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A Task Allocation Method for Stream Processing with Recovery Latency Constraint

Journal of computer science & Technology 2018年第6期33卷 1125-1139页

作者： Hong-Liang Li Jie Wu Zhen Jiang Xiang Li Xiao-Hui Wei College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education Changchun 130012 China Department of Computer and Information Sciences Temple University Philadelphia PA 19122 U.S.A. Department of Computer Science West Chester University of Pennsylvania West Chester PA 19383 U.S.A.

Stream processing applications continuously process large amounts of online streaming data in real time or nearreal time. They have strict latency constraints. However, the continuous processing makes them vulnerable to any failures,and the recoveries may slow down the entire processing pipeline and break latency constraints. The upstream backupscheme is one of the most widely applied fault-tolerant schemes for stream processing systems. It introduces complexbackup dependencies to tasks, which increases the difficulty of controlling recovery latencies. Moreover, when dependenttasks are located on the same processor, they fail at the same time in processor-level failures, bringing extra recovery latencies that increase the impacts of failures. This paper studies the relationship between the task allocation and therecovery latency of a stream processing application. We present a correlated failure effect model to describe the recoverylatency of a stream topology in processor-level failures under a task allocation plan. We introduce a recovery-latency awaretask allocation problem （RTAP） that seeks task allocation plans for stream topologies that will achieve guaranteed recoverylatencies. We discuss the difference between RTAP and classic task allocation problems and present a heuristic algorithmwith a computational complexity of O（n log2 n） to solve the problem. Extensive experiments were conducted to verify thecorrectness and effectiveness of our approach. It improves the resource usage by 15%-20% on average.

关键词： stream processing task allocation fault-tolerance upstream backup, recovery latency

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ClaRA (C++ learning at RWTH Aachen) change from classical teaching to e-learning

ClaRA (C++ learning at RWTH Aachen) change from classical te...

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7th International Conference on Information Technology Based Higher Education and Training, ITHET

作者： Hermanns, Annette Jaenen, Verena Heide, Andrea Henning, Klaus Center for Learning and Knowledge Management Department of Computer Science in Mechanical Engineering RWTH Aachen University Germany

ISBN: (纸本)1424404061

Within the scope of the course computer science in Mechanical engineering, a blended learning concept is used in order to teach students of mechanical engineering the basic principles of computer science. This concept comprises of classical lectures and tutorials, project work and an e-learning platform and is designed for about 1400 students per semester. Basic elements of the e-learning platform are multimedia learning applications, a message board, live recordings of the lectures and in the future ClaRA, an interactive e-learning unit. ClaRA is web-based and supports the tutoring of the basics of object-oriented programming using the programming language C++. It substitutes courses with compulsory attendance, providing the students a chance to teach themselves C++ irrespective of the factors like time and place. The paper describes on one hand the new e-learning unit ClaRa and the implementation and evaluation of the project, on the other hand, the actual experiences with the change in the blended learning concept. © 2006 IEEE.

关键词： Students

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SimCon: A tool for modeling context sources for rapid evaluation of pervasive applications using virtual reality 5

SimCon: A tool for modeling context sources for rapid evalua...

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5th International ICST Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2008

作者： McGlinn, Kris O'Neill, Eleanor Lewis, David Knowledge and Data Engineering Group Department of Computer Science Trinity College Dublin Dublin 2 Ireland

Here we present the SimCon tool to enable evaluators of pervasive applications to rapidly place and configure context sources within a Virtual Reality Environment to conduct repeatable evaluations early in the develop... 详细信息

ISBN: (纸本)9789639799219

关键词： Ubiquitous computing

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A semi-supervised learning framework to cluster mixed data types

A semi-supervised learning framework to cluster mixed data t...

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4th International Conference on knowledge Discovery and Information Retrieval, KDIR 2012

作者： Abdullin, Artur Nasraoui, Olfa Department of Computer Engineering and Computer Science Knowledge Discovery and Web Mining Lab University of Louisville Louisville KY United States

ISBN: (纸本)9789898565297

We propose a semi-supervised framework to handle diverse data formats or data with mixed-type attributes. Our preliminary results in clustering data with mixed numerical and categorical attributes show that the proposed semi-supervised framework gives better clustering results in the categorical domain. Thus the seeds obtained from clustering the numerical domain give an additional knowledge to the categorical clustering algorithm. Additional results show that our approach has the potential to outperform clustering either domain on its own or clustering both domains after converting them to the same target domain. Copyright © 2012 SciTePress - science and Technology Publications.

关键词： Clustering algorithms

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An Initial Study of Machine Learning Underspecification Using Feature Attribution Explainable AI Algorithms: A COVID-19 Virus Transmission Case Study 18th

An Initial Study of Machine Learning Underspecification Usin...

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18th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2021

作者： Hinns, James Fan, Xiuyi Liu, Siyuan Raghava Reddy Kovvuri, Veera Yalcin, Mehmet Orcun Roggenbach, Markus Computer Science Department Swansea University Swansea United Kingdom Department of Data Science and Knowledge Engineering Maastricht University Maastricht Netherlands

ISBN: (纸本)9783030891879

From a dataset, one can construct different machine learning (ML) models with different parameters and/or inductive biases. Although these models give similar prediction performances when tested on data that are currently available, they may not generalise equally well on unseen data. The existence of multiple equally performing models exhibits underspecification of the ML pipeline used for producing such models. In this work, we propose identifying underspecification using feature attribution algorithms developed in Explainable AI. Our hypothesis is: by studying the range of explanations produced by ML models, one can identify underspecification. We validate this by computing explanations using the Shapley additive explainer and then measuring statistical correlations between them. We experiment our approach on multiple datasets drawn from the literature, and in a COVID-19 virus transmission case study. © 2021, Springer Nature Switzerland AG.

关键词： COVID-19

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A computational framework for Carreau nanomaterial induced by stretchy regime considering Brownian diffusion, viscous dissipation, ferromagnetism and thermophoresis

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Partial Differential Equations in Applied Mathematics 2025年 13卷

作者： Hussain, Iftikhar Khan, Waqar Azeem Tabrez, Muhammad Waqas, M. Ibrahim, Talib K. Saidani, Taoufik Kausar, M.S. Zamri, Nurnadiah Abdullaeva, Barno Garalleh, Hakim AL Department of Mathematics Mohi-ud-Din Islamic University Nerian Sharif Jammu and Kashmir Azad 12010 Pakistan School of Mathematics and Statistics Beijing Institute of Technology Beijing 100081 China NUTECH School of Applied Sciences and Humanities National University of Technology Islamabad 44000 Pakistan Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Besut Campus Terengganu Besut 22200 Malaysia Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon Department of Petroleum Engineering College of Engineering Knowledge University Erbil 44001 Iraq Department of Petroleum Engineering Al-Kitab University Altun Kupri Iraq Center for Scientific Research and Entrepreneurship Northern Border University Arar 73213 Saudi Arabia Faculty of Informatics and Computing Universiti Sultan Zainal Abidin (Kampus Gong Badak) Terengganu Kuala Terengganu 21300 Malaysia Department of Mathematics and Information Technologies Vice-Rector for Scientific Affairs Tashkent State Pedagogical University Tashkent Uzbekistan Department of Mathematical Science College of Engineering University of Business and Technology Jeddah 21361 Saudi Arabia

In recent decade, the research in nanotechnology brought the idea of nanofluids which are highly conducting materials. Some important applications of nanofluids are justified in pharmaceutical industry, coolants in vehicles engine, preparation process of various medicines for treatment of fatal diseases like cancer, aircraft industry, latest heat exchangers etc. The ferro particles are special class of nanomaterial which attract variety of interest from the researchers. The objective of current research is to perform the investigation for heat and mass transfer subject to Carreau nanofluid to observe the enhancement of heat transmission phenomena. The induction of magnetic dipole has been observed for thermal transport phenomenon. The flow is causing by stretched surface. A simplified system is obtained by utilizing the dimensionless variables. Physical interpretation of results have been presented. Result showed that temperature profile in presence of ferrofluid fluid boosts up with escalation in thermophoresis parameter, while opposite behavior is noted for power law index. The concentration of ferrofluid showing declining behavior for Schmidt numbers and rises for thermophoresis parameter. © 2024

关键词： Carreau ferrofluid Heat and mass transfer Magnetic dipole Numerical solution

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New physical structures and patterns to the optical solutions of the nonlinear Schrödinger equation with a higher dimension

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Communications in Theoretical Physics 2023年第8期75卷 25-41页

作者： Karmina K Ali Abdullahi Yusuf Marwan Alquran Sibel Tarla Department of Mathematics Faculty of ScienceUniversity of ZakhoZakhoIraq Department of Computer Science College of ScienceKnowledge UniversityErbil 44001Iraq Department of Computer Engineering Biruni UniversityIstanbulTurkey Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Department of Mathematics Near East University TRNCMersin 10Nicosia 99138Turkey Department of Mathematics and Statistics Jordan University of Science&TechnologyIrbid 22110Jordan Department of Mathematics Faculty of ScienceFirat UniversityElazigTurkey

It is commonly recognized that,despite current analytical approaches,many physical aspects of nonlinear models remain *** is critical to build more efficient integration methods to design and construct numerous other unknown solutions and physical attributes for the nonlinear models,as well as for the benefit of the largest audience *** achieve this goal,we propose a new extended unified auxiliary equation technique,a brand-new analytical method for solving nonlinear partial differential *** proposed method is applied to the nonlinear Schrödinger equation with a higher dimension in the anomalous *** interesting solutions have been ***,to shed more light on the features of the obtained solutions,the figures for some obtained solutions are *** propagation characteristics of the generated solutions are *** results show that the proper physical quantities and nonlinear wave qualities are connected to the parameter *** is worth noting that the new method is very effective and efficient,and it may be applied in the realisation of novel solutions.

关键词： exact solutions nonlinear Schrodinger equation new extended unified auxiliary equation method Jacobi elliptic functions

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Stream-dashboard: A framework for mining, tracking and validating clusters in a data stream

Stream-dashboard: A framework for mining, tracking and valid...

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1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications, BigMine-12 - Held in Conjunction with SIGKDD Conference

作者： Hawwash, Basheer Nasraoui, Olfa Department of Computer Engineering and Computer Science Knowledge Discovery and Web Mining Lab University of Louisville Louisville KY United States

ISBN: (纸本)9781450315470

Clustering data streams is a challenging problem that has received significant attention in the recent decade. In this paper, we address the hitherto inadequately addressed challenge of managing the output of stream clustering. This task comprises the continuous cluster model validation, monitoring, trend and change detection, and summarization of the cluster mining output. For this purpose, we propose a complete framework to mine, track and validate the clusters in a data stream. The proposed framework keeps track of each discovered cluster model of the stream through time, while quantifying, modeling and summarizing the cluster evolution trends, and storing a summary of the cluster models and the evolution trends only at milestones corresponding to the occurrence of significant changes. Our experiments demonstrate the accuracy of the proposed framework in tracking cluster evolution over time, while generating a concise summary of the evolution trends over the lifetime of the stream. Copyright © 2012 ACM.

关键词： Data mining

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A Seed-Based Inter-Domain Supervised Framework to Cluster Mixed Data Types

A Seed-Based Inter-Domain Supervised Framework to Cluster Mi...

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4th International Joint Conference on knowledge Discovery, knowledge engineering and knowledge Management, IC3K 2012

作者： Abdullin, Artur Nasraoui, Olfa Knowledge Discovery and Web Mining Lab Department of Computer Engineering and Computer Science University of Louisville Louisville KY United States

ISBN: (纸本)9783642541049

We propose a Seed-based Inter-Domain Supervised (IDS) framework to handle possibly diverse data formats, mixed-type attributes and different sources of data. This approach can be used for combining diverse representations of the data, in particular where data comes from different sources, some of which may be unreliable or uncertain, or for exploiting optional external concept set labels to guide the clustering of the main data set in its original domain. Unlike semi-supervised clustering, our approach exploits the synergy between different domains instead of external labels. Also ensemble clustering and our proposed IDS clustering are different mechanisms with distinct goals: (i) the former aims to combine independent clustering results from many independent subsets sampled from the same data set or from different clustering algorithm results on the same data set, into one consensus, (ii) while the latter (IDS) aims to exploit a mutual synergy between different data domains or sources to guide the clustering in these different domains or sources. Our preliminary results in clustering data with mixed numerical and categorical attributes show that the proposed IDS framework gives better clustering results in the categorical domain. Thus the seeds or the constraints obtained from clustering the numerical domain give an additional knowledge to the categorical clustering algorithm. Additional results show that our approach outperforms clustering either domain on its own or clustering both domains converted to the same target domain. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Clustering algorithms

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Adding Semantics to Social Software engineering: (Re-)Using Ontologies in a Community-oriented Requirements engineering Environment

Adding Semantics to Social Software Engineering: (Re-)Using ...

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2010 Workshopband (inkl.Doktorandensymposium), Fachtagung des GI-Fachbereichs Softwaretechnik, Software engineering 2010 - 2010 Workshop (incl. Doctoral Symposium), Conference of the GI Division on Software engineering, Software engineering 2010

作者： Lohmann, Steffen Riechert, Thomas DEI Laboratory Computer Science Department Carlos III University of Madrid Spain Agile Knowledge Engineering and Semantic Web Department of Computer Science University of Leipzig Germany

ISBN: (纸本)9783885792543

Social Software is typically characterized by low formal semantics and weakly structured contents. Software engineering, in contrast, requires at least a certain degree of formality and structure. In order to face these opposing demands, we propose to ground Social Software engineering on concepts and technologies from the Semantic Web. In particular, we present a Semantic Wiki based approach in this paper that uses well-known ontologies to represent activities and artifacts that emerge in an online environment for community-oriented Requirements engineering. We illustrate the benefits of reusing these domain-independent ontologies and show how they can fruitfully be combined and interlinked in one common upper ontology. © 2010 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Ontology

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