High level context recognition and situation detection are enabling technologies for unobtrusive mobile computing systems. Significant progress has been made in processing and managing context information, leading to ...
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High level context recognition and situation detection are enabling technologies for unobtrusive mobile computing systems. Significant progress has been made in processing and managing context information, leading to sophisticated frameworks, middlewares, and algorithms. Despite great improvements, context aware systems still require a significantly increased recognition accuracy for high-level context information on uncertain sensor data to enable the robust execution of context-aware applications. Recently Adaptable Pervasive Workflows (APF)s have been presented as innovative programming paradigm for mobile context-aware applications. We propose a novel Flow Context System (FlowCon) that builds upon APFs. FlowCon uses structural information from the APF to increase accuracy of uncertain high-level context information up to 49%. this way we make an important step to enable robust execution of mobile context-aware applications.
the base technologies for realizing distributed sensor network systems using many wireless sensor terminals have developed rapidly. the sensor network systems are expected to find applications in various fields such a...
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the base technologies for realizing distributed sensor network systems using many wireless sensor terminals have developed rapidly. the sensor network systems are expected to find applications in various fields such as disaster prevention, environmental monitoring, agricultural support, health care, logistics, and business applications. M2M (machine-to-machine) technology enables machines to communicate with each other without human intervention. the M2M technology could possibly play big role in the future in applications such as sensor network systems, networked embedded systems and information-processing systems. this paper proposes a set of student experiment methods that assist students to understand the basic M2M technology by implementing sensor network systems.
Photovoltaic systems have been considered as one of most promising fields of application for SiC semiconductors mainly due to the requirements for very high efficiency *** other system aspects like volume and cost may...
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Photovoltaic systems have been considered as one of most promising fields of application for SiC semiconductors mainly due to the requirements for very high efficiency *** other system aspects like volume and cost may also profit from the interesting characteristics of such innovative *** based on SiC show a large variety of technologies,ranging from bipolar devices like BJTs to unipolar devices like MOSFETs and *** latter is rather uncommon in power electronic applications but seems very promising,mainly due to its relative structural *** are mainly two basic variants of SiC-JFETs which will be presented and discussed in this publication.
Robotic swarms, like all spatial computers, are a challenging environment for the execution of distributed consensus algorithms due to their scale, diameter, and frequent failures. Exact consensus is generally impract...
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ISBN:
(纸本)9780982657119
Robotic swarms, like all spatial computers, are a challenging environment for the execution of distributed consensus algorithms due to their scale, diameter, and frequent failures. Exact consensus is generally impractical on spatial computers, so we consider approximate consensus algorithms. In this paper, we show that the family of self-organizing protocols based on the graph Laplacian of a network[19] are impractical as well. With respect to the structure of a finite-neighborhood spatial computer, we find that these protocols have an expected convergence time of O(diameter2) when the inputs are strongly correlated with location. Verifying this result in simulation, we further determine that the constant factor on the convergence time is high, rendering Laplacian-based approximate consensus unsuitable for general use on spatial computers.
A parallel version of a new automatic Harris-based corner detector is presented. A scheduler to dynamically and homogeneously distribute high computational workload on heterogeneous parallel architectures such as Grid...
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ISBN:
(纸本)9781424452910
A parallel version of a new automatic Harris-based corner detector is presented. A scheduler to dynamically and homogeneously distribute high computational workload on heterogeneous parallel architectures such as Grid systems has been implemented to speedup the whole procedure. Experimental results show the robustness of the underlying scheduler, which can be easily exploited in various automatic image analysis systems.
Finding a vast array of applications, the problem of computingthe convex hull of a set of sorted points in the plane is one of the fundamental tasks in pattern recognition, morphology and image processing. the main c...
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ISBN:
(纸本)9781424452910
Finding a vast array of applications, the problem of computingthe convex hull of a set of sorted points in the plane is one of the fundamental tasks in pattern recognition, morphology and image processing. the main contribution of this paper is to show a simple parallel algorithm for computingthe convex hull of a set of n sorted points in the plane and evaluate the performance on the dual quad-core processors. the experimental results show that, our implementation achieves a speed-up factor of approximately 7 using 8 processors. Since the speed-up factor of more than 8 is not possible, our parallel implementation for computingthe convex hull is close to optimal. Also, for 2 or 4 processors, we achieved a super linear speed up.
Withthe advent of multi-core processors, desktop application developers must finally face parallelcomputing and its challenges. A large portion of the computational load in a program rests within iterative computati...
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ISBN:
(纸本)9781424452910
Withthe advent of multi-core processors, desktop application developers must finally face parallelcomputing and its challenges. A large portion of the computational load in a program rests within iterative computations. In object-oriented languages these are commonly handled using iterators which are inadequate for parallel programming. Consequently, the powerful parallel Iterator concept was developed. this paper presents various developments of the parallel Iterator, such as parallel traversal of complex collections with partial ordering (such as a tree). Other features include reductions, parallel remove semantics and exception handling. Along withthe ease of use, the results reveal great speedup in comparison to traditional Java parallelism approaches.
Genetic fuzzy rule selection has been successfully used to design accurate and interpretable fuzzy classifiers from numerical data. In our former study, we proposed its paralleldistributed implementation which can dr...
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ISBN:
(纸本)9781424447350
Genetic fuzzy rule selection has been successfully used to design accurate and interpretable fuzzy classifiers from numerical data. In our former study, we proposed its paralleldistributed implementation which can drastically decrease the computational time by dividing both a population and a training data set into sub-groups. In this paper, we examine the effect of data reduction on the generalization ability of fuzzy rule-based classifiers designed by our paralleldistributed approach. through computational experiments, we show that data reduction can be realized without severe deterioration in the generalization ability of the designed fuzzy classifiers.
Withparallelcomputing system scaling up, the system reliability drastically decreases, so parallelapplications running on such system must tolerate hardware failures. Checkpointing is widely used in the domain of l...
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ISBN:
(纸本)9781424452910
Withparallelcomputing system scaling up, the system reliability drastically decreases, so parallelapplications running on such system must tolerate hardware failures. Checkpointing is widely used in the domain of large-scale parallelcomputing, which periodically saves the state of computation to stable storage. this produces innegligible fault tolerance overhead. the traditional speedup only measures the performance of failure-free system. In this paper, we firstly propose the speedup metric taking into account checkpointing overhead. the new metric unifies the performance and reliability measures, and evaluates the practical speedup of parallel application with checkpointing. Furthermore, this paper classifies and analyzes existing parallel systems according to the proposed speedup metric, and makes suggestions on system design and fault tolerance techniques improvement. Finally, we validate the analysis of this new speedup metric by experiment. the experimental results indicate that the proposed speedup for parallel application with checkpointing is an effective metric.
Many data mining techniques have been proposed for parallelapplications performance analysis, the most interesting being clustering analysis. Most cases have been used to detect processors with similar behavior. In p...
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ISBN:
(纸本)9781424452910
Many data mining techniques have been proposed for parallelapplications performance analysis, the most interesting being clustering analysis. Most cases have been used to detect processors with similar behavior. In previous work, we presented a different approach: clustering was used to detect the computation structure of the applications and how these different computation phases behave. In this paper, we present a method to evaluate the accuracy of this structure detection. this new method is based on the Single Program Multiple Data (SPMD) paradigm exhibited by real parallel programs. Assuming an SPMD structure, we expect that all tasks of a parallel application execute the same operation sequence. Using a Multiple Sequence Alignment (MSA) algorithm, we check the sequence ordering of the detected clusters to evaluate the quality of the clustering results.
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