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The abundant aspects of big data and it's technology are increasing due to new methods of fetching data and diverse needs. Meteorological data is also the source of big data in terms of volume, variety, veracity and velocity, and it includes structured, unstructured and hybrid forms. This paper aims to apply Hadoop architecture and MapReduce algorithm into meteorological big data. It also describes...
Live Virtual Machine (VM) migration across data centers is an important support technology which will bring benefits to both cloud providers and users. At present, VM storage migration becomes the bottleneck of this technology as it explores only the static data feature of image files without much consideration on data semantics. In this paper, we propose a new space-efficient VM image structure–three-layer...
Understanding the hydrodynamic maneuvering capabilities of our Navy's submarines is a vital aspect of submarine design and in-service life. In the Hydrodynamics Testing Branch at the Naval Surface Warfare Center, Carderock Division (NSWCCD), autonomous underwater vehicles (AUVs) that are scale models of the Navy's submarines are developed to provide high fidelity data on maneuvering characteristics...
Nowadays, the current global socio-economic challenges offer new opportunities for engineering. Advances in electrical engineering have been central to human progress ever since the discovery of the electromagnetic field. In the last hundred and fifty years, electrical engineering has transformed the world we live in, contributing to a significantly longer life expectancy and has enhanced life quality...
Statistical anomaly detection is emerging as an important complement to signature-based methods for enterprise network defence. In this paper, we isolate a persistent structure in two different enterprise network data sources. This structure provides the basis of a regression-based anomaly detection method. The procedure is demonstrated on a large public domain data set.
The possibility for theft or misuse of legitimate user credentials is a potential cyber-security weakness in any enterprise computer network which is almost impossible to eradicate. However, by monitoring the network traffic patterns, it can be possible to detect misuse of credentials. This article presents an initial investigation into deconvolving the mixture behaviour of several individuals within...
A visibility-culling-based geometric rendering algorithm is proposed in this paper so as to visualize large-scale particle data efficiently. In the algorithm, the particles are culled based on their visibility at two granularities. All data patches beyond the OpenGL view frustum are firstly thrown away as a coarse culling. And then, the remaining particles will be judged their visibility based on...
The Internet of Things has created an influx of data-generating devices. Applications that use these devices require the generated data to be transmitted in a timely manner. In this paper, we consider a Pull model, where remote clients will send requests to retrieve the information generated by multiple sources from the same random process. We assume that the update processes and response times of...
In this paper, we present a hierarchical butterfly communication model, which is applied to an asynchronous distributed ADMM algorithm. The goal is to minimize the communication overhead of the distributed ADMM algorithm in the fully connected network. We give a theoretical analysis of the convergence of the algorithm with hierarchical butterfly communication model. Experiments show that hierarchical...
With the emergence of a variety of data cloud services, especially composite data cloud services, service trustworthiness problem is particularly prominent. Data cloud service credibility becomes focus of cloud service consumers. Data cloud service is essentially a Web service and its quality is associated with the Web service evolution process. In this paper, considering how provenance information,...
Analysts of different fields have shown a good interest in data mining. Data mining is the process of inferring useful patterns from the huge amount of data. Regarding data storage and management process, classical statistical models are however protective. Big data is a popular terminology which is intermittently discussed in the present day, used to describe the enormous quantity of data that may...
With the highly demanded requirements for manipulating large scientific datasets, scientists are in need of flexible cluster-level software to execute fast scientific data analysis. In this paper, we discuss whether the Apache Spark framework is suitable for scientific data management. We present our system SparkArray, which extends Spark with a multidimensional array data model and a set of common...
With the development of computer science and technology and the further progress of IC fabrication, GPU-accelerating computer systems are more and more widely used to provide higher performance on HPCs(High Performance Computers) and even regular desktop and laptop computers. Almost the same time, the Internet era and the rise of mobile Internet produced PBs of data. Bulk data are useless until carefully...
Regulating agencies mandate that model verification of power system components must be performed to make sure the system analysis software perform accurately. Such verification is necessary for series compensation devices used in transmission systems, since they deteriorate due to aging or prolonged subjection to stressed condition, leading to changes in compensation levels or voltage-current characteristic...
The deployment of technology across the globe towards efficient learning environments is growing rapidly. In the United Kingdom, for example, the government is investing 1.1 million pounds towards primary and secondary school early programming lessons; with similar investments happening in other countries. The ideology behind this push is to strengthen the link between the younger generation and the...
This paper proposes an approach using MapReduce-based Rocchio relevance feedback algorithm, which improved the traditional Rocchio algorithm in the MapReduce paradigm, to resolve the problem of massive information filtering. Traditional text classification algorithms have vital impact on information filtering.
Due to the huge increase in the size of the data it becomes troublesome to perform efficient analysis using the current traditional techniques. Big data put forward a lot of challenges due to its several characteristics like volume, velocity, variety, variability, value and complexity. Today there is not only a necessity for efficient data mining techniques to process large volume of data but in addition...
Intrusion detection and forensic analysis techniques depend upon monitors to collect information about possible attacks. Since monitoring can be expensive, however, monitors must be selectively deployed to maximize their overall utility. This paper introduces a methodology both to evaluate monitor deployments quantitatively in terms of security goals and to deploy monitors optimally based on cost...
The research progress of data acquisition technology and large data processing model has an important contribution to the development of urban traffic data. The control of urban transportation depends on the effective processing of real-time traffic observation data, which is usually the nature of data intensive. We study a large number of floating car data processing (FCD) traffic control in the...
In order to mine the abnormal learning behavior of learner in virtual learning community and carry on personalized supervision and guidance, behavior filtering model based on the factor analysis of the behavior is constructed to solve the problem of the relationship between behavior factors in the learning behavior vector space model. In view of the disadvantage of neglecting local abnormal points...
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