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作者： Abdallah, Zahraa Said Gaber, Mohamed Medhat Srinivasan, Bala Krishnaswamy, Shonali Centre for Distributed Systems and Software Engineering Monash University Melbourne Australia School of Computing University of Portsmouth Portsmouth Hampshire PO1 3HE United Kingdom Singapore Faculty of Computer and Information Science Ain Shams University Cairo Egypt

ISBN: (纸本)9783642353253

Activity recognition focuses on inferring current user activities by leveraging sensory data available on today's sensor rich environment. Supervised learning has been applied pervasively for activity recognition. Typical activity recognition techniques process sensory data based on point-by-point approaches. In this paper, we propose a novel Cluster Based Classification for Activity Recognition Systems, CBARS. The novel approach processes activities as clusters to build a robust classification framework. CBARS integrates supervised, unsupervised and active learning and applies hybrid similarity measures technique for recognising activities. Extensive experimental results using real activity recognition dataset have evidenced that our new approach shows improved performance over other existing state-of-the-art learning methods. © Springer-Verlag Berlin Heidelberg 2012.

关键词： Pattern recognition

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Realising Edge Analytics for Early Prediction of Readmission: A Case Study

Realising Edge Analytics for Early Prediction of Readmission...

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IEEE International Conference on Cloud Engineering (IC2E)

作者： Yucen Nan Wei Li Feng Lu Flavia C. Delicato Albert Y. Zomaya Centre for Distributed and High Performance Computing School of Computer Science The University of Sydney Australia School of Computer Science Huazhong University of Science and Technology China Department of Computer Science Fluminense Federal University Brazil

ISBN: (数字)9781728110998

ISBN: (纸本)9781728111001

The post-discharge support is increasingly suggested for stroke patients to be discharged earlier and start rehabilitation at home. Considering that stroke patients usually have a high chance of recurrence, a good prognostic program is essential to improve diagnostic capabilities while reducing readmission rate to further save medical sources. In this context, various machine learning methods have been leveraged to obtain diagnostic findings and guide further treatments. However, those approaches mainly focus on performing analysis using a single data source obtained from the hospital, which could ignore the information complementarity between different groups of features and several subtle and discrete differences of physical interpretation among them. In this paper, we propose an Edge-based system design for post-stroke surveillance and warning prediction, called PSMART (Post-Stroke Mobile Auxiliary Rudiment Treatment), for processing enriched pathogenic factors of ischemic stroke from multi-sensors (views) to make readmission warning predictions. Our approach can considerably enrich the distinctive features from raw data, as well as exploit the consistency and complementary proprieties of different views, leading to better learning results. We evaluate the performance of the proposed approach on a real-world dataset, and the accuracy can reach up to 98.98%. Moreover, experiment results also show that our proposed approach can provide better accuracy when compared to the single-view ones.

关键词： Medical diagnostic imaging Interpolation Hospitals Sensors Surveillance

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Guidelines for commercial off-the-shelf Simulation Package interoperability 08

Guidelines for commercial off-the-shelf Simulation Package i...

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Simulation Winter Conference

作者： Simon J.E. Taylor Stephen J. Turner Steffen Strassburger Centre for Applied Simulation Modelling School of Information Systems Computing & Maths Brunei University Uxbridge Middlesex UK Parallel & Distributed Computing Centre School of Computer Engineering Nanyang Technological University Singapore School of Economic Sciences Technical University Ilmenau Ilmenau Germany

ISBN: (纸本)9781424427086

Commercial-off-the-shelf (COTS) Simulation Packages (CSPs) are widely used visual interactive modeling environments such as Arena™, Anylogic™, Flexsim™, Simul8™, Witness™, etc. CSP Interoperability (or distributed simulation) is a technique that allows a simulation to be executed over several computers or for several simulations running on different computers to run together. This also relates to simulation languages such as SLX™ and GPSS/H™. There have been various attempts to interoperate these CSPs, some with the IEEE 1516 high level architecture (HLA). These can be quite complex and it is easy to loose track of exactly what is occurring between interoperating CSPs and their models. This paper introduces a set of interoperability reference models (IRMs), or design patters for CSP Interoperability, that can be used as guidelines to simplify the interoperability process.

关键词： Guidelines Computational modeling computer simulation Discrete event simulation distributed computing Chip scale packaging Production facilities Concurrent computing computer architecture Logistics

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An energy-efficient scheduling algorithm for sporadic real-time tasks in multiprocessor systems

An energy-efficient scheduling algorithm for sporadic real-t...

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13th IEEE International Workshop on FTDCS 2011, the 8th International Conference on ATC 2011, the 8th International Conference on UIC 2011 and the 13th IEEE International Conference on HPCC 2011

作者： Zhang, Dong-Song Chen, Fang-Yuan Li, Hong-Hua Jin, Shi-Yao Guo, De-Ke National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha 410073 China School of Computing Science Simon Fraser University 8888 University Drive Burnaby BC V5A 1S6 Canada National Laboratory for Information System Engineering School of Information Systems and Management National University of Defense Technology Changsha 410073 China

ISBN: (纸本)9780769545387

As the energy consumption of embedded multiprocessor systems becomes increasingly prominent, the real-time energy-efficient scheduling in multiprocessor systems becomes an urgent problem to reduce the system energy consumption while meeting real-time constraints. For a multiprocessor with independent DVFS and DPM at each processor, this paper proposes an energy-efficient real-time scheduling algorithm named LRE-DVFS-EACH, based on LRE-TL which is an optimal real-time scheduling algorithm for sporadic tasks. LRE-DVFS-EACH utilizes the concept of TL plane and the idea of fluid scheduling to dynamically scale the voltage and frequency of processors at the initial time of each TL plane as well as the release time of a sporadic task in each TL plane. Consequently, LRE-DVFS-EACH can obtain a reasonable tradeoff between the real-time constraints and the energy saving. LRE-DVFS-EACH is also adaptive to the change of workload caused by the dynamic release of sporadic tasks, which can obtain more energy savings. The experimental results show that compared with existing algorithms, LRE-DVFS-EACH can not only guarantee the optimal feasibility of sporadic tasks, but also achieve more energy savings in all cases, especially in the case of high workloads. © 2011 IEEE.

关键词： Real time systems

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Routing with uncertainty in wireless mesh networks

Routing with uncertainty in wireless mesh networks

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International Workshop on Quality of Service

作者： Fajun Chen Jiangchuan Liu Zongpeng Li Yijie Wang Key Laboratory of Science and Technology for National Defence of Parallel and Distributed Processing National University of Defense Technology China School of Computing Science Simon Fraser University Department of Computer Science University of Caglary

Existing routing protocols for Wireless Mesh Networks (WMNs) are generally optimized with statistical link measures, while not addressing on the intrinsic uncertainty of wireless links. We show evidence that, with the transient link uncertainties at PHY and MAC layers, a pseudo-deterministic routing protocol that relies on average or historic statistics can hardly explore the full potentials of a multi-hop wireless mesh. We study optimal WMN routing using probing-based online anypath forwarding, with explicit consideration of transient link uncertainties. We show the underlying connection between WMN routing and the classic Canadian Traveller Problem (CTP). Inspired by a stochastic recoverable version of CTP (SRCTP), we develop a practical SRCTP-based online routing algorithm under link uncertainties. We study how dynamic next hop selection can be done with low cost, and derive a systematic selection order for minimizing transmission delay. We conduct simulation studies to verify the effectiveness of the SRCTP algorithms under diverse network configurations. In particular, compared to deterministic routing, reduction of end-to-end delay (51.15~73.02%) and improvement on packet delivery ratio (99.76%) are observed.

关键词： Uncertainty Wireless mesh networks Delay Routing protocols Physical layer Statistics Stochastic processes Relays computer networks Concurrent computing

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Cloud workload prediction based on workflow execution time discrepancies

arXiv

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arXiv 2018年

作者： Kecskemeti, Gabor Nemeth, Zsolt Kertesz, Attila Ranjan, Rajiv Department of Computer Science Liverpool John Moores University Laboratory of Parallel and Distributed Systems MTA SZTAKI Software Engineering Department University of Szeged School of Computing Newcastle University

Infrastructure as a service clouds hide the complexity of maintaining the physical infrastructure with a slight disadvantage: they also hide their internal working details. Should users need knowledge about these details e.g., to increase the reliability or performance of their applications, they would need solutions to detect behavioural changes in the underlying system. Existing runtime solutions for such purposes offer limited capabilities as they are mostly restricted to revealing weekly or yearly behavioural periodicity in the infrastructure. This article proposes a technique for predicting generic background workload by means of simulations that are capable of providing additional knowledge of the underlying private cloud systems in order to support activities like cloud orchestration or workflow enactment. Our technique uses long-running scientific workflows and their behaviour discrepancies and tries to replicate these in a simulated cloud with known (trace-based) workloads. We argue that the better we can mimic the current discrepancies the better we can tell expected workloads in the near future on the real life cloud. We evaluated the proposed prediction approach with a biochemical application on both real and simulated cloud infrastructures. The proposed algorithm has shown to produce significantly (∼20%) better workload predictions for the future of simulated clouds than random workload selection. Copyright © 2018, The Authors. All rights reserved.

关键词： Infrastructure as a service (IaaS)

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Commercial-Off-The-Shelf Simulation Package interoperability: Issues and futures 09

Commercial-Off-The-Shelf Simulation Package interoperability...

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Simulation Winter Conference

作者： Simon J. E. Taylor Navonil Mustafee Stephen J. Turner Ke Pan Steffen Strassburger Centre of Applied Simulation Modelling School of Information Systems Computing & Maths Brunei University Uxbridge Middlesex UK Parallel & Distributed Computing Centre School of Computer Engineering Nanyang Technological University Singapore Singapore School of Economic Sciences Technical University Ilmenau Ilmenau Germany

ISBN: (纸本)9781424457717

Commercial-Off-The-Shelf Simulation Packages (CSPs) are widely used in industry to simulate discrete-event models. Interoperability of CSPs requires the use of distributed simulation techniques. Literature presents us with many examples of achieving CSP interoperability using bespoke solutions. However, for the wider adoption of CSP-based distributed simulation it is essential that, first and foremost, a standard for CSP interoperability be created, and secondly, these standards are adhered to by the CSP vendors. This advanced tutorial is on an emerging standard relating to CSP interoperability. It gives an overview of this standard and presents case studies that implement some of the proposed standards. Furthermore, interoperability is discussed in relation to large and complex models developed using CSPs that require large amount of computing resources. It is hoped that this tutorial will inform the simulation community of the issues associated with CSP interoperability, the importance of these standards and its future.

关键词： Computational modeling Context modeling computer simulation Chip scale packaging distributed computing Concurrent computing Logistics computer languages Grid computing Information systems

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A novel application development environment for large-scale scientific computations 00

A novel application development environment for large-scale ...

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Proceedings of the 14th international conference on Supercomputing

作者： X. Shen W. Liao A. Choudhary G. Memik M. Kandemir S. More G. Thiruvathukal A. Singh Center for Parallel and Distributed Computing Department of Electrical and Computer Engineering Northwestern University Evanston IL Department of Computer Science and Engineering The Pennsylvania State University University Park PA School of Computing Telecommunications and Information Sciences JHPC Laboratory Depaul University

Our results demonstrate that our novel application development environment provides both ease-of-use and high performance for large-scale, I/O-intensive scientific applications.

ISBN: (纸本)9781581132700

Our results demonstrate that our novel application development environment provides both ease-of-use and high performance for large-scale, I/O-intensive scientific applications.

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Soft-Constrained Nonnegative Matrix Factorization via Normalization

Soft-Constrained Nonnegative Matrix Factorization via Normal...

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International Joint Conference on Neural Networks

作者： Long Lan Naiyang Guan Xiang Zhang Dacheng Tao Zhigang Luo Science and Technology on Parallel and Distributed Processing Laboratory School of Computer Science National University of Defense Technology Centre for Quantum Computation & Intelligent Systems and the Faculty of Engineering and Information Technology University of Technology

ISBN: (纸本)9781479914821

Semi-supervised clustering aims at boosting the clustering performance on unlabeled samples by using labels from a few labeled samples. Constrained NMF (CNMF) is one of the most significant semi-supervised clustering methods, and it factorizes the whole dataset by NMF and constrains those labeled samples from the same class to have identical encodings. In this paper, we propose a novel soft-constrained NMF (SCNMF) method by softening the hard constraint in CNMF. Particularly, SCNMF factorizes the whole dataset into two lower-dimensional factor matrices by using multiplicative update rule (MUR). To utilize the labels of labeled samples, SCNMF iteratively normalizes both factor matrices after updating them with MURs to make encodings of labeled samples close to their label vectors. It is therefore reasonable to believe that encodings of unlabeled samples are also close to their corresponding label vectors. Such strategy significantly boosts the clustering performance even when the labeled samples are rather limited, e.g., each class owns only a single labeled sample. Since the normalization procedure never increases the computational complexity of MUR, SCNMF is quite efficient and effective in practices. Experimental results on face image datasets illustrate both efficiency and effectiveness of SCNMF compared with both NMF and CNMF.

关键词： Matrix decomposition Encoding Vectors Clustering methods Clustering algorithms Time complexity Face

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Box-constrained Projective Nonnegative Matrix Factorization via Augmented Lagrangian Method

Box-constrained Projective Nonnegative Matrix Factorization ...

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International Joint Conference on Neural Networks

作者： Xiang Zhang Naiyang Guan Long Lan Dacheng Tao Zhigang Luo Science and Technology on Parallel and Distributed Processing Laboratory School of Computer Science National University of Defense Technology Centre for Quantum Computation & Intelligent Systems and the Faculty of Engineering and Information Technology University of Technology

ISBN: (纸本)9781479914821

Projective non-negative matrix factorization (PNMF) projects a set of examples onto a subspace spanned by a non-negative basis whose transpose is regarded as the projection matrix. Since PNMF learns a natural parts-based representation, it has been successfully used in text mining and pattern recognition. However, it is non-trivial to analyze the convergence of the optimization algorithms for PNMF because its objective function is non-convex. In this paper, we propose a Box-constrained PNMF (BPNMF) method to overcome this deficiency of PNMF. In particular, BPNMF introduces an auxiliary variable, i.e., the coefficients of examples, and incorporates the following two types of constraints: 1) each entry of the basis is non-negative and upper-bounded, i.e., box-constrained, and 2) the coefficients equal to the projected points of the examples. The first box constraint makes the basis to be bound and the second equality constraint keeps its equivalence to PNMF. Similar to PNMF, BPNMF is difficult because the objective function is non-convex. To solve BPNMF, we developed an efficient algorithm in the frame of augmented Lagrangian multiplier (ALM) method and proved that the ALM-based algorithm converges to local minima. Experimental results on two face image datasets demonstrate the effectiveness of BPNMF compared with the representative methods.

关键词： Accuracy Linear programming Training Convergence Optimization Face Educational institutions

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