Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 18 of 18 for “"big data processing"”.
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What about big data?
… BS final project will be analyzing the different big data processing approaches and techniques. In other words, we will focus on the Velocity concept, specifically in the different solutions based in batch processing techniques. The study will focus on the two major current proposed solutions: …
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Research on High-performance and Scalable Data Access in Parallel Big Data Computing
To facilitate big data processing, many dedicated data-intensive storage systems such as Google File System(GFS), Hadoop Distributed File System(HDFS) and Quantcast File System(QFS) have been developed. Currently, the Hadoop Distributed File System(HDFS) [20] is the state-of-art and most popular …
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I2MAPREDUCE: DATA MINING FOR BIG DATA
… Incremental MapReduce for Mining Evolving Big Data . i<sup>2</sup>MapReduce is used for incremental big data processing, which uses a fine-grained incremental engine, a general purpose iterative model that includes iteration algorithms such as PageRank, Fuzzy-C-Means(FCM), Generalized …
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A Distributed Approach to EpiFast using Apache Spark
… Spark-EpiFast based on the Apache Spark big data processing engine and Charm-EpiFast based on the Charm++ parallel programming framework. The study focuses on exploiting features of both systems that we believe could potentially benefit in terms of performance and scalability. We present …
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An Application-Attuned Framework for Optimizing HPC Storage Systems
… understand the behavior of complex phenomena. Big data driven scientific simulations are resource intensive and require both computing and I/O capabilities at scale. There is a crucial need for revisiting the HPC I/O subsystem to better optimize for and manage the increased pressure on the …
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Testing infrastructure and other considerations in a waferscale processor
… by emerging workloads, like machine learning, big data processing, and cloud computing, which are either inherently parallel workloads or easily parallelizable, processor core count continues to increase. Simply cramming more and more processor cores into an ever larger chip is not feasible …
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Irrigator Responses to Changes in Water Availability in Idaho's Snake River Plain
… due to climate change. Using remote sensing data, I examined irrigator responses to seasonal changes in water availability in Idaho's Snake River Plain over the past 33 years. Google Earth Engine's high performance cloud computing and big data processing capabilities were used to compare the …
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Design and development of a vulnerability detection framework using artificial intelligence for embedded systems
… the embedded OS layer, we introduced the EVDD dataset (Embedded Vulnerability Detection) to enhance Linux kernel vulnerability detection. Using big data processing, we construct a balanced dataset to improve machine learning models for intrusion detection and OS-level security analysis. Deep …
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Energy-efficient system design for mobile processing platforms
… such as high-performance multimedia, "big-data" processing and smart healthcare, in real-time on mobile platforms of the future. This thesis presents an energy-efficient system design approach with algorithm, architecture and circuit co-design for multiple application areas. A shared …
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Protection and efficient management of big health data in cloud environment
Healthcare data has become a great concern in the academic world and in industry. The deployment of electronic health records (EHRs) and healthcare-related services on cloud platforms will reduce the cost and complexity of handling and integrating medical records while improving efficiency and …
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Optimisation techniques for finding connected components in large graphs using GraphX
… has been well studied. It is an essential pre-processing step to many graph computations, and a fundamental task in graph analytics applications, such as social network analysis, web graph mining and image processing. Recently, it has been a major area of interest within the field of large …
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Design and Control of Versatile High-Speed and Large-Range Atomic Force Microscopes
… to images, to observe and compare experimental data with theoretical predictions, and verify models without speculating about intermediate dynamics. However, conventional AFMs have limited throughput that allow for static imaging only and require transparent working environments. The …
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Big data toward vehicle health monitoring system: an engine health perspective
… high volume, high velocity, and heterogeneous data streams, limiting real-time fault detection, predictive maintenance, and operational reliability. Addressing these limitations requires a cohesive, multi-layered framework that unifies scalable data management, real-time analytics, and …
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Advancing Internet Viewpoint Diversity: A Novel Algorithm and a Corpus Creation Tool
… documents. To achieve this, we first develop a big data processing architecture for creating indexed corpora from the Common Crawl web archives. The architecture is instantiated into an automated tool that generates an intelligible topical corpus through a series of steps involving processing, …
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Large Web Archive Collection Infrastructure and Services
… to standardize the preservation of web archive data. In addition to its preservation purpose, web archive data is also used as a source for research and for lost information recovery. However, the reuse of web archive data is inherently challenging because of the scale of data size and …
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Efficient Spatio-Temporal Network Analytics in Epidemiological Studies using Distributed Databases
… studies. The size of the spatio-temporal data has been increasing tremendously over the years, gradually evolving into Big Data. The processing in such domains are highly data and compute intensive. High performance computing resources resources are actively being used to handle such …
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Enabling virtualization technologies for enhanced cloud computing
… as well as large scale organizations. Data-center owners maintain clusters of thousands of machines and lease out resources like CPU, memory, network bandwidth, and storage to clients. For organizations, cloud computing provides the means to offload server infrastructure and obtain …
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A scalable analysis framework for large-scale RDF data
… of the Semantic Web, the availability of RDF datasets from multiple domains as Linked Data has taken the corpora of this web to a terabyte-scale, and challenges modern knowledge storage and discovery techniques. Research and engineering on RDF data management systems is a very active area with …