Computer Engineering Commons^™

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.

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 …

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 …

Efficient Private Information Retrieval, Konstantinos Nikolopoulos

Dissertations, Theses, and Capstone Projects

A vast amount of today's Internet users' on line activities consists of queries to various types of databases. From traditional search engines to modern cloud based services, a person's everyday queries over a period of time on various data sources, will leave a trail visible to the query processor, which can reveal significant and possibly sensitive information about her. Private Information Retrieval (PIR) algorithms can be leveraged for providing perfect privacy to users' queries, though at a restrictive computational cost. In this work, we consider today's highly distributed computing environments, as well as certain secure-hardware devices, for optimizing existing PIR …

Compliance Of Open Source Ehr Applications With Hipaa And Onc Security And Privacy Requirements, Maryam Farhadi, Hisham Haddad, Hossain Shahriar

Master of Science in Computer Science Theses

Electronic Health Records (EHRs) are digital versions of paper-based patient's health information. EHR applications are increasingly being adopted in many countries. They have resulted in improved quality in healthcare, convenient access to histories of patient medication and clinic visits, easier follow up of patient treatment plans, and precise medical decision-making process. EHR applications are guided by measures of the Health Insurance Portability and Accountability Act (HIPAA) to ensure confidentiality, integrity, and availability. However, there have been reported breaches of Protected Health Identifier (PHI) data stored by EHR applications. In many reported breaches, improper use of EHRs has resulted in disclosure …

The Use Of Generic Scripting In Certain Application Development Projects, Vance Allen Etnyre, Jian Denny Lin, Nanfei Sun

Journal of International Technology and Information Management

This article discusses generic scripting, a useful scripting technology for developing applications. In its simplest use, generic scripting can be used as a documentation tool to replace flowcharting or pseudocode. in certain situations, generic scripting can lead directly to a working application without the need to write, compile and test a new program. Generic scripting is discussed as a tool which can be used in logical design, detailed design and implementation of a new application. An example is presented to show how generic scripting can be used by non-programmers to simplify the development of applications. This example is used to …

College Choice Criteria Utilizing Conjoint Analysis Enabled On A Saas Platform, Alison Munsch

Journal of International Technology and Information Management

College enrollments and low to moderate household incomes are stagnating while tuition costs are increasing. The New York State Legislature enacted the nation’s first tuition-free degree program, the Excelsior Scholarship, designed to make a college education more affordable to middle class families. This legislation can impact what institution of higher education students will choose upon high school graduation. In order to understand the choice criteria for selecting an institution of higher education, a research study was conducted among a representative sample of high school upper classmen and parents of this respondent segment. The data collection and analysis were accomplished using …

An Explainable Sequence-Based Deep Learning Predictor With Applications To Song Recommendation And Text Classification., Khalil Damak

Electronic Theses and Dissertations

Streaming applications are now the predominant tools for listening to music. What makes the success of such software is the availability of songs and especially their ability to provide users with relevant personalized recommendations. 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 (listening to a song) using a memory-based deep learning structure that learns from temporal sequences of user actions. Despite advances in deep learning models for song recommendation systems, none has taken …

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.

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 …

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 …

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 …

Paper Prototyping Comfortable Vr Play For Diverse Sensory Needs, Louanne E. Boyd, Kendra Day, Ben Wasserman, Kaitlyn Abdo, Gillian Hayes, Erik J. Linstead

Engineering Faculty Articles and Research

We co-designed paper prototype dashboards for virtual environments for three children with diverse sensory needs. Our goal was to determine individual interaction styles in order to enable comfortable and inclusive play. As a first step towards an inclusive virtual world, we began with designing for three sensory-diverse children who have labels of neurotypical, ADHD, and autism respectively. We focused on their leisure interests and their individual sensory profiles. We present the results of co-design with family members and paper prototyping sessions conducted by family members with the children. The results contribute preliminary empirical findings for accommodating different levels of engagement …

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, …

Modeling Of Complex Parts For Industrial Waterjet Cleaning, Braden James

Graduate Theses and Dissertations

Industrial high-pressure waterjet cleaning is common to many industries. The modeling in this paper functions inside a collaborative robotic framework for high mix, low volume processes where human robot collaboration is beneficial. Automation of pressure washing is desirable for economic and ergonomic reasons. An automated cleaning system needs path simulation and analysis to give the operator insight into the predicted cleaning performance of the system. In this paper, ablation, the removal of a substrate coating by waterjet, is modeled for robotic cleaning operations. The model is designed to work with complex parts often found in spray cleaning operations, namely parts …

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 …

University Of Rhode Island Course Information Assistant, Daniel Gauthier

Senior Honors Projects

Personal voice-interactive systems have become ubiquitous in daily life. There are many of these digital assistants such as Siri, Alexa, and Google Assistant. The chances are high you have access to one right now. This technology has reached a point where the context of a conversation can be maintained, which is a vast improvement over earlier technology. Interactions without conversational context can limit interactions greatly and this was the case for previous digital assistants. Every time someone would say something to an assistant, it was like they were constantly changing operators on a customer service line. The assistants can now …

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 …

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 …

Community Discovery In Heterogeneous Social Networks, Lei Meng, Ah-Hwee Tan, Donald C. Wunsch

Research Collection School Of Computing and Information Systems

Discovering social communities of web users through clustering analysis of heterogeneous link associations has drawn much attention. However, existing approaches typically require the number of clusters a priori, do not address the weighting problem for fusing heterogeneous types of links, and have a heavy computational cost. This chapter studies the commonly used social links of users and explores the feasibility of the proposed heterogeneous data co-clustering algorithm GHF-ART, as introduced in Sect. 3.6, for discovering user communities in social networks. Contrary to the existing algorithms proposed for this task, GHF-ART performs real-time matching of patterns and one-pass learning, which guarantees …

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 …

Debiasing The Human-Recommender System Feedback Loop In Collaborative Filtering, Wenlong Sun, Sami Khenissi, Olfa Nasraoui, Patrick Shafto

Faculty and Staff Scholarship

Recommender Systems (RSs) are widely used to help online users discover products, books, news, music, movies, courses, restaurants,etc. Because a traditional recommendation strategy always shows the most relevant items (thus with highest predicted rating), traditional RS’s are expected to make popular items become even more popular and non-popular items become even less popular which in turn further divides the haves (popular) from the have-nots (un-popular). Therefore, a major problem with RSs is that they may introduce biases affecting the exposure of items, thus creating a popularity divide of items during the feedback loop that occurs with users, and this may …

Comparison Of Lqr And Lqr-Mrac For Linear Tractor-Trailer Model, Kevin Richard Gasik

Master's Theses

The United States trucking industry is immense. Employing over three million drivers and traveling to every city in the country. Semi-Trucks travel millions of miles each week and encompass roads that civilians travel on. These vehicles should be safe and allow efficient travel for all. Autonomous vehicles have been discussed in controls for many decades. Now fleets of autonomous vehicles are beginning their integration into society. The ability to create an autonomous system requires domain and system specific knowledge. Approaches to implement a fully autonomous vehicle have been developed using different techniques in control systems such as Kalman Filters, Neural …

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 …

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 …

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 …

The Affective Perceptual Model: Enhancing Communication Quality For Persons With Pimd, Jadin Tredup

UNLV Theses, Dissertations, Professional Papers, and Capstones

Methods for prolonged compassionate care for persons with Profound Intellectual and Multiple Disabilities (PIMD) require a rotating cast of import people in the subjects life in order to facilitate interaction with the external environment. As subjects continue to age, dependency on these people increases with complexity of communications while the quality of communication decreases. It is theorized that a machine learning (ML) system could replicate the attuning process and replace these people to promote independence. This thesis extends this idea to develop a conceptual and formal model and system prototype.

The main contributions of this thesis are: (1) proposal of …

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. …

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 …