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 17 of 17 for “"activity prediction"”.
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Implementation of Multiple-Instance Learning in Drug Activity Prediction
… are responsible for the observed biological activity. In this work we aimed to predict bioactive conformers using a variant of supervised learning, named multiple-instance learning. A single molecule, treated as a bag of conformers, is biologically active if and only if at least one of its …
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Development of Machine Learning Models for Generation and Activity Prediction of the Protein Tyrosine Kinase Inhibitors
<p>The field of computational drug discovery and development continues to grow at a rapid pace, using generative machine learning approaches to present us with solutions to high dimensional and complex problems in drug discovery and design. In this work, we present a platform of Machine Learning …
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Transit Demand Estimation And Crowding Prediction Based On Real-Time Transit Data
… a proactive Transit Demand Estimation and Prediction System (TraDEPS) – an approach that has the potential to prevent crowding and improve transit service, by measuring the transit activity (the number of passengers on the individual modes of public transportation and the demand on a …
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Random Forests Based Rule Learning And Feature Elimination
… for good interpretation while preserving the prediction performance. We propose an efficient approach, combining rule extraction and feature elimination, based on 1-norm regularized random forests. This approach simultaneously extracts a small number of rules generated by random forests and …
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Computational and Data-Driven Design of Perturbed Metal Sites for Catalytic Transformations
… and attribution analysis enables accurate prediction equipped with mechanistic insights. In addition, novel physics effect controlling surface reactivity beyond conventional understanding is uncovered. Secondly, we develop a computational and data-driven framework to model high entropy …
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Discovery of Novel Glycogen Synthase Kinase-3beta Inhibitors: Molecular Modeling, Virtual Screening, and Biological Evaluation
… compound exhibiting sub-micromolar inhibitory activity is a reasonable starting point for further optimization. To further identify structurally novel GSK-3â inhibitors, we performed virtual screening by implementing another mixed ligand-based/structure-based approach, which included …
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A monitoring framework for side-channel information leaks
… intrusion detection systems which monitor system activity for suspicious patterns are also available and are commonly deployed in production environments. What is missing, however, is the consideration of implicit information flows, or side-channels. One significant factor which has been holding …
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Human activity recognition and gymnastics analysis through depth imagery
… as object recognition, human detection, human activity recognition, and sports analysis. The goal of my work is twofold: (1) use depth imagery to effectively analyze the pommel horse event in men’s gymnastics, and (2) explore and build upon the use of depth imagery to recognize human activities …
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Enhanced flare prediction by advanced feature extraction from solar images : developing automated imaging and machine learning techniques for processing solar images and extracting features from active regions to enable the efficient prediction of solar flares.
… and enable the development of an accurate flare prediction system, which can warn industries most at risk to take preventative measures to mitigate or avoid the effects of space weather. This thesis introduces novel technologies developed by combining advances in statistical physics, image …
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Enhanced flare prediction by advanced feature extraction from solar images : developing automated imaging and machine learning techniques for processing solar images and extracting features from active regions to enable the efficient prediction of solar flares
… and enable the development of an accurate flare prediction system, which can warn industries most at risk to take preventative measures to mitigate or avoid the effects of space weather. This thesis introduces novel technologies developed by combining advances in statistical physics, image …
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Flavonoids and Related Compounds as Nucleoside Transporter Inhibitors
… utilized to perform quantitative structure–activity relationship studies which indeed helped to understand the effects of different functionalities in the inhibition of nucleoside transporters. The validated 3D-QSAR models were used for design and activity prediction of new compounds. …
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Adversarial Activity Detection and Prediction Using Behavioral Biometrics
… and propose novel methods for near-future activity prediction.</p><p>First, we study gait signals captured using smartphone accelerometer sensor and build a model to predict a future gait signal. Activity recognition using body movements captured from mobile phone sensors has been a major …
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Automated Prediction of Solar Flares Using SDO Data. The Development of An Automated Computer System for Predicting Solar Flares Based on SDO Satellite Data Using HMI Images Analysis, Visualisation, and Deep Learning Technologies
… to achieve the following: 1) We developed a new prediction algorithm based on the Automated Solar Activity Prediction system (ASAP) system. The proposed algorithm updates the ASAP system by extending the training process and optimizing the learning rules to the optimize performance better. Two …
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Automated Prediction of Solar Flares Using SDO Data. The Development of An Automated Computer System for Predicting Solar Flares Based on SDO Satellite Data Using HMI Images Analysis, Visualisation, and Deep Learning Technologies
… to achieve the following: 1) We developed a new prediction algorithm based on the Automated Solar Activity Prediction system (ASAP) system. The proposed algorithm updates the ASAP system by extending the training process and optimizing the learning rules to the optimize performance better. Two …
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A density functional theory study on the rational design of heterogeneous catalysis
… energies around the theoretical highest activity point. Ten high-activity alloys were successfully designed, which can even reach the theoretically predicted highest activity in the volcano surface. <br/><br/>Due to several species co-adsorbing on the surface in the real environment, we …
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Neural recommender models for sparse and skewed behavioral data
… are a fundamental characteristic of human activity, owing to the bursty nature of human attention. As a result, we often observe skew in data facets that involve human interaction. While there are superficial similarities to Zipf's law in textual data and other domains, the challenges with …