Physical Sciences and Mathematics Commons^™

The Structural Information Filtered Features Potential For Machine Learning Calculations Of Energies And Forces Of Atomic Systems., Jorge Arturo Hernandez Zeledon

Graduate Theses, Dissertations, and Problem Reports

In the last ten years, machine learning potentials have been successfully applied to the study of crystals, and molecules. However, more complex materials like clusters, macro-molecules, and glasses are out reach of current methods. The input of any machine learning system is a tensor of features (the most universal type are rank 1 tensors or vectors of features), the quality of any machine learning system is directly related to how well the feature space describes the original physical system. So far, the feature engineering process for machine learning potentials can not describe complex material. The current methods are highly inefficient …

Intelligent Malware Detection Using File-To-File Relations And Enhancing Its Security Against Adversarial Attacks, Lingwei Chen

Graduate Theses, Dissertations, and Problem Reports

With computing devices and the Internet being indispensable in people's everyday life, malware has posed serious threats to their security, making its detection of utmost concern. To protect legitimate users from the evolving malware attacks, machine learning-based systems have been successfully deployed and offer unparalleled flexibility in automatic malware detection. In most of these systems, resting on the analysis of different content-based features either statically or dynamically extracted from the file samples, various kinds of classifiers are constructed to detect malware. However, besides content-based features, file-to-file relations, such as file co-existence, can provide valuable information in malware detection and make …

Pharmaceutical Scheduling Using Simulated Annealing And Steepest Descent Method, Bryant Jamison Spencer

Graduate Theses, Dissertations, and Problem Reports

In the pharmaceutical manufacturing world, a deadline could be the difference between losing a multimillion-dollar contract or extending it. This, among many other reasons, is why good scheduling methods are vital. This problem report addresses Flexible Flowshop (FF) scheduling using Simulated Annealing (SA) in conjunction with the Steepest Descent heuristic (SD).

FF is a generalized version of the flowshop problem, where each product goes through S number of stages, where each stage has M number of machines. As opposed to a normal flowshop problem, all ‘jobs’ do not have to flow in the same sequence from stage to stage. The …

Evaluation And Understandability Of Face Image Quality Assessment, Mohammad I. Nouyed

Graduate Theses, Dissertations, and Problem Reports

Face image quality assessment (FIQA) has been an area of interest to researchers as a way to improve the face recognition accuracy. By filtering out the low quality images we can reduce various difficulties faced in unconstrained face recognition, such as, failure in face or facial landmark detection or low presence of useful facial information. In last decade or so, researchers have proposed different methods to assess the face image quality, spanning from fusion of quality measures to using learning based methods. Different approaches have their own strength and weaknesses. But, it is hard to perform a comparative assessment of …

Using Social Media To Combat Opioid Epidemic, Yiming Zhang

Graduate Theses, Dissertations, and Problem Reports

Opioid addiction has become one of the largest and deadliest epidemics in the United States. To combat such deadly epidemic, there is an urgent need for novel tools and methodologies to gain new insights into the behavioral processes of opioid abuse and addiction. The role of social media in biomedical knowledge mining has turned into increasingly significant in recent years. The data from social media may contribute information beyond the knowledge of domain professionals (e.g., psychiatrists and epidemics researchers) and could potentially assist in sharpening our understanding toward the behavioral process of opioid addiction and treatment.

In this thesis, we …

Description Of Motor Control Using Inverse Models, Anton Sobinov

Graduate Theses, Dissertations, and Problem Reports

Humans can perform complicated movements like writing or running without giving them much thought. The scientific understanding of principles guiding the generation of these movements is incomplete. How the nervous system ensures stability or compensates for injury and constraints – are among the unanswered questions today. Furthermore, only through movement can a human impose their will and interact with the world around them. Damage to a part of the motor control system can lower a person’s quality of life. Understanding how the central nervous system (CNS) forms control signals and executes them helps with the construction of devices and rehabilitation …

Quantifying Human Biological Age: A Machine Learning Approach, Syed Ashiqur Rahman

Graduate Theses, Dissertations, and Problem Reports

Quantifying human biological age is an important and difficult challenge. Different biomarkers and numerous approaches have been studied for biological age prediction, each with its advantages and limitations. In this work, we first introduce a new anthropometric measure (called Surface-based Body Shape Index, SBSI) that accounts for both body shape and body size, and evaluate its performance as a predictor of all-cause mortality. We analyzed data from the National Health and Human Nutrition Examination Survey (NHANES). Based on the analysis, we introduce a new body shape index constructed from four important anthropometric determinants of body shape and body size: body …

Automatic Detection Of Insecure Codes In Stack Overflow, Shifu Hou

Graduate Theses, Dissertations, and Problem Reports

As the popularity of modern social coding paradigm such as Stack Overflow grows, its potential security risks increase as well (e.g., insecure codes could be easily embedded and distributed). To address this largely overlooked issue, we bring a new insight to exploit social coding properties in addition to code content for automatic detection of insecure code snippets in Stack Overflow. To determine if the given code snippets are insecure, we not only analyze the code content, but also utilize various kinds of relations among users, badges, questions, answers, code snippets and keywords in Stack Overflow. To model the rich semantic …

Browsing Via Sonification, Taylor C. Cutlip

Graduate Theses, Dissertations, and Problem Reports

Based on unexpected results in her previous research, Dr. Frances Van Scoy became inspired to develop a tool that allows the user to navigate spaces using auditory instead of visual cues to detect objects or anomalies in a given space in an effort to overcome the encountered obstacles. This problem report details the work of one of her grad students in exploring different open source software for developing the tool as well as research into gestures and other considerations when furthering this research into the third dimension at a future date.

Autonomous Systems With Reuse: A Survey On The State-Of-The-Practice, Denny Laverne Hood Iii

Graduate Theses, Dissertations, and Problem Reports

This problem report presents the results of an anonymous online survey that was used to collect information about software systems that use model-based software engineering, contain autonomy and where software reuse plays an important role. Recent advancements in computation ability and the emergence of decision-making algorithms have increased interest in and use of autonomy in applications areas such as aeronautics, automotive, military, and space industries. In these application domains, autonomy is used to reduce costs, reduce reaction times, and improve performance. Due to the emerging nature of autonomy, very little research has been done regarding the level of autonomy of …

Deep Learning For Image Restoration And Robotic Vision, Yixin Du

Graduate Theses, Dissertations, and Problem Reports

Traditional model-based approach requires the formulation of mathematical model, and the model often has limited performance. The quality of an image may degrade due to a variety of reasons: It could be the context of scene is affected by weather conditions such as haze, rain, and snow; It's also possible that there is some noise generated during image processing/transmission (e.g., artifacts generated during compression.). The goal of image restoration is to restore the image back to desirable quality both subjectively and objectively. Agricultural robotics is gaining interest these days since most agricultural works are lengthy and repetitive. Computer vision is …

Multimodal Approach For Malware Detection, Jarilyn M. Hernandez Jimenez

Graduate Theses, Dissertations, and Problem Reports

Although malware detection is a very active area of research, few works were focused on using physical properties (e.g., power consumption) and multimodal features for malware detection. We designed an experimental testbed that allowed us to run samples of malware and non-malicious software applications and to collect power consumption, network traffic, and system logs data, and subsequently to extract dynamic behavioral-based features. We also extracted code-based static features of both malware and non-malicious software applications. These features were used for malware detection based on: feature level fusion using power consumption and network traffic data, feature level fusion using network traffic …

Analyzing Satisfiability And Refutability In Selected Constraint Systems, Piotr Jerzy Wojciechowski

Graduate Theses, Dissertations, and Problem Reports

This dissertation is concerned with the satisfiability and refutability problems for several constraint systems. We examine both Boolean constraint systems, in which each variable is limited to the values true and false, and polyhedral constraint systems, in which each variable is limited to the set of real numbers R in the case of linear polyhedral systems or the set of integers Z in the case of integer polyhedral systems. An important aspect of our research is that we focus on providing certificates. That is, we provide satisfying assignments or easily checkable proofs of infeasibility depending on whether the instance …

Object-Based Supervised Machine Learning Regional-Scale Land-Cover Classification Using High Resolution Remotely Sensed Data, Christopher A. Ramezan

Graduate Theses, Dissertations, and Problem Reports

High spatial resolution (HR) (1m – 5m) remotely sensed data in conjunction with supervised machine learning classification are commonly used to construct land-cover classifications. Despite the increasing availability of HR data, most studies investigating HR remotely sensed data and associated classification methods employ relatively small study areas. This work therefore drew on a 2,609 km2, regional-scale study in northeastern West Virginia, USA, to investigates a number of core aspects of HR land-cover supervised classification using machine learning. Issues explored include training sample selection, cross-validation parameter tuning, the choice of machine learning algorithm, training sample set size, and feature selection. A …

Security Bug Report Classification Using Feature Selection, Clustering, And Deep Learning, Tanner D. Gantzer

Graduate Theses, Dissertations, and Problem Reports

As the numbers of software vulnerabilities and cybersecurity threats increase, it is becoming more difficult and time consuming to classify bug reports manually. This thesis is focused on exploring techniques that have potential to improve the performance of automated classification of software bug reports as security or non-security related. Using supervised learning, feature selection was used to engineer new feature vectors to be used in machine learning. Feature selection changes the vocabulary used by selecting words with the greatest impact on classification. Feature selection was able to increase the F-Score across the datasets by increasing the precision. We also explored …

Reconciling The Dissonance Between Historic Preservation And Virtual Reality Through A Place-Based Virtual Heritage System., Danny J. Bonenberger

Graduate Theses, Dissertations, and Problem Reports

This study explores a problematic disconnect associated with virtual heritage and the immersive 3D computer modeling of cultural heritage. The products of virtual heritage often fail to adhere to long-standing principles and recent international conventions associated with historic preservation, heritage recording, designation, and interpretation. By drawing upon the geographic concepts of space, landscape, and place, along with advances in Geographic Information Systems, first-person serious games, and head-mounted Virtual Reality platforms this study envisions, designs, implements, and evaluates a virtual heritage system that seeks to reconcile the dissonance between Virtual Reality and historic preservation. Finally, the dissertation examines the contributions and …