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 20 of 30 for “"Big Data Analysis"”.
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Cloud-based machine learning architecture for big data analysis
… machine-learning that leverages large amounts of data (big data) is increasingly important in many areas of business and research. To help cope with the demanding resources required by these applications, solutions including hardware platforms (e.g. graphics cards), more efficient algorithms (e.g. …
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MACHINE LEARNING ALGORITHM PERFORMANCE OPTIMIZATION: SOLVING ISSUES OF BIG DATA ANALYSIS
… space, generating machine learning models for big data is difficult. This research is introducing a novel approach to optimize the performance of learning algorithms with a particular focus on big data manipulation. To implement this method a machine learning platform using eighteen machine …
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A Workload-aware Resource Management and Scheduling System for Big Data Analysis
The big data era has driven the needs for data analysis in every aspect of our daily lives. With the rapid growth of data size and complexity of data analysis models, modern big data analytic applications face the challenge to provide timely results often with limited resources. Such demand drives …
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From genomes to metagenomes: Big data analysis of microbes related to public health
Bacterial infections represent a major public health concern mainly in young children in the developing world and in immunocompromised individuals. Despite recent developments in clinical microbiology, our understanding of the molecular and ecological mechanisms underlying the …
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Big data analysis interrogating raw material variability and the impact on process performance
… 89 % average accuracy on predictions for new data. In addition to the demonstrated predictive power, the models developed were highly interpretable and illustrated correlations with several material attributes. Henceforth, the framework developed is the starting point of a novel methodology …
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Content-aware compression for big textual data analysis
… value of this semi-structured and unstructured data has been widely acknowledged, with consequent scientific and commercial exploitation. The ever-increasing data production, however, pushes data analytic platforms to their limit. This thesis proposes techniques for more efficient textual big …
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Network-on-chip design for a chiplet-based waferscale processor
… large parallel tasks like machine learning and big data analysis, processors continue to increase in area and incorporate more computational cores. This growth requires innovation in manufacturing processes to build larger systems, and architectural changes to enable performance to scale …
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A Statistical Investigation of Stock Market Activity and Instances of Financial Crime
… crime in Illinois, Texas, and Utah through big data analysis techniques using data from the FBI’s Federal Bureau of Investigation’s National Incident-Based Reporting System (NIBRS) database. By analyzing the occurrences of financial crime by location, year, and type in relation to the S&P …
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Understanding Mobility in Sierra Leone During COVID-19 Using Call Detail Records
… resource for understanding mobility patterns in data-poor environments, while often applied towards transportation applications. This thesis seeks to use CDR to understand the impact of government policies during fast-moving public health threats. To test the usefulness of CDR data, we apply it …
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Using Big Data Analytics to Optimize Practical Large Databases
<p>Big data analytics is gaining popularity for enterprises in optimizing their business processes ranging from retailers, supply chains, to online shopping stores. Existing practical raw data are far from usable to achieve the goal. Therefore, a good data pre-processing approach is required and is …
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Machine learning and data analytics for multilayer data in policy planning
“Does bigger data lead to better decisions?” has been a frequent question for discussion among many decision makers—data scientists as well as organizational leaders and managers. Educational institutions, finance, and the retail industry have had big data for several decades that did not …
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Developing a predictive model for factors related to risk of aggression in psychiatric inpatients using physiological and clinical data
… during psychiatric stays, the study employs big data analysis on an actual clinical data set extracted from patients’ medical records to develop a predictive model for clinical aggression risk factors. Retrospective analysis covers variables such as heart rate, blood pressure, age, incidents, …
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SensAnalysis: A Big Data Platform for Vibration-Sensor Data Analysis
… as external activities. The recorded vibration data can be used to develop real-time applications for monitoring the health of the building or detecting human activity in the building. However, the lack of infrastructure to handle the massive scale of the data, and the steep learning curve of …
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Multi-omics approaches for diagnosis, prognosis and response to treatment of colorectal cancer.
… stratification is required. The advent of Big Data analysis in medical research has revolutionized the traditional hypothesis-driven approach. Big Data analysis provides an invaluable opportunity to improve individual and public health. In fact, the availability of large databases to …
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Socialinių medijų panaudojimo iššūkiai ir galimybės verslo analitikoje /
… work is to analyze the potential of social media data analytics in various business sectors based on theoretical aspects of social media data analysis, the application of technologies, and the practice of different industries, and to create recommendations on how companies can effectively use …
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Towards an automated system for evaluation of visualizations
… field focuses on the visualization of abstract data, and with the growing interest in big data analysis, the need for analyzing complex datasets is nowadays highly relevant. With the growing amount and diversity of these datasets new and exciting ways to visualize them are being developed. …
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Domain Adaptation with a Classifier Trained by Robust Pseudo-Labels
… are achieved by assuming the source and target data are collected from the same probability distribution. However, this assumption is usually too strict to be satisfied in many real-world applications, such as big data analysis, natural language processing, and computer vision classification …
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Facilitating High Performance Code Parallelization
… source APIs on the other hand, the amount of data that can be processed is as well vastly increasing. In addition, the world of computing has recently been witnessing a growing shift towards massively parallel distributed systems due to the increasing importance of transforming data into …
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Applications of Data Science and Artificial Intelligence to Decision Making in Healthcare and Finance
… program that allows us to fill in missing data and infer phase transitions from clinical trial metadata. We investigate the PoSs across various therapeutic areas, and then conduct further analysis for areas that are of public interest (e.g., oncology, vaccine, and anti-infective …
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Location and Data Privacy Preservation in Intelligent Systems
… a significant contribution to the volume of data collected, which brings us to the big data era. Intelligent system (IS) becomes an emerging paradigm for integrating big data, analytics, privacy, and artificial intelligence. The IS is any formal or informal system to manage data gathering, to …
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