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检索条件"任意字段=10th International Conference on Parallel and Distributed Computing, Applications and Technologies"

共 1765 条记录，以下是491-500 订阅

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Recognizing ADLs of One Person Household based on Non-intrusive Environmental Sensing 18

Recognizing ADLs of One Person Household based on Non-intrus...

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18th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD)

作者： Niu, Long Saiki, Sachio Nakamura, Masahide Kobe Univ Grad Sch Syst Informat Nada Ku 1-1 Rokkodai Kobe Hyogo 6578501 Japan

ISBN: (纸本)9781509055043

Pervasive sensing technologies are promising for increasing one-person households (OPH), where the sensors monitor and assist the resident to maintain healthy life rhythm. Towards the practical use, the recognition of activities of daily living (ADL) is an important step. Many studies of the ADL recognition have been conducted so far, for real-life and human-centric applications such as eldercare and healthcare. However, most existing methods have limitations in deployment cost, privacy exposure, and inconvenience for residents. To cope with the limitations, this paper presents a new indoor ADL recognition system especially for OPH. To minimize the deployment cost as well as the intrusions to user and house, we exploit an IoT-based environment-sensing device, called Autonomous Sensor Box (SensorBox) which can autonomously measure 7 kinds of environment attributes. We apply machine-learning techniques to the collected data, and predicts 7 kinds of ADLs. We conduct an experiment within an actual apartment of a single user. the result shows that the proposed system achieves the average accuracy of ADL recognition with more than 88%, by carefully developing the features of environment attributes.

关键词： Non-intrusive environment sensing Activities of Daily Living ADLs recognition Feature Engineering Machine Learning

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Multi-level Grid Based Clustering and GPU parallel Implementations 14

Multi-level Grid Based Clustering and GPU Parallel Implement...

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14th international Symposium on Pervasive Systems, Algorithms and Networks (I-SPAN) / 11th international conference on Frontier of Computer Science and Technology (FCST) / 3rd international Symposium of Creative computing (ISCC)

作者： Qian, Quan Zhao, Shuai Xiao, Chao-Jie Hung, Che-Lun Shanghai Univ Sch Comp Engn & Sci Shanghai 200444 Peoples R China Shanghai Univ Mat Genome Inst Shanghai 200444 Peoples R China Providence Univ Dept Comp Sci & Commun Engn Taichung Taiwan

ISBN: (纸本)9781538608401

Clustering algorithm for stream data, as one of stream data mining technologies, has extensive applications on network traffic analysis, telecommunication, planetary remote sensing, web site analysis, etc. Clustering algorithm for stream data has a high demand for real-time processing, but current clustering algorithms for stream data, such as Clustream, Dstream, are all based on sequential algorithms, which are unable to meet the realtime requirement. In this paper, we propose a multi-grid based clustering algorithm for stream data. the algorithm partitions the grid space appropriately on the basis of conventional grid-based DBSCAN clustering algorithm, which can effectively limit the searching scope of grid neighbours to accelerate processing performance. Meanwhile, we utilize CUDA to conduct parallel computing in order to further speed up processing. through the experiments tested on the KDDCUP-99 open testing dataset, it shows that the processing speed of the algorithm proposed by the paper is 10 times faster than that of the conventional grid-based algorithm and moreover the CUDA based algorithm can achieve an speedup of 3 compared with the algorithm executed on CPU.

关键词： Multi-grid clustering algorithm for stream data GPU parallelization

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A lightweight MapReduce framework for secure processing with SGX 17

A lightweight MapReduce framework for secure processing with...

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17th IEEE/ACM international Symposium on Cluster, Cloud and Grid computing (CCGRID)

作者： Pires, Rafael Gavril, Daniel Felber, Pascal Onica, Emanuel Pasin, Marcelo Univ Neuchatel Neuchatel Switzerland Alexandru Ioan Cuza Univ Iasi Romania

ISBN: (纸本)9781509066117

MapReduce is a programming model used extensively for parallel data processing in distributed environments. A wide range of algorithms were implemented using MapReduce, from simple tasks like sorting and searching up to complex clustering and machine learning operations. Many of these implementations are part of services externalized to cloud infrastructures. Over the past years, however, many concerns have been raised regarding the security guarantees offered in such environments. Some solutions relying on cryptography were proposed for countering threats but these typically imply a high computational overhead. Intel, the largest manufacturer of commodity CPUs, recently introduced SGX (software guard extensions), a set of hardware instructions that support execution of code in an isolated secure environment. In this paper, we explore the use of Intel SGX for providing privacy guarantees for MapReduce operations, and based on our evaluation we conclude that it represents a viable alternative to a crypto-graphic mechanism. We present results based on the widely used k-means clustering algorithm, but our implementation can be generalized to other applications that can be expressed using MapReduce model.

关键词： distributed processing security MapReduce

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Information-Analytical technologies of Decision Support in Management of Power Systems 10th

Information-Analytical Technologies of Decision Support in M...

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10th international conference on Management Science and Engineering Management (ICMSEM)

作者： Ayupov, Shavkat Arifjanov, Abdulla Acad Sci Uzbek Inst Math Tashkent Uzbekistan Acad Sci Uzbek Inst Energy & Automat Tashkent Uzbekistan

ISBN: (纸本)9789811018374;9789811018367

In market conditions the effective control of the operation of power systems is directly dependent on the implementation of management decisions. Management decisions in turn depend on whether, what information (volume and quality) comes, how it is processed and used. In the coming decades the relevance of this problem will grow since information becomes the main strategic resource in the competitive struggle. In this regard it becomes topical the problems associated with the unification of territorially distributed facilities power systems into a single information space, which provides: integrated view of the complex control object as a whole;a comprehensive analysis of the collected information about him;the extraction from the huge volume of detailed data some useful information-knowledge about the regularities of its development. Solving these problems is possible by introduction in the practice of modern information and intelligent decision making support technology. In the basis of these technologies are the automated information-analytical systems (IAS) for the collection, storage systematization, processing, analysis and presentation of information. this report is dedicated of the new information-analytical technologies, allowing automating the management of energy efficiency in enterprises. For disclosure essence of information-analytical system of support for management decision-making is considered a formal model of control process. Considered issues of the designing of structure and semantics of the data to form a data warehouse of the information-analytical system for decisions support in Management with the use of a balanced scorecard.

关键词： Effective control of the operation of power systems Management decisions Modern information and intelligent decision making support technology Information-analytical technologies Formal model of control process Balanced scorecard

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CLOSER 2017 - Proceedings of the 7th international conference on Cloud computing and Services Science

CLOSER 2017 - Proceedings of the 7th International Conferenc...

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7th international conference on Cloud computing and Services Science, CLOSER 2017

ISBN: (纸本)9789897582431

the proceedings contain 84 papers. the topics discussed include: a CKAN plugin for data harvesting to the Hadoop distributed file system;a computation- and network-aware energy optimization model for virtual machines allocation;cost optimization on public cloud provider for big geospatial data;reconfigurable and adaptive spark applications;managing and unifying heterogeneous resources in cloud environments;an ontological template for context expressions in attribute-based access control policies;highly reconfigurable computing platform for high performance computing infrastructure as a service: Hi-IaaS;combining TOSCA and BPMN to enable automated cloud service provisioning;anything to topology - a method and system architecture to topologize technology-specific application deployment artifacts;ROP defense in the cloud through live text page-level re-ordering - the LITPR system;a framework for certification of large-scale component-based parallel computing systems in a cloud computing platform for HPC services;recovery-oriented resource management in hybrid cloud environments;component-wise application migration in bidimensional cross-cloud environments;uncertainty-aware optimization of resource provisioning, a cloud end-user perspective;DISCO: a dynamic self-configuring discovery service for semantic web services;and Internet of things out of the box: using TOSCA for automating the deployment of IoT environments.

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Runtime Data Layout Scheduling for Machine Learning Dataset 46

Runtime Data Layout Scheduling for Machine Learning Dataset

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46th international conference on parallel Processing Workshops (ICPPW)

作者： You, Yang Demmel, James Univ Calif Berkeley Div Comp Sci Berkeley CA 94720 USA

ISBN: (纸本)9781538610428

Machine Learning (ML) approaches are widely-used classification/regression methods for data mining applications. However, the time-consuming training process greatly limits the efficiency of ML approaches. We use the example of SVM (traditional ML algorithm) and DNN (state-of-the-art ML algorithm) to illustrate the idea in this paper. For SVM, a major performance bottleneck of current tools is that they use a unified data storage format because the data formats can have a significant influence on the complexity of storage and computation, memory bandwidth, and the efficiency of parallel processing. To address the problem above, we study the factors influencing the algorithm's performance and conduct auto-tuning to speed up SVM training. DNN training is even slower than SVM. For example, using a 8-core CPUs to train AlexNet model by CIFAR-10 dataset costs 8.2 hours. CIFAR-10 is only 170 MB, which is not efficient for distributed processing. Moreover, due to the algorithm limitation, only a small batch of data can be processed at each iteration. We focus on finding the right algorithmic parameters and using auto-tuning techniques to make the algorithm run faster. For SVM training, our implementation achieves 1.7-16.3x speedup (6.8x on average) against the non-adaptive case (using the worst data format) for various datasets. For DNN training on CIFAR-10 dataset, we reduce the time from 8.2 hours to only roughly 1 minute. We use the benchmark of dollars per speedup to help the users to select the right deep learning hardware.

关键词： parallel auto-tuning machine learning

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Proceedings - 10th IEEE international conference on Software Testing, Verification and Validation Workshops, ICSTW 2017

Proceedings - 10th IEEE International Conference on Software...

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10th IEEE international conference on Software Testing, Verification and Validation Workshops, ICSTW 2017

ISBN: (纸本)9781509066766

the proceedings contain 67 papers. the topics discussed include: impact of education and experience level on the effectiveness of exploratory testing: an industrial case study;a test case recommendation method based on morphological analysis, clustering and the Mahalanobis-Taguchi method;results of a comparative study of code coverage tools in computer vision;a process for sound conformance testing of cyber-physical systems;targeted mutation: efficient mutation analysis for testing non-functional properties;runtime verification for detecting suspension bugs in multicore and parallel software;speeding-up mutation testing via data compression and state infection;mutation patterns for temporal requirements of reactive systems;an architecture for the development of mutation operators;mutation score, coverage, model inference: quality assessment for T-way combinatorial test-suites;optimizing IPOG's vertical growth with constraints based on hypergraph coloring;test case generation with regular expressions and combinatorial techniques;applications of practical combinatorial testing methods at Siemens industry inc., building technologies division;and suggestion of practical quantification measuring method of test design which can represent the current status.

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Towards an ontology development for automated applications in smart city environment of SmartME project 10

Towards an ontology development for automated applications i...

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10th EAI international conference on Performance Evaluation Methodologies and Tools, ValueTools 2016

作者： Kushwaha, Nidhi Vyas, O.P. Puliafito, Carlo Vyas, Ranjana Indian Institute of Information Technology Allahabad India International Institute of Information Technology Naya Raipur India Dipartimento di Ingegneria Elettrica Elettronica e Informatica University of Catania Italy

ISBN: (纸本)9781631901416

Cities are becoming everyday smarter, with an increasing multitude of electronic nodes distributed throughout the territory. these range from rather simple ones, such as sensors/actuators, but also smartphones, to more complex ones, such as data centers and workstations. Citizens may have a central role in consuming, but also producing the data. the consequence of all this is that the amount of data collected is enormous and these data need to be properly processed in order to make the most of them. Unfortunately, there are several challenges in data processing, but exploiting the Semantic Web technologies and linking data among them is the right way to face them. this paper introduces the SmartME project developed by the University of Messina, Italy, and discusses the technologies and approached that cat be utilized to properly manage the collected data. In this paper, we are working towards the incorporation of semantic layer with the SmartME project of University of Messina. In this, our contribution is to built logic for maintaining sensors and their collected information query them in more meaningful way for getting accurate results. Also, we have presented a way of modifying a previously developed Ontology, SSN and customized it for our purpose. Other than manual entry of a new sensor, which mitigates the burden of manual entry. To build up this logic, we have exploited Jena API of Semantic Web in Java. Copyright © 2016 EAI.

关键词： Semantic Web

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A Fine-grained parallel Approach for one Logical Process on Multi-core Machines 17

A Fine-grained Parallel Approach for one Logical Process on ...

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10th EAI international conference on Simulation Tools and Techniques, SIMUTOOLS 2017

作者： Fei, Jiawei Yao, Yiping Luan, Jing Li, Lufan Bao, Yingqian College of Information System and Management National University of Defense Technology 137 Yanwachi Changsha China

ISBN: (纸本)9781450363884

Currently, the time management algorithms applied in various parallel discrete event simulation (PDES) engines take the logical process as the smallest parallel unit which corresponds to a physical process and represents a sequential simulation. Before the simulation system is running, all the entities are distributed to each logical process. the parallelism of the simulation system depends on the parallelism between logical processes. the performance of this parallel approach is greatly affected by the entity distribution scheme. For example, when the computing hotspots are assigned to one LP, the performance of the parallel simulation is almost the same as that of the serial simulation. And it is difficult to find a suitable entity distribution scheme when it comes to simulation with hotspots which migrate between LPs dynamically. Besides, we always use as many LPs as possible to improve parallelism, but this also brings greater communication and synchronization overhead. Focusing on these drawbacks of current simulation engines, we propose an approach which supports fine grain parallelism in one LP. Based on the traditional time management algorithms, our approach can process events of different entities in one LP in parallel with multi threads. © 2017 ACM.

关键词： Discrete event simulation

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Dos and Donts Integrated System based on GPS and Cloud technologies for Pilgrims 14

Dos and Donts Integrated System based on GPS and Cloud Techn...

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14th IEEE international conference on Mobile Ad Hoc and Sensor Systems (MASS)

作者： Kanakri, Wafaa Tawalbeh, Lo'ai A. AlHarbi, Ayman Umm Al Qura Univ Dept Comp Engn Mecca 21955 Saudi Arabia

ISBN: (纸本)9781538623237

All over the world, the crowd management is a big challenge facing the organizations of any event with large number of people. It is clear that this task is becoming more difficult and complicated when the event is larger. In the recent few years, the there are many new technologies developed that can be utilized in crowed management. Among these new technologies is wireless communications, cloud computing, GPS services and many others. Moreover, the wide spread of smart phones and there useful applications made it easier to benefit directly from these technologies. One of the largest worldwide people gathering event is the Pilgrim. Every year, millions of people visit the holy city of Makkah from different countries of the world with different languages and cultural backgrounds. Pilgrim includes certain doings at certain times at certain locations which emphasizes the complexity of crowd management task of the biggest event worldwide. Besides the transportation, housing, and feeding management, there is the dos and donts management of this huge event since it is being a timed and location-based worship. In this research, we utilize the advanced technologies to develop a mobile application to guide the visitors of Makkah (including the elders and those of hearing disability) to perform the correct worship doings and to avoid the worship donts at the holy place of Makkah. the application detects the GPS location of the visitor and sends notifications if he/she commits any donts at that location using a cloud-based decision system. the notifications can be sent as text, image, and video (with deaf sign language integrated). More features of our application, and given that the diversity of Pilgrim, it supports three main languages;Arabic, English, and Urdu, and it is compatible with iOS and Android. the application development process followed the best practices in software engineering that is shown in this paper. To test the application efficiency and functionality, r

关键词： Cloud computing Mobile applications Crowd Management Smart Mobile Devices GPS Technology

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