Computer Engineering Commons^™

Machine Learning For Analog/Mixed-Signal Integrated Circuit Design Automation, Weidong Cao

McKelvey School of Engineering Graduate Student Theses & Dissertations

Analog/mixed-signal (AMS) integrated circuits (ICs) play an essential role in electronic systems by processing analog signals and performing data conversion to bridge the analog physical world and our digital information world.Their ubiquitousness powers diverse applications ranging from smart devices and autonomous cars to crucial infrastructures. Despite such critical importance, conventional design strategies of AMS circuits still follow an expensive and time-consuming manual process and are unable to meet the exponentially-growing productivity demands from industry and satisfy the rapidly-changing design specifications from many emerging applications. Design automation of AMS IC is thus the key to tackling these challenges and has been …

Duck Hunt: Memory Forensics Of Usb Attack Platforms, Tyler Thomas, Mathew Piscitelli, Bhavik Ashok Nahar, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

To explore the memory forensic artifacts generated by USB-based attack platforms, we analyzed two of the most popular commercially available devices, Hak5's USB Rubber Ducky and Bash Bunny. We present two open source Volatility plugins, usbhunt and dhcphunt, which extract artifacts generated by these USB attacks from Windows 10 system memory images. Such artifacts include driver-related diagnostic events, unique device identifiers, and DHCP client logs. Our tools are capable of extracting metadata-rich Windows diagnostic events generated by any USB device. The device identifiers presented in this work may also be used to definitively detect device usage. Likewise, the DHCP logs …

Another Brick In The Wall: An Exploratory Analysis Of Digital Forensics Programs In The United States, Syria Mccullough, Stella Abudu, Ebere Onwubuariri, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

We present a comprehensive review of digital forensics programs offered by universities across the United States (U.S.). While numerous studies on digital forensics standards and curriculum exist, few, if any, have examined digital forensics courses offered across the nation. Since digital forensics courses vary from university to university, online course catalogs for academic institutions were evaluated to curate a dataset. Universities were selected based on online searches, similar to those that would be made by prospective students. Ninety-seven (n = 97) degree programs in the U.S. were evaluated. Overall, results showed that advanced technical courses are missing from curricula. We …

Data Management System For A Semiautonomous Shuttle Car For Underground Room And Pillar Coal Mines, Vasilis Androulakis, Steven Schafrik, Joseph Sottile, Zacharias Agioutantis

Mining Engineering Faculty Publications

In recent years, autonomous solutions in the multidisciplinary field of mining engineering have been an extremely popular applied research topic. This is a result of the increasing demands of society on mineral resources along with the accelerating exploitation of the currently economically viable resources, which lead the mining sector to turn to deeper, more-difficult-to-mine orebodies. An appropriate data management system comprises a crucial aspect of the designing and the engineering of a system that involves autonomous or semiautonomous vehicles. The vast volume of data collected from onboard sensors, as well as from a potential IoT network dispersed around a smart …

An Automated Method To Enrich Consumer Health Vocabularies Using Glove Word Embeddings And An Auxiliary Lexical Resource, Mohammed Ibrahim, Susan Gauch, Omar Salman, Mohammed Alqahtani

Computer Science and Computer Engineering Faculty Publications and Presentations

Background

Clear language makes communication easier between any two parties. A layman may have difficulty communicating with a professional due to not understanding the specialized terms common to the domain. In healthcare, it is rare to find a layman knowledgeable in medical terminology which can lead to poor understanding of their condition and/or treatment. To bridge this gap, several professional vocabularies and ontologies have been created to map laymen medical terms to professional medical terms and vice versa.

Objective

Many of the presented vocabularies are built manually or semi-automatically requiring large investments of time and human effort and consequently the …

Finding Bert’S Idiomatic Key, Vasudevan Nedumpozhimana, John Kelleher

Conference papers

Sentence embeddings encode information relating to the usage of idioms in a sentence. This paper reports a set of experiments that combine a probing methodology with input masking to analyse where in a sentence this idiomatic information is taken from, and what form it takes. Our results indicate that BERT’s idiomatic key is primarily found within an idiomatic expression, but also draws on information from the surrounding context. Also, BERT can distinguish between the disruption in a sentence caused by words missing and the incongruity caused by idiomatic usage.

Reducing Power During Manufacturing Test Using Different Architectures, Yi Sun

Computer Science and Engineering Theses and Dissertations

Power during manufacturing test can be several times higher than power consumption in functional mode. Excessive power during test can cause IR drop, over-heating, and early aging of the chips. In this dissertation, three different architectures have been introduced to reduce test power in general cases as well as in certain scenarios, including field test.

In the first architecture, scan chains are divided into several segments. Every segment needs a control bit to enable capture in a segment when new faults are detectable on that segment for that pattern. Otherwise, the segment should be disabled to reduce capture power. We …

Power-Over-Tether Unmanned Aerial System Leveraged For Trajectory Influenced Atmospheric Sensing, Daniel Rico

School of Computing: Dissertations, Theses, and Student Research

The use of unmanned aerial systems (UASs) in agriculture has risen in the past decade and is helping to modernize agriculture. UASs collect and elucidate data previously difficult to obtain and are used to help increase agricultural efficiency and production. Typical commercial off-the-shelf (COTS) UASs are limited by small payloads and short flight times. Such limits inhibit their ability to provide abundant data at multiple spatiotemporal scales. In this thesis, we describe the design and construction of the tethered aircraft unmanned system (TAUS), which is a novel power-over-tether UAS configured for long-term, high throughput atmospheric monitoring with an array of …

Comparison Of Concrete And Steel Jacket Methods For Reinforcing A Concrete Bridge Pier By Numerical And Experimental Studies, Hadi Faghihmaleki

Makara Journal of Technology

Various rehabilitation and strengthening procedures have been developed in recent decades. A study to determine which methods can be implemented to increase the useful life of the bridge before strengthening must be performed. In this study, the seismic behavior of a reinforced concrete bridge pier with dimension 3.5 × 3.5 m, which was reinforced by two steel and a concrete jacket, was investigated. Nonlinear geometric models and materials were analyzed to estimate the seismic parameters of the pier. Results show an increase in energy absorption, ultimate strength, and ductility for the steel jacket, as well as a greater increase in …

Effect Of Arc Plasma Sintering On The Structural And Microstructural Properties Of Fe-Cr-Ni Austenitic Stainless Steels, Parikin Parikin, M. Dani, A. Dimyati, N. D. Purnamasari, B. Sugeng, M. Panitra, A. Insani, T. H. Priyanto, S. Mustofa, Syahbuddin Syahbuddin, A. Huang

Makara Journal of Technology

X-ray diffraction techniques were performed to determine the actual crystal structure of A2 austenitic stainless steel (ASS) as-cast and A2 ASS after arc plasma sintering (APS) for 2 s. Computations were conducted on the basis of the Bragg arithmetic formula by comparing the S2 arithmetic with the interplanar spacing. The Bragg arithmetic formula is a simple series for the determination of the crystalline phase of materials based on the Miller indices of cubic shapes or other shapes. A2 ASS as-cast was identified to have a crystal structure of face-centered cubic with lattice parameter a = 3.58 Å. A similar crystal …

Trend Significance Levels Of Rain Onset And Cessation And Lengths Of The Wet And Dry Seasons In Epe, Lagos State, Nigeria, Adekunle Adedeji Alli, Olorunwa Eric Omofunmi

Makara Journal of Technology

This study aims to reduce crop failure resulting from a dry spell, which is the first occurrence of unsustainable rainfall that deceives farmers into planting. Thus, trends need to be tested using hypothesis, kurtosis, and other statistics to analyze the risks associated with unstable planting calendars and their possible mitigation strategies. The daily rainfall data from 1982 to 2018 were obtained from the archive of NASA/POWER SRB/FLASH, and the research location is Epe, Lagos State, Nigeria, which lies at latitude 6.585° N and longitude 3.962° E. Microsoft Excel was used to perform the tests. Results show that the null hypothesis …

Kinetic Modeling Study Of Laminar Burning Velocity Of Gasoline–Ethanol–Methanol Blends At Elevated Temperature And Pressure, Ahmad Syihan Auzani, Cahyo Setyo Wibowo, Riesta Anggarani, Yulianto Sulistyo Nugroho, Bambang Sugiarto

Makara Journal of Technology

Gasoline–ethanol–methanol (GEM) blends have been considered to replace pure gasoline as spark ignition engine fuel. Their physical and chemical properties and performance and emission measurements from real engines have been reported previously. However, a fundamental study that can explain the unique results of GEM compared with those of pure gasoline is lacking. This study aims to compare the laminar burning velocity of GEM blends at different mixtures, equivalence ratios, temperatures, and pressures with that of pure gasoline. A laminar flame propagation model and reaction mechanisms from the literature were were for a numerical simulation. In this study, the chemical components …

Improvement Of Electrical Properties Of Cmc-Pva Doped With Various Contents Of Lino3 As An Application For Hybrid Polymer Electrolytes, Amalia Zulkifli, Norfatihah Mazuki, Ahmad Salihin Samsudin

Makara Journal of Technology

The present work was carried out with the development of hybrid polymer electrolytes (HPEs) by using carboxymethyl cellulose (CMC)–polyvinyl alcohol (PVA) doped with different contents of lithium nitrate (LiNO3) for the determination of their structural and conduction properties. The structural analysis was conducted by using Fourier transform infra-red spectroscopy and showed the interaction between the blend host polymer and ionic dopant, which formed via the coordinating site of CMC-PVA and Li+-NO3−. The complexes of CMC-PVA doped LiNO3 led to an increment in ionic conductivity, as observed by electrical impedance spectroscopy, and the sample containing 20 wt% LiNO3 obtained the highest …

Music Information Retrieval Based On Active Frequency, Hardianto Wibowo, Wildan Suharso, Yufis Azhar, Galih Wasis Wicaksono, Agus Eko Minarno, Dani Harmanto

Makara Journal of Technology

Music is the art of combining frequencies. A balance of frequencies gives rise to a harmonious tone. Several features of music can be analyzed, and they include sociocultural background, lyrics, mood, tempo, rhythm, harmony, melody, timbre, and instrumentation. In this study, we use the frequency of instrumentation as a feature for classification because each instrument has a frequency range. To test this frequency range, we use five music genres and one music playing skill. The five genres are dangdut, electronic dance music (EDM), metal, pop/rock, and reggae. The music playing skill is acoustic. Active frequencies are tested using the k-nearest …

Predictive Delivery Man Assignment Problem Using Deep Learning, Rahmadini Payla Juarsa, Taufik Djatna

Makara Journal of Technology

Dispatching is a critical part in current online shopping. It relates to how the delivery man assignment should minimize cost along with the service from a source to an end customer with an appropriate scheduled time. The problem arises as neither enough products to deliver nor delivery men are available for dispatch, resulting in suboptimal service and a waste of money. The study aimed to formulate the cost of restaurant dispatching for inducing a deep learning-based solution with the gated recurrent unit recurrent neural network to receive hourly order data and to engage the result for near feature delivery man …

Narrow Band Active Contour Attention Model For Medical Segmentation, Ngan Le, Toan Bui, Viet-Khao Vo-Ho, Kashu Yamazaki, Khoa Luu

Computer Science and Computer Engineering Faculty Publications and Presentations

Medical image segmentation is one of the most challenging tasks in medical image analysis and widely developed for many clinical applications. While deep learning-based approaches have achieved impressive performance in semantic segmentation, they are limited to pixel-wise settings with imbalanced-class data problems and weak boundary object segmentation in medical images. In this paper, we tackle those limitations by developing a new two-branch deep network architecture which takes both higher level features and lower level features into account. The first branch extracts higher level feature as region information by a common encoder-decoder network structure such as Unet and FCN, whereas the …

Snr: Software Library For Introductory Robotics, Spencer F. Shaw

Master's Theses

This thesis introduces "SNR," a Python library for programming robotic systems in the context of introductory robotics courses. Greater demand for roboticists has pressured educational institutions to expand robotics curricula. Students are now more likely to take robotics courses earlier and with less prior programming experience. Students may be attempting to simultaneously learn a systems programming language, a library API, and robotics concepts. SNR is written purely in Python to present familiar semantics, eliminating one of these learning curves. Industry standard robotics libraries such as ROS often require additional build tools and configuration languages. Students in introductory courses frequently lack …

Hardware For Quantized Mixed-Precision Deep Neural Networks, Andres Rios

Open Access Theses & Dissertations

Recently, there has been a push to perform deep learning (DL) computations on the edge rather than the cloud due to latency, network connectivity, energy consumption, and privacy issues. However, state-of-the-art deep neural networks (DNNs) require vast amounts of computational power, data, and energyâ??resources that are limited on edge devices. This limitation has brought the need to design domain-specific architectures (DSAs) that implement DL-specific hardware optimizations. Traditionally DNNs have run on 32-bit floating-point numbers; however, a body of research has shown that DNNs are surprisingly robust and do not require all 32 bits. Instead, using quantization, networks can run on …

A Real-World, Hybrid Event Sequence Generation Framework For Android Apps, Jun Sun

School of Computing: Dissertations, Theses, and Student Research

Generating meaningful inputs for Android apps is still a challenging issue that needs more research. Past research efforts have shown that random test generation is still an effective means to exercise User-Interface (UI) events to achieve high code coverage. At the same time, heuristic search approaches can effectively reach specified code targets. Our investigation shows that these approaches alone are insufficient to generate inputs that can exercise specific code locations in complex Android applications.

This thesis introduces a hybrid approach that combines two different input generation techniques--heuristic search based on genetic algorithm and random instigation of UI events, to reach …

Using Contextual Bandits To Improve Traffic Performance In Edge Network, Aziza Al Zadjali

School of Computing: Dissertations, Theses, and Student Research

Edge computing network is a great candidate to reduce latency and enhance performance of the Internet. The flexibility afforded by Edge computing to handle data creates exciting range of possibilities. However, Edge servers have some limitations since Edge computing process and analyze partial sets of information. It is challenging to allocate computing and network resources rationally to satisfy the requirement of mobile devices under uncertain wireless network, and meet the constraints of datacenter servers too. To combat these issues, this dissertation proposes smart multi armed bandit algorithms that decide the appropriate connection setup for multiple network access technologies on the …

Aerial Flight Paths For Communication, Alisha Bevins

School of Computing: Dissertations, Theses, and Student Research

This body of work presents an iterative process of refinement to understand naive perception of communication using the motion of an unmanned aerial vehicle (UAV). This includes what people believe the UAV is trying to communicate, and how they expect to respond through physical action or emotional response. Previous work in this area sought to communicate without clear definitions of the states attempting to be conveyed. In an attempt to present more concrete states and better understand specific motion perception, this work goes through multiple iterations of state elicitation and label assignment. The lessons learned in this work will be …

Passive Method For 3d Reconstruction Of Human Jaw: Theory And Application., Mohamad Ghanoum

Electronic Theses and Dissertations

Oral dental applications based on visual data pose various challenges. There are problems with lighting (effect of saliva, tooth dis-colorization, gum texture, and other sources of specularity) and motion (even inevitable slight motions of the upper/ lower jaw may lead to errors far beyond the desired tolerance of sub-millimeter accuracy). Nowadays, the dental CAM systems have become more compromised and accurate to obtain the geometric data of the jaw from the active sensor (laser scanner). However, they have not met the expectations and the needs of dental professionals in many ways. The probes in these systems are bulky { even …

Signal Fingerprinting And Machine Learning Framework For Uav Detection And Identification., Olusiji Oloruntobi Medaiyese

Electronic Theses and Dissertations

Advancement in technology has led to creative and innovative inventions. One such invention includes unmanned aerial vehicles (UAVs). UAVs (also known as drones) are now an intrinsic part of our society because their application is becoming ubiquitous in every industry ranging from transportation and logistics to environmental monitoring among others. With the numerous benign applications of UAVs, their emergence has added a new dimension to privacy and security issues. There are little or no strict regulations on the people that can purchase or own a UAV. For this reason, nefarious actors can take advantage of these aircraft to intrude into …

Cosine-Based Explainable Matrix Factorization For Collaborative Filtering Recommendation., Pegah Sagheb Haghighi

Electronic Theses and Dissertations

Recent years saw an explosive growth in the amount of digital information and the number of users who interact with this information through various platforms, ranging from web services to mobile applications and smart devices. This increase in information and users has naturally led to information overload which inherently limits the capacity of users to discover and find their needs among the staggering array of options available at any given time, the majority of which they may never become aware of. Online services have handled this information overload by using algorithmic filtering tools that can suggest relevant and personalized information …

Motion And Emotion Estimation For Robotic Autism Intervention., Jacob M Berdichevsky

Electronic Theses and Dissertations

Robots have recently emerged as a novel approach to treating autism spectrum disorder (ASD). A robot can be programmed to interact with children with ASD in order to reinforce positive social skills in a non-threatening environment. In prior work, robots were employed in interaction sessions with ASD children, but their sensory and learning abilities were limited, while a human therapist was heavily involved in “puppeteering” the robot. The objective of this work is to create the next-generation autism robot that includes several new interactive and decision-making capabilities that are not found in prior technology. Two of the main features that …

Multilateration Index., Chip Lynch

Electronic Theses and Dissertations

We present an alternative method for pre-processing and storing point data, particularly for Geospatial points, by storing multilateration distances to fixed points rather than coordinates such as Latitude and Longitude. We explore the use of this data to improve query performance for some distance related queries such as nearest neighbor and query-within-radius (i.e. “find all points in a set P within distance d of query point q”). Further, we discuss the problem of “Network Adequacy” common to medical and communications businesses, to analyze questions such as “are at least 90% of patients living within 50 miles of a covered emergency …

Linking Social Media, Medical Literature, And Clinical Notes Using Deep Learning., Mohsen Asghari

Electronic Theses and Dissertations

Researchers analyze data, information, and knowledge through many sources, formats, and methods. The dominant data format includes text and images. In the healthcare industry, professionals generate a large quantity of unstructured data. The complexity of this data and the lack of computational power causes delays in analysis. However, with emerging deep learning algorithms and access to computational powers such as graphics processing unit (GPU) and tensor processing units (TPUs), processing text and images is becoming more accessible. Deep learning algorithms achieve remarkable results in natural language processing (NLP) and computer vision. In this study, we focus on NLP in the …

Flight Trajectory Prediction For Aeronautical Communications., Nathan T Schimpf

Electronic Theses and Dissertations

The development of future technologies for the National Airspace System (NAS) will be reliant on a new communications infrastructure capable of managing a limited spectrum among aircraft and ground systems. Emerging approaches to this spectrum allocation task mostly consider machine learning techniques reliant on aircraft and Air Traffic Control (ATC) sector data. Much of this data, however, is not directly available. This thesis considers the development of two such data products: the 4D trajectory (latitude, longitude, altitude, and time) of aircraft, and the anticipated airspace utilization and communication demand within an ATC sector. Data predictions are treated as a time …

Internet Of Things Security Case Studies And Internet Of Things Core Service Comparions, Jaseong Koo

Electronic Theses, Projects, and Dissertations

This culminating project conducted an analysis of IoT security breach case studies. The analysis identified numerous vulnerable points: software failure, node tampering attack, eavesdropping, code injection, unauthorized access, social engineering attack, hardware exploitation, and node insertion. It therefor seems that even with the proper tests conducted on vulnerabilities to discover solutions, regular end users are unable to apply patches or other technical solutions to protect themselves. This project solely focuses on analyzing of comprehensive IoT security services that come with devices connected to home network. The devices are those provided by the big three: Amazon, Google, and Microsoft, on the …

Analysis Of Microscopic Objects Using Computer Vision Methods, Yuan Dao

UNLV Theses, Dissertations, Professional Papers, and Capstones

As an essential and powerful tool to observe living organisms, three-dimensional fluorescence microscopy is widely used in biological research and diagnosis. The 4D fluorescence microscopy data can be obtained using time-lapsed videos of 3D images. To analyze and extract useful information from the increasingly large and complex biological image dataset, efficient and effective computational tools are in need but still lagging behind. In analyzing biological data, two major challenges are faced. First, time-lapsed fluorescence microscopic images typically have a low SNR. Second, biological objects often change their morphology and internal structure frequently. As such, conventional image processing methods may not …