This document presents the transportation research on the information systems, the geographic information systems, and the advanced computing.

关键词：电子信息；地理；信息系统

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Presentation about NASA's first Cloud Computing environment.

关键词：电子信息；云计算；云创新；宇航局

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This document presents a summary of cyber security challenges associated with utilization of cloud computing in the electric utility industry.

关键词：电子信息；云计算；电力工业；网络安全

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Given today’s technological advances in Cloud computing and data consolidation, DoD has the opportunity for significant positive impact on its core mission through IT modernization. This modernization should not be viewed as an end in itself, but as a means to a greater end of enhanced combat capability. Selected findings are listed below, with the complete findings listed in the accompanying presentation.

关键词：电子信息；云计算；数据整合；信息技术

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How should the Department of Defense (DoD) apply best business practices to Information Technology (IT) modernization, Data Center Consolidation (DCC), and the efficient, effective, and secure implementation of Cloud computing to support DoD business approaches and its warfighting mission.

关键词：电子信息；云计算；信息技术；整合

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Mobile cloud computing is growing rapidly because its device (i.e., smart phone) is becoming one of the main processing devices for users nowadays. Due to the limitation of resources such as battery life time, CPU and memory capacity, etc., a mobile device cannot satisfy some applications which usually demand more resources than it can afford. To alleviate this, the mobile device should collaborate with external resources to increase its capacity. In order to address these problems, we introduce a collaboration of thin-thick clients which enhances thin client capacities. We further propose a strategy to optimize the data distribution, especially big data in cloud computing. Moreover, we present an algorithm to allocate resources to meet service level agreement (SLA) and conduct simulations to evaluate our approach. Our results evaluation shows that our approach can improve resource allocation efficiency and has better performance than existing approaches.

关键词：电子信息；云计算；数据分布；资源分配

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Computational methods have evolved over the years giving developers and researchers more sophisticated and faster ways to solve hard data processing tasks. However, with new data collecting and storage technologies, the amount of gathered data increases everyday making the analysis of it a more and more complex task. One of the main forms of storing data is plain unstructured text and one of the most common ways of analyzing this kind of data is through Text Mining. Text Mining is similar to other types of data mining but the problem is that differently from other forms of data that are properly structured (such as XML) in text mining data in the best case scenario is semi-structured. In order for them to derive valuable information, text mining systems have to execute a lot of complex natural language processing algorithms. In this chapter we focus on text processing tools dealing with stemming algorithms. Stemming is the step that deals with finding the stem (or root) of the word which is essential in every text processing procedure. Stemming algorithms are complex and require high computational effort. In this chapter we present an Apache Mahout plugin for a stemming algorithm making possible to execute the algorithm in a cloud computing environment. We investigate the performance of the algorithm in the cloud and show that the new approach significantly reduces the execution time of the original algorithm over a large dataset of text documents.

关键词：电子信息；云计算；堵文本；文本挖掘；数据收集；数据存储

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Cloud computing is an emerging technology that can help organizations become more efficient and agile, and respond more quickly and reliably to their customers’ needs. Many government and private sector organizations are currently using or considering the use of cloud computing to increase the performance and efficiency of their information system operations, and to improve the delivery of services.

关键词：电子信息；云计算；信息系统；安全；隐私

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This chapter focuses on how to monitor marine spills using powerful tools such as remote sensing and Geographic Information Systems (GIS). On the one hand, remote sensing has been widely used as one of the main ways to periodically monitor large areas, as it allows to obtain data under poor weather conditions and in spite of darkness. We particularly center upon a. sensor called "Advanced Synthetic Aperture Radar" (ASAR), which is part of the Envisat payload. On the other hand, GIS have emerged in recent years as a set of standards for data organization and representation that allow the management of geographic data. We provide a detailed description of the design and implementation of a tool that provides an integrated framework for the detection and localization of marine spills using remote sensing, GIS, and cloud computing. Cloud computing is used because of the enormous amount of data to be processed and the need of communication between users.

关键词：电子信息；云计算；GIS；海洋检测

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Rapid computer usage growth and Internet expansion along with growth in big data and analytics Desire for computing application solution that is: Cost-effective Able to meet consumer needs, especially adaptability and availability Reliable Secure.

关键词：电子信息；云计算；大数据；国防部

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