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International Conference on Computer Supported Cooperative Work in Design

作者： Qingyu Xu Jiguo Yu Anming Dong Zihao Shang Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China School of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Big Data Institute Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Shandong Data Intelligence Information Technology Co. Ltd. Jinan China

ISBN: (数字)9798350349184

ISBN: (纸本)9798350349191

In the context of Industry 4.0 and the rise of intelligent manufacturing, the quality of industrial products is becoming more and more important. Strip steel surface defect detection, as a key link in industrial production, is crucial to ensure the quality of industrial products. However, due to the irregularity of the defect scale and the inconspicuous defect features in the surface defect image of strip steel, it is difficult for the existing detection algorithms to realize the effective detection of defects. In order to better extract the features of defects and improve the network’s ability to detect defects, this paper proposes an algorithm for detecting surface defects on industrial strip steel based on receptive field and feature information supplementation. First, we design a receptive field (RF) module to replace the residual structure in the C3 module, which we name C3RF. This module can effectively increase the network’s receptive field, allowing the network to fully capture irregular defect features without increasing the cost. Second, for the characteristics that defective features are not obvious and tend to lose detail information as the network deepens, an extra information supplemental branching feature fusion pyramid (EFPN) is proposed on the basis of the original PAFPN architecture to compensate for the detail information that is lost by the fragile features in deeper layers. Finally, convolutional block attention module (CBAM) is introduced to replace the spatial pooling pyramid (SPPF) in the baseline network, which enhances the contrast between defects and backgrounds, and improves the classification and localization ability of the network. Our network achieves an accuracy of 82.2% on the publicly available strip steel defect detection dataset, which is a 4.0% improvement over the baseline. The results show that the network constructed in this paper can realize effective defect detection.

关键词： Radio frequency Location awareness Strips Production Feature extraction Real-time systems Hardware

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Meet Changes with Constancy: Learning Invariance in Multi-Source Translation 28

Meet Changes with Constancy: Learning Invariance in Multi-So...

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28th International Conference on Computational Linguistics, COLING 2020

作者： Liu, Jianfeng Luo, Ling Ao, Xiang Song, Yan Xu, Haoran Ye, Jian Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences China Beijing Key Laboratory of Mobile Computing and Pervasive Device China Key Laboratory of Intelligent Information Processing Chinese Academy of Sciences China The Chinese University of HongKong Shenzhen China Shenzhen Research Institute of Big Data China

ISBN: (纸本)9781952148279

Multi-source neural machine translation aims to translate from parallel sources of information (e.g. languages, images, etc.) to a single target language, which has shown better performance than most one-to-one systems. Despite the remarkable success of existing models, they usually neglect the fact that multiple source inputs may have inconsistencies. Such differences might bring noise to the task and limit the performance of existing multi-source NMT approaches due to their indiscriminate usage of input sources for target word predictions. In this paper, we attempt to leverage the potential complementary information among distinct sources and alleviate the occasional conflicts of them. To accomplish that, we propose a source invariance network to learn the invariant information of parallel sources. Such network can be easily integrated with multi-encoder based multi-source NMT methods (e.g. multi-encoder RNN and transformer) to enhance the translation results. Extensive experiments on two multi-source translation tasks demonstrate that the proposed approach not only achieves clear gains in translation quality but also captures implicit invariance between different sources. © 2020 COLING 2020 - 28th International Conference on Computational Linguistics, Proceedings of the Conference. All rights reserved.

关键词： Signal encoding

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Dynamical reciprocity in interacting games: Numerical results and mechanism analysis

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Physical Review E 2022年第5期105卷 054302-054302页

作者： Rizhou Liang Qinqin Wang Jiqiang Zhang Guozhong Zheng Lin Ma Li Chen School of Physics and Information Technology Shaanxi Normal University Xi'an 710062 People's Republic of China School of Physics and Electronic-Electrical Engineering Ningxia University Yinchuan 750021 People's Republic of China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing 100191 People's Republic of China Robert Koch-Institute Nordufer 20 13353 Berlin Germany

We study the evolution of two mutually interacting pairwise games on different topologies. On two-dimensional square lattices, we reveal that the game-game interaction can promote the cooperation prevalence in all cases, and the cooperation-defection phase transitions even become absent and fairly high cooperation is expected when the interaction becomes very strong. A mean-field theory is developed that points out dynamical routes arising therein. Detailed analysis shows indeed that there are rich categories of interactions in either the individual or bulk scenario: invasion, neutral, and catalyzed types; their combination puts cooperators at a persistent advantage position, which boosts the cooperation. The robustness of the revealed reciprocity is strengthened by the studies of model variants, including the public goods game, asymmetrical or time-varying interactions, games of different types, games with timescale separation, different updating rules, etc. The structural complexities of the underlying population, such as Newman-Watts small world networks, Erdős-Rényi random networks, and Barabási-Albert networks, also do not alter the working of the dynamical reciprocity. In particular, as the number of games engaged increases, the cooperation level continuously improves in general. However, our analysis shows that the dynamical reciprocity works only in structured populations, otherwise the game-game interaction has no any impact on the cooperation at all. In brief, our work uncovers a cooperation mechanism in the structured populations, which indicates the great potential for human cooperation since concurrent issues are so often seen in the real world.

关键词： Patterns in complex systems Population dynamics Social systems

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WAN Internet Traffic Parameter Analysis on Metro-E Campus Network

WAN Internet Traffic Parameter Analysis on Metro-E Campus Ne...

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IEEE Control and System Graduate Research Colloquium (ICSGRC)

作者： Nor Paezah Abdullah Sayang Mohd Deni Murizah Kassim School of Electrical Engineering College of Engineering Universiti Teknologi MARA Shah Alam Selangor Malaysia Institut Kemahiran Tinggi PERDA (PERDA-TECH) Pulau Pinang Malaysia College of Computing Informatics and Media Studies Kompleks Al-Khawarizmi Universiti Teknologi MARA 40450 Shah Alam Selangor Malaysia Institute for Big Data Analytics and Artificial Intelligence (IBDAAI) Universiti Teknologi MARA Shah Alam Selangor Malaysia

This paper presents a parameter analysis of WAN internet traffic on a Metro-E campus network that addressed the network congestion and delay issues in network Quality of Service (QoS) bandwidth management. Recently, internet traffic has been gradually increasing which results in bandwidth bursts that affect network QoS. The method involves analyzing data collected over 12 months on the Metro-E 100Mbps campus network using Exinda Network Orchestrator. The result presents heavy-tailed distributions on an inbound packet kurtosis value of 347 and an outbound packet kurtosis value of 780. Bytes outbound and inbound are skewed at 122 and right at 17 accordingly. The average amount of data inbound and outbound is 458.5MB and 34.8MB. A weak positive correlation at 0.0284 exists between the maximum inbound and maximum outbound throughput on the network. The correlation coefficient’s 95% confidence interval ranges between 0.021 to 0.035. However, a strong positive correlation at 0.985 between inbound intervals and outbound intervals, and the correlation coefficient’s 95% confidence interval ranges between 0.984 to 0.985 This research is significant in the future deployment of traffic scheduling, policing, and shaping algorithms for QoS bandwidth management on the WAN Metro-E campus network. This study has implications for Wan Metro-E Network traffic scheduling, policing traffic, and future QoS shaping.

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Empowering Small and Medium Enterprises with data Analytics for Enhanced Competitiveness

Empowering Small and Medium Enterprises with Data Analytics ...

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IEEE International Conference on Control System, computing and Engineering (ICCSCE)

作者： Aissa Mosbah Musab A. M. Ali Nooritawati Md Tahir College of Commerce and Business Administration Dhofar University Salalah Oman College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Sultanate of Oman Department of Computer Engineering and Information Security International Information Technology University Almaty Kazakhstan School of Electrical Engineering College of Engineering Universiti Teknologi MARA Malaysia Institute for Big Data Analytics and Artificial Intelligence (IBDAAI) Universiti Teknologi MARA Malaysia

In today’s competitive landscape, Small and Medium-sized Enterprises (SMEs) are increasingly embracing business data analytics to gain valuable insights and make informed decisions. However, the true essence of big data lies not only in its volume but also in the analysis process and the derived insights that aid managers in making effective business choices. Despite this, limited knowledge exists regarding SMEs’ utilization of data analytics and its potential in facilitating informed decision-making. Therefore, this paper aims to elucidate the concept of business data analytics within the context of SMEs and outline the essential requirements for its effective implementation, enabling SMEs to leverage data analytics for enhanced competitiveness. It is proposed that the foundation of a successful data analytics system for SMEs should encompass four key elements: data, people, technology, and process. The degree to which data analytics contributes to a firm’s competitiveness is largely influenced by four factors: data quality, well-defined objectives, the caliber of analytic tools and techniques, and analytical skills. data generates information and insights, which in turn foster knowledge that ultimately leads to wisdom. However, due to limited resources, SMEs may be less inclined to engage in advanced predictive and prescriptive analytics compared to larger firms.

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A Hybrid of Bat Algorithm and Minimization of Metabolic Adjustment for Succinate and Lactate Production 14th

A Hybrid of Bat Algorithm and Minimization of Metabolic Adju...

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14th International Conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2020

作者： Man, Mei Yen Mohamad, Mohd Saberi Choon, Yee Wen Ismail, Mohd Arfian Artificial Intelligence and Bioinformatics Research Group Faculty of Computing Universiti Teknologi Malaysia SkudaiJohor81310 Malaysia Institute for Artificial Intelligence and Big Data Universiti Malaysia Kelantan City Campus Pengkalan Chepa Kota BharuKelantan16100 Malaysia Faculty of Bioengineering and Technology Universiti Malaysia Kelantan Jeli Campus JeliKelantan17600 Malaysia College of Computing and Applied Sciences Universiti Malaysia Pahang Lebuhraya Tun Razak Gambang KuantanPahang Darul Makmur26300 Malaysia

ISBN: (纸本)9783030545673

The elementary concept of metabolic engineering is to manipulate those potential genes to augment the yields of metabolite production by restructuring and deregulating the metabolic networks. However, the yields of biochemical products are far below their theoretical maximums, although many conventional methods that have been introduced. These conventional methods had encountered problems in getting stuck at a local minimum. This paper proposes a hybrid of the Bat Algorithm (BAT) and the Minimization of Metabolic Adjustment (MOMA) to predict an ideal set of solutions in order to improve the production of succinate and lactate. The dataset utilized in this paper was the Escherichia coli core model, which is the subset of the iAF1260 E. coli metabolic network. The experimental results include the production rate, growth rate, and a list of knockout genes. From the comparative analysis, BATMOMA has better performance in terms of production rate compared to previous works, proving that it has the potential for resolving genetic engineering problems. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Metabolic engineering

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A Constraint-Based Model for the Frequent Itemset Hiding Problem 8th

A Constraint-Based Model for the Frequent Itemset Hiding Pro...

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8th e-Democracy International Conference on Safeguarding Democracy and Human Rights in the Digital Age, e-Democracy 2019

作者： Verykios, Vassilios S. Stavropoulos, Elias C. Zorkadis, Vasilis Elmagarmid, Ahmed K. Big Data Analytics and Anonymization Laboratory School of Science and Technology Hellenic Open University Patras Greece Educational Content Methodology and Technology Laboratory Hellenic Open University Patras Greece Hellenic Data Protection Authority Athens Greece Qatar Computing Research Institute HBKU Doha Qatar

ISBN: (纸本)9783030375447

This paper introduces a novel constraint-based hiding model to drastically reduce the preprocessing overhead that is incurred by border-based techniques in the hiding of sensitive frequent itemsets. The proposed model is solved by an efficient constraint-based mining algorithm that pushes a conjunction of antimonotone constraints into an Apriori-like algorithm, for inducing the support theory of non-sensitive frequent itemsets along with its negative border. The patterns induced by the constraint-based mining algorithm can be used in border-based hiding algorithms to construct a sanitized version of the original database, where the sensitive knowledge is concealed. The efficiency of the constraint-based mining algorithm is evaluated on real and synthetic datasets. © Springer Nature Switzerland AG 2020.

关键词： Linear programming

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Evaluating Interpolation and Extrapolation Performance of Neural Retrieval Models

arXiv

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arXiv 2022年

作者： Zhan, Jingtao Xie, Xiaohui Mao, Jiaxin Liu, Yiqun Guo, Jiafeng Zhang, Min Ma, Shaoping Department of Computer Science and Technology Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China Beijing Key Laboratory of Big Data Management and Analysis Methods Gaoling School of Artificial Intelligence Renmin University of China Beijing100872 China CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China

A retrieval model should not only interpolate the training data but also extrapolate well to the queries that are different from the training data. While neural retrieval models have demonstrated impressive performance on ad-hoc search benchmarks, we still know little about how they perform in terms of interpolation and extrapolation. In this paper, we demonstrate the importance of separately evaluating the two capabilities of neural retrieval models. Firstly, we examine existing ad-hoc search benchmarks from the two perspectives. We investigate the distribution of training and test data and find a considerable overlap in query entities, query intent, and relevance labels. This finding implies that the evaluation on these test sets is biased toward interpolation and cannot accurately reflect the extrapolation capacity. Secondly, we propose a novel evaluation protocol to separately evaluate the interpolation and extrapolation performance on existing benchmark datasets. It resamples the training and test data based on query similarity and utilizes the resampled dataset for training and evaluation. Finally, we leverage the proposed evaluation protocol to comprehensively revisit a number of widely-adopted neural retrieval models. Results show models perform differently when moving from interpolation to extrapolation. For example, representation-based retrieval models perform almost as well as interaction-based retrieval models in terms of interpolation but not extrapolation. Therefore, it is necessary to separately evaluate both interpolation and extrapolation performance and the proposed resampling method serves as a simple yet effective evaluation tool for future IR studies. Copyright © 2022, The Authors. All rights reserved.

关键词： Extrapolation

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Improved publicly verifiable auditing protocol for cloud storage

Improved publicly verifiable auditing protocol for cloud sto...

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作者： Zhang, Jindan Lin, Chuan Ogiela, Urszula Nedjah, Nadia Sangaiah, Arun K. Wang, Xuan Department of Electronic Information Xianyang Vocational Technical College Xianyang China Guizhou Provincial Key Laboratory of Public Big Data GuiZhou University Guiyang China Pedagogical University of Krakow Krakow Poland Department of Electronics Engineering and Telecommunications at the Faculty of Engineering State University of Rio de Janeiro Rio de Janeiro Brazil School of Computing Science and Engineering Vellore Institute of Technology Vellore India

Outsourcing data to cloud servers is a popular service for data owners, however, how to check the integrity and freshness of the outsourced data is very challenge. Recently, Jin et al. proposed a cloud auditing protocol with full integrity and freshness support for cloud data, unfortunately in this article, we show their proposal is not secure. Concretely, the cloud servers can forge the authentication tag and thus has the ability to forge proof of data possession, which obviously invalidates their cloud auditing protocol. We also give a new cloud auditing protocol and analysis its security and performance. The results show our protocol is more efficient and secure. © 2020 John Wiley & Sons, Ltd.

关键词： Cloud storage

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Survey of time series data processing in industrial internet

Survey of time series data processing in industrial internet

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2019 IEEE International Conferences on Ubiquitous computing and Communications and data Science and Computational Intelligence and Smart computing, Networking and Services, IUCC/DSCI/SmartCNS 2019

作者： Wang, Miao-Qiong Wei, Kai Jiang, Chun-Yu China Academy of Information and Communication Technology Cloud Computing and Big Data Research Institute Beijing China

ISBN: (纸本)9781728152097

This paper focuses on the processing requirements of time series data in industrial and IoT fields. The study of time series data processing in industry is continued for a long time, and a mature solution of using real-time/ historian database has been formed. However, with the new demand of Industrial Internet, old architectures are unable to fully support requirements (i.e., large amount and real-time analysis of industrial data). Meanwhile, a new architecture for processing real-time data in mobile Internet started to mature, this forms a solution called time-series database, which provides lots of new advantages. When we try to use a new technology to replace an old one, many aspects should be considered. This paper focuses on these challenges, starting with the demands of the industry, to analyze how to solve traditional problems with new technologies. This paper also analyzes the development trend of time series data processing and puts forward some general requirements for the application of new technology in the field of Industrial Internet, which lays a theoretical foundation for the application and development of basic technologies of Industrial Internet. © 2019 IEEE.

关键词： database systems

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