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 “"Robust Prediction"”.
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Robust Prediction of Large Spatio-Temporal Datasets
This thesis describes a robust and efficient design of Student-t based Robust Spatio-Temporal Prediction, namely, St-RSTP, to provide estimation based on observations over spatio-temporal neighbors. It is crucial to many applications in geographical information systems, medical imaging, urban …
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DWCox: A density-weighted Cox model for outlier-robust prediction of prostate cancer survival
Reliable predictions on the risk and survival time of prostate cancer patients based on their clinical records can help guide their treatment and provide hints about the disease mechanism. The Cox regression is currently a commonly accepted approach for such tasks in clinical applications. More …
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Computational Algorithms for Predicting Membrane Protein Assembly From Angstrom to Micron Scale
… architecture of tight junctions, forming a robust prediction with molecular details packed for up to four orders of magnitude in length scale. This work is intended to bridge the gap between the computational nano-scale studies and the experimental micron-scale observations and provide a …
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Computational Algorithms For Predicting Membrane Protein Assembly From Angstrom To Micron Scale
… architecture of tight junctions, forming a robust prediction with molecular details packed for up to four orders of magnitude in length scale. This work is intended to bridge the gap between the computational nano-scale studies and the experimental micron-scale observations and provide a …
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Probabilistic methods for drug discovery
… of local experts algorithm which provides robust prediction and a model to estimate feature saliency simultaneously with the training of a projection algorithm.Local models are useful since a single global model cannot capture the full variability of a heterogeneous data space such as the …
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AN EXPLORATORY STUDY ON SOCIAL LEARNING THEORY, SOCIAL BOND THEORY, EXPERIENCES WITH POLICE AND DEMOGRAPHIC EFFECTS ON COLLEGE STUDENT ATTITUDES TOWARD POLICE
… incorporates all the variables provides the most robust prediction for the variation in attitudes toward police. A discussion of the limitations of the current study and recommendations for future research is also provided.
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AN EXPLORATORY STUDY ON SOCIAL LEARNING THEORY, SOCIAL BOND THEORY, EXPERIENCES WITH POLICE AND DEMOGRAPHIC EFFECTS ON COLLEGE STUDENT ATTITUDES TOWARD POLICE
… incorporates all the variables provides the most robust prediction for the variation in attitudes toward police. A discussion of the limitations of the current study and recommendations for future research is also provided.
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Exploring applications of big data analytics in supply chain management
… to develop a comprehensible, data-driven demand prediction of remanufactured products. Validated with a real-world Amazon dataset, the result shows that the proposed approach can produce a highly accurate and robust prediction of product demand, as well as providing insights into the non-linear …
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Developing near- and mid-infrared spectroscopy analysis methods for rapid assessment of soil quality in Illinois
… quality assessment has grown rapidly. Ideally robust calibration of models can be developed to rapidly and affordably predict soil quality (SQ) indicators that are more costly to measure. Refinement of data libraries and standardization of data processing steps are needed to improve prospects …
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Skyrmions -- beyond rigid body quantisation
… ground state spin. Further, the model leads to a robust prediction that the ground state of the nucleus has a larger root mean square matter radius than the second quantum state, in contrast with standard nuclear models. We consider the vibrational modes of the tetrahedral $B=16$ Skyrmion, to …
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Extending the System Dynamics Toolbox to Address Policy Problems in Transportation and Health
… these models there is a need to define a single robust prediction equation for Basal Metabolic Rate (BMR), which is an element of the energy expenditure of the body. In our approach, we perform an extensive literature review to explore the relationship between BMR and different factors including …
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Efficient Algorithms for Mining Large Spatio-Temporal Data
… tasks, including spatial outlier detection, robust<br />spatio-temporal prediction, and novel applications to real world<br />problems.<br /><br />Spatial novelty patterns, or spatial outliers, are those data points<br />whose characteristics are markedly different from their spatial<br …
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ALGORITHMIC SOLUTIONS TO COMBAT ONLINE FAKE NEWS
… algorithms for accurate, explainable, early, and robust prediction of fake news. It first introduces social theories and empirical patterns of fake news into feature extraction. It designs the neural networks that explicitly and adaptively capture the linguistic style of various news articles …
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Potential implications of climate change for Rooibos (A. linearis) production and distribution in the greater Cederberg region, South Africa
… initially indicated. This study provides a more robust prediction of rooibos plant responses to climate change factors to enable more effective adaptive planning and conservation management in a changing climate.
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Predicting progressions and clinical subtypes of Alzheimer’s disease using machine learning
… care, with individualized risk, progression and prediction related patient advice in AD is narrow. This facilitates the yet unfulfilled need for an early prediction of the disease course to assist its treatment and tailor therapy options to the progression rate. Additionally, there are …
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Large-scale Optimization for Robust Multi-Class Prediction and Resource Allocation
… arising from data, first in the context of robust multi-class prediction and second for prescriptive analytics for medical resource allocation. In the first part, we make progress on training robust multi-class classifiers using error-correcting output codes (ECOC). We propose linear and …
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Prediction and Anomaly Detection Techniques for Spatial Data
… tasks, including spatial outlier detection, robust inference for spatial dataset, and spatial prediction for large multivariate non-Gaussian data. spatial outlier analysis, which aims at detecting abnormal objects in spatial contexts, can help extract important knowledge in many applications. …