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 12 of 12 for “"Machine-Learning Process"”.
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Exploration of the Application of Machine Learning to the Improvement of Interatomic Potentials
… In this thesis, the application of a specific machine learning process, artificial neural networks (ANNs), to the improvement of IPs and MD simulation is discussed.
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Visual Analytics and Interactive Machine Learning for Human Brain Data
… multi-modal data visualization and interactive machine learning. For multi-modal data visualization, a major challenge is how to integrate structural, functional and connectivity data to form a comprehensive visual context. We develop a new integrated visualization solution for brain imaging …
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Automatic Scheduling of Compute Kernels Across Heterogeneous Architectures
… from heterogeneous multi- and many-core processors due to the power, memory and instruction-level parallelism walls. All trends point towards increased processor heterogeneity as a means for increasing application performance, from smartphones to servers. These various architectures are …
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Enhancement of network security by use machine learning
… simulation on enhancement network security using machine learning. The design use MATLAB coding to show the simulation. The coding is designed in a way that there is an attack of malicious to destroy the data. Because there is a machine-learning scheme in the security, the system have done …
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Small-scale distributed machine learning in R
Machine learning is increasing in popularity, both in applied and theoretical statistical fields. Machine learning models generally require large amounts of data to train and thus are computationally expensive, both in the absolute sense of actual compute time, and in the relative sense of the …
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Three Essays on the Evolution of the Determinants of Educational Attainment and its Consequences
… evolved over the years. The chapter utilizes the machine-learning process and logistic regression model to identify inequality of opportunity. The second chapter examines the age demographic distribution of graduates across cohorts from 1940 until 1990. Using the PSID data, the paper explored the …
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VastMM-Tag: Semantic Indexing and Browsing of Videos for E-Learning
… the domain of lecture videos though the use of machine learning, to gather semantic information about the videos; and through user interface design, to enable users to fully utilize this new information. First, we use machine learning techniques to gather the semantic information. We develop a …
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Beyond Privacy Concerns: Examining Individual Interest in Privacy in the Machine Learning Era
The deployment of human-augmented machine learning (ML) systems has become a recommended organizational best practice. ML systems use algorithms that rely on training data labeled by human annotators. However, human involvement in reviewing and labeling consumers' voice data to train speech …
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Computational and Machine Learning-Reinforced Modeling and Design of Materials under Uncertainty
… inherent material uncertainty by incorporating machine learning techniques. To achieve this objective, the study addresses gradient-based and machine learning-driven design optimization methods to enhance homogenized linear and non-linear properties of polycrystalline microstructures. However, …
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Process modeling and optimization using industrial semiconductor fabrication data
… these differences are device yield, breadth of processing conditions, throughput, number of reaction chambers operating in parallel, metrology, and data collection. These differences are reflected in the data available in the fab databases. This research explores the use of a neural network …
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Machine-assisted synthesis and development in pharmaceutical industry
Machine-assisted synthesis and development in pharmaceutical industry Perman Jorayev Process development of novel chemical transformations is often a laborious and complex task. This is mostly due to the difficulties in identifying the underlying reaction mechanism(s), selection of chemical …
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Accelerating process development of complex chemical reactions
Process development of new complex reactions in the pharmaceutical and fine chemicals industries is challenging, and expensive. The field is beginning to see a bridging between fundamental first-principles investigations, and utilisation of data-driven statistical methods, such as machine learning. …