Physical Sciences and Mathematics | Open Access Articles

Monte Carlo And Experimental Analysis Of A Novel Directional Rotating Scatter Mask Gamma Detection System, Julie V. Logan, Darren E. Holland, Larry W. Burggraf, Justin A. Clinton, Buckley E. O'Day Iii

Faculty Publications

Excerpt: This work demonstrates successful experimental operation of a prototype system to identify source direction which was modeled using a library of signals simulated using GEANT and a novel algorithm....

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Generating Electromagnetic Nonuniformly Correlated Beams, Milo W. Hyde Iv, Xifeng Xiao, David G. Voelz

Faculty Publications

We develop a method to generate electromagnetic nonuniformly correlated (ENUC) sources from vector Gaussian Schell-model (GSM) beams. Having spatially varying correlation properties, ENUC sources are more difficult to synthesize than their Schell-model counterparts (which can be generated by filtering circular complex Gaussian random numbers) and, in past work, have only been realized using Cholesky decomposition—a computationally intensive procedure. Here we transform electromagnetic GSM field instances directly into ENUC instances, thereby avoiding computing Cholesky factors resulting in significant savings in time and computing resources. We validate our method by generating (via simulation) an ENUC beam with desired parameters. We find the …

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E700xd Portable Doppler Radar Energy Systems Analysis, Brandon M. Bailey [*], Torrey J. Wagner, Jada Williams

Faculty Publications

Occurring in industrialized nations, inexpensive and abundantly available power is routinely taken for granted. However, energy resilience and to a lesser extent price are key concerns when considering potential solutions for disaster response, disaster relief, or military operations. The Department of Defense (DoD) currently uses a 5 kW generator to power the E700XD portable Doppler radar system when grid power is unavailable [1]. While the radar has an approximate power consumption of 2.5 kW, there is a potential for higher demand due to weather conditions [2]. This paper examines the cost of operating a currently installed generator, compared to the …

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Deep Donors And Acceptors In Β-Ga2O3 Crystals: Determination Of The Fe2+/3+ Level By A Noncontact Method, Christopher A. Lenyk, Trevor A . Gustafson, Larry E. Halliburton, Nancy C. Giles

Faculty Publications

Electron paramagnetic resonance (EPR), infrared absorption, and thermoluminescence (TL) are used to determine the Fe^2+/3+ level in Fe-doped β-Ga₂O₃ crystals. With these noncontact spectroscopy methods, a value of 0.84 ± 0.05 eV below the conduction band is obtained for this level. Our results clearly establish that the E2 level observed in deep level transient spectroscopy (DLTS) experiments is due to the thermal release of electrons from Fe²⁺ ions. The crystals used in this investigation were grown by the Czochralski method and contained large concentrations of Fe acceptors and Ir donors, and trace amounts of Cr …

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Gamma-Ray Radiation Effects In Graphene-Based Transistors With H-Bn Nanometer Film Substrates, E. J. Cazalas, Michael R. Hogsed, S. R. Vangala, Michael R. Snure, John W. Mcclory

Faculty Publications

Radiation effects on graphene field effect transistors (GFETs) with hexagonal boron nitride (h-BN) thin film substrates are investigated using 60Co gamma-ray radiation. This study examines the radiation response using many samples with varying h-BN film thicknesses (1.6 and 20 nm thickness) and graphene channel lengths (5 and 10 μm). These samples were exposed to a total ionizing dose of approximately 1 Mrad(Si). I-V measurements were taken at fixed time intervals between irradiations and postirradiation. Dirac point voltage and current are extracted from the I-V measurements, as well as mobility, Dirac voltage hysteresis, and the total number of GFETs that remain …

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Measurement Of Electron Density And Temperature From Laser-Induced Nitrogen Plasma At Elevated Pressure (1–6 Bar), Ashwin P. Rao [*], Mark Gragston, Anil K. Patnaik, Paul S. Hsu, Michael B. Shattan

Faculty Publications

Laser-induced plasmas experience Stark broadening and shifts of spectral lines carrying spectral signatures of plasma properties. In this paper, we report time-resolved Stark broadening measurements of a nitrogen triplet emission line at 1–6 bar ambient pressure in a pure nitrogen cell. Electron densities are calculated using the Stark broadening for different pressure conditions, which are shown to linearly increase with pressure. Additionally, using a Boltzmann fit for the triplet, the electron temperature is calculated and shown to decrease with increasing pressure. The rate of plasma cooling is observed to increase with pressure. The reported Stark broadening based plasma diagnostics in …

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Multiple Pursuer Multiple Evader Differential Games, Eloy Garcia, David Casbeer, Alexander Von Moll, Meir Pachter

Faculty Publications

In this paper an N-pursuer vs. M-evader team conflict is studied. The differential game of border defense is addressed and we focus on the game of degree in the region of the state space where the pursuers are able to win. This work extends classical differential game theory to simultaneously address weapon assignments and multi-player pursuit-evasion scenarios. Saddle-point strategies that provide guaranteed performance for each team regardless of the actual strategies implemented by the opponent are devised. The players' optimal strategies require the co-design of cooperative optimal assignments and optimal guidance laws. A representative measure of performance is proposed and …

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Fkrr-Mvsf: A Fuzzy Kernel Ridge Regression Model For Identifying Dna-Binding Proteins By Multi-View Sequence Features Via Chou's Five-Step Rule, Yi Zou, Yijie Ding, Jijun Tang, Fei Guo, Li Peng

Faculty Publications

DNA-binding proteins play an important role in cell metabolism. In biological laboratories, the detection methods of DNA-binding proteins includes yeast one-hybrid methods, bacterial singles and X-ray crystallography methods and others, but these methods involve a lot of labor, material and time. In recent years, many computation-based approachs have been proposed to detect DNA-binding proteins. In this paper, a machine learning-based method, which is called the Fuzzy Kernel Ridge Regression model based on Multi-View Sequence Features (FKRR-MVSF), is proposed to identifying DNA-binding proteins. First of all, multi-view sequence features are extracted from protein sequences. Next, a Multiple Kernel Learning (MKL) algorithm …

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Quantitative Analysis Of Cerium-Gallium Alloys Using A Hand-Held Laser Induced Breakdown Spectroscopy Device, Ashwin P. Rao, Matthew Cook, Howard L. Hall, Michael B. Shattan

Faculty Publications

A hand-held laser-induced breakdown spectroscopy device was used to acquire spectral emission data from laser-induced plasmas created on the surface of cerium-gallium alloy samples with Ga concentrations ranging from 0–3 weight percent. Ionic and neutral emission lines of the two constituent elements were then extracted and used to generate calibration curves relating the emission line intensity ratios to the gallium concentration of the alloy. The Ga I 287.4-nm emission line was determined to be superior for the purposes of Ga detection and concentration determination. A limit of detection below 0.25%was achieved using a multivariate regression model of the Ga I …

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Fkrr-Mvsf: A Fuzzy Kernel Ridge Regression Model For Identifying Dna-Binding Proteins By Multi-View Sequence Features Via Chou's Five-Step Rule, Yi Zou, Yije Ding, Jijun Tang, Fei Guo, Li Peng

Faculty Publications

DNA-binding proteins play an important role in cell metabolism. In biological laboratories, the detection methods of DNA-binding proteins includes yeast one-hybrid methods, bacterial singles and X-ray crystallography methods and others, but these methods involve a lot of labor, material and time. In recent years, many computation-based approachs have been proposed to detect DNA-binding proteins. In this paper, a machine learning-based method, which is called the Fuzzy Kernel Ridge Regression model based on Multi-View Sequence Features (FKRR-MVSF), is proposed to identifying DNA-binding proteins. First of all, multi-view sequence features are extracted from protein sequences. Next, a Multiple Kernel Learning (MKL) algorithm …

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Near-Field Effects On Partially Coherent Light Scattered By An Aperture, Milo W. Hyde Iv, Michael J. Havrilla

Faculty Publications

We investigate how the near field affects partially coherent light scattered from an aperture in an opaque screen. Prior work on this subject has focused on the role of surface plasmons, and how they affect spatial coherence is well documented. Here, we consider other near-field effects that might impact spatial coherence. We do this by examining the statistics of the near-zone field scattered from an aperture in a perfect electric conductor plane—a structure that does not support surface plasmons. We derive the near-field statistics (in particular, cross-spectral density functions) by applying electromagnetic equivalence theorems and the Method of Moments. We …

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A Review Of Text Corpus-Based Tourism Big Data Mining, Qin Lin, Shaobo Li, Sen Zhang, Jie Hu, Jianjun Hu

Faculty Publications

With the massive growth of the Internet, text data has become one of the main formats of tourism big data. As an effective expression means of tourists’ opinions, text mining of such data has big potential to inspire innovations for tourism practitioners. In the past decade, a variety of text mining techniques have been proposed and applied to tourism analysis to develop tourism value analysis models, build tourism recommendation systems, create tourist profiles, and make policies for supervising tourism markets. The successes of these techniques have been further boosted by the progress of natural language processing (NLP), machine learning, and …

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A Review Of Text Corpus-Based Tourism Big Data Mining, Qin Li, Shaobo Li, Sen Zhang, Jie Hu, Jianhun Hu

Faculty Publications

With the massive growth of the Internet, text data has become one of the main formats of tourism big data. As an effective expression means of tourists’ opinions, text mining of such data has big potential to inspire innovations for tourism practitioners. In the past decade, a variety of text mining techniques have been proposed and applied to tourism analysis to develop tourism value analysis models, build tourism recommendation systems, create tourist profiles, and make policies for supervising tourism markets. The successes of these techniques have been further boosted by the progress of natural language processing (NLP), machine learning, and …

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Subsurface Mimo: A Beamforming Design In Internet Of Underground Things For Digital Agriculture Applications, Abdul Salam

Faculty Publications

In underground (UG) multiple-input and multiple-output (MIMO), the transmit beamforming is used to focus energy in the desired direction. There are three different paths in the underground soil medium through which the waves propagates to reach at the receiver. When the UG receiver receives a desired data stream only from the desired path, then the UG MIMO channel becomes three path (lateral, direct, and reflected) interference channel. Accordingly, the capacity region of the UG MIMO three path interference channel and degrees of freedom (multiplexing gain of this MIMO channel requires careful modeling). Therefore, expressions are required for the degree of …

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3d Plasmonic Design Approach For Efficient Transmissive Huygens Metasurfaces, Bryan M. Adomanis, D. Bruce Burckel, Michael A. Marciniak

Faculty Publications

In this paper we present a design concept for 3D plasmonic scatterers as high- efficiency transmissive metasurface (MS) building blocks. A genetic algorithm (GA) routine partitions the faces of the walls inside an open cavity into a M x N grid of voxels which can be either covered with metal or left bare, and optimizes the distribution of metal coverage needed to generate electric and magnetic modes of equal strength with a targeted phase delay (Φt) at the design wavelength. Even though the electric and magnetic modes can be more complicated than typical low order modes, with their spectral overlap …

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Personalized Product Evaluation Based On Gra-Topsis And Kansei Engineering, Huafeng Quan, Shaobo Li, Hongjing Wei, Jianjun Hu

Faculty Publications

With the improvement of human living standards, users’ requirements have changed from function to emotion. Helping users pick out the most suitable product based on their subjective requirements is of great importance for enterprises. This paper proposes a Kansei engineering-based grey relational analysis and techniques for order preference by similarity to ideal solution (KE-GAR-TOPSIS) method to make a subjective user personalized ranking of alternative products. The KE-GRA-TOPSIS method integrates five methods, including Kansei Engineering (KE), analytic hierarchy process (AHP), entropy, game theory, and grey relational analysis-TOPSIS (GRA-TOPSIS). First, an evaluation system is established by KE and AHP. Second, we define …

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Towards Lakosian Multilingual Software Design Principles, Damian Lyons, Saba Zahra, Thomas Marshall

Faculty Publications

Large software systems often comprise programs written in different programming languages. In the case when cross-language interoperability is accomplished with a Foreign Function Interface (FFI), for example pybind11, Boost.Python, Emscripten, PyV8, or JNI, among many others, common software engineering tools, such as call-graph analysis, are obstructed by the opacity of the FFI. This complicates debugging and fosters potential inefficiency and security problems. One contributing issue is that there is little rigorous software design advice for multilingual software. In this paper, we present our progress towards a more rigorous design approach to multilingual software. The approach is based on the existing …

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Analyzing The Efficiency Of Horizontal Photovoltaic Cells In Various Climate Regions, Parker A. Hines, Torrey J. Wagner, Clay M. Koschnick, Steven J. Schuldt

Faculty Publications

This research presents the development of linear regression models to predict horizontal photovoltaic power output. We collected a dataset from 14 global Department of Defense (DoD) installations over a timeframe of one year using an experimental apparatus, resulting in 24,179 usable data points. We developed a linear model to predict power output, which incorporated site-specific weather and geographical characteristics, along with Köppen-Geiger climate classifications in order to determine the effect of adding climate to the model. After performing a Wald test between the full model and a reduced model without Köppen-Geiger climate variables, it was determined that including Köppen-Geiger climate …

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Using Big Data Analytics To Improve Hiv Medical Care Utilisation In South Carolina: A Study Protocol, Bankole Olatosi, Jiajia Zhang, Sharon Weissman, Jianjun Hu, Mohammad Rifat Haider, Xiaoming Li

Faculty Publications

Introduction Linkage and retention in HIV medical care remains problematic in the USA. Extensive health utilisation data collection through electronic health records (EHR) and claims data represent new opportunities for scientific discovery. Big data science (BDS) is a powerful tool for investigating HIV care utilisation patterns. The South Carolina (SC) office of Revenue and Fiscal Affairs (RFA) data warehouse captures individual-level longitudinal health utilisation data for persons living with HIV (PLWH). The data warehouse includes EHR, claims and data from private institutions, housing, prisons, mental health, Medicare, Medicaid, State Health Plan and the department of health and human services. The …

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Statistical Viability Analysis Of United States Air Force Estimating Cost Factor For Sustainable Construction, Philip A. Ramsey, Diedrich Prigge, Torrey J. Wagner, Alfred E. Thal Jr.

Faculty Publications

Varying legislation and executive orders coupled with needs for energy resiliency have led the United States Air Force (USAF) to pursue sustainable construction. However, the limited understanding of initial costs to implement these changes have contributed to poor project cost estimating, resulting in 62 percent of USAF projects experiencing more than 5 percent cost growth. After reviewing 1628 USAF Military Construction (MILCON) construction projects in 922 category codes (CATCODEs), a twotailed t-test for populations with unequal variance was accomplished on the final normalized contract cost for 340 projects in 16 CATCODEs executed between 2002 and 2017. This analysis provides a …

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Deep Autoencoder Neural Networks For Short-Term Traffic Congestion Prediction Of Transportation Networks, Sen Zhang, Yong Yao, Jie Hu, Yong Zhao, Shaobo Li, Jianjun Hu

Faculty Publications

Traffic congestion prediction is critical for implementing intelligent transportation systems for improving the efficiency and capacity of transportation networks. However, despite its importance, traffic congestion prediction is severely less investigated compared to traffic flow prediction, which is partially due to the severe lack of large-scale high-quality traffic congestion data and advanced algorithms. This paper proposes an accessible and general workflow to acquire large-scale traffic congestion data and to create traffic congestion datasets based on image analysis. With this workflow we create a dataset named Seattle Area Traffic Congestion Status (SATCS) based on traffic congestion map snapshots from a publicly available …

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Using Wind And Hydro Power To Sustain The Off-Grid Power Supply For A 50' Cruising Sailboat, Keisha Meyer, Torrey J. Wagner, Jada Williams

Faculty Publications

Cruising sailboats operate with a power requirement modest enough to operate mostly or completely on renewable energy technology sources. Cruisers without renewable energy systems use the vessel’s diesel engine to charge the boat’s batteries; if the systems are operated at anchor, this dramatically decreases the time before the engine needs major overhaul. System users estimate a diesel engine can run approximately 8,000 hours underway before needing major overhaul, whereas operating 500 hours at anchor produces similar wear and tear on engine pistons. Although renewable energy systems have a high initial capital cost, these systems can provide the vessel’s electrical system …

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A Cooperative Overlay Approach At The Physical Layer Of Cognitive Radio For Digital Agriculture, Abdul Salam, Umit Karabiyik

Faculty Publications

In digital agriculture, the cognitive radio technology is being envisaged as solution to spectral shortage problems by allowing agricultural cognitive users to co-exist with noncognitive users in the same spectrum on the field. Cognitive radios increase system capacity and spectral efficiency by sensing the spectrum and adapting the transmission parameters. This design requires a robust, adaptable and flexible physical layer to support cognitive radio functionality. In this paper, a novel physical layer architecture for cognitive radio based on cognition, cooperation, and cognitive interference avoidance has been developed by using power control for digital agriculture applications. The design is based on …

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Urban Underground Infrastructure Monitoring Iot: The Path Loss Analysis, Abdul Salam, Syed Shah

Faculty Publications

The extra quantities of wastewater entering the pipes can cause backups that result in sanitary sewer overflows. Urban underground infrastructure monitoring is important for controlling the flow of extraneous water into the pipelines. By combining the wireless underground communications and sensor solutions, the urban underground IoT applications such as real time wastewater and storm water overflow monitoring can be developed. In this paper, the path loss analysis of wireless underground communications in urban underground IoT for wastewater monitoring has been presented. It has been shown that the communication range of up to 4 kilometers can be achieved from an underground …

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An Underground Radio Wave Propagation Prediction Model For Digital Agriculture, Abdul Salam

Faculty Publications

Underground sensing and propagation of Signals in the Soil (SitS) medium is an electromagnetic issue. The path loss prediction with higher accuracy is an open research subject in digital agriculture monitoring applications for sensing and communications. The statistical data are predominantly derived from site-specific empirical measurements, which is considered an impediment to universal application. Nevertheless, in the existing literature, statistical approaches have been applied to the SitS channel modeling, where impulse response analysis and the Friis open space transmission formula are employed as the channel modeling tool in different soil types under varying soil moisture conditions at diverse communication distances …

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Convolutional Neural Networks For Crystal Material Property Prediction Using Hybrid Orbital-Field Matrix And Magpie Descriptors, Zhuo Cao, Yabo Dan, Zheng Xiong, Chengcheng Niu, Xiang Li, Songrong Qian, Jianjun Hu

Faculty Publications

Computational prediction of crystal materials properties can help to do large-scale in-silicon screening. Recent studies of material informatics have focused on expert design of multi-dimensional interpretable material descriptors/features. However, successes of deep learning such as Convolutional Neural Networks (CNN) in image recognition and speech recognition have demonstrated their automated feature extraction capability to effectively capture the characteristics of the data and achieve superior prediction performance. Here, we propose CNN-OFM-Magpie, a CNN model with OFM (Orbital-field Matrix) and Magpie descriptors to predict the formation energy of 4030 crystal material by exploiting the complementarity of two-dimensional OFM features and Magpie features. Experiments …

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Underground Environment Aware Mimo Design Using Transmit And Receive Beamforming In Internet Of Underground Things, Abdul Salam

Faculty Publications

In underground (UG) multiple-input and multiple-output (MIMO), the transmit beamforming is used to focus energy in the desired direction. There are three different paths in the underground soil medium through which the waves propagates to reach at the receiver. When the UG receiver receives a desired data stream only from the desired path, then the UG MIMO channel becomes three path (lateral, direct, and reflected) interference channel. Accordingly, the capacity region of the UG MIMO three path interference channel and degrees of freedom (multiplexing gain of this MIMO channel requires careful modeling). Therefore, expressions are required derived the degrees of …

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Austere Location Wind Turbine Energy System Analysis, Lukas Cowen, Douglas S. Dudis, Torrey J. Wagner

Faculty Publications

One promising technology to combat an energy shortage in austere locations is wind energy. In combination with battery storage and generator backup, we explore the feasibility of using a hybrid energy system to reduce the volume of diesel fuel required. Modeling the energy demands in austere locations will enable missions in remote settings to optimize their energy costs, increased their energy resiliency and assure their supply. For a modeled time-series energy requirement that varied between 2.4 MW and 5.1 MW, the optimal wind system size was 9.9 MW of installed wind power paired with a 741 kWh battery. Assuming an …

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36% Reduction In Fuel Resupply Using A Hybrid Generator & Battery System For An Austere Location, David J. Chester [*], Torrey J. Wagner, Douglas S. Dudis

Faculty Publications

The DOD energy policy is to increase energy security resiliency, and mitigate costs in the use and management of energy^[1] Forward operating bases (FOBs) are remote, austere base camps that support an operationally defined mission with a limited or no ability to draw from an energy grid and have historically relied on diesel-powered generators for the primary production of energy.^[2] Generators are sized to meet a theoretical peak demand, but steady state loads are far below this peak, resulting in under-loaded generators.^[3] Under-loaded diesel generators decrease efficiency and increase the need for maintenance, affecting the lifespan of …

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A Theoretical Model Of Underground Dipole Antennas For Communications In Internet Of Underground Things, Abdul Salam, Mehmet C. Vuran, Xin Dong, Christos Argyropoulos, Suat Irmak

Faculty Publications

The realization of Internet of Underground Things (IOUT) relies on the establishment of reliable communication links, where the antenna becomes a major design component due to the significant impacts of soil. In this paper, a theoretical model is developed to capture the impacts of change of soil moisture on the return loss, resonant frequency, and bandwidth of a buried dipole antenna. Experiments are conducted in silty clay loam, sandy, and silt loam soil, to characterize the effects of soil, in an indoor testbed and field testbeds. It is shown that at subsurface burial depths (0.1-0.4m), change in soil moisture impacts …

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Full-Text Articles in Physical Sciences and Mathematics

Monte Carlo And Experimental Analysis Of A Novel Directional Rotating Scatter Mask Gamma Detection System, Julie V. Logan, Darren E. Holland, Larry W. Burggraf, Justin A. Clinton, Buckley E. O'Day Iii

Faculty Publications

Generating Electromagnetic Nonuniformly Correlated Beams, Milo W. Hyde Iv, Xifeng Xiao, David G. Voelz

Faculty Publications

E700xd Portable Doppler Radar Energy Systems Analysis, Brandon M. Bailey [*], Torrey J. Wagner, Jada Williams

Faculty Publications

Deep Donors And Acceptors In Β-Ga2O3 Crystals: Determination Of The Fe2+/3+ Level By A Noncontact Method, Christopher A. Lenyk, Trevor A . Gustafson, Larry E. Halliburton, Nancy C. Giles

Faculty Publications

Gamma-Ray Radiation Effects In Graphene-Based Transistors With H-Bn Nanometer Film Substrates, E. J. Cazalas, Michael R. Hogsed, S. R. Vangala, Michael R. Snure, John W. Mcclory

Faculty Publications

Measurement Of Electron Density And Temperature From Laser-Induced Nitrogen Plasma At Elevated Pressure (1–6 Bar), Ashwin P. Rao [*], Mark Gragston, Anil K. Patnaik, Paul S. Hsu, Michael B. Shattan

Faculty Publications

Multiple Pursuer Multiple Evader Differential Games, Eloy Garcia, David Casbeer, Alexander Von Moll, Meir Pachter

Faculty Publications

Fkrr-Mvsf: A Fuzzy Kernel Ridge Regression Model For Identifying Dna-Binding Proteins By Multi-View Sequence Features Via Chou's Five-Step Rule, Yi Zou, Yijie Ding, Jijun Tang, Fei Guo, Li Peng

Faculty Publications

Quantitative Analysis Of Cerium-Gallium Alloys Using A Hand-Held Laser Induced Breakdown Spectroscopy Device, Ashwin P. Rao, Matthew Cook, Howard L. Hall, Michael B. Shattan

Faculty Publications

Fkrr-Mvsf: A Fuzzy Kernel Ridge Regression Model For Identifying Dna-Binding Proteins By Multi-View Sequence Features Via Chou's Five-Step Rule, Yi Zou, Yije Ding, Jijun Tang, Fei Guo, Li Peng

Faculty Publications

Near-Field Effects On Partially Coherent Light Scattered By An Aperture, Milo W. Hyde Iv, Michael J. Havrilla

Faculty Publications

A Review Of Text Corpus-Based Tourism Big Data Mining, Qin Lin, Shaobo Li, Sen Zhang, Jie Hu, Jianjun Hu

Faculty Publications

A Review Of Text Corpus-Based Tourism Big Data Mining, Qin Li, Shaobo Li, Sen Zhang, Jie Hu, Jianhun Hu

Faculty Publications

Subsurface Mimo: A Beamforming Design In Internet Of Underground Things For Digital Agriculture Applications, Abdul Salam

Faculty Publications

3d Plasmonic Design Approach For Efficient Transmissive Huygens Metasurfaces, Bryan M. Adomanis, D. Bruce Burckel, Michael A. Marciniak

Faculty Publications

Personalized Product Evaluation Based On Gra-Topsis And Kansei Engineering, Huafeng Quan, Shaobo Li, Hongjing Wei, Jianjun Hu

Faculty Publications

Towards Lakosian Multilingual Software Design Principles, Damian Lyons, Saba Zahra, Thomas Marshall

Faculty Publications

Analyzing The Efficiency Of Horizontal Photovoltaic Cells In Various Climate Regions, Parker A. Hines, Torrey J. Wagner, Clay M. Koschnick, Steven J. Schuldt

Faculty Publications

Using Big Data Analytics To Improve Hiv Medical Care Utilisation In South Carolina: A Study Protocol, Bankole Olatosi, Jiajia Zhang, Sharon Weissman, Jianjun Hu, Mohammad Rifat Haider, Xiaoming Li

Faculty Publications

Statistical Viability Analysis Of United States Air Force Estimating Cost Factor For Sustainable Construction, Philip A. Ramsey, Diedrich Prigge, Torrey J. Wagner, Alfred E. Thal Jr.

Faculty Publications

Deep Autoencoder Neural Networks For Short-Term Traffic Congestion Prediction Of Transportation Networks, Sen Zhang, Yong Yao, Jie Hu, Yong Zhao, Shaobo Li, Jianjun Hu

Faculty Publications

Using Wind And Hydro Power To Sustain The Off-Grid Power Supply For A 50' Cruising Sailboat, Keisha Meyer, Torrey J. Wagner, Jada Williams

Faculty Publications

A Cooperative Overlay Approach At The Physical Layer Of Cognitive Radio For Digital Agriculture, Abdul Salam, Umit Karabiyik

Faculty Publications

Urban Underground Infrastructure Monitoring Iot: The Path Loss Analysis, Abdul Salam, Syed Shah

Faculty Publications

An Underground Radio Wave Propagation Prediction Model For Digital Agriculture, Abdul Salam

Faculty Publications

Convolutional Neural Networks For Crystal Material Property Prediction Using Hybrid Orbital-Field Matrix And Magpie Descriptors, Zhuo Cao, Yabo Dan, Zheng Xiong, Chengcheng Niu, Xiang Li, Songrong Qian, Jianjun Hu

Faculty Publications

Underground Environment Aware Mimo Design Using Transmit And Receive Beamforming In Internet Of Underground Things, Abdul Salam

Faculty Publications

Austere Location Wind Turbine Energy System Analysis, Lukas Cowen, Douglas S. Dudis, Torrey J. Wagner

Faculty Publications

36% Reduction In Fuel Resupply Using A Hybrid Generator & Battery System For An Austere Location, David J. Chester [*], Torrey J. Wagner, Douglas S. Dudis

Faculty Publications

A Theoretical Model Of Underground Dipole Antennas For Communications In Internet Of Underground Things, Abdul Salam, Mehmet C. Vuran, Xin Dong, Christos Argyropoulos, Suat Irmak

Faculty Publications