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Key element protection of combat system is a challenging problem in modern combat. Effectively evaluating the key elements would be of great help in force deployment in crisis situations. This paper proposes a new evaluation method that combines expert evaluation, PCA (Principal Component Analysis) and TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution). Specifically, we first...
Recently, convolutional neural networks (CNNs) have achieved great success in fields such as computer vision, natural language processing, and artificial intelligence. Many of these applications utilize parallel processing in GPUs to achieve higher performance. However, it remains a daunting task to optimize for GPUs, and most researchers have to rely on vendor-provided libraries for such purposes...
Epidemic routing is considered useful for wireless mobile sensor networks where infrastructure support is limited and sensed information has to be disseminated in a timely manner. The relaying overhead of epidemic routing, however, needs to be reduced to conserve energy. In this paper, we study a new problem: what is a good strategy in epidemic routing to self-stop forwarding a message when a certain...
The increasingly important data-intensive scientific discovery presents a critical question to the high performance computing (HPC) community - how to efficiently support these growing scientific big data applications with HPC systems that are traditionally designed for big compute applications? The conventional HPC systems are computing-centric and designed for computation-intensive applications...
The data volume of many scientific applications has substantially increased in the past decade and continues to increase due to the rising needs of high-resolution and fine- granularity scientific discovery. The data movement between stor- age and compute nodes has become a critical performance factor and has attracted intense research and development attention in recent years. In this paper, we propose...
In this paper, an extended ANFIS architecture is proposed. By incorporating an extra layer for the fuzzification process, the extended architecture is able to fit both type-1 and interval type-2 models. The learning properties of the proposed architecture based on the least-squares estimate method are studied on selected type-1 and interval type-2 ANFIS models. We show that the least-squares estimate...
The fast growing data volume poses significant challenges as well as opportunities to research and industry. Data scientists and domain experts demand high productive and high-performance data analytics platform, which will alleviate their work, tackle these challenges, and find more opportunities from data. The objective of our research is to build such a productive data analytics cloud platform...
This paper presents a transfer learning-based approach for bearing fault diagnosis, where the transfer strategy is proposed to improve diagnostic performance of the bearings under various operating conditions. The main idea of transfer learning is to utilize selective auxiliary data to assist target data classification, where a weight adjustment between them is involved in the TrAdaBoost algorithm...
Thanks to the advances of data acquisition techniques, we can acquire ventricular blood flow data with very high quality. This extremely complex spatiotemporal data calls for novel visualization and analysis tools. In particular, the new tools need to assist domain experts in quick identification of critical patterns. In this paper, we present a method using topo-logical data analysis tools with simulated...
The I/O bottleneck issue has been acknowledged as one of main performance issues of high performance computing (HPC) systems for data-intensive scientific applications, and has attracted intensive studies in recent years. With the enlarging gap between the computing bandwidth and I/O bandwidth in projected next-generation HPC systems, this issue will become even worse. In this paper, we present a...
Many high-end computing applications in critical areas of science and technology are becoming more and more data intensive. These applications transfer large amounts of data from storage nodes to compute nodes for processing, which is costly and bandwidth consuming. The data movement often dominates the applications' run time. Active storage provides a promising solution for these applications by...
Active storage provides an effective method to mitigate the I/O bottleneck problem of data intensive high performance computing applications. It can reduce the amount of data transferred as the application runs by moving appropriate computations close to the data. Prior research has achieved considerable progress in developing several active storage prototypes. However, existing studies have neglected...
High-end computing (HEC) applications in critical areas of science and technology tend to be more and more data intensive. I/O has become a vital performance bottleneck of modern HEC practice. Conventional HEC execution paradigms, however, are computing-centric for computation intensive applications. They are designed to utilize memory and CPU performance and have inherent limitations in addressing...
Based on Any Lagrange-Euler algorithm( ALE), using ANSYS/LS-DYNA, the paper analyses the propagation of shockwave after encountering an elastic thin plate which is fixed around when an explosion takes place at altitude and on the rigid ground. The reflex rule is investigated when shockwave meets the plate with explosive in different distance to the plate in the air, as well as the reflection and diffraction...
This paper addresses issues of safety in pervasive spaces. We show how pervasive systems are different from traditional computer systems, and how their cyber-physical nature ties intimately with the users. Errors and conflicts in such space could have detrimental, dangerous or undesired effects on the user, the space, or the devices. There are no support systems or programming models conscious of...
This article proposed a nonparametric test method by using Gaussian mixture model application idea for reference to evaluating the construction of index architecture. First use Gaussian mixture model to cluster analysis the index architecture. Second use rank correlation coefficient of nonparametric test method to select index architecture. Then determined the evaluate index architecture and guarantee...
Pervasive computing systems are begging for programming models and methodologies specifically suited to the particular cyber-physical nature of these systems. Reactive (rule-based) programming is an attractive model to use due to its built-in safety features and intuitive application development style. Without careful optimization however, reactive programming engines could turn into monstrous power...
This paper describes simulation work in modeling a city-wide trunked radio system and evaluating its performance under stress. Specifically, traffic models are developed to simulate both routine background traffic and the traffic load associated with an emergency scenario of a high-rise apartment fire. An analysis of a one-month radio data log provided insights on the traffic distribution among different...
Trust is very important to semantic Web. We propose a trust model of semantic Web by using classic linear regression models, time series models and vector auto regression generalized autoregressive conditional heteroskedasticity models. First, we discuss the background and related work about trust in semantic Web. Then the management of uncertainty is analyzed. At last, we give the prediction algorithm...
The conventional octree construction method is implemented iteratively at consecutive subdivision levels. The resultant octree models at different subdivision levels contain quite different octant compositions, so the system performance, in terms of model accuracy, memory space and construction time, changes widely with the subdivision level number. Since the big system performance gap is not desirable...
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