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 11 of 11 for “"analytical tasks"”.
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The Effects of Anticipated Feedback Proximity on Performance: Exploring the Moderating Role of Self-Efficacy and Task Type
… moderating role of self-efficacy and task types (analytical or creative). I hypothesized that expecting rapid feedback should yield better performance than expecting delayed feedback, for people with high self-efficacy or those who receive analytical tasks. For those who receive creative tasks or …
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Development of a computer-understandable representation of design rationale to support value engineering
… also allows a computer system to perform analytical tasks on the design rationale data. Examples of analytical tasks a computer system can perform on design rationale data include: generating a parameter dependency network and resolving data conflicts. This dissertation defines this data …
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Natural Language Interfaces for Data Analytics
… users to be 30% more productive when solving analytical tasks, which further highlights the important improvements in usability language-based interfaces can provide.
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Toward AI-augmented data analysis: challenges and opportunities
… these systems remain limited to simple analytical tasks over standard data modalities. This thesis systematically investigates the limitations of AI-assisted data analysis along two critical dimensions: (1) data complexity and (2) analytic complexity. Specifically, it evaluates how well …
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Beyond Measures of Speed & Accuracy: Evaluating Visualization Perception, Reasoning & Decision-Making
… speed and accuracy across comprehension and analytical tasks, there lacks research on how they can benefit decision-making. Decision-making is a complex task which involves risk comprehension and rational thinking but also various heuristics and external factors. While research has shown that …
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Visual encoding quality and scalability in information visualization
… Scalable encodings offer good support for basic analytical tasks at scale by carrying design decisions that consider the limits of human perception and cognition. In this thesis, I present three case studies that explore different aspects of visual encoding quality and scalability: information …
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Feature extraction and data reduction for hyperspectral remote sensing Earth observation
… large data sets, with high potential in analytical tasks but at the cost of advanced signal processing. In this thesis, effective/efficient feature extraction methods are proposed. Initially, contributions are introduced for efficient computation of the covariance matrix widely used in …
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Computer-aided categorisation and quantification of connectives in English and Arabic (based on newspaper text corpora).
… written in SPITBOL to accomplish a variety of analytical tasks, and in particular to perform a battery of measurements intended to quantify the textual functioning of connectives in each corpus. Concordances and some word lists are produced by using OCP. Results of these researches confirm the …
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Learning representations for information mining from text corpora with applications to cyber threat intelligence
… this goal, a series of machine learning tasks are defined, and learning representations are developed to detect crucial information in these documents: cyber threat entities, types, and events. Using hybrid transformer-based implementations of these learning models, CTI-relevant key …
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The application of computational modeling to data visualization
… and optimizing data visualizations for an analytical task using a computational model of human vision. The method relies on a neural network simulation of early perceptual processing in the retina and visual cortex. The neural activity resulting from viewing an information visualization is …
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BUILDING EFFICIENT AND COST-EFFECTIVE CLOUD-BASED BIG DATA MANAGEMENT SYSTEMS
… scientists to get progressive answers to complex analytical tasks over large volumes of data. Typically, this involves manually extracting samples of increasing data size (progressive samples) for exploratory querying. This provides the data scientists with user control, repeatable semantics, and …