methods for classifying Tor applications are limited by their reliance on single packet size or time-related features of traffic flows, which limits the potential for improving classification accuracy. To address this challenge, we propose an end-to-end classification framework called the Matrix of Fused Features Network (MFFN). This framework fuses direction, packet size, and time-related features of the raw flows to generate matrices that represent Tor applications. We then use the residual net-work, a popular deep learning model, to automatically extract potential features from these matrices and classify them into Tor applications. We evaluate our approach on the public dataset ISCXTor2016, and experimental results demonstrate that MFFN achieves 97% accuracy for Tor application classification, outperforming existing methods. © 2023 IEEE.

关键词： Quality of service

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Novel Audio Mosaic Using LPC-Coefficient and Excitation-Codeword Permutations

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IEEE Signal Processing Letters 2024年 31卷 1690-1694页

作者： Tsai, Morris C.-H. Wu, Hsiao-Chun Huang, Scott C.-H. Chang, Shih Yu National Tsing Hua University Department of Electrical Engineering Hsinchu30013 Taiwan Louisiana State University School of Electrical Engineering and Computer Science Baton RougeLA70803 United States Yuan Ze University Innovation Center for Ai Applications Taoyuan City32003 Taiwan San Jose State University Department of Applied Data Science San JoseCA95192 United States

In this letter, a novel light-weight audio mosaic scheme using permutations of linear predictive coding (LPC) coefficients as LPC has been widely adopted in many audio codecs (coder-encoders) nowadays. We establish the theoretical secrecy analysis with respect to the degree of the original LPC polynomial and the minimum-phase population of permuted LPC polynomials. The mosaic (destructuring) performance in terms of DCT-KLD (Kullback-Leibler divergence of discrete cosine transform) is also evaluated through simulations. In comparison with the existing audio-mosaic method using waveform permutations, our proposed new audio-mosaic scheme using LPC-coefficient permutations can achieve a much better mosaic performance (a much higher DCT-KLD) subject to the same key size. © 1994-2012 IEEE.

关键词： Cryptography

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Evolutional Codes: Novel Efficient Graph Data Representation for Mobile Edge Computing

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IEEE Transactions on Network science and engineering 2024年第1期11卷 1387-1397页

作者： Sun, Elaine Y.-N. Wu, Hsiao-Chun Huang, Scott C.-H. Kuan, Yen-Cheng Yung, Chi National Tsing Hua University Department of Electrical Engineering Hsinchu30013 Taiwan Louisiana State University School of Electrical Engineering and Computer Science Baton RougeLA70803 United States Yuan Ze University Innovation Center for Ai Applications Chungli32003 Taiwan International College of Semiconductor Technology Hsinchu30010 Taiwan

To transmit big graph data emerging from prevalent social networks and biological networks over mobile devices has become challenging nowadays. Since graphs are usually represented by the associated adjacency matrices or graph data structures, dynamic node (vertex) re-ordering to reflect the nodes' real relations (for example, spatial or structural relations) is desirable in practice but impossible for these two existing graph-representation methods. Lately, we proposed a novel evolutional coding technique, which can restructure graph data dynamically, flexibly, and efficiently for transmission among mobile devices. Memory efficiency, in terms of number of memory storage units, is a crucial performance measure for mobile edge computing. To select the optimal graph-representation strategy for arbitrary graph data, we define a new graph-taxonomy metric dependent on the edge density (edges per node) in this work. According to our newly defined graph-taxonomy metric, one can choose the optimal graph-representation solution among the three aforementioned methods in terms of required memory-storage space for any application. Pertinent theorems and proofs for the underlying comparative studies on graph representation are presented in this article. © 2013 IEEE.

关键词： Digital storage

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La-substituted W-type barium-nickel ferrites for tunable and high-performance electromagnetic wave absorption

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International Journal of Minerals,Metallurgy and Materials 2025年第3期32卷 645-656页

作者： Long Wang Jiurong Liu Shenghui Xie Yanli Deng Zhou Wang Shanyue Hou Shengying Yue Gang Wang Na Wu Zhihui Zeng Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials(Ministry of Education) School of Materials Science and EngineeringShandong UniversityJinan 250061China Electronic Materials Research Laboratory Key Laboratory of the Ministry of Education and International Center for Dielectric ResearchSchool of Electronic Science and EngineeringXi’an Jiaotong UniversityXi’an 710049China Army Engineering University of PLA College of Field Engineering Nanjing 210007China Laboratory for Multiscale Mechanics and Medical Science State Key Laboratory for Strength and Vibration of Mechanical StructuresSchool of AerospaceXi’an Jiaotong UniversityXi’an 710049China Department of Electrical and Computer Engineering Beckman Institute for Advanced Science and TechnologyUniversity of Illinois at Urbana-ChampaignUrbana 61801USA School of Chemistry and Chemical Engineering Shandong UniversityJinan 250100China

W-type barium-nickel ferrite(BaNi_(2)Fe_(16)O_(27))is a highly promising material for electromagnetic wave(EMW)absorption be-cause of its magnetic loss capability for EMW,low cost,large-scale production potential,high-temperature resistance,and excellent chemical ***,the poor dielectric loss of magnetic ferrites hampers their utilization,hindering enhancement in their EMW-absorption *** efficient strategies that improve the EMW-absorption performance of ferrite is highly desired but re-mains ***,an efficient strategy substituting Ba^(2+)with rare earth La^(3+)in W-type ferrite was proposed for the preparation of novel La-substituted ferrites(Ba_(1-x)LaxNi_(2)Fe_(15.4)O_(27)).The influences of La^(3+)substitution on ferrites’EMW-absorption performance and the dissipative mechanism toward EMW were systematically explored and ***^(3+)efficiently induced lattice defects,enhanced defect-induced polarization,and slightly reduced the ferrites’bandgap,enhancing the dielectric properties of the ***^(3+)also enhanced the ferromagnetic resonance loss and strengthened magnetic *** effects considerably improved the EMW-absorption perform-ance of Ba_(1-x)LaxNi_(2)Fe_(15.4)O_(27)compared with pure W-type *** x=0.2,the best EMW-absorption performance was achieved with a minimum reflection loss of-55.6 dB and effective absorption bandwidth(EAB)of 3.44 GHz.

关键词： electromagnetic wave absorption W-type barium ferrite rare earth dielectric

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Mechanistic modeling of copper corrosions in data center environments

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Building Simulation 2024年第3期17卷 483-492页

作者： Rui Zhang Jianshun Zhang Roger Schmidt Jeremy L.Gilbert Department of Mechanical and Aerospace Engineering College of Engineering and Computer ScienceSyracuse UniversitySyracuseNY13244USA Buildings and Transportation Science Division Oak Ridge National LaboratoryOak RidgeTN37830USA SyracuseCoE-New York Center of Excellence in Environmental and Energy Systems Syracuse University727 E.Washington StreetSyracuseNY13244USA Department of Bioengineering Clemson UniversityClemson-Medical University of South Carolina Bioengineering ProgramCharlestonSC29425USA

Air-side economizers are increasingly used to take advantage of“free-cooling”in data centers with the intent of reducing the carbon footprint of ***,they can introduce outdoor pollutants to indoor environment of data centers and cause corrosion damage to the information technology *** evaluate the reliability of information technology equipment under various thermal and air-pollution conditions,a mechanistic model based on multi-ion transport and chemical reactions was *** model was used to predict Cu corrosion caused by Cl_(2)-containing pollutant *** also accounted for the effects of temperature(25℃and 28℃),relative humidity(50%,75%,and 95%),and *** also identified higher air temperature as a corrosion barrier and higher relative humidity as a corrosion accelerator,which agreed well with the experimental *** average root mean square error of the prediction was 13.7Å.The model can be used to evaluate the thermal guideline for data centers design and operation when Cl_(2)is present based on pre-established acceptable risk of corrosion in data centers’environment.

关键词： chloride pollutant mixture copper corrosion model data center temperature relative humidity synergistic effect

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A Privacy-preserving Surface Defect Detection Scheme for Strip Steel 38

A Privacy-preserving Surface Defect Detection Scheme for Str...

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38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023

作者： Tang, Xuan Zheng, Xiao Wang, Xiujun Huang, Jun Anhui University of Technology School of Computer Science and Technology Maanshan China Hefei Comprehensive National Science Center Institute of Artificial Intelligence Hefei China Anhui Engineering Research Center for Intelligent Applications and Security of Industrial Internet Maanshan China

ISBN: (纸本)9798350303636

As the Industrial Internet becomes an integral part of the steel industry, the next question is naturally how to combine powerful computing power as well as data sharing capabilities for effective detection of surface defects in strip steel. However, existing classification algorithms focus on the accuracy of the classification without considering how to protect the privacy of the manufacturer or the company, as the data is uploaded to the cloud and easily discovered by attackers. To address this problem, in this paper, we propose a privacy-preserving classification scheme that provides both privacy protection and improved classification accuracy in the industrial Internet. Specifically, our approach first adaptively encrypts the original steel image using a homomorphic encryption scheme. The homomorphic encryption scheme is followed by designing a convolutional neural network which can handle the encrypted images well and provide better classification accuracy. In addition, the execution efficiency of our method can be further improved under the edge computing architecture by using distributed computing with cloud-edge architecture. Experiments conducted on real image datasets of strip steel surface show that the encryption scheme not only protects the privacy of manufacturers or companies contained in the steel images and guarantees classification accuracy, but also outperforms existing methods in terms of efficiency. © 2023 IEEE.

关键词： Convolution neural network Defect category detection Edge computing Homomorphic encryption Privacy-preserving Strip steel

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Social-Aware Group Display Configuration in VR Conference 38

Social-Aware Group Display Configuration in VR Conference

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38th AAAI Conference on Artificial Intelligence, AAAI 2024

作者： Hsu, Bay-Yuan Shen, Chih-Ya Yuan, Hao Shan Lee, Wang-Chien Yang, De-Nian Department of Industrial Engineering and Engineering Management National Tsing Hua University China Department of Computer Science National Tsing Hua University China Institute of Information Systems and Applications National Tsing Hua University China Department of Computer Science and Engineering Pennsylvania State University United States Institute of Information Science Academia Sinica Taiwan Research Center of Information Technology Innovation Academia Sinica Taiwan

ISBN: (纸本)1577358872

Virtual Reality (VR) has emerged due to advancements in hardware and computer graphics. During the pandemic, conferences and exhibitions leveraging VR have gained attention. However, large-scale VR conferences, face a significant problem not yet studied in the literature - displaying too many irrelevant users on the screen which may negatively impact the user experience. To address this issue, we formulate a new research problem, Social-Aware VR Conference Group Display Configuration (SVGD). Accordingly, we design the Social Utility-Aware VR Conference Group Formation (SVC) algorithm, which is a 2-approximation algorithm to SVGD. SVC iteratively selects either the P-Configuration or S-Configuration based on their effective ratios. This ensures that in each iteration, SVC identifies and chooses the solution with the highest current effectiveness. Experiments on real metaverse datasets show that the proposed SVC outperforms 11 baselines by 75% in terms of solution quality. Copyright © 2024, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Virtual reality

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CNN-Based Classification and Diagnosis of Alzheimer's from Baseline MRI Scans

CNN-Based Classification and Diagnosis of Alzheimer's from B...

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iNnovative Informatics of Biskra (ISNIB), International Symposium on

作者： Manel Femmam Amel Saraoui Abdeljalil Naceri Maroua Grid Mohamed Elkabir Fareh Sami Slimani Computer Science Department Laboratory of Science for mathematics computer science and engineering applications University Center of Barika Barika Algeria Computer Science Department LINFI Laboratory Biskra University Biskra Algeria

ISBN: (数字)9798331509576

ISBN: (纸本)9798331509583

The diagnosis of neurodegenerative diseases like Alzheimer's remains a medical challenge, relying heavily on physicians' interpretation of symptoms. Early detection and man-agement are critical for improving patient outcomes, but there is a lack of automated tools to assist in decision-making. This project aims to address this gap a framework for detecting Alzheimer's disease from MRI scans. A convolutional neural network (CNN) is used in the proposed method to classify images into four categories: No Dementia (ND), Very Mild Dementia (VMD), Mild Dementia (MD), and Moderate Dementia (MOD). Leveraging the proven capabilities of CNNs in medical image classification, a tailored architecture was designed and implemented. The model delivered strong performance, demonstrating its potential for early detection of Alzheimer's. This system could be used in clinical settings to assist physicians in identifying cases of Alzheimer's disease and improving diagnostic efficiency.

关键词： Deep learning Magnetic resonance imaging Medical services Brain modeling Transformers Convolutional neural networks Alzheimer's disease Informatics Medical diagnostic imaging Overfitting

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Analytical Study of the Features and Parameters of Off-Angle Iris Image vs. Deep Learning Model

Analytical Study of the Features and Parameters of Off-Angle...

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2024 International Conference on Decision Aid sciences and applications, DASA 2024

作者： Suleiman, Aghiad Khedr Shafek, Darin Mahfuri, Mahmoud Khishe, Mohammad Saeed, Ali Ghwanmeh, Sameh Alma'Moon University College Cybersecurity and Cloud Computing Technologies Engineering Dept. Baghdad Iraq Alma'Moon University College Computer Engineering Techniques Dept. Baghdad Iraq International University for Science and Technology Computer and Information Technology Department Syria Innovation Center for Artificial Intelligence Applications Yuan Ze University Taiwan Jadara Research Center Jadara University Jordan Jordan Computer Center Northern Technical University Ninevah Iraq College of Computer Information Technology Computer Science Dept American University in the Emirates United Arab Emirates

ISBN: (纸本)9798350369106

This paper presents an analytical study and a technique for extracting the features of a common case of images of the iris called off-angle iris which was taken for persons identification systems. The main problem when using biological iris measurements to identify the persons is the difficulty of identifying and extracting features of the iris. This problem is increasing when dealing with off-angle iris and it leads to decreased system accuracy and increased system rate error. In return, all the transfer learning techniques face difficulties in the case of heavily degraded data and partially occluded, and off-angle. A new method has a whole new methodology to deal with the image as it is without transformation processes. A new algorithm has been included for extracting features of the iris through the pupil switching points. The most discriminating points of the iris depend on the biological human eye statistics and analytical study. It has been trained and tested on the common images of the off-angle iris database so-called: 'CASIA Iris 1.0'. It has been implemented in the MATLAB environment. The results showed the efficiency of this technique, high precision and more importantly low failed acceptance rate. It emphasized that it is adaptive as well as efficiency improvement of the system. © 2024 IEEE.

关键词： Contrastive Learning

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