Engineering Commons^™

Generating Energy Data For Machine Learning With Recurrent Generative Adversarial Networks, Mohammad Navid Fekri, Ananda M. Ghosh, Katarina Grolinger

Electrical and Computer Engineering Publications

The smart grid employs computing and communication technologies to embed intelligence into the power grid and, consequently, make the grid more efficient. Machine learning (ML) has been applied for tasks that are important for smart grid operation including energy consumption and generation forecasting, anomaly detection, and state estimation. These ML solutions commonly require sufficient historical data; however, this data is often not readily available because of reasons such as data collection costs and concerns regarding security and privacy. This paper introduces a recurrent generative adversarial network (R-GAN) for generating realistic energy consumption data by learning from real data. Generativea adversarial …

Protein And Polysaccharide-Based Magnetic Composite Materials For Medical Applications., Elizabeth J Bealer, Kyril Kavetsky, Sierra Dutko, Samuel Lofland, Xiao Hu

Faculty Scholarship for the College of Science & Mathematics

The combination of protein and polysaccharides with magnetic materials has been implemented in biomedical applications for decades. Proteins such as silk, collagen, and elastin and polysaccharides such as chitosan, cellulose, and alginate have been heavily used in composite biomaterials. The wide diversity in the structure of the materials including their primary monomer/amino acid sequences allow for tunable properties. Various types of these composites are highly regarded due to their biocompatible, thermal, and mechanical properties while retaining their biological characteristics. This review provides information on protein and polysaccharide materials combined with magnetic elements in the biomedical space showcasing the materials used, …

Low Temperature Liquid Metal Batteries For Energy Storage Applications, Cameron A. Lippert, Kunlei Liu, James Landon, Susan A. Odom, Nicolas E. Holubowitch

Center for Applied Energy Research Faculty Patents

The present invention relates to a molten metal battery of liquid bismuth and liquid tin electrodes and a eutectic electrolyte. The electrodes may be coaxial and coplanar. The eutectic electrolyte may be in contact with a surface of each electrode. The eutectic electrolyte may comprise ZnC1₂:KCI.

Synthesis And Connection Of Iridium Hydrogen Evolution Catalyst To Chlorella Vulgaris Photosystem I For Light-Driven Hydrogen Evolution, Anna Ramirez

Honors Program Theses and Projects

Hydrogen gas has been shown to be a promising energy source as options other than fossil fuels are being looked at in the face of anthropogenic climate change. It is known that anthropogenic climate change is caused by the production of greenhouse gases being let into the atmosphere, specifically a common reason for this is the burning of fossil fuels for energy. The overall goal of this project is to design a biochemical hybrid system that will be used to make H 2 gas and does not require the use of fossil fuels. Burning hydrogen as fuel produces only water …

Point Cloud Processing With Neural Networks, Stephanie Miller, Jiahao Li

All Computer Science and Engineering Research

In this project, we explore new techniques and architectures for applying deep neural networks when the input is point cloud data. We first consider applying convolutions on regular pixel and voxel grids, using polynomials of point coordinates and Fourier transforms to get a rich feature representation for all points mapped to the same pixel or voxel. We also apply these ideas to generalize the recently proposed "interpolated convolution", by learning continuous-space kernels as a combination of polynomial and Fourier basis kernels. Experiments on the ModelNet40 dataset demonstrate that our methods have superior performance over the baselines in 3D object recognition.

Bridging The Gaps In Elementary Life Science Lessons, Kaitlin Cook

Honors Program Theses and Projects

The United States is experiencing a rise in science, technology, engineering and mathematics (STEM) careers while facing a shortage of STEM workers. This could partly be due to a decline in the amount of time allowed for science in elementary schools or possibly because many life science lessons in elementary school lack originality and may not stimulate an interest in science. Lack of captivating STEM education prior to college may be contributing to the decline of students graduating with STEM based degrees. My thesis focuses on getting out of the routine of using monotonous life science lesson plans. I identify …

Founding The Domain Of Ai Forensics, Ibrahim Baggili, Vahid Behzadan

Electrical & Computer Engineering and Computer Science Faculty Publications

With the widespread integration of AI in everyday and critical technologies, it seems inevitable to witness increasing instances of failure in AI systems. In such cases, there arises a need for technical investigations that produce legally acceptable and scientifically indisputable findings and conclusions on the causes of such failures. Inspired by the domain of cyber forensics, this paper introduces the need for the establishment of AI Forensics as a new discipline under AI safety. Furthermore, we propose a taxonomy of the subfields under this discipline, and present a discussion on the foundational challenges that lay ahead of this new research …

Using Machine Learning Classification Methods To Detect The Presence Of Heart Disease, Nestor Pereira

Dissertations

Cardiovascular disease (CVD) is the most common cause of death in Ireland, and probably, worldwide. According to the Health Service Executive (HSE) cardiovascular disease accounting for 36% of all deaths, and one important fact, 22% of premature deaths (under age 65) are from CVD.

Using data from the Heart Disease UCI Data Set (UCI Machine Learning), we use machine learning techniques to detect the presence or absence of heart disease in the patient according to 14 features provide for this dataset. The different results are compared based on accuracy performance, confusion matrix and area under the Receiver Operating Characteristics (ROC) …

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....

Zirconia-Based Compositions For Use In Passive NoX Adsorber Devices, Deborah Jayne Harris, David Alastair Scapens, John G. Darab, Mark Crocker, Yaying Ji

Chemistry Faculty Patents

A passive NO_x adsorbent includes: palladium, platinum or a mixture thereof and a mixed or composite oxide including the following elements in percentage by weight, expressed in terms of oxide: 10-90% by weight zirconium and 0.1-50% by weight of least one of the following: a transition metal or a lanthanide series element other than Ce.

Although the passive NO_x adsorbent can include Ce in an amount ranging from 0.1 to 20% by weight expressed in terms of oxide, advantages are obtained particularly in the case of low-Ce or a substantially Ce-free passive NO_x adsorbent.

Bringing Statistical Learning Machines Together For Hydro-Climatological Predictions - Case Study For Sacramento San Joaquin River Basin, California, Balbhadra Thakur, Ajay Kalra, Sajjad Ahmad, Kenneth W. Lamb, Venkat Lakshmi

Civil and Environmental Engineering and Construction Faculty Research

Study region: Sacramento San Joaquin River Basin, California Study focus: The study forecasts the streamflow at a regional scale within SSJ river basin with largescale climate variables. The proposed approach eliminates the bias resulting from predefined indices at regional scale. The study was performed for eight unimpaired streamflow stations from 1962–2016. First, the Singular Valued Decomposition (SVD) teleconnections of the streamflow corresponding to 500 mbar geopotential height, sea surface temperature, 500 mbar specific humidity (SHUM500), and 500 mbar U-wind (U500) were obtained. Second, the skillful SVD teleconnections were screened non-parametrically. Finally, the screened teleconnections were used as the streamflow predictors …

Factor Analysis Of Mixed Data (Famd) And Multiple Linear Regression In R, Nestor Pereira

Dissertations

In the previous projects, it has been worked to statistically analysis of the factors to impact the score of the subjects of Mathematics and Portuguese for several groups of the student from secondary school from Portugal.

In this project will be interested in finding a model, hypothetically multiple linear regression, to predict the final score, dependent variable G3, of the student according to some features divide into two groups. One group, analyses the features or predictors which impact in the final score more related to the performance of the students, means variables like study time or past failures. The second …

College Of Engineering Senior Design Competition Fall 2019, University Of Nevada, Las Vegas

Fred and Harriet Cox Senior Design Competition Projects

Part of every UNLV engineering student’s academic experience, the senior design project stimulates engineering innovation and entrepreneurship. Each student in their senior year chooses, plans, designs, and prototypes a product in this required element of the curriculum. A capstone to the student’s educational career, the senior design project encourages the student to use everything learned in the engineering program to create a practical, real world solution to an engineering challenge. The senior design competition helps focus the senior students in increasing the quality and potential for commercial application for their design projects. Judges from local industry evaluate the projects on …

Sensor Emulation With Physiolocal Data In Immersive Virtual Reality Driving Simulator, Jungsu Pak, Oliver Mathias, Ariane Guirguis, Uri Maoz

Student Scholar Symposium Abstracts and Posters

Can we enhance the safety and comfort of AVs by training AVs with physiological data of human drivers? We will train and compare AV algorithm with/without physiological data.

Static Taint Analysis Of Binary Executables Using Architecture-Neutral Intermediate Representation, Elaine Cole

All Computer Science and Engineering Research

Ghidra, National Security Agency’s powerful reverse engineering framework, was recently released open-source in April 2019 and is capable of lifting instructions from a wide variety of processor architectures into its own register transfer language called p-code. In this project, we present a new tool which leverages Ghidra’s specific architecture-neutral intermediate representation to construct a control flow graph modeling all program executions of a given binary and apply static taint analysis. This technique is capable of identifying the information flow of malicious input from untrusted sources that may interact with key sinks or parts of the system without needing access to …

Advanced Security Analysis For Emergent Software Platforms, Mohannad Alhanahnah

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Emergent software ecosystems, boomed by the advent of smartphones and the Internet of Things (IoT) platforms, are perpetually sophisticated, deployed into highly dynamic environments, and facilitating interactions across heterogeneous domains. Accordingly, assessing the security thereof is a pressing need, yet requires high levels of scalability and reliability to handle the dynamism involved in such volatile ecosystems.

This dissertation seeks to enhance conventional security detection methods to cope with the emergent features of contemporary software ecosystems. In particular, it analyzes the security of Android and IoT ecosystems by developing rigorous vulnerability detection methods. A critical aspect of this work is the …

The Trolley Problem In Virtual Reality, Jungsu Pak, Ariane Guirguis, Nicholas Mirchandani, Scott Cummings, Uri Maoz

Student Scholar Symposium Abstracts and Posters

Would people react to the Trolley problem differently based on the medium? Immersive Virtual Reality Driving Simulator was used to examine participants respond to the trolley problem in a realistic and controlled simulated environment.

Anomalous Stranski-Krastanov Growth Of (111)-Oriented Quantum Dots With Tunable Wetting Layer Thickness, Christopher F. Schuck, Simon K. Roy, Trent Garrett, Paul J. Simmonds

Materials Science and Engineering Faculty Publications and Presentations

Driven by tensile strain, GaAs quantum dots (QDs) self-assemble on In_0.52Al_0.48As(111)A surfaces lattice-matched to InP substrates. In this study, we show that the tensile-strained self-assembly process for these GaAs(111)A QDs unexpectedly deviates from the well-known Stranski-Krastanov (SK) growth mode. Traditionally, QDs formed via the SK growth mode form on top of a flat wetting layer (WL) whose thickness is fixed. The inability to tune WL thickness has inhibited researchers’ attempts to fully control QD-WL interactions in these hybrid 0D-2D quantum systems. In contrast, using microscopy, spectroscopy, and computational modeling, we demonstrate that for GaAs(111)A QDs, we …

Thermodynamic Model Of Co2 Deposition In Cold Climates, Sandra K. S. Boetcher, Ted Von Hippel, Matthew J. Traum

Publications

A thermodynamic model, borrowing ideas from psychrometric principles, of a cryogenic direct-air CO2-capture system utilizing a precooler is used to estimate the optimal CO2 removal fraction to minimize energy input per tonne of CO2. Energy costs to operate the system scale almost linearly with the temperature drop between the ingested air and the cryogenic desublimation temperature of CO2, driving siting to the coldest accessible locations. System performance in three Arctic/Antarctic regions where the proposed system can potentially be located is analyzed. Colder ambient temperatures provide colder system input air temperature yielding lower CO2 removal energy requirements. A case is also …

Small Ruminant Health Intervention Calendar In Ethiopia, Mesfin Mekonnen, Ayalew Assefa, Tesfalem Nane, Firdawok Ayele, Asrat Arke, Belay Elias, Barbara Wieland

Daugherty Water for Food Global Institute: Faculty Publications

Contents

1 Background................................................................................................... 3
2 Developing the health intervention calendar............................................................ 4
The treatment calendar ......................................................... 4 Applying the calendar..................................................................... 5 4 References................................................................... 8

Seer: An Explainable Deep Learning Midi-Based Hybrid Song Recommender System, Khalil Damak, Olfa Nasraoui

Faculty Scholarship

State of the art music recommender systems mainly rely on either matrix factorization-based collaborative filtering approaches or deep learning architectures. Deep learning models usually use metadata for content-based filtering or predict the next user interaction by learning from temporal sequences of user actions. Despite advances in deep learning for song recommendation, none has taken advantage of the sequential nature of songs by learning sequence models that are based on content. Aside from the importance of prediction accuracy, other significant aspects are important, such as explainability and solving the cold start problem. In this work, we propose a hybrid deep learning …

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 …

Ldakm-Eiot: Lightweight Device Authentication And Key Management Mechanism For Edge-Based Iot Deployment, Mohammad Wazid, Ashok Kumar Das, Sachin Shetty, Joel J. P. C. Rodrigues, Youngho Park

VMASC Publications

In recent years, edge computing has emerged as a new concept in the computing paradigm that empowers several future technologies, such as 5G, vehicle-to-vehicle communications, and the Internet of Things (IoT), by providing cloud computing facilities, as well as services to the end users. However, open communication among the entities in an edge based IoT environment makes it vulnerable to various potential attacks that are executed by an adversary. Device authentication is one of the prominent techniques in security that permits an IoT device to authenticate mutually with a cloud server with the help of an edge node. If authentication …

Finding Needles In A Haystack: Leveraging Co-Change Dependencies To Recommend Refactorings, Marcos César De Oliveira, Davi Freitas, Rodrigo Bonifacio, Gustavo Pinto, David Lo

Research Collection School Of Computing and Information Systems

A fine-grained co-change dependency arises when two fine-grained source-code entities, e.g., a method,change frequently together. This kind of dependency is relevant when considering remodularization efforts (e.g., to keep methods that change together in the same class). However, existing approaches forrecommending refactorings that change software decomposition (such as a move method) do not explorethe use of fine-grained co-change dependencies. In this paper we present a novel approach for recommending move method and move field refactorings, which removes co-change dependencies and evolutionary smells, a particular type of dependency that arise when fine-grained entities that belong to different classes frequently change together. First …

Digitalization In Practice: The Fifth Discipline Advantage, Siu Loon Hoe

Research Collection School Of Computing and Information Systems

Purpose The purpose of this paper is to provide advice to organizations on how to become successful in the digital age. The paper revisits Peter Senge's (1990) notion of the learning organization and discusses the relevance of systems thinking and the other four disciplines, namely, personal mastery, mental models, shared vision and team learning in the context of the current digitalization megatrend. Design/methodology/approach This paper is based on content analysis of essays from international organizations, strategy experts and management scholars, and insights gained from the author's consulting experience. A comparative case study from the health and social sector is also …

Iomt Malware Detection Approaches: Analysis And Research Challenges, Mohammad Wazid, Ashok Kumar Das, Joel J.P.C. Rodrigues, Sachin Shetty, Youngho Park

VMASC Publications

The advancement in Information and Communications Technology (ICT) has changed the entire paradigm of computing. Because of such advancement, we have new types of computing and communication environments, for example, Internet of Things (IoT) that is a collection of smart IoT devices. The Internet of Medical Things (IoMT) is a specific type of IoT communication environment which deals with communication through the smart healthcare (medical) devices. Though IoT communication environment facilitates and supports our day-to-day activities, but at the same time it has also certain drawbacks as it suffers from several security and privacy issues, such as replay, man-in-the-middle, impersonation, …

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 …

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 …

Energy And Exergy Analysis Of A Novel Multiple-Effect Vapor Chamber Distillation System For High-Salinity Wastewater Treatment, Hamidreza Shabgard, Ramkumar Parthasarathy, Ben Xu

Mechanical Engineering Faculty Publications and Presentations

A novel modular thermally-driven multiple-effect vapor chamber distillation (MVCD) system is presented for compact and portable desalination applications. The MVCD system consists of several vapor chambers connected in series with the condenser section of the upstream vapor chambers serving as the evaporator section of the following effect. A heat transfer model accounting for the major thermal resistances was developed to predict the heat transfer and distilled water production rates. A mass transfer analysis was performed to evaluate the effect of the accumulation of the non-condensable gasses within the chambers. An exergy analysis was also conducted to quantify the efficiency of …

Defining Boat Wake Impacts On Shoreline Stability Toward Management And Policy Solutions, Donna Marie Bilkovic, Molly M. Mitchell, Jennifer Davis, Julie Herman, Elizabeth Andrews, Angela King, Pamela Mason, Navid Tahvildari, Jana Davis, Rachel L. Dixon

Civil & Environmental Engineering Faculty Publications

Coastal economies are often supported by activities that rely on commercial or recreational vessels to move people or goods, such as shipping, transportation, cruising, and fishing. Unintentionally, frequent or intense vessel traffic can contribute to erosion of coastlines; this can be particularly evident in sheltered systems where shoreline erosion should be minimal in the absence of boat waves. We reviewed the state of the science of known effects of boat waves on shoreline stability, examined data on erosion, turbidity, and shoreline armoring patterns for evidence of a response to boat waves in Chesapeake Bay, and reviewed existing management and policy …