Engineering Commons^™

Monitored Compression Therapy: Using Smart Technology To Optimize The Treatment Of Lower Extremity Swelling, James Skelly

UNLV Theses, Dissertations, Professional Papers, and Capstones

Chronic Venous Insufficiency (CVI) and Venous Stasis Ulcers (VSUs) are symptoms which stem from diabetes – a disease effecting over 34 million people in the United States alone as of 2020. This Thesis details the design of a pressure-sensing garment used to enhance the treatment of CVI. The garment uses small force sensors (four levels: the insole of the foot, the lower leg, the lower calf, and the upper calf) to sense the pressure applied by a compression stocking. The sensed data is transmitted wirelessly via Bluetooth to a smartphone application that was developed to display the data and interface …

Network Management, Optimization And Security With Machine Learning Applications In Wireless Networks, Mariam Nabil

Theses and Dissertations

Wireless communication networks are emerging fast with a lot of challenges and ambitions. Requirements that are expected to be delivered by modern wireless networks are complex, multi-dimensional, and sometimes contradicting. In this thesis, we investigate several types of emerging wireless networks and tackle some challenges of these various networks. We focus on three main challenges. Those are Resource Optimization, Network Management, and Cyber Security. We present multiple views of these three aspects and propose solutions to probable scenarios. The first challenge (Resource Optimization) is studied in Wireless Powered Communication Networks (WPCNs). WPCNs are considered a very promising approach towards sustainable, …

Flow Choice Architecture: Cognitive Augmentation Of Knowledge Workers, Troy Ricardo Weekes

Theses and Dissertations

The Flow Choice Architecture (FCA) is a biofeedback-based behavior modification tool that was designed for operation by human knowledge workers (KWs) before, during, and after the performance of work tasks. FCA utilizes human-aware artificial intelligence (AI) that senses patterns in its operator’s bio-signals to derive their cognitive and affective states. The states are contextualized using relevant information about the operator, task, and work timeline. The contextualized operator states are then used to recommend effective nudges that orient the human KW towards the flow state. This dissertation outlines the state-of-the-art on flow, neurofeedback, and AI then explains how FCA was designed, …

Ahmedabad City App, Rushabh Picha

Electronic Theses, Projects, and Dissertations

The Ahmedabad City App is a city guide app that provides information on the city's accessible resources. The project's goal is to provide a concrete, one-stop platform for finding information on all of Ahmedabad's accessible resources. The main goal is to simplify the railway's schedule and make it easier for customers to get from one point to another swiftly and safely. Emergency connections such as the blood bank, fire department, police station, and hospitals will be included in the app. Restaurants and picnic areas are also included in the rejuvenation process.

The proposed system uses SQLite as the database and …

Lossy Compression And Its Application On Large Scale Scientific Datasets, Tasmia Reza

All Theses

High Performance Computing (HPC) applications are always expanding in data size and computational complexity. It is becoming necessary to consider fault tolerance and system recovery to reduce computation and resource cost in HPC systems. The computation of modern large scale HPC applications are facing bottleneck due to computation complexities, increased runtime and large data storage requirements. These issues can not be ignored in current supercomputing era. Data compression is one of the effective ways to address data storage issue. Among data compression, the lossy compression is much more feasible and efficient than the traditional lossless compression due to low I/O …

Forecasting Sep Events Based On Merged Cme Catalogs Using Machine Learning, Peter William Tarsoly

Theses and Dissertations

The lack of preparation for a Solar Energetic Particle (SEP) event may be catastrophic for astronauts and aircraft passengers alike, along with their electronic equipment. It is widely theorized that SEP events are caused by Coronal Mass Ejections (CMEs), some occurring up to a full day beforehand, accompanied by additional space weather conditions. The only significant models for SEP forecasting are statistically or machine learning-based, often developed on imprecise data. We present an enhanced catalog of CMEs, along with other space weather phenomena, and their relationship with the occurrence of SEP events. Using the enhanced CME catalog, we combine machine …

Smart Glasses Assisting Visually-Impaired People, Ali Delham Algarni

Theses and Dissertations

Smart Glasses Assisting Visually-Impaired artificial intelligence system providing speech recognition, object recognition, face recognition, and distance to all features for visually impaired people's enhanced (daily) autonomy. Smart Glasses Assisting Visually-Impaired People is a new integrative process that combines as such, the invention is both a further use of the technologies supporting the features listed above and an improvement to the overall activities carried out by visually impaired people in their daily lives activities such as: providing vocal commands, being able to read text, being able to receive spoken information about various objects in their surroundings, being aware of their location …

A Youthful Metaverse: Towards Designing Safe, Equitable, And Emotionally Fulfilling Social Virtual Reality Spaces For Younger Users, Divine Maloney

All Dissertations

Social virtual reality (VR) represents the modern rendition of the metaverse, this dissertation aims to fill the research gaps while highlighting trends of youth in VR. The scientific contributions of this research include 1) expanding the current HCI understanding of the social dynamics and the interactions of teens in emerging novel online digital spaces; 2) bridging two research areas that have not been widely studied in HCI, social VR and young users in social VR; and 3) generating design implications to inform the design of future social VR platforms to better support and protect teens’ online social experiences, results which …

Optimizing A Virtual Human Platform For Depression/Suicide Ideation Identification For The American Soldier, Christina M. Monahan

Master's Theses

Suicide surpassed homicide to be the second leading cause of death among people 10-24 years old in the United States \cite{1}. This statistic is alarming especially when combined with the more than eight distinctly different types of clinical depression among society today \cite{2}. To further complicate this health crisis, let’s consider the current worldwide isolating pandemic often referred to as COVID-19 that has spanned 12 months. It is more important than ever to consider how we can get ahead of the crisis by identifying the symptoms as they set in and more importantly ahead of the decision to commit suicide. …

Wi-Fi Sensing: Device-Free In-Zone Object Movement Detection, Nicholas P. Schnorr

Master's Theses

Wi-Fi Sensing is becoming a prominent field with a wide range of potential applications. Using existing hardware on a wireless network such as access points, cell phones, and smart home devices, important information can be inferred about the current physical environment. Through the analysis of Channel State Information collected in the Neighborhood Discovery Protocol process, the wireless network can detect disturbances in Wi-Fi signals when the physical environment changes. This results in a system that can sense motion within the Wi-Fi network, allowing for movement detection without any wearable devices.

The goal of this thesis is to answer whether Wi-Fi …

Integration Of Internet Of Things And Health Recommender Systems, Moonkyung Yang

Electronic Theses, Projects, and Dissertations

The Internet of Things (IoT) has become a part of our lives and has provided many enhancements to day-to-day living. In this project, IoT in healthcare is reviewed. IoT-based healthcare is utilized in remote health monitoring, observing chronic diseases, individual fitness programs, helping the elderly, and many other healthcare fields. There are three main architectures of smart IoT healthcare: Three-Layer Architecture, Service-Oriented Based Architecture (SoA), and The Middleware-Based IoT Architecture. Depending on the required services, different IoT architecture are being used. In addition, IoT healthcare services, IoT healthcare service enablers, IoT healthcare applications, and IoT healthcare services focusing on Smartwatch …

English-To-Ipa Transcription, Riley Roberts

Undergraduate Honors Capstone Projects

The purpose of this project was to create a tool that could automate English-to-IPA (International Phonetic Alphabet) transcription. Research was done to determine what would be required to perform such a transcription. After researching and experimenting with existing tools, it was determined that developing the signal processing and Artificial Intelligence model portion of the application would be too intensive to successfully complete within the timeframe of this project.

The choice was made to develop an iOS application, with the Python library Allosaurus used to do the speech processing and as the Artificial Intelligence model. This model was then deployed in …

The Network Link Outlier Factor (Nlof) For Localizing Network Faults, Christopher Mendoza

Open Access Theses & Dissertations

This work presents the Network Link Outlier Factor (NLOF), a data analytics pipeline for network fault detection and localization solution that consists of four stages. In the first stage, flow record throughput values are clustered in two sub-stages: using Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and then a novel domain-specific ThroughPut Cluster (TPCluster) technique. In the second stage, Flow Outlier Factor (FOF) scores are computed for each flow. In the third stage, flows are traced onto the network. Finally, in the fourth stage, each link is given a Network Link Outlier Factor (NLOF) score which is the ratio …

Addressing Security And Privacy Issues By Analyzing Vulnerabilities In Iot Applications, Francsico Javier Candelario Burgoa

Open Access Theses & Dissertations

The Internet of Things (IoT) environment has been expanding rapidly for the past few years into several areas of our lives, from factories, to stores and even into our own homes. All these new devices in our homes make our day-to-day lives easier and more comfortable with less effort on our part, converting our simple houses into smart homes. This increase in inter-connectivity brings multiple benefits including the improvement in energy efficiency in our homes, however it also brings with it some potential dangers since more points of connection mean more potential vulnerabilities in our grid. These vulnerabilities bring security …

Machine Learning For Unmanned Aerial System (Uas) Networking, Jian Wang

Doctoral Dissertations and Master's Theses

Fueled by the advancement of 5G new radio (5G NR), rapid development has occurred in many fields. Compared with the conventional approaches, beamforming and network slicing enable 5G NR to have ten times decrease in latency, connection density, and experienced throughput than 4G long term evolution (4G LTE). These advantages pave the way for the evolution of Cyber-physical Systems (CPS) on a large scale. The reduction of consumption, the advancement of control engineering, and the simplification of Unmanned Aircraft System (UAS) enable the UAS networking deployment on a large scale to become feasible. The UAS networking can finish multiple complex …

Deep Learning Based Speech Enhancement And Its Application To Speech Recognition, Ju Lin

All Dissertations

Speech enhancement is the task that aims to improve the quality and the intelligibility of a speech signal that is degraded by ambient noise and room reverberation. Speech enhancement algorithms are used extensively in many audio- and communication systems, including mobile handsets, speech recognition, speaker verification systems and hearing aids. Recently, deep learning has achieved great success in many applications, such as computer vision, nature language processing and speech recognition. Speech enhancement methods have been introduced that use deep-learning techniques, as these techniques are capable of learning complex hierarchical functions using large-scale training data. This dissertation investigates the deep learning …

Approaches To Improve The Execution Time Of A Quantum Network Simulation, Joseph B. Tippit

Theses and Dissertations

Evaluating quantum networks is an expensive and time-consuming task that benefits from simulation. A potential improvement is to utilize GPUs, namely by leveraging NVIDIA's programming framework, CUDA. To avoid performance pitfalls of higher level languages and programming models such as the so called "two language problem," the Julia Programming Language provides the basis for the development effort. This research develops a two module prototype quantum network simulation framework using GPUs and Julia. Performance of the software is measured and compared against other languages such as MATLAB.

A Testing And Experimenting Environment For Microscopic Traffic Simulation Utilizing Virtual Reality And Augmented Reality, Mahmud Hasan

Computational Modeling & Simulation Engineering Theses & Dissertations

Microscopic traffic simulation (MTS) is the emulation of real-world traffic movements in a virtual environment with various traffic entities. Typically, the movements of the vehicles in MTS follow some predefined algorithms, e.g., car-following models, lane changing models, etc. Moreover, existing MTS models only provide a limited capability of two- and/or three-dimensional displays that often restrict the user’s viewpoint to a flat screen. Their downscaled scenes neither provide a realistic representation of the environment nor allow different users to simultaneously experience or interact with the simulation model from different perspectives. These limitations neither allow the traffic engineers to effectively disseminate their …

Data-Driven Operational And Safety Analysis Of Emerging Shared Electric Scooter Systems, Qingyu Ma

Computational Modeling & Simulation Engineering Theses & Dissertations

The rapid rise of shared electric scooter (E-Scooter) systems offers many urban areas a new micro-mobility solution. The portable and flexible characteristics have made E-Scooters a competitive mode for short-distance trips. Compared to other modes such as bikes, E-Scooters allow riders to freely ride on different facilities such as streets, sidewalks, and bike lanes. However, sharing lanes with vehicles and other users tends to cause safety issues for riding E-Scooters. Conventional methods are often not applicable for analyzing such safety issues because well-archived historical crash records are not commonly available for emerging E-Scooters.

Perceiving the growth of such a micro-mobility …

Generation, Analysis, And Evaluation Of Patient-Specific, Osteoligamentous, Spine Meshes, Austin R. Tapp

Biomedical Engineering Theses & Dissertations

Scoliosis, an abnormal curvature of the spine, is traditionally corrected with bracing treatments or by a highly invasive posterior spinal fusion (PSF) operation. These correction strategies are constrained by current imaging modalities, which fail to elucidate the soft tissue anatomy that is known to play a critical role in spinal stiffness and overall structure. Osteoligamentous segmentations of the spinal column offer a foundation for downstream finite element (FE) studies seeking to optimize bracing treatments or determine ideal surgical approaches.

This thesis presents methods for automatically and semi-automatically segmenting vertebrae and surrounding soft tissues of the spinal column using X-ray computed …

Towards Characterizing Adversarial Opportunity And Behavior In Critical Infrastructure Network, Md Sharif Ullah

Electrical & Computer Engineering Theses & Dissertations

The growth of information and communication technology is constantly revolutionizing various domains, e.g., energy utility systems, healthcare, the internet of things, etc. This inception of widespread cyber technology enables reliability and first operability of the system, yet simultaneously imposed a risk of significant impact due to disruption of safe and secure operation. The attack surface is expanding, creating a cyber exposure gap which indicates a higher threat landscape and increased risk of compromise. Motivated by this increased threat exposure, this dissertation investigates the attack surface as a static and dynamic indicator of adversary propagation, seeking an efficient modeling paradigm to …

Joint Linear And Nonlinear Computation With Data Encryption For Efficient Privacy-Preserving Deep Learning, Qiao Zhang

Electrical & Computer Engineering Theses & Dissertations

Deep Learning (DL) has shown unrivalled performance in many applications such as image classification, speech recognition, anomalous detection, and business analytics. While end users and enterprises own enormous data, DL talents and computing power are mostly gathered in technology giants having cloud servers. Thus, data owners, i.e., the clients, are motivated to outsource their data, along with computationally-intensive tasks, to the server in order to leverage the server’s abundant computation resources and DL talents for developing cost-effective DL solutions. However, trust is required between the server and the client to finish the computation tasks (e.g., conducting inference for the newly-input …

Let's Read: Designing A Smart Display Application To Support Codas When Learning Spoken Language, Katie Rodeghiero, Yingying Yuki Chen, Annika M. Hettmann, Franceli L. Cibrian

Engineering Faculty Articles and Research

Hearing children of Deaf adults (CODAs) face many challenges including having difficulty learning spoken languages, experiencing social judgment, and encountering greater responsibilities at home. In this paper, we present a proposal for a smart display application called Let's Read that aims to support CODAs when learning spoken language. We conducted a qualitative analysis using online community content in English to develop the first version of the prototype. Then, we conducted a heuristic evaluation to improve the proposed prototype. As future work, we plan to use this prototype to conduct participatory design sessions with Deaf adults and CODAs to evaluate the …

Digital Markers Of Autism, Ivonne Monarca, Franceli L. Cibrian, Monica Tentori

Engineering Faculty Articles and Research

Autism Spectrum Disorder (ASD) is a neurological condition that affects how a people communicate and interact with others. The use of screening tools during childhood is very important to detect those children who need to be referred for a diagnosis of ASD. However, most screening tools are based on parents' responses so the result can be subjective. In addition, most screening tools focus on social and communicative skills leaving aside sensory features, which have shown to have the potential to be ASD markers. Tactile processing has been little explored due to lack of tools to asses it, however with the …

Feel And Touch: A Haptic Mobile Game To Assess Tactile Processing, Ivonne Monarca, Monica Tentori, Franceli L. Cibrian

Engineering Faculty Articles and Research

Haptic interfaces have great potential for assessing the tactile processing of children with Autism Spectrum Disorder (ASD), an area that has been under-explored due to the lack of tools to assess it. Until now, haptic interfaces for children have mostly been used as a teaching or therapeutic tool, so there are still open questions about how they could be used to assess tactile processing of children with ASD. This article presents the design process that led to the development of Feel and Touch, a mobile game augmented with vibrotactile stimuli to assess tactile processing. Our feasibility evaluation, with 5 children …

Deepfakes Generated By Generative Adversarial Networks, Olympia A. Paul

Honors College Theses

Deep learning is a type of Artificial Intelligence (AI) that mimics the workings of the human brain in processing data such as speech recognition, visual object recognition, object detection, language translation, and making decisions. A Generative adversarial network (GAN) is a special type of deep learning, designed by Goodfellow et al. (2014), which is what we call convolution neural networks (CNN). How a GAN works is that when given a training set, they can generate new data with the same information as the training set, and this is often what we refer to as deep fakes. CNN takes an input …

Plasmonic Field-Effect Transistors (Terafets) For 6g Communications, Michael Shur, Gregory Aizin, Taiichi Otsuji, Victor Ryzhii

Publications and Research

Ever increasing demands of data traffic makes the transition to 6G communications in the 300 GHz band inevitable. Short-channel field-effect transistors (FETs) have demonstrated excellent potential for detection and generation of terahertz (THz) and sub-THz radiation. Such transistors (often referred to as TeraFETs) include short-channel silicon complementary metal oxide (CMOS). The ballistic and quasi-ballistic electron transport in the TeraFET channels determine the TeraFET response at the sub-THz and THz frequencies. TeraFET arrays could form plasmonic crystals with nanoscale unit cells smaller or comparable to the electron mean free path but with the overall dimensions comparable with the radiation wavelength. Such …

An Adaptive Hybrid Genetic-Annealing Approach For Solving The Map Problem On Belief Networks, Manar Hosny

Archived Theses and Dissertations

No abstract provided.

Ggnb: Graph-Based Gaussian Naive Bayes Intrusion Detection System For Can Bus, Riadul Islam, Maloy K. Devnath, Manar D. Samad, Syed Md Jaffrey Al Kadry

Computer Science Faculty Research

The national highway traffic safety administration (NHTSA) identified cybersecurity of the automobile systems are more critical than the security of other information systems. Researchers already demonstrated remote attacks on critical vehicular electronic control units (ECUs) using controller area network (CAN). Besides, existing intrusion detection systems (IDSs) often propose to tackle a specific type of attack, which may leave a system vulnerable to numerous other types of attacks. A generalizable IDS that can identify a wide range of attacks within the shortest possible time has more practical value than attack-specific IDSs, which is not a trivial task to accomplish. In this …

Real-Time Bidding Campaigns Optimization Using User Profile Settings, Luis Miralles-Pechuán, Muhammad Atif Qureshi, Brian Mac Namee

Articles

Real-time bidding is nowadays one of the most promising systems in the online advertising ecosystem. In this study, the performance of RTB campaigns is improved by optimising the parameters of the users' profiles and the publishers' websites. Most studies concerning optimising RTB campaigns are focused on the bidding strategy, i.e., estimating the best value for each bid. However, this research focuses on optimising RTB campaigns by finding out configurations that maximise both the number of impressions and the average profitability of the visits. An online campaign configuration generally consists of a set of parameters along with their values such as …