Dynamic characteristics of threshold value and extension field selections for vacuum-blowing cleaning system

To provide theoretical guidelines for threshold value selections on performance characteristics of extension field, the flow characteristic in the vacuum-blowing cleaning system was simulated using the average velocity and pressure of the front inlet surface, and the average velocity of the outlet surface, as indices to evaluate the effect of the extension field’s structural parameters. It is found that the extension field parameters have implications for the simulation calculation, and that each parameter has a corresponding threshold. If the structural parameter is greater than the corresponding threshold, the calculation result is not affected, and the threshold values are analyzed by using computational fluid dynamics (CFD). The dimensions of the front, back, left, and right extension fields are recommended as follows: lf=lb=ll=lr=210 mm and θf =θb =θl =θr =55 degree. The flow field distribution characteristic does not have a distinct difference with or without the extension field corner. The extension field with a corner can be used if high accuracy is required. However, to reduce the amount of grid computation and shorten the calculation time, the corner extension field model is not recommended. Finally, the simulation results are verified experimentally and can be used to improve the calculation accuracy and reduce the required computational resources.

Weak and strong error analysis of recursive quantization: a general approach with an application to jump diffusions

Observing that the recent developments of spatial discretization schemes based on recursive (product) quantization can be applied to a wide family of discrete time Markov chains, including all standard time discretization schemes of diffusion processes, we establish in this paper a generic strong error bound for such quantized schemes under a Lipschitz propagation assumption. We also establish a marginal weak error estimate that is entirely new to our best knowledge. As an illustration of their generality, we show how to recursively quantize the Euler scheme of a jump diffusion process, including details on the algorithmic aspects grid computation, transition weight computation, etc. Finally, we test the performances of the recursive quantization algorithm by pricing a European put option in a jump Merton model.

High Performance Fault Tolerant Resource Scheduling in Computational Grid Environment

Virtual resources team up to create a computational grid, which is used in computation-intensive problem solving. A majority of these problems require high performance resources to compute and generate results, making grid computation another type of high performance computing. The optimization in computational grids relates to resource utilization which in turn is achieved by the proper distribution of loads among participating resources. This research takes up an adaptive resource ranking approach, and improves the effectiveness of NDFS algorithm by scheduling jobs in those ranked resources, thereby increasing the number of job deadlines met and service quality agreements met. Moreover, resource failure is taken care of by introducing a partial backup approach. The benchmark codes of Fast Fourier Transform and Matrix Multiplication are executed in a real test bed of a computational grid, set up by Globus Toolkit 5.2 for the justification of propositions made in this article.

Autonomous Compliance Implementation in Grid Environment

Progress in IT and software technology has led to an explosive development in computer systems and apps that affect all elements of our lives. Computing devices are anticipated to be efficient and helpful when implemented first and are still helpful in changing conditions. Their design, their setup and leadership difficulties override current instruments and methodologies with increasing complexity of devices and apps. This makes the scheme unsafe and unmanageable. Thus the notion of autonomous computation is developed to create the devices self-manageable and safe. Autonomous computation provides a possible answer to these difficult issues in studies. Grid computation is the fundamental implementation region for autonomous computation. The IT inventions include both autonomic computation and cloud computation. Autonomic computation seeks to solve the rapid growth of complexities in the IT sector by endeavoring to share shared computer assets and information assets in the cloud computing sector. The fundamental objective is to achieve grid-related autonomous computation, such as autonomous job distribution and grid management and independent resource allotment

Analisis Kinerja Sistem Komputasi Grid Menggunakan Perangkat Lunak Globus Toolkit Dan MPICH-G2

The grid computation was developed by using fedora 14 operating system and globus toolkit software, NTP and certificate authority to built a grid system as well as MPICH-G2 as a reference to run parallel program. It was examined with matrix multiplication and was compared with single computation system based on processing time. This research employed 2 units of personal computer which earned a faster processing time than the single system, if only the program is divided into three process/jobs or more. If there was only 1 or 2 jobs, the process will not run faster than single computation. It can be concluded that the grid system will perform better if there are more nodes and core processor in each node and also balanced with the amount of the process/job.

Ontology-based workflow extraction from texts using word sense disambiguation

This paper introduces a method for automatic workflow extraction from texts using Process-Oriented Case-Based Reasoning (POCBR). While the current workflow management systems implement mostly different complicated graphical tasks based on advanced distributed solutions (e.g.cloud computing and grid computation), workflow knowledge acquisition from texts using case-based reasoning represents more expressive and semantic cases representations. We propose in this context, an ontology-based workflow extraction framework to acquire processual knowledge from texts. Our methodology extends classic NLP techniques to extract and disambiguate tasks in texts. Using a graph-based representation of workflows and a domain ontology, our extraction process uses a context-based approach to recognize workflow components : data and control flows. We applied our framework in a technical domain in bioinformatics : i.e. phylogenetic analyses. An evaluation based on workflow semantic similarities on a gold standard proves that our approach provides promising results in the process extraction domain. Both data and implementation of our framework are available in :http://labo.bioinfo.uqam.ca/tgrowler.