Computer Engineering Commons^™

Drone Path Scheduling For Data Gathering In Disaster Effected Environments, James Bologna

Theses and Dissertations

Creative networks in a disaster effected area have been a concern for a long time. With the innovation of flying ad hoc networks the problem can be tackled from a more practical standpoint. The use of low altitude drones equipped with wireless transmission and receiving capability can be used under the circumstances to enable ad-hoc communication. Drone coordination and route planning is a critical consideration when determining how to gather data from ground nodes, since the drones are constrained by limited battery capacity. In this research, we set out to explore a wide range of policies for determining the trajectories …

3d Printed Smart Mobile, Bingfang Chen

Publications and Research

The goal of this research project is to design and build a prototype of a smart mobile robot to participate and compete in IEEE Micro-mouse and similar competitions. The robot has to find its way out of a maze as quickly as possible, by exploring and learning the paths in the maze. 3D printing technology will be used to build a lightweight robot frame so that it can move at a fast speed.

Fashion Merchandising: An Augmented Reality, Naeha A. Sayed

Dissertations, Theses, and Capstone Projects

There is a continuous and constant transformation in the field of Augmented Reality (AR), both in the Retail, and the Manufacturing sector. It has started to influence everything from fashion runway shows to online shopping. Consumers dynamics have shifted in the fashion industry, the ways becoming more dominant than the old observant ones- the simple buying experience no longer satisfies them. Due to the emergence of the new digital platforms and technological enhancements, the consumers are looking for more- be it a more exciting buying experience or more user interaction or more enhanced products. This technological change starts with the …

Incentivizing Collaboration In A Competition, Arunesh Sinha, Michael P. Wellman

Research Collection School Of Computing and Information Systems

Research and design competitions aim to promote innovation or creative production, which are often best achieved through collaboration. The nature of a competition, however, typically necessitates sorting by individual performance. This presents tradeoffs for the competition designer, between incentivizing global performance and distinguishing individual capability. We model this situation in terms of an abstract collaboration game, where individual effort also benefits neighboring agents. We propose a scoring mechanism called LSWM that rewards agents based on localized social welfare. We show that LSWM promotes global performance, in that social optima are equilibria of the mechanism. Moreover, we establish conditions under which …

Emerging App Issue Identification From User Feedback: Experience On Wechat, Cuiyun Gao, Wujie Zheng, Yuetang Deng, David Lo, Jichuan Zeng, Michael R. Lyu, Irwin King

Research Collection School Of Computing and Information Systems

It is vital for popular mobile apps with large numbers of users to release updates with rich features while keeping stable user experience. Timely and accurately locating emerging app issues can greatly help developers to maintain and update apps. User feedback (i.e., user reviews) is a crucial channel between app developers and users, delivering a stream of information about bugs and features that concern users. Methods to identify emerging issues based on user feedback have been proposed in the literature, however, their applicability in industry has not been explored. We apply the recent method IDEA to WeChat, a popular messenger …

Characterization Of Rf Signal Propagation For Wireless Sensor Network Deployed In Mountainous Environment, Bandar Mohammad Alshawi

Theses and Dissertations

Wireless sensor network (WSN) nodes, in mountainous forests, report real-time data to base stations concerning events, in which researchers and decision makers are interested in. A thorough research reveals the deficiency of any study modeling radio frequency (RF) in that environment. The lack of accurately modeling RF signal propagation in any environment can have a great impact on the network life, connectivity, and coverage. This dissertation models the loss of RF signal in the mountainous environment and demonstrates the inconsistency of theoretical models, compared to actual measurements. The models proposed in this research yield satisfactory results, and the theoretical models …

Formal Trust Architecture For Assuring Trusted Interactions In The Internet Of Things, Milankumar Patel

Theses and Dissertations

The Internet of Things (IoT) has provided a flexible platform for a large number of heterogeneous devices to dynamically join and leave the network. This enhances the availability of a diverse range of services provided by a network. However, this dynamic expansion of the network with mobile IoT devices introduces a major challenge to security especially related to management of trust across the IoT platforms. Furthermore, IoT is open and distributed in nature, which allows the integration and registration of diverse entities. Thus arises the necessity for a mechanism that can ensure the selection of secure and trusted devices as …

Image Processing Algorithms For Elastin Lamellae Inside Cardiovascular Arteries, Mahmoud Habibnezhad

School of Computing: Dissertations, Theses, and Student Research

Automated image processing methods are greatly needed to replace the tedious, manual histology analysis still performed by many physicians. This thesis focuses on pathological studies that express the essential role of elastin lamella in the resilience and elastic properties of the arterial blood vessels. Due to the stochastic nature of the shape and distribution of the elastin layers, their morphological features appear as the best candidates to develop a mathematical formulation for the resistance behavior of elastic tissues. However, even for trained physicians and their assistants, the current measurement procedures are highly error-prone and prolonged. This thesis successfully integrates such …

Analysis Of Bitcoin Cryptocurrency And Its Mining Techniques, Suman Ghimire

UNLV Theses, Dissertations, Professional Papers, and Capstones

Bitcoin is a peer-to-peer digital, decentralized cryptocurrency created by an individual under pseudonym Satoshi Nakamoto. In fact, it is the first digital, decentralized currency. Several developers and organizations have explored the importance of digital cryptocurrency and the concept of the blockchain. Bitcoin is assumed to be one of the secure and comfortable payment methods that can be used in the upcoming days. The backbone of Bitcoin mining is the concept of the blockchain, which is assumed to beone of the ingenious invention of this century. The blockchain is the collection of blocks that are linked together in such a way …

Multi-Resolution Spatio-Temporal Change Analyses Of Hydro-Climatological Variables In Association With Large-Scale Oceanic-Atmospheric Climate Signals, Kazi Ali Tamaddun

UNLV Theses, Dissertations, Professional Papers, and Capstones

The primary objective of the work presented in this dissertation was to evaluate the change patterns, i.e., a gradual change known as the trend, and an abrupt change known as the shift, of multiple hydro-climatological variables, namely, streamflow, snow water equivalent (SWE), temperature, precipitation, and potential evapotranspiration (PET), in association with the large-scale oceanic-atmospheric climate signals. Moreover, both observed datasets and modeled simulations were used to evaluate such change patterns to assess the efficacy of the modeled datasets in emulating the observed trends and shifts under the influence of uncertainties and inconsistencies. A secondary objective of this study was to …

Segmentation And Classification Of Lung Nodules From Thoracic Ct Scans : Methods Based On Dictionary Learning And Deep Convolutional Neural Networks., Mohammad Mehdi Farhangi

Electronic Theses and Dissertations

Lung cancer is a leading cause of cancer death in the world. Key to survival of patients is early diagnosis. Studies have demonstrated that screening high risk patients with Low-dose Computed Tomography (CT) is invaluable for reducing morbidity and mortality. Computer Aided Diagnosis (CADx) systems can assist radiologists and care providers in reading and analyzing lung CT images to segment, classify, and keep track of nodules for signs of cancer. In this thesis, we propose a CADx system for this purpose. To predict lung nodule malignancy, we propose a new deep learning framework that combines Convolutional Neural Networks (CNN) and …

Multimodal Emotion Classification, Anurag Illendula, Amit Sheth

Publications

Most NLP and Computer Vision tasks are limited to scarcity of labelled data. In social media emotion classification and other related tasks, hashtags have been used as indicators to label data. With the rapid increase in emoji usage of social media, emojis are used as an additional feature for major social NLP tasks. However, this is less explored in case of multimedia posts on social media where posts are composed of both image and text. At the same time, w.e have seen a surge in the interest to incorporate domain knowledge to improve machine understanding of text. In this paper, …

Knowledge-Aware Assessment Of Severity Of Suicide Risk For Early Intervention, Manas Gaur, Amanuel Alambo, Joy Prakash Sain, Ugur Kursuncu, Krishnaprasad Thirunarayan, Ramakanth Kavuluru, Amit Sheth, Randon S. Welton, Jyotishman Pathak

Publications

Mental health illness such as depression is a significant risk factor for suicide ideation, behaviors, and attempts. A report by Substance Abuse and Mental Health Services Administration (SAMHSA) shows that 80% of the patients suffering from Borderline Personality Disorder (BPD) have suicidal behavior, 5-10% of whom commit suicide. While multiple initiatives have been developed and implemented for suicide prevention, a key challenge has been the social stigma associated with mental disorders, which deters patients from seeking help or sharing their experiences directly with others including clinicians. This is particularly true for teenagers and younger adults where suicide is the second …

Classification Of The 4 Stages Of Diabetic Retinopathy Using A Low Complexity Convolutional Neural Network., Zeliha Ogur

Electronic Theses and Dissertations

Diabetic Retinopathy is an eye disease that affects the blood vessels of the retina tissue found in the back of the eye. The blood vessels in the retina discharge fluid or cause hemorrhage when affected by diabetic retinopathy. It leads to loss of eye vision with people with diabetics and also among working adults. The disease may advance in four stages which include Mild nonproliferative, moderate nonproliferative, severe nonproliferative and proliferative diabetic retinopathy. In the mild stage also known as background retinopathy, lumps occur in the blood vessel and distort a little amount of blood. At this stage, you are …

Asynchronous Circuit Synthesis Using Multi-Threshold Null Convention Logic, Nicholas Renoudet Mize

Graduate Theses and Dissertations

As the demand for an energy-efficient alternative to traditional synchronous circuit design grows, hardware designers must reconsider the traditional clock tree. By doing away with the constrains of a clock, asynchronous sequential circuit designs can achieve a much greater level of efficiency. The utilization of asynchronous logic synthesis flows has enabled researchers to better implement asynchronous circuit designs which have been optimized using the same industry standard tools that are already used in sequential synchronous designs. This thesis offers a new flow for such tools which implements the MTNCL asynchronous circuit architecture.

Towards A Prototype Platform For Ros Integrations On A Ground Robot, Taylor Joseph Linville Whitaker

Graduate Theses and Dissertations

The intent of this work was to develop, evaluate, and demonstrate a prototype robot platform on which ROS integrations could be explored. With observations of features and requirements of existing industrial and service mobile ground robots, a platform was designed and outfitted with appropriate components to enable the most common operational-critical functionalities and account for unforeseen components and features. The resulting Arlo Demonstration Robot accommodates basic mapping, localization, and navigation in both two and three-dimensional space as well as additional safety and teleoperation features. The control system is centered around the Zybo Z7 FPGA SoC hosting a custom hardware design. …

Enhanced Security System With Image Feature Identification, Musharrat Chowdhury

Publications and Research

Open source hardware and software will be used to acquire camera images and recognize and identify objects of interest in the image that would be used in new or existing personal security system. The mechanism of this system rotates either automatically or manually to track a face when a human is within view of the camera. The biometric security recognition system is a real world applications with complex effects of illumination and imaging conditions on live images.

Wavelet–Based Functional Data Analysis For Classification And Change Point Detection, Nenad Mijatovic

Theses and Dissertations

Data collection and analysis, performed close to the source and transferred to other devices for different analysis, are the major paradigms of the Internet of Things (IoT). Usually, the raw data comes in the form of a time-series sequence that can be considered as functions, and as such can be examined by the functional analysis apparatus. Among others, the two major tasks in data analysis are (1) categorical signal classification and (2) change detection in signal statistical parameters. Here, we study both problems: featureless signal classification using discriminative interpolation regularized with the ℓ1 norm is performed using Classification by Discriminative …

A Purely Defeasible Argumentation Framework, Zimi Li

Dissertations, Theses, and Capstone Projects

Argumentation theory is concerned with the way that intelligent agents discuss whether some statement holds. It is a claim-based theory that is widely used in many areas, such as law, linguistics and computer science. In the past few years, formal argumentation frameworks have been heavily studied and applications have been proposed in fields such as natural language processing, the semantic web and multi-agent systems. Studying argumentation provides results which help in developing tools and applications in these areas. Argumentation is interesting as a logic-based approach to deal with inconsistent information. Arguments are constructed using a process like logical inference, with …

Cure: Flexible Categorical Data Representation By Hierarchical Coupling Learning, Songlei Jian, Guansong Pang, Longbing Cao, Kai Lu, Hang Gao

Research Collection School Of Computing and Information Systems

The representation of categorical data with hierarchical value coupling relationships (i.e., various value-to-value cluster interactions) is very critical yet challenging for capturing complex data characteristics in learning tasks. This paper proposes a novel and flexible coupled unsupervised categorical data representation (CURE) framework, which not only captures the hierarchical couplings but is also flexible enough to be instantiated for contrastive learning tasks. CURE first learns the value clusters of different granularities based on multiple value coupling functions and then learns the value representation from the couplings between the obtained value clusters. With two complementary value coupling functions, CURE is instantiated into …

Designated-Server Identity-Based Authenticated Encryption With Keyword Search For Encrypted Emails, Hongbo Li, Qiong Huang, Jian Shen, Guomin Yang, Willy Susilo

Research Collection School Of Computing and Information Systems

In encrypted email system, how to search over encrypted cloud emails without decryption is an important and practical problem. Public key encryption with keyword search (PEKS) is an efficient solution to it. However, PEKS suffers from the complex key management problem in the public key infrastructure. Its variant in the identity-based setting addresses the drawback, however, almost all the schemes does not resist against offline keyword guessing attacks (KGA) by inside adversaries. In this work we introduce the notion of designated-server identity-based authenticated encryption with keyword search (dIBAEKS), in which the email sender authenticates the message while encrypting so that …

Unicorn Framework: A User-Centric Approach Toward Formal Verification Of Privacy Norms, Rezvan Joshaghani

Boise State University Theses and Dissertations

In the development of complex systems, such as user-centric privacy management systems with multiple components and attributes, it is important to formalize the process and develop mathematical models that can be utilized to automatically make decisions on the information sharing actions of users. While valuable, the current state-of-the-art models are mostly based on enterprise/organizational privacy perspectives and leave the main actor, i.e., the user, uninvolved or with limited ability to control information sharing actions. These approaches cannot be applied to a user-centric environment since user privacy policies are dynamic because they change based on the information sharing context and environment. …

Towards Fully Additively-Manufactured Permanent Magnet Synchronous Machines: Opportunities And Challenges, Fan Wu, Ayman M. El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

With the growing interest in electrification and as hybrid and pure electric powertrains are adopted in more applications, electrical machine design is facing challenges in terms of meeting very demanding performance metrics for example high specific power, harsh environments, etc. This provides clear motivation to explore the impact of advanced materials and manufacturing on the performance of electrical machines. This paper provides an overview of additive manufacturing (AM) approaches that can be used for constructing permanent magnet (PM) machines, with a specific focus on additively-manufactured iron core, winding, insulation, PM as well as cooling systems. Since there has only been …

Survey Of Insulation Systems In Electrical Machines, Rasul Hemmati, Fan Wu, Ayman M. El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

Insulating materials and insulation systems design have been gaining more attentions as more electrical machines tend to operate in harsher environments for various applications. Harsh environments include high temperature, humidity, erosion, low air pressure, etc. This paper discusses recent advances in insulation systems for electrical machines. Insulation tests as well as test standards that have been used to evaluate insulation systems and detect insulation failures will be discussed. Insulating materials used for a wide range of industrial applications such as wind turbine generators, aerospace hybrid/electric powertrain, and hydro generators have been summarized. For the emerging high-altitude, highvoltage aerospace applications, partial …

A Survey Of Prediction And Classification Techniques In Multicore Processor Systems, Cristinel Ababei, Milad Ghorbani Moghaddam

Electrical and Computer Engineering Faculty Research and Publications

In multicore processor systems, being able to accurately predict the future provides new optimization opportunities, which otherwise could not be exploited. For example, an oracle able to predict a certain application's behavior running on a smart phone could direct the power manager to switch to appropriate dynamic voltage and frequency scaling modes that would guarantee minimum levels of desired performance while saving energy consumption and thereby prolonging battery life. Using predictions enables systems to become proactive rather than continue to operate in a reactive manner. This prediction-based proactive approach has become increasingly popular in the design and optimization of integrated …

Quantitative Detection Of Complex Mixtures Using A Single Chemical Sensor: Analysis Of Response Transients Using Multi-Stage Estimation, Karthick Sothivelr, Florian Bender, Fabien Josse, Edwin E. Yaz, Antonio J. Ricco

Electrical and Computer Engineering Faculty Research and Publications

Most chemical sensors are only partially selective to any specific target analyte(s), making identification and quantification of analyte mixtures challenging, a problem often addressed using arrays of partially selective sensors. This work presents and experimentally verifies a signal-processing technique based on estimation theory for online identification and quantification of multiple analytes using only the response data collected from a single polymer-coated sensor device. The demonstrated technique, based on multiple stages of exponentially weighted recursive least-squares estimation (EW-RLSE), first determines which of the analytes included in the sensor response model are absent from the mixture being analyzed; these are then eliminated …

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

Computer Information Technology 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 …

Public Blockchain Scalability: Advancements, Challenges And The Future, Amritraj .

Master of Science in Software Engineering Theses

In the last decade, blockchain has emerged as one of the most influential innovations in software architecture and technology. Ideally, blockchains are designed to be architecturally and politically decentralized, similar to the Internet. But recently, public and permissionless blockchains such as Bitcoin and Ethereum have faced stumbling blocks in the form of scalability. Both Bitcoin and Ethereum process fewer than 20 transactions per second, which is significantly lower than their centralized counterpart such as VISA that can process approximately 1,700 transactions per second. In realizing this hindrance in the wide range adoption of blockchains for building advanced and large scalable …

Design And Creation Of A System Of Machines To Automate Quality Control Processes For Atms, Miguel D. Pedrozo

Undergraduate Distinction Papers

This project is based around the quality control processes used to test ATMs. Currently, a person will manually run through each function of the ATM in order to find modes of failure. As the case with all repetitive jobs, it is an unwanted task and is simple enough to be automated. The new solution I propose allows for a system of devices to operate the functions of the ATM autonomously with little to no human intervention. Additionally, this solution is more reliable when diagnosing a problem as it will eventually communicate with the ATM directly in a closed loop system …

Predicting Unethical Physician Behavior At Scale: A Distributed Computing Framework, Quinn Keck, Robert Sandor, Miguel Romero, Diane Woodbridge, Paul Intrevado

Creative Activity and Research Day - CARD

As the amount of publicly shared data increases,

developing a robust pipeline to stream, store and process data is

critical, as the casual user often lacks the technology, hardware

and/or skills needed to work with such voluminous data. In

this research, the authors employ Amazon EC2 and EMR,

MongoDB, and Spark MLlib to explore 28.5 gigabytes of CMS

Open Payments data in an attempt to identify physicians who

may have a high propensity to act unethically, owing to significant

transfers of wealth from medical companies. A Random Forest

Classifier is employed to predict the top decile of physicians who

have …