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IEEE International Conference on Big data

作者： Dongyao Wu Sherif Sakr Liming Zhu Qinghua Lu Data61 Eveleigh NSW AU King Saud bin Abdulaziz University for Health Sciences Saudi Arabia Software Systems Research Group NICTA Sydney Australia School of Computer Science and Engineering University of New South Wales Sydney Australia College of Computer and Communication Engineering University of Petroleum Qingdao China

Over the past years, frameworks such as MapReduce and Spark have been introduced to ease the task of developing big data programs and applications. However, the jobs in these frameworks are roughly defined and packaged as executable jars without any functionality being exposed or described. This means that deployed jobs are not natively composable and reusable for subsequent development. Besides, it also hampers the ability for applying optimizations on the data flow of job sequences and pipelines. In this paper, we present the Hierarchically Distributed data Matrix (HDM) which is a functional, strongly-typed data representation for writing composable big data applications. Along with HDM, a runtime framework is provided to support the execution of HDM applications on distributed infrastructures. Based on the functional data dependency graph of HDM, multiple optimizations are applied to improve the performance of executing HDM jobs. The experimental results show that our optimizations can achieve improvements of between 10% to 60% of the Job-Completion-Time for different types of operation sequences when compared with the current state of art, Apache Spark.

关键词： Semantics Optimization Big data Distributed databases Sparks Programming Writing

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Process Support and Knowledge Representation in Health Care 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Richard Lenz Silvia Miksch Mor Peleg Manfred Reichert David Riaño Annette Teije

ISBN: (数字)9783642364389

ISBN: (纸本)9783642364372

This book constitutes thoroughly refereed revised selected papers from the BPM 2012 Joint Workshop on Process-Oriented Information Systems and Knowledge Representation in Health Care, ProHealth 2012/KR4HC 2012, held in Tallinn, Estonia, in September 2012. The 9 papers presented were carefully reviewed and selected from 19 submissions. In addition the book contains 1 keynote paper and 2 invited contributions. The papers are organized in topical sections named: guidelines and summarization; archetypes and cooperation; and process mining and temporal analysis.

关键词： Artificial Intelligence Information Systems Applications (incl. Internet) Information Storage and Retrieval database Management User Interfaces and Human Computer Interaction Computer Communication Networks

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Empowering software Startups with Agile Methods and Practices: A Design Science Approach

SSRN

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SSRN 2022年

作者： Gandomani, Taghi Javdani Nafchi, Mina Ziaei Parizi, Reza M. Department of Computer Science Shahrekord University Shahrekord Iran CHB Science and Technology Park Shahrekord Iran Data Science Research Group Department of Computer Science Shahrekord University Shahrekord Iran Department of Software Engineering and Game Development Kennesaw State University MariettaGA30060 United States

In recent years, the number of software startups is increasing rapidly and employing a proper software development methodology in these startups is a concern. Recently, these startups have been using agile software development methodologies and practices. However, due to the special conditions of these startups and the focus on producing the Minimum Viable Product, it seems that the use of these methodologies and practices is not done correctly. Accordingly, these startups face more severe challenges, making their success more difficult. The literature review shows that few studies have been done regarding the correct methods of using agile methods and practices in software startups. This research has used Design Science research Methodology (DSRM) to fill this research gap and develop agile adaptation guidelines in software startups. The developed guidelines were validated with the participation of 23 experts from 7 software startup teams through survey questionnaires and open discussion. Eventually, final guidelines containing 13 recommendations were developed in three categories: selection of agile methods and practices, preparation for adaptation, and application and adaptation of agile methods and practices. The evaluation results show the simplicity of understanding these guidelines, their usefulness, and their support for the expected agility of the software development process. © 2022, The Authors. All rights reserved.

关键词： software design

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Self-Healing Secure Blockchain Framework in Microgrids

arXiv

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arXiv 2022年

作者： Rath, Suman Nguyen, Lam Duc Sahoo, Subham Popovski, Petar The Department of Computer Science and Engineering University of Nevada RenoNV89557 United States Software Systems Research Group CSIRO's Data61 Sydney2015 Australia The Department of Energy Aalborg University Aalborg9220 Denmark The Department of Electronic Systems Aalborg University Aalborg9220 Denmark

Blockchain has recently been depicted as a secure protocol for information exchange in cyber-physical microgrids. However, it is still found vulnerable to consensus manipulation attacks. These stealth attacks are often difficult to detect as they use kernel-level access to mask their actions. In this paper, we firstly build a trusted and secured peer-to-peer network mechanism for physical DC microgrids' validation of transactions over Distributed Ledger. Secondly, we leverage from a physics-informed approach for detecting malware-infected nodes and then recovering from stealth attacks using a self-healing recovery scheme augmented into the microgrid Blockchain network. This scheme allows compromised nodes to adapt to a reconstructed trustworthy signal in a multi-hop manner using corresponding measurements from the reliable nodes in the network. Additionally, recognizing the possible threat of denial-of-service attacks and random time delays (where information sharing via communication channels is blocked), we also integrate a model-free predictive controller with the proposed system that can locally reconstruct an expected version of the attacked/delayed signals. This supplements the capabilities of Blockchain, enabling it to detect and mitigate consensus manipulation attempts, and network latencies. © 2022, CC BY.

关键词： Blockchain

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A Lightweight Privacy Preserving Approach for Analyzing Communication Records to Prevent VoIP Attacks Using Toll Fraud as an Example

A Lightweight Privacy Preserving Approach for Analyzing Comm...

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Stefan Hofbauer Kristian Beckers Gerald Quirchmayr Christoph Sorge Network Department Danube Data Center GmbH Vienna Austria Software Engineering paluno University of Duisburg-Essen Dusiburg Germany School of Computer and Information Security University of South Australia Adelaide Australia Research Group University of Technology Vienna Vienna Austria Security in Networks University of Paderborn Paderborn Germany

ISBN: (纸本)9781467321723

Voice-over-IP systems are quite frequently attacked with the intent of service theft. While VoIP security has been intensively researched in the past, devised solutions often demand significant changes to the VoIP systems. In addition, several solutions propose the filtering of telephone calls, but these solutions only have a limited focus on the privacy rights of the call participants. We propose a method for analyzing communication records with the primary purpose to prevent VoIP attacks. Moreover, our approach integrates with little effort into common VoIP usage scenarios. As an example we use the prevention of toll-fraud attacks as a running example. The analysis of the communication records, however, requires investigating personal information in the communication records, e.g., call habits and phone numbers. Consequently we give an overview of major US and EU laws and regulations to elicit privacy requirements. We also demonstrate how these requirements can be implemented using Comercial-Off-The-Shelf VoIP systems.

关键词： Privacy Security data privacy Telecommunications Timing Logic gates Educational institutions

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Automatic Text Summarization Method Based on Improved Textrank Algorithm and K-Means Clustering

SSRN

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SSRN 2023年

作者： Liu, Wenjun Sun, Yuyan Yu, Bao Wang, Hailan Peng, Qingcheng Hou, Mengshu Guo, Huan Wang, Hai Liu, Cheng Chengdu611731 China School of Computer and Software Engineering XiHua University Chengdu610039 China School of Big Data and Artificial Intelligence Chengdu Technological University Chengdu611730 China Science and Technology on Communication Security Laboratory The 30th Research Institute of China Electronics Technology Group Corporation Chengdu610041 China

Automatic text summarization is to obtain a summary by compressing the text while retaining its important information, and then users can obtain the important content of the text by reading the summary. In the research literatures, the extraction method is widely used and is also one of the main research methods of most abstracts. However, this summary method still has some problems. The selection of the initial cluster center has not been carefully determined, and in articles with complex sentences, the sentence redundancy summarized is high. In order to solve the above problems, this paper proposes an automatic text summarization method based on improved TextRank algorithm and K-Means clustering. This method uses the improved BM25 model to calculate the BM25 similarity between sentences, and then uses the TextRank model to obtain the TR score of sentences. Then, the TR score is used to select the initial center of K-Means clustering. Finally, the summary is obtained through the class score and sentence score. The experimental results show that the proposed BM25Rank algorithm has a better effect on DUC2004 dataset. In conclusion, the improved TextRank and K-Means method proposed in this paper improve the accuracy of automatic text summarization and reduce the redundancy. © 2023, The Authors. All rights reserved.

关键词： K-means clustering

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Optimizing Ethanol Production in Escherichia Coli Using a Hybrid of Particle Swarm Optimization and Artificial Bee Colony 22

Optimizing Ethanol Production in Escherichia Coli Using a Hy...

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Proceedings of the 6th International Conference on Advances in Artificial Intelligence

作者： Mohamad Faiz Dzulkalnine Mohd Saberi Mohamad Yee Wen Choon Muhammad Akmal Remli Hany Alashwal Artificial Intelligence and Bioinformatics Research Group Faculty of Computing Universiti Teknologi Malaysia Malaysia Health Data Science Lab Department of Genetics and Genomics College of Medical and Health Sciences United Arab Emirates University UAE and Big Data Analytics Center United Arab Emirates University UAE Institute for Artificial Intelligence and Big Data Universiti Malaysia Kelantan Malaysia and Department of Data Science Universiti Malaysia Kelantan Malaysia Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University UAE and Big Data Analytics Center United Arab Emirates University UAE

ISBN: (纸本)9781450396943

Metabolic engineering for biomass production using microorganisms’ cell has received considerable attention in recent years. This is due to the biomass products being extensively used in the field of food additives, supplements, pharmaceuticals, and polymer materials. In this paper, ethanol production in Escherichia coli (E. coli) is the desired product. Sugarcane and corn are often used to produce ethanol. However, one of the problems to produce adequate amounts of ethanol is that large areas are needed to plant sugarcane and corn. Furthermore, the amount of time for the process of dry milling and wet milling is high, which are 40 to 50 hours and 24 to 48 hours, respectively. The wet laboratory is also having limitation on the production of ethanol in microorganisms because the amount of the ethanol produced is not satisfying. Hence, a lot of metabolic engineering techniques is introduced to enhance the production of ethanol in E. coli, such as gene knockout strategy, but the production is yet to meet the demand. Therefore, this paper proposes a hybrid algorithm of Particle Swarm Optimization with the Artificial Bee Colony algorithm (PSOABC) to identify the optimal set of gene knockout strategy to improve the ethanol production in E. coli. A list of genes to knockout, production of the desired product, and growth rate are presented in this paper. PSOABC has shown better performance in terms of production, growth rate and accuracy.

关键词： Gene Knockouts Particle Swarm Optimization Artificial Bee Colony Ethanol Flux Balance Analysis

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Novel Truncated-rank Graph-structured and Tree-guided Sparse Linear Mixed Models for Variable Selection on Genome-wide Association Studies

Novel Truncated-rank Graph-structured and Tree-guided Sparse...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Liu, Xiang Liu, Xueling Diao, Jing Zheng, Mengyao Li, Jihe Xie, Yongyi Lai, Kang Geng, Xiao Song, Yijun Jiang, Linshan National University of Singapore School of Computing Singapore National University Health System Group Technology Office Singapore Peking University School Hospital of Stomatology National Center for Stomatology National Clinical Research Center for Oral Diseases Department of Preventive Dentistry China Harvard University Harvard T.H. Chan School of Public Health United States Peking University School of Software and Microelectronics China Tongji University Shanghai Skin Disease Hospital Institute of Dermatology School of Medicine China Nanyang Technological University School of Mechanical & Aerospace Engineering Singapore Peking University Third Hospital Engineering Research Center of Bone and Joint Precision Medicine Ministry of Education Orthopaedic Department China Zhejiang University of Finance & Economics Dongfang College China National University of Singapore Institute of Data Science Singapore

ISBN: (纸本)9798350386226

Variable selection for genome-wide association studies is a key focus for bioinformatics researchers in high-performance computing. The rapid growth of biological and biomedical data demands has led to high-dimensional, heterogeneous datasets characterized by non-i.i.d. properties and numerous response variables, often resulting in false negatives or positives in recovered results. Traditional methods, when nalively applied, yield suboptimal performance due to confounding factors. To account for the complex interdependencies in heterogeneous data and enhance the practical outcomes of genome-wide association studies, we introduce two methods, TGsLMM and TTsLMM, which balance effects between response and explanatory variables for subpopulation inference. Our unified framework performs sparse variable selection using graph-structured or tree-guided structures in a low-rank linear mixed model. Additionally, we extend our approach to high-dimensional datasets and adaptively select the covariance structure for genomic data. Extensive experiments on synthetic and three real-world datasets emphasize the robustness and effectiveness of our proposed methods, achieving the highest ROC area compared to baselines and superior results for future potential. © 2024 IEEE.

关键词： Confounding factors genome-wide association study mixed model variable selection

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Towards automated metamorphic test identification for ocean system models

arXiv

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arXiv 2021年

作者： Hiremath, Dilip Jagadeeshwarswamy Claus, Martin Hasselbring, Wilhelm Rath, Willi MarDATA - Helmholtz School for Marine Data Science GEOMAR Helmholtz Centre for Ocean Research Kiel Kiel University Kiel Germany Software Engineering Group Computer Science Department Kiel University Kiel Germany Ocean Circulation and Climate Dynamics Department GEOMAR Helmholtz Centre for Ocean Research Kiel Kiel University Kiel Germany Ocean Circulation and Climate Dynamics Department GEOMAR Helmholtz Centre for Ocean Research Kiel Kiel Germany

Metamorphic testing seeks to verify software in the absence of test oracles. Our application domain is ocean system modeling, where test oracles rarely exist, but where symmetries of the simulated physical systems are known. The input data set is large owing to the requirements of the application domain. This paper presents work in progress for the automated generation of metamorphic test scenarios using machine learning. We extended our previously proposed method [1] to identify metamorphic relations with reduced computational complexity. Initially, we represent metamorphic relations as identity maps. We construct a cost function that minimizes for identifying a metamorphic relation orthogonal to previously found metamorphic relations and penalize for the identity map. A machine learning algorithm is used to identify all possible metamorphic relations minimizing the defined cost function. We propose applying dimensionality reduction techniques to identify attributes in the input which have high variance among the identified metamorphic relations. We apply mutation on these selected attributes to identify distinct metamorphic relations with reduced computational complexity. For experimental evaluation, we subject the two implementations of an ocean-modeling application to the proposed method to present the use of metamorphic relations to test the two implementations of this *** Codes J.2 © 2021, CC BY-SA.

关键词： Cost functions

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Verification of adaptive systems

Verification of adaptive systems

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AIAA Infotech at Aerospace Conference and Exhibit 2012

作者： Pullum, Laura Cui, Xiaohui Vassev, Emil Hinchey, Mike Rouff, Christopher Buskens, Richard Computational Data Analytics Group Oak Ridge National Laboratory P.O. Box 2008 MS-6085 Oak Ridge TN 37830 United States Computer Science Department New York Institute of Technology 1855 Broadway Manhattan NY 10023 United States Lero - The Irish Software Engineering Research Centre University of Limerick Limerick Ireland Lockheed Martin Advanced Technology Laboratories Informatics Laboratory 3 Executive Campus Suite 600 Cherry Hill NJ 08002 United States Lockheed Martin Advanced Technology Laboratories Informatics Laboratory Applied Science Laboratory 3 Executive Campus Cherry Hill NJ 08002 United States

ISBN: (数字)9781600869396

ISBN: (纸本)9781600869396

Adaptive systems are critical for future space and other unmanned and intelligent systems. Verification of these systems is also critical for their use in systems with potential harm to human life or with large financial investments. Due to their nondeterministic nature and extremely large state space, current methods for verification of software systems are not adequate to provide a high level of assurance for them. The combination of stabilization science, high performance computing simulations, compositional verification and traditional verification techniques, plus operational monitors, provides a complete approach to verification and deployment of adaptive systems that has not been used before. This paper gives an overview of this approach. © 2012 by the American Institute of Aeronautics and Astronautics, Inc.

关键词： Adaptive systems

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