We present LM, a tool for mining scenario-based specifications in the form of Live Sequence Charts, a visual language that extends sequence diagrams with modalities. LM comes with a project management component, a wiz...
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We present LM, a tool for mining scenario-based specifications in the form of Live Sequence Charts, a visual language that extends sequence diagrams with modalities. LM comes with a project management component, a wizard-like interface to the mining algorithm, a set of pre- and post-processing extensions, and a visualization module.
Early works on Private Information Retrieval (PIR) focused on minimizing the necessary communication overhead. Theyseemed to achieve this goal but at the expense of query response time. To mitigate this weakness, prot...
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Existing time synchronization algorithms and protocols mostly focus on improving the synchronization accuracy. However, they usually require frequent resynchronization to keep designed precision in actual applications...
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Existing time synchronization algorithms and protocols mostly focus on improving the synchronization accuracy. However, they usually require frequent resynchronization to keep designed precision in actual applications, which leads to high energy consumption and heavy traffic load. This paper presents a Prediction based Long-cycle Time Synchronization algorithm (PLTS), which puts emphasis on reducing the resynchronization frequency while guaranteeing a given accuracy. PLTS is a combination of periodic synchronization and prediction synchronization. It makes use of an existing time synchronization protocol to accomplish the periodic synchronization, while during the intervals of periodic synchronization, each node applies a prediction model to calibrate its own logic time according to the crystal oscillator's frequency characteristics. By this means, all nodes can keep synchronization till next periodic synchronization starts. Experiment results show that PLTS can reduce resynchronization frequency remarkably and possesses good merits in saving energy and reducing traffic load.
Testing-as-a-service (TaaS) is a new model to provide testing capabilities to end users. Users save the cost of complicated maintenance and upgrade effort, and service providers can upgrade their services without impa...
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Testing-as-a-service (TaaS) is a new model to provide testing capabilities to end users. Users save the cost of complicated maintenance and upgrade effort, and service providers can upgrade their services without impact on the end-users. Due to uneven volumes of concurrent requests, it is important to address the elasticity of TaaS platform in a cloud environment. Scheduling and dispatching algorithms are developed to improve the utilization of computing resources. We develop a prototype of TaaS over cloud, and evaluate the scalability of the platform by increasing the test task load;analyze the distribution of computing time on test task scheduling and test task processing over the cloud;and examine the performance of proposed algorithms by comparing others.
In this study, a novel spatial information based support vector machine for hyperspectral image classification, named spatial-contextual semi-supervised support vector machine (SC 3 SVM), is proposed. This approach mo...
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In this study, a novel spatial information based support vector machine for hyperspectral image classification, named spatial-contextual semi-supervised support vector machine (SC 3 SVM), is proposed. This approach modifies the SVM algorithm by using the spectral information and spatial-contextual information. The concept of SC 3 SVM is to utilize other information, obtain from the pixels of a neighborhood system in the spatial domain, to modify the effective of each patterns. Experimental results show a sound performance of classification on the famous hyperspectral images, Indian Pine site. Especially, the overall classification accuracy of whole hyperspectral image (Indian Pine site with 16 classes) is up to 96.4%, the kappa accuracy is up to 95.9%.
According to recent work, duplicate bug reports impact negatively on software maintenance and evolution productivity due to, among other factors, the increased time spent on report analysis and validation. Therefore, ...
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According to recent work, duplicate bug reports impact negatively on software maintenance and evolution productivity due to, among other factors, the increased time spent on report analysis and validation. Therefore, a considerable amount of time is lost mainly with duplicate bug report analysis. In this sense, this work presents am exploratory study using data from bug trackers from private and open source projects, in order to understand the possible factors (i.e. software life-time, size, amount of bug reports, etc.) that cause bug report duplication and its impact on software development. This work also discusses bug report characteristics that could help identifying duplicates.
Utilizing virtualization technology to combine real-time operating system(RTOS)and off-the-shelf time-sharing general purpose operating system (GPOS)is attracting much more interest *** combination has the potential t...
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Utilizing virtualization technology to combine real-time operating system(RTOS)and off-the-shelf time-sharing general purpose operating system (GPOS)is attracting much more interest *** combination has the potential to provide a large application base,and to guarantee timely deterministic response to real-time applications,yet there is no convincible experimental result about its real-time *** this paper,we analyze the interrupt latency of RTOS running on Linux KVM based on some preliminary tunings,and find out System Management Interrupt (SMI) is the main factor which makes the maximum latency unideal, so we propose a method to limit the worst-case interrupt latency in an acceptable ***,we also find out that boosting priority may result in wastes of CPU resources when RTOS is not executing real-time tasks,so we design a co-scheduling mechanism to improve the CPU throughput of the GPOS system.
GPUs are many-core processors with tremendous computational power. However, as automatic parallelization has not been realized yet, developing high-performance parallel code for GPUs is still very challenging. The pap...
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GPUs are many-core processors with tremendous computational power. However, as automatic parallelization has not been realized yet, developing high-performance parallel code for GPUs is still very challenging. The paper presents a novel translation framework designed for virtual execution environment based on CPU/GPU architecture. It addresses two major challenges of taking advantage of general purpose computation on graphics processing units (GPGPU) to improve performance: no rewriting the existing source code and resolving binary compatibility issues between different GPUs. The translation framework uses semi-automatic parallelization technology to port existing code to explicitly parallel programming models. It not only offers a mapping strategy from X86 platform to CUDA programming model, but also synchronizes the execution between the CPU and the GPUs. The input to our translation framework is parallelizable part of the program within binary code. With an additional information related to the parallelizable part, the translation framework transforms the sequential code into PTX code and execute it on GPUs. Experimental results on several programs from CUDA SDK Code Samples and Parboil Benchmark Suite show that our translation framework could achieve very high performance, even up to several tens of times speedup over the X86 native version.
In order to get rid of the limit of traditional methods and provide a decision making reference for the supervision of securities organizations and the risk control of investors, A novel model based on SOM2W network (...
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In order to get rid of the limit of traditional methods and provide a decision making reference for the supervision of securities organizations and the risk control of investors, A novel model based on SOM2W network (SOM with 2 winners self-organizing map) is proposed for assessment financial performance of the listed companies. In addition, a tabu-mapping method is proposed to avoid that the same output node is mapped by more than one input. The financial indexes reflecting the whole performance level of companies are used in the simulated experiments including earning per share, net asset yield and main profit margin. Simulation results show that the proposed model is feasible for assessment listed reality companies. It could provide an effective approach for analyzing and selecting listed companies, which has good potential in the financial field.
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