Browsing ETDs: Virginia Tech Electronic Theses and Dissertations by Title
Now showing items 22222-22241 of 38510
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MAC and Physical Layer Design for Ultra-Wideband Communications
(Virginia Tech, 2004-05-04)Ultra-Wideband has recently gained great interest for high-speed short-range communications (e.g. home networking applications) as well as low-speed long-range communications (e.g. sensor network applications). Two flavors ... -
A mach 1.95 free-jet facility for experimental investigation of injectant flow patterns
(Virginia Tech, 1991)Inspired by the need to study injectant flow patterns near the test surface, a supersonic free-jet facility was designed and constructed. This facility provides a Mach 1.95 flow over a test section area of 6.35 cm by 5.08 ... -
Mach bands, Hermann grid, and lateral inhibition in the retina
(Virginia Tech, 1990-08-06)Literature about two illusions that are traditionally linked to lateral inhibitory processes in the retina is surveyed. Despite much research and a long history, the Mach bands illusion has not yet been very well-understood. ... -
Machiavellianism, social insight, and power of department heads
(Virginia Polytechnic Institute and State University, 1982)Department heads are viewed in this study as potential administrative agents of change for innovation in higher educational organizations. Due, however, to the low role power attributed to them by faculty, it was hypothesized ... -
A Machine for Imagination
(Virginia Tech, 2011-11-10)It began with the question, "What if the Modern Man was successful in his dominion over nature?" By means of Architecture this thesis became a speculation and commentary on the human condition. But, more than that, ... -
Machine Learning and Field Inversion approaches to Data-Driven Turbulence Modeling
(Virginia Tech, 2021-04-27)There still is a practical need for improved closure models for the Reynolds-averaged Navier-Stokes (RANS) equations. This dissertation explores two different approaches for using experimental data to provide improved ... -
Machine Learning and Multivariate Statistics for Optimizing Bioprocessing and Polyolefin Manufacturing
(Virginia Tech, 2022-01-07)Chemical engineers have routinely used computational tools for modeling, optimizing, and debottlenecking chemical processes. Because of the advances in computational science over the past decade, multivariate statistics ... -
Machine Learning and Quantum Computing for Optimization Problems in Power Systems
(Virginia Tech, 2023-01-26)While optimization problems are ubiquitous in all domains of engineering, they are of critical importance to power systems engineers. A safe and economical operation of the power systems entails solving many optimization ... -
Machine Learning Applications in Structural Analysis and Design
(Virginia Tech, 2022-10-05)Artificial intelligence (AI) has progressed significantly during the last several decades, along with the rapid advancements in computational power. This advanced technology is currently being employed in various engineering ... -
A Machine Learning Approach for Data Unification and Its Application in Asset Performance Management
(Virginia Tech, 2016-03-28)The amount of data is growing fast with the advance of data capturing and management technologies. However, data from different source are often isolated and not ready to be analyzed together as one data set. The effort ... -
A Machine Learning Approach for Next Step Prediction in Walking using On-Body Inertial Measurement Sensors
(Virginia Tech, 2018-02-22)This thesis presents the development and implementation of a machine learning prediction model for concurrently aggregating interval linear step distance predictions before future foot placement. Specifically, on-body ... -
A Machine Learning Approach for the Objective Sonographic Assessment of Patellar Tendinopathy in Collegiate Basketball Athletes
(Virginia Tech, 2021-06-07)Patellar tendinopathy (PT) is a knee injury resulting in pain localized to the patellar tendon. One main factor that causes PT is repetitive overloading of the tendon. Because of this mechanism, PT is commonly seen in ... -
A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in Arabidopsis Using Time Series Gene Expression Data
(Virginia Tech, 2016-07-08)Gene regulatory networks (GRNs) provide a natural representation of relationships between regulators and target genes. Though inferring GRN is a challenging task, many methods, including unsupervised and supervised approaches, ... -
Machine Learning Approaches for Identifying microRNA Targets and Conserved Protein Complexes
(Virginia Tech, 2017-04-27)Much research has been directed toward understanding the roles of essential components in the cell, such as proteins, microRNAs, and genes. This dissertation focuses on two interesting problems in bioinformatics research: ... -
Machine Learning Approaches for Modeling and Correction of Confounding Effects in Complex Biological Data
(Virginia Tech, 2021-06-09)With the huge volume of biological data generated by new technologies and the booming of new machine learning based analytical tools, we expect to advance life science and human health at an unprecedented pace. Unfortunately, ... -
Machine Learning based Methods to Improve Power System Operation under High Renewable Pennetration
(Virginia Tech, 2022-09-19)In an attempt to thwart global warming in a concerted way, more than 130 countries have committed to becoming carbon neutral around 2050. In the United States, the Biden ad- ministration has called for 100% clean energy ... -
Machine Learning for Millimeter Wave Wireless Systems: Network Design and Optimization
(Virginia Tech, 2021-06-16)Next-generation cellular systems will rely on millimeter wave (mmWave) bands to meet the increasing demand for wireless connectivity from end user equipment. Given large available bandwidth and small-sized antenna elements, ... -
Machine Learning from Computer Simulations with Applications in Rail Vehicle Dynamics and System Identification
(Virginia Tech, 2016-07-01)The application of stochastic modeling for learning the behavior of multibody dynamics models is investigated. The stochastic modeling technique is also known as Kriging or random function approach. Post-processing data ... -
Machine Learning Models in Fullerene/Metallofullerene Chromatography Studies
(Virginia Tech, 2019-08-08)Machine learning methods are now extensively applied in various scientific research areas to make models. Unlike regular models, machine learning based models use a data-driven approach. Machine learning algorithms can ... -
Machine Learning Simulation: Torso Dynamics of Robotic Biped
(Virginia Tech, 2007-08-10)Military, Medical, Exploratory, and Commercial robots have much to gain from exchanging wheels for legs. However, the equations of motion of dynamic bipedal walker models are highly coupled and non-linear, making the ...
