134347
VR-GIS: an integrated platform of VR navigation and GIS analysis for city/region simulation
This paper introduces a virtual city oriented VR-GIS platform which synthesizes several latest information technologies including virtual reality, 3D geographical information system, remote sensing and multi-dimensional visualization. The platform is a seamless integration of VR functions and GIS analysis methods, which can be used to organize and present massive spatial data. It also supplies 3D spatial analysis functions, 3D visualization for spatial process and natural simulation, and serves as an engine platform for digital city.
20054988
Elastic Algorithm: A New Path Planning Algorithm About Auto-navigation in 3D Virtual Scene
Elastic Algorithm proposed in this paper is a new and fast path planning algorithm to solve the problem of auto-navigation in 3D virtual scene. First, with a grid model based representation of virtual environments, different obstacles are assigned different color in the projection map of scene and their encasing boxes are stored to provide local path. Then, Elastic Algorithm is designed to optimize the basic path. It can be applied to complex condition and moving object, and has high stability and efficiency in solving the path planning problem.
20203347
RBF Kernel Based Support Vector Machine with Universal Approximation and Its Application
The SVM has been used to the nonlinear function mapping successfully, but the universal approximation property of the SVM has never been proved in theory. This paper proves the universal approximation of the SVM with RBF kernel to arbitrary functions on a compact set and deduces it to the approximation of discrete function. From simulation we can see that the RBF kernel based LS-SVM is more effective in nonlinear function estimation and can prevent the system from noise pollution, so it has high generalization ability.
17024398
Runtime parallel incremental scheduling of DAGs
A runtime parallel incremental DAG scheduling approach is described in this paper. A DAG is expanded incrementally, scheduled, and executed on a parallel machine. A DAG scheduling algorithm is parallelized to scale to large systems. In this approach, a large DAG can be executed without consuming large amount of memory space. Inaccurate estimation of task execution time and communication time can be tolerated. This runtime approach can also execute dynamic DAGs. Implementation of this parallel incremental system demonstrates the feasibility of this approach. Preliminary results show that it is superior to other approaches.
10931722
STAS: A Scalability Testing and Analysis System
Scalability is a crucial factor in performance evaluation and analysis of parallel and distributed systems. Much effort has been devoted to scalability research and several metrics are proposed. However, the lacking of an effective scalability analysis toolkit is still a major barrier for researchers to measure and analyze scalabilities. Isospeed scalability is a known metric and has been extended for general computing systems recently. This paper proposes an effective scalability testing and analysis system, called STAS, and presents its implementation with isospeed-e scalability metric. STAS provides the facility to conduct automated isospeed-e scalability measure and analysis. It reduces the burden for users to evaluate the performance of algorithms and systems. Experiments have been conducted to verify the design and implementation
21872537
A unified rational expansion method to construct a series of explicit exact solutions to nonlinear evolution equations
A unified basic frame of rational expansion methods is presented, which leads to closed-form solutions of nonlinear evolution equations (NLEEs). The new unified algorithms are given to find exact rational formal polynomial solutions of NLEEs in terms of Jacobi elliptic functions, solutions of the Riccati equation and solutions of the generalized Riccati equation. They can be implemented in symbolic computation system Maple. As applications of the methods, we choose some physical significance NLEEs to illustrate the methods. As a consequence, we not only can successfully obtain the solutions found by most existing Jacobi elliptic function methods and tanh methods, but also find other new and more general solutions at the same time.
14170978
Improving Data Access Performance with Server Push Architecture
Data prefetching, where data is fetched before CPU demands for it, has been considered as an effective solution to mask data access latency. However, the current client-initiated prefetching strategies do not work well for applications with complex, non-contiguous data access patterns. While technology advances continue to enlarge the gap between computing and data access performance, trading computing power for data access delay has become a natural choice. We propose a server-based data-push approach. In this server-push architecture, a dedicated server named data push server (DPS) initiates and proactively pushes data closer to the client in time. We present the DPS architecture and study the issues such as what data to fetch, when to fetch, how to push, and data access modeling.