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Examining the Reproducibility of Using Dynamic Loop Scheduling Techniques in Scientific applications

Examining the Reproducibility of Using Dynamic Loop Scheduli...

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IEEE international symposium on Parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Franziska Hoffeins Florina M. Ciorba Ioana Banicescu Technische Universität Dresden Center for Information Services and High Performance Computing Dresden Germany Department of Mathematics and Computer Science University of Basel Basel Switzerland Department of Computer Science and Engineering Mississippi State Mississippi State University MS USA

Reproducibility of the execution of scientific applications on parallel and distributed systems is a growing concern, underlying the trustworthiness of the experiments and the conclusions derived from experiments. Dynamic loop scheduling (DLS) techniques are an effective approach towards performance improvement of scientific applications via load balancing. These techniques address algorithmic and systemic sources of load imbalance by dynamically assigning tasks to processing elements. The DLS techniques have demonstrated their effectiveness when applied in real applications. Complementing native experiments, simulation is a powerful tool for studying the behavior of parallel and distributed applications. In earlier work, the scalability [1], robustness [2], and resilience [3] of the DLS techniques were investigated using the MSG interface of the SimGrid simulation framework [4]. The present work complements the earlier work and concentrates on the verification via reproducibility of the implementation of the DLS techniques in SimGrid-MSG. This work describes the challenges of verifying the performance of using DLS techniques in earlier implementations of scientific applications. The verification is performed via reproducibility of simulations based on SimGrid-MSG. To simulate experiments selected from earlier literature, the reproduction process begins by extracting the information needed from the earlier literature and converting it into the input required by SimGrid-MSG. The reproducibility study is carried out by comparing the performance of SimGrid-MSG-based experiments with those reported in two selected publications in which the DLS techniques were originally proposed. While the reproduction was not successful for experiments from one of the selected publications, it was successful for experiments from the other. This successful reproduction implies the verification of the DLS implementation in SimGrid-MSG for the considered applications and systems, and thus

关键词： Dynamic scheduling Processor scheduling Computational modeling Heuristic algorithms Analytical models Load modeling Scalability

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Development of a Hybrid Defensive Embedded System with Face Recognition 19

Development of a Hybrid Defensive Embedded System with Face ...

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19th IEEE international Conference on Computational science and engineering, 14th IEEE international Conference on Embedded and Ubiquitous computing and 15th international symposium on distributed computing and applications to business, engineering and science, CSE-EUC-DCABES 2016

作者： Tsourma, Maria Dasygenis, Minas Department of Informatics and Telecommunications Engineering University of Western Macedonia Kozani50100 Greece

ISBN: (纸本)9781509035939

The rapid development of Internet of Things and the current capabilities of high performance embedded systems have made them more attractive for the replacement of human personnel in hazardous or tedious duties. One such application is for guarding certain areas, such as the entrance of a warehouse for example. The aim of this work is to design an autonomous embedded security system for surveillance reasons. This system consists of a sentry gun and a camera. The software directing the sentry gun's actions is based on face and motion detection and face recognition. This gun locates, tracks and aims those who enter guarded areas and after verbal warning it fires, when facial recognition fails. This process is automated and works with high accuracy in real time circumstances. It also has the ability to inform its user when an intruder enters the area. The system meets the characteristics of ubiquitous computing as it is autonomous, can be used in any location and can be operated remotely via a web interface. It is hybrid because it supports two different versions of software with different hardware on each one, in order to allow the user to select the proper system version for him. The asymmetric embedded system's first version consists of a single board computer and the second version consists of a mini desktop for the computationally intensive tasks. A microcontroller is being used for high accuracy on the actuators and the system has the capability to use both USB and stereoscopic camera. © 2016 IEEE.

关键词： Face recognition

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Study on Fast Human Activity Recognition Based on Optimized Feature Selection

Study on Fast Human Activity Recognition Based on Optimized ...

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2017 16th international symposium on distributed computing and applications to business,engineering and science（DCABES 2017）

作者： Hanyuan Xu Zhibin Huang Jue Wang Zilu Kang School of Computer Science Beijing University of Posts and Telecommunications Institute of Internet of Things Technology China Electronic Technology Group Corporation Information Engineering Research Center

Sensor-based human activity recognition has attracted much scholarly attention due to its merit of wide ***,because of such hardware limitations as battery capacity and computing power,most current generation of wearable devices cannot yet benefit from those activity recognition methods based on deep learning theory and high dimension features since implementing these methods are time-consuming and need a relatively large amount of calculation.A solution,therefore,is proposed for this situation,which aims to reduce computational complexity by reducing the feature dimension through analyzing the linear correlation between the *** on the support vector machine model of single-layer fully connected network,the training and recognition time are significantly reduced while the recognition accuracy is still *** experiment is based on the public dataset in the UCI Machine Learning Repository,and it uses Caffe,a deep learning framework,to structure the support vector machine *** the experiment,when the feature dimension is reduced from 561 to 130,the training time can be reduced by 70% while the recognition accuracy is kept at a promising 91%.

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Application of BP Neural Network Based on Quasi-Newton Method in Aerodynamic Modeling

Application of BP Neural Network Based on Quasi-Newton Metho...

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2017 16th international symposium on distributed computing and applications to business,engineering and science（DCABES 2017）

作者： Yang Huiying Huang Zhibin Zhou Feng School of Computer Science Beijing University of Posts and Telecommunications

In the study of BP neural network for aerodynamic modeling,few studies have considered improving the generalization ability of *** generalization ability is important in the study of neural network *** typical methods to improve the generalization ability are tested in this paper,which are based on the LBFGS algorithm rather than the traditional gradient descent method when training BP neural *** indicate that when training neural network based on quasi-Newton method for aerodynamic modeling:1,adding the penalty term can improve the generalization ability 2,adding small variance noise will not improve the generalization ability.

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Research on User Interface Transformation Method Based On MDA

Research on User Interface Transformation Method Based On MD...

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2017 16th international symposium on distributed computing and applications to business,engineering and science（DCABES 2017）

作者： Gao Miao Liu Hongxing Lin Juncai Xie Songyu School of Computer Science and Technology Wuhan University of Technology

The user interface development method based on model driven architecture can effectively solve the problem that different platform-specific user interfaces have to be developed for the same application when the application needs to run on different *** method firstly designs the platform-independent model(PIM) of the user interface,then transforms the PIM into a variety of mainstream platform-specific model(PSM) automatically or semi-automatically,and finally transforms the PSM to a platform specific *** user interface transformation method from PIM to PSM is presented in this ***,a user interface PSM meta-model is ***,the mapping rules of PIM elements to PSM elements are defined in the meta-model level,and the transformation algorithm from PIM to PSM is *** verify the effectiveness of the method,we implemented a user interface software development tool which supports the transformation from PIM to PSM based on EMF and GMF.

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Symptom Distribution Regulation of Core Symptoms in Insomnia Based on Infomap-SA Algorithm

Symptom Distribution Regulation of Core Symptoms in Insomnia...

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2017 16th international symposium on distributed computing and applications to business,engineering and science（DCABES 2017）

作者： Fang Hu Yulu Qiao Guangjing Xie Yanhui Zhu Yalin Jia PanPan Huang College of Information Engineering Hubei University of Chinese Medicine College of Basic Medicine Hubei University of Chinese Medicine

In the recent decade,clinical data mining in Traditional Chinese Medicine(TCM) based on complex networks has been becoming a hot *** this paper,we construct the "Symptom-Prescription" bipartite network in insomnia,which can intuitively reflect the relationship between prescriptions and symptoms in *** then,through projection of this bipartite network,the "symptom" network is *** on the "symptom" network,the idea of node centrality is introduced to identify the core symptom nodes,which disclose the key factors in clinical diagnosis and ***,the "symptom" network is divided into several communities detected by Infomap-SA algorithm,the nodes in the same community reveal the concurrent rule of symptoms in insomnia,which has practical guiding significance for clinical diagnosis and treatment in TCM.

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Dimensions of Internet Use and Threat Sensitivity: An Exploratory Study among Students of Higher Education 19

Dimensions of Internet Use and Threat Sensitivity: An Explor...

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作者： Farooq, Ali Balakrishnan, Lalitha Phadung, Muneeroh Virtanen, Seppo Isoaho, Johanna Poudel, Dhan Prasad Isoaho, Jouni Department of Information Technology University of Turku Turku Finland Chennai India Faculty of Science Technology and Agriculture Yala Rajabhat University Yala Thailand Nepal Engineering College Kathmandu Nepal

ISBN: (纸本)9781509035939

The property space of internet use has three dimensions: type of use, amount of use and variety of use. While internet is one of the sources of information security knowledge among students, the relationship of dimensions of internet use and information security awareness has not yet been explored. The purpose of this paper is to explore relationship between dimensions of internet use and, information security and privacy (IS&P) threats sensitivity-defined as the ability of a person to assess impact of a threat to their IS&P through perceived importance of a threat. Threat sensitivity is measured by calculating threat sensitivity scores for seventy four different IS&P threats in fourteen functional areas [13]. Using convenient sampling, a response set of 1280 was collected from the students of six higher education institutions in India, Malaysia, Nepal, Pakistan and Thailand. Dimensions of internet use are computed and their correlations are calculated with student's overall threat sensitivity. Only type of use is found significantly correlated with overall threat sensitivity. Application of ANalysis Of VAriance (ANOVA) shows that students are significantly different in overall threat sensitivity, if divided into groups based upon the type of internet use. Further, the relationship between dimensions of internet use and student's threat sensitivity within all fourteen functional areas was also examined. © 2016 IEEE.

关键词： Students

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Learning from internet: Handling uncertainty in robotic environment modeling 17

Learning from internet: Handling uncertainty in robotic envi...

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9th Asia-Pacific symposium on Internetware, Internetware 2017

作者： Li, Yiying Wang, Huaimin Ding, Bo Che, Huimin National Key Laboratory of Parallel and Distributed Processing College of Computer National University of Defense Technology ChangSha China

ISBN: (纸本)1595930361

Uncertainty is a great challenge for environment perception of autonomous robots. For instance, while building semantic maps (i.e., maps with semantic labels such as object names), the robot may encounter unexpected objects of which it has no knowledge. It will lead to inevitable failures in traditional environment modeling software. The abundant knowledge being accumulated on the Internet has the potential to assist robots to handle such kind of uncertainty. However, existing researches have not touched this issue yet. This paper proposes a cloud-based semantic mapping engine named SemaCloud, which can not only augment robot's environment modeling capability by the rich cloud resources but also cope with uncertainty by utilizing the Internet knowledge on necessary. It adopts a state-of-art Deep Neural Network (DNN) for real-time and accurate recognition of pre-trained objects. If an object is beyond the knowledge of this DNN, a special mechanism named QoS-aware cloud phase transition is triggered to seek help from existing recognition services on the Internet. By a set of carefullydesigned algorithms, it can maximize benefits and minimize the negative impacts on the Quality of Service (QoS) properties of robotic applications, which is essential to many robot scenarios. The experiments on both open datasets and real robots show that our work can handle uncertainty successfully in robotic semantic mapping without sacrificing critical real-time constraints. © 2017 Association for computing Machinery.

关键词： Deep neural networks

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An Advanced Inventory Data Mining System for business Intelligence

An Advanced Inventory Data Mining System for Business Intell...

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IEEE international Conference on Big Data computing Service and applications (BigDataService)

作者： Qifeng Zhou Bin Xia Wei Xue Chunqiu Zeng Ruyuan Han Tao Li Automation Department Xiamen University Xiamen Fujian China School of Computer Science Technology and Engineering Nanjing University of Science and Technology Nanjing China School of Computing and Information Sciences Florida International University FL USA Florida International University Miami FL US

ISBN: (纸本)9781509063192

Inventory management plays a critical role to track inventory levels, orders, and sales of the retailing business. Effective inventory management is a capability necessary to lead in the global marketplace. In the current retailing market, a huge amount of data regarding stocked items in inventory is generated and collected every day. Due to the increasing volume of transaction data and their correlated relations, it is often a non-trivial task to efficiently manage stocked goods, yet it is imperative to explore the underlying dependencies of the inventory items and give insights into implementing intelligent management systems. However, existing inventory management systems rely on statistical analysis of the historical inventory data, and have a limited capability of intelligent management. For example, they usually do not have the ability to forecast item demand and detect anomalous patterns of item inventory transactions. There is little work reported in implementing intelligent inventory management solutions to reveal hidden relations with integrated data-driven analysis. In this paper, we present an intelligent system, called iMiner, to facilitate managing enormous inventory data. We utilize distributed computing resources to process the huge volume of inventory data and incorporate the latest advances in data mining technologies. iMiner provides comprehensive support for conducting many inventory management tasks, such as forecasting inventory, detecting anomalous items, and analyzing inventory aging.

关键词： Inventory management Forecasting Data analysis Time series analysis Predictive models Data mining

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Multigrain Parallelism: Bridging Coarse-Grain Parallel Programs and Fine-Grain Event-Driven Multithreading

Multigrain Parallelism: Bridging Coarse-Grain Parallel Progr...

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international symposium on Parallel and distributed Processing (IPDPS)

作者： Jaime Arteaga Stéphane Zuckerman Guang R. Gao Department of Electrical and Computer Engineering University of Delaware Newark DE USA Department of Computer Science Michigan Technological University Houghton MI USA

The overwhelming wealth of parallelism exposed by Extreme-scale computing is rekindling the interest for finegrain multithreading, particularly at the intranode level. Indeed, popular parallel programming models, such as OpenMP, are integrating fine-grain tasking in their newest standards. Yet, classical coarse-grain constructs are still largely preferred, as they are considered simpler to express parallelism. In this paper, we present a Multigrain Parallel Programming environment that allows programmers to use these well-known coarse-grain constructs to generate a fine-grain multithreaded application to be run on top of a fine-grain event-driven program execution model. Experimental results with four scientific benchmarks (Graph500, NAS Data Cube, NWChem-SCF, and ExMatEx's CoMD) show that fine-grain applications generated by and run on our environment are competitive and even outperform their OpenMP counterparts, especially for data-intensive workloads with irregular and dynamic parallelism, reaching speedups as high as 2.6x for Graph500 and 50x for NAS Data Cube.

关键词： Runtime Parallel processing Copper Parallel programming Computational modeling Program processors Standards

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