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Applications of deep neural networks to protein structure prediction
(University of Missouri--Columbia, 2018)
Protein secondary structure, backbone torsion angle and other secondary structure features can provide useful information for protein 3D structure prediction and protein functions. Deep learning offers a new opportunity ...
An algorithm for the automatic construction of Bayesian networks with limited domain knowledge, as applied to the prediction of economic and development indicators of 248 countries and world regions
(University of Missouri--Columbia, 2016)
Humans have a natural tendency to express knowledge in terms of generalities, instead of individually measurable variables. However, to make for computers to make sense of a domain, information must be expressed in terms ...
Template-based methods for protein model quality assessment
(University of Missouri--Columbia, 2016)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Protein structure prediction is an important open problem in the bioinformatics filed. One of the difficulties of solving this problem is to develop ...
Design and implementation of orthopedic trauma surgery rehabilitation and health monitoring system (OTSRS)
(University of Missouri--Columbia, 2016)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] A very common problem relating to rehabilitation of orthopedic trauma surgery is that patients do not have access, whether for financial reasons or ...
Wearable sensing analysis : identifying alcohol drinking from daily physiological data
(University of Missouri--Columbia, 2016)
In practical psychology research, questionnaires and interviews with examinees are commonly used. Besides, to study about certain human behaviors such as our subject -- alcohol drinking craving, it usually lasts for several ...
Activity identification from animal GPS tracks with spatial temporal clustering method DDB-SMoT
(University of Missouri--Columbia, 2016)
With various GPS devices or services growing rapidly, large amount of GPS track- ing data has been collected, both for human beings and wild animals. However, the raw GPS data cannot directly provide us with any valuable ...
Animal stay region detection and behavior analysis based on GPS trajectories
(University of Missouri--Columbia, 2016)
Nowadays, GPS technology is becoming an important tool in tracking and understanding wild animal behaviors. For example, Missouri Department of Conservation (MDC) has put GPS collars on more than 80 black bears and more ...
Empirical study of deep neural network architectures for protein secondary structure prediction
(University of Missouri--Columbia, 2017)
Protein secondary structure prediction is a sub-problem of protein structure prediction. Instead of fully recovering the whole three dimensional structure from amino acid sequence, protein secondary structure prediction ...
Physiological data analysis -- alcohol drinking prediction using statistical and deep learning methods
(University of Missouri--Columbia, 2017)
Alcohol craving can cause many problems for people's life. However, there are very few related works doing alcohol prediction based on physiological data, except some from our lab. The goal of this research is to predict ...
AMD, analysis of mood dysregulation : a machine learning approach
(University of Missouri--Columbia, 2016)
There is a popular saying, "Stress kills." This statement can be true with repeated exposures to psychological mood dysregulation, which can lead to or worsen stress related conditions such as heart disease and cancer. ...
Region based object detectors for recognizing birds in aerial images
(University of Missouri--Columbia, 2019)
This project explores different types of deep neural networks (DNNs) for recognizing birds in aerial images based on real data provided by the Missouri Department of Conservation. The pipeline to identify birds from an ...
Computational protein structure prediction using deep learning
(University of Missouri--Columbia, 2020)
Protein structure prediction is of great importance in bioinformatics and computational biology. Over the past 30 years, many machine learning methods have been developed for this problem in homology-based and ab-initio ...
Improving object recognition in aerial image and ambulatory assessment analysis by deep learning
(University of Missouri--Columbia, 2019)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] With the widespread usage of many different types of sensors in recent years, large amounts of diverse and complex sensor data have been generated and ...
Deep learning for small object detection in images
(University of Missouri--Columbia, 2020)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] With the rapid development of deep learning in computer vision, especially deep convolutional neural networks (CNNs), significant advances have been ...
An evolutionary method for training autoencoders for Deep Learning Networks
(University of Missouri--Columbia, 2014)
Introduced in 2006, Deep Learning has made large strides in both supervised an unsupervised learning. The abilities of Deep Learning have been shown to beat both generic and highly specialized classification and clustering ...
Active labeling in deep learning and its application to emotion prediction
(University of Missouri--Columbia, 2013)
Recent breakthroughs in deep learning have made possible the learning of deep layered hierarchical representations of sensory input. Stacked restricted Boltzmann machines (RBMs), also called deep belief networks (DBNs), ...
Application of deep learning networks to crime prediction
(University of Missouri--Columbia, 2013)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Crimes are a major public concern in cities. Every day, a tremendous amount of law enforcement and policemen have been assigned to patrol and protect ...
Acoustic feature-based sentiment analysis of call center data
(University of Missouri--Columbia, 2017)
With the advancement of machine learning methods, audio sentiment analysis has become an active research area in recent years. For example, business organizations are interested in persuasion tactics from vocal cues and ...
A deep learning method for protein model quality assessment
(University of Missouri--Columbia, 2014)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.]
Multi-dimensional scaling and MODELLER based evolutionary algorithms for protein model refinement
(University of Missouri--Columbia, 2013)
To computationally obtain an accurate prediction of the three-dimensional structure of a protein from its primary sequence is one of the most important problems in bioinformatics and has been actively researched for many ...