Computer Engineering Commons^™

Micron/Nano Structure Creation Through Dual Pulse Femtosecond Laser Surface Processing, Nicholas Roth

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

A new technique has been developed for creating multiscale micro/nanoscale surfaces on metals. This technique is based on past work in femtosecond laser surface processing (FLSP) and dual pulse laser induced breakdown spectroscopy (LIBS). Using a femtosecond laser, pulse pairs were created with varying pulse separations between 0 ps to 500 ps. The creation of surface structures with dual pulse FLSP was studied on Ag, Cu, Ti, Al, Ni, and 304 stainless steel in relation to pulse separation.

Using dual pulse FLSP micro/nano structures have been created for the first time on silver. The silver structures are multiscale in nature …

Scaling Up An Infrastructure For Controlled Experimentation With Testing Techniques, Wayne D. Motycka

School of Computing: Dissertations, Theses, and Student Research

Software testing research often involves reproducing previous experimental results. Previous work created a repository infrastructure for containment and dissemination of testable research subjects using a private centralized storage mechanism for hosting these test subject archives. While this is a good way to store these subjects it can be inefficient when the size of subjects increases or the number of versions of the subject’s source code is large. The delivery of these large subjects from a centralized repository can be quite large and on occasion may not succeed requiring the user to repeat the download request. Coupled with the limited resources …

Spam Elimination And Bias Correction : Ensuring Label Quality In Crowdsourced Tasks., Lingyu Lyu

Electronic Theses and Dissertations

Crowdsourcing is proposed as a powerful mechanism for accomplishing large scale tasks via anonymous workers online. It has been demonstrated as an effective and important approach for collecting labeled data in application domains which require human intelligence, such as image labeling, video annotation, natural language processing, etc. Despite the promises, one big challenge still exists in crowdsourcing systems: the difficulty of controlling the quality of crowds. The workers usually have diverse education levels, personal preferences, and motivations, leading to unknown work performance while completing a crowdsourced task. Among them, some are reliable, and some might provide noisy feedback. It is …

Code Smells For Model-View-Controller Architectures, Maurício Aniche, Gabriele Bavota, Christoph Treude, Marco Aurélio Gerosa, Arie Van Deursen

Research Collection School Of Computing and Information Systems

Previous studies have shown the negative effects that low-quality code can have on maintainability proxies, such as code change- and defect-proneness. One of the symptoms of low-quality code are code smells, defined as sub-optimal implementation choices. While this definition is quite general and seems to suggest a wide spectrum of smells that can affect software systems, the research literature mostly focuses on the set of smells defined in the catalog by Fowler and Beck, reporting design issues that can potentially affect any kind of system, regardless of their architecture (e.g., Complex Class). However, systems adopting a specific architecture (e.g., the …

Customer Segmentation Using Online Platforms: Isolating Behavioral And Demographic Segments For Persona Creation Via Aggregated User Data, Jisun An, Haewoon Kwak, Soon‑Gyo Jung, Joni Salminen, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

We propose a novel approach for isolating customer segments using online customer data for products that are distributed via online social media platforms. We use non-negative matrix factorization to first identify behavioral customer segments and then to identify demographic customer segments. We employ a methodology for linking the two segments to present integrated and holistic customer segments, also known as personas. Behavioral segments are generated from customer interactions with online content. Demographic segments are generated using the gender, age, and location of these customers. In addition to evaluating our approach, we demonstrate its practicality via a system leveraging these customer …

Secure Device And Knowledge Discovery In Internet Of Things, Shahab Taregh Tayeb

UNLV Theses, Dissertations, Professional Papers, and Capstones

With the ever-growing adoption of Internet of Things (IoT), there is continued development and deployment of new nodes with various capabilities and services. Such heterogeneity introduces complexity and a significant need for neighbor service discovery frameworks. Because the types of services available are orders of magnitude more than pre-IoT era, researchers need new techniques to accurately discover not only the topologies and adjacencies but also the capability of other nodes and neighbors. Device discovery is usually the first task to be performed, immediately after deployment, as it enables communications, scheduling, and channel estimation. The existing discovery mechanisms do not consider …

A Practical Incremental Learning Framework For Sparse Entity Extraction, Hussein Al-Olimat, Steven Gustafson, Jason Mackay, Krishnaprasad Thirunarayan, Amit Sheth

Publications

This work addresses challenges arising from extracting entities from textual data, including the high cost of data annotation, model accuracy, selecting appropriate evaluation criteria, and the overall quality of annotation. We present a framework that integrates Entity Set Expansion (ESE) and Active Learning (AL) to reduce the annotation cost of sparse data and provide an online evaluation method as feedback. This incremental and interactive learning framework allows for rapid annotation and subsequent extraction of sparse data while maintaining high accuracy. We evaluate our framework on three publicly available datasets and show that it drastically reduces the cost of sparse entity …

Machine Learning For Internet Of Things Data Analysis: A Survey, Mohammad Saeid Mahdavinejad, Mohammadreza Rezvan, Mohammadamin Barekatain, Peyman Adibi, Payam Barnaghi, Amit Sheth

Publications

Rapid developments in hardware, software, and communication technologies have facilitated the emergence of Internet-connected sensory devices that provide observations and data measurements from the physical world. By 2020, it is estimated that the total number of Internet-connected devices being used will be between 25 and 50 billion. As these numbers grow and technologies become more mature, the volume of data being published will increase. The technology of Internet-connected devices, referred to as Internet of Things (IoT), continues to extend the current Internet by providing connectivity and interactions between the physical and cyber worlds. In addition to an increased volume, the …

Exact Processing Of Uncertain Top-K Queries In Multi-Criteria Settings, Kyriakos Mouratidis, Bo Tang

Research Collection School Of Computing and Information Systems

Traditional rank-aware processing assumes a dataset that contains available options to cover a specific need (e.g., restaurants, hotels, etc) and users who browse that dataset via top-k queries with linear scoring functions, i.e., by ranking the options according to the weighted sum of their attributes, for a set of given weights. In practice, however, user preferences (weights) may only be estimated with bounded accuracy, or may be inherently uncertain due to the inability of a human user to specify exact weight values with absolute accuracy. Motivated by this, we introduce the uncertain top-k query (UTK). Given uncertain preferences, that is, …

Learning Representations Of Ultrahigh-Dimensional Data For Random Distance-Based Outlier Detection, Guansong Pang, Longbing Cao, Ling Chen, Defu Lian, Huan Liu

Research Collection School Of Computing and Information Systems

Learning expressive low-dimensional representations of ultrahigh-dimensional data, e.g., data with thousands/millions of features, has been a major way to enable learning methods to address the curse of dimensionality. However, existing unsupervised representation learning methods mainly focus on preserving the data regularity information and learning the representations independently of subsequent outlier detection methods, which can result in suboptimal and unstable performance of detecting irregularities (i.e., outliers).This paper introduces a ranking model-based framework, called RAMODO, to address this issue. RAMODO unifies representation learning and outlier detection to learn low-dimensional representations that are tailored for a state-of-the-art outlier detection approach - the random …

Split Latency Allocator: Process Variation-Aware Register Access Latency Boost In A Near-Threshold Graphics Processing Unit, Asmita Pal

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Over the last decade, Graphics Processing Units (GPUs) have been used extensively in gaming consoles, mobile phones, workstations and data centers, as they have exhibited immense performance improvement over CPUs, in graphics intensive applications. Due to their highly parallel architecture, general purpose GPUs (GPGPUs) have gained the foreground in applications where large data blocks can be processed in parallel. However, the performance improvement is constrained by a large power consumption. Likewise, Near Threshold Computing (NTC) has emerged as an energy-efficient design paradigm. Hence, operating GPUs at NTC seems like a plausible solution to counteract the high energy consumption. This work …

Apple Flower Detection Using Deep Convolutional Networks, Philipe A. Dias, Amy Tabb, Henry P. Medeiros

Electrical and Computer Engineering Faculty Research and Publications

To optimize fruit production, a portion of the flowers and fruitlets of apple trees must be removed early in the growing season. The proportion to be removed is determined by the bloom intensity, i.e., the number of flowers present in the orchard. Several automated computer vision systems have been proposed to estimate bloom intensity, but their overall performance is still far from satisfactory even in relatively controlled environments. With the goal of devising a technique for flower identification which is robust to clutter and to changes in illumination, this paper presents a method in which a pre-trained convolutional neural network …

The Singularity May Be Near, Roman V. Yampolskiy

Faculty and Staff Scholarship

Toby Walsh in "The Singularity May Never Be Near" gives six arguments to support his point of view that technological singularity may happen, but that it is unlikely. In this paper, we provide analysis of each one of his arguments and arrive at similar conclusions, but with more weight given to the "likely to happen" prediction.

Cmos Radioactive Isotope Identification With Multichannel Analyzer And Embedded Neural Network, Samuel Murray

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

A radiation detection and identification system is designed and implemented to perform gamma ray spectroscopy on radioactive sources and identify which isotopes are present in the sources. A multichannel analyzer is implemented on an ASIC to process the signal produced from gamma rays detected by a scintillator and photomultiplier tube and to quantize the gamma ray energies to build a histogram. A fast, low memory embedded neural network is implemented on a microcontroller ASIC to identify the isotopes present in the gamma ray histogram produced by the multichannel analyzer in real time.

Advisors: Sina Balkir and Michael W. Hoffman

Chaotic Phase-Coded Waveforms With Space-Time Complementary Coding For Mimo Radar Applications, Sheng Hong, Fuhui Zhou, Yantao Dong, Zhixin Zhao, Yuhao Wang, Maosong Yan

Electrical and Computer Engineering Faculty Publications

A framework for designing orthogonal chaotic phase-coded waveforms with space-time complementary coding (STCC) is proposed for multiple-input multiple-output (MIMO) radar applications. The phase-coded waveform set to be transmitted is generated with an arbitrary family size and an arbitrary code length by using chaotic sequences. Due to the properties of chaos, this chaotic waveform set has many advantages in performance, such as anti-interference and low probability of intercept. However, it cannot be directly exploited due to the high range sidelobes, mutual interferences, and Doppler intolerance. In order to widely implement it in practice, we optimize the chaotic phase-coded waveform set from …

An Application Of Game Theory In Distributed Collaborative Decision Making, Angran Xiao

Publications and Research

In a distributed product realization environment, new paradigms and accompanying software systems are necessary to support the collaborative work of geographically dispersed engineering teams from different disciplines who have different knowledge, experience, tools and resources. To verify the concept of collaboration by separation, we propose a generic information communication medium to enable knowledge representation and exchange between engineering teams, a digital interface. Across digital interfaces, each engineering team maintains its own perspective towards the product realization problem, and each controls a subset of design variables and seeks to maximize its own payoff function subject to individual constraints. Hence, we postulate …

How Much Privacy Do We Have Today? A Study Of The Life Of Marc Mezvinsky, Miguel Mares, Salomon Gilles, Brian D. Gobran, Dan Engels

SMU Data Science Review

In this paper, we present a case study evaluating the level of information available about an individual through public, Internet-accessible sources. Privacy is a basic tenet of democratic society, but technological advances have made access to information and the identification of individuals much easier through Internet-accessible databases and information stores. To determine the potential level of privacy available to an individual in today’s interconnected world, we sought to develop a detailed history of Marc Mezvinsky, a semi-public figure, husband of Chelsea Clinton, and son of two former members of the United States House of Representatives. By utilizing only publicly and …

Retrieval Of Infotainment System Artifacts From Vehicles Using Ive, Celia J. Whelan, John Sammons, Brian Mcmanus, Terry W. Fenger

Journal of Applied Digital Evidence

The analysis of mobile devices and hard drives has been the focus of the digital forensics world for years, but there is another source of potential evidence not often considered: vehicles. Many of today’s “connected cars” have systems that function like computers, storing information they process including user data from devices synced to the system. There has been little to no research done regarding what types of user artifacts can be found on the system, how long these artifacts remain, whether or not the user can remove those artifacts, and whether certain systems provide more information than others. For this …

Advanced Recurrent Network-Based Hybrid Acoustic Models For Low Resource Speech Recognition, Jian Kang, Wei-Qiang Zhang, Wei-Wei Liu, Jia Liu, Michael T. Johnson

Electrical and Computer Engineering Faculty Publications

Recurrent neural networks (RNNs) have shown an ability to model temporal dependencies. However, the problem of exploding or vanishing gradients has limited their application. In recent years, long short-term memory RNNs (LSTM RNNs) have been proposed to solve this problem and have achieved excellent results. Bidirectional LSTM (BLSTM), which uses both preceding and following context, has shown particularly good performance. However, the computational requirements of BLSTM approaches are quite heavy, even when implemented efficiently with GPU-based high performance computers. In addition, because the output of LSTM units is bounded, there is often still a vanishing gradient issue over multiple layers. …

Tunable Plasmonic Resonances In Highly Porous Nano-Bamboo Si-Au Superlattice-Type Thin Films, Ufuk Kılıç, Alyssa Mock, René Feder, Derek Sekora, Matthew J. Hilfiker, Rafal Korlacki, Eva Schubert, Christos Argyropoulos, Mathias Schubert

Department of Electrical and Computer Engineering: Faculty Publications

We report on fabrication of spatially-coherent columnar plasmonic nanostructure superlattice-type thin films with high porosity and strong optical anisotropy using glancing angle deposition. Subsequent and repeated depositions of silicon and gold lead to nanometer-dimension subcolumns with controlled lengths. The superlattice-type columns resemble bamboo structures where smaller column sections of gold form junctions sandwiched between larger silicon column sections (“nano-bamboo”). We perform generalized spectroscopic ellipsometry measurements and finite element method computations to elucidate the strongly anisotropic optical properties of the highly-porous nano-bamboo structures. The occurrence of a strongly localized plasmonic mode with displacement pattern reminiscent of a dark quadrupole mode is …

An Ensemble Stacked Convolutional Neural Network Model For Environmental Event Sound Recognition, Shaobo Li, Yong Yao, Jie Hu, Guokai Liu, Xuemei Yao, Jianjun Hu

Faculty Publications

Convolutional neural networks (CNNs) with log-mel audio representation and CNN-based end-to-end learning have both been used for environmental event sound recognition (ESC). However, log-mel features can be complemented by features learned from the raw audio waveform with an effective fusion method. In this paper, we first propose a novel stacked CNN model with multiple convolutional layers of decreasing filter sizes to improve the performance of CNN models with either log-mel feature input or raw waveform input. These two models are then combined using the Dempster–Shafer (DS) evidence theory to build the ensemble DS-CNN model for ESC. Our experiments over three …

Me2b

SIGNED: The Magazine of The Hong Kong Design Institute

Fixing the internet's biggest flaw

Intelligent Computational Transportation, Yuming Zhang

Electrical and Computer Engineering ETDs

Transportation is commonplace around our world. Numerous researchers dedicate great efforts to vast transportation research topics. The purpose of this dissertation is to investigate and address a couple of transportation problems with respect to geographic discretization, pavement surface automatic examination, and traffic ow simulation, using advanced computational technologies. Many applications require a discretized 2D geographic map such that local information can be accessed efficiently. For example, map matching, which aligns a sequence of observed positions to a real-world road network, needs to find all the nearby road segments to the individual positions. To this end, the map is discretized by …

High-Performance Testbed For Vision-Aided Autonomous Navigation For Quadrotor Uavs In Cluttered Environments, Shakeeb Ahmad

Electrical and Computer Engineering ETDs

This thesis presents the development of an aerial robotic testbed based on Robot Operating System (ROS). The purpose of this high-performance testbed is to develop a system capable of performing robust navigation tasks using vision tools such as a stereo camera. While ensuring the computation of robot odometery, the system is also capable of sensing the environment using the same stereo camera. Hence, all the navigation tasks are performed using a stereo camera and an inertial measurement unit (IMU) as the main sensor suite. ROS is used as a framework for software integration due to its capabilities to provide efficient …

Compact Hardware Implementation Of A Sha-3 Core For Wireless Body Sensor Networks, Yi Yang, Debiao He, Neeraj Kumar, Sherali Zeadally

Information Science Faculty Publications

One of the most important Internet of Things applications is the wireless body sensor network (WBSN), which can provide universal health care, disease prevention, and control. Due to large deployments of small scale smart sensors in WBSNs, security, and privacy guarantees (e.g., security and safety-critical data, sensitive private information) are becoming a challenging issue because these sensor nodes communicate using an open channel, i.e., Internet. We implement data integrity (to resist against malicious tampering) using the secure hash algorithm 3 (SHA-3) when smart sensors in WBSNs communicate with each other using the Internet. Due to the limited resources (i.e., storage, …

A Study Of Comparing Cad/Cam Simulated Machining Time With Practical Cnc Machining Time And The Influence Of The Parameter Setting In Cnc, Jinming Wan

Morehead State Theses and Dissertations

A thesis presented to the faculty of the College of Business and Technology at Morehead State University in partial fulfillment of the requirements for the degree of Master of Science by Jinming Wan on July 11, 2018.

Survey Results On Adults And Cybersecurity Education, Frank Breitinger, Joseph Ricci, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

Cyberattacks and identity theft are common problems nowadays where researchers often say that humans are the weakest link in the security chain. Therefore, this survey focused on analyzing the interest for adults for ‘cyber threat education seminars’, e.g., how to project themselves and their loved ones. Specifically, we asked questions to understand a possible audience, willingness for paying / time commitment, or fields of interest as well as background and previous training experience. The survey was conducted in late 2016 and taken by 233 participants. The results show that many are worried about cyber threats and about their children exploring …

Adaptive Virtual Impedance Droop Control Based On Consensus Control Of Reactive Current, Zhilin Lu, Qing Wei, Yiyi Zhang, Junhui Zhao, Emad Manla

Electrical & Computer Engineering and Computer Science Faculty Publications

It is difficult to achieve accurate distribution of reactive power based on conventional droop control due to the line impedance mismatch in an islanded microgrid. An adaptive virtual impendence method based on consensus control of reactive current is proposed in this paper. A distributed control structure without the central controller has been established. In this structure, each distributed generation unit (DG) is an independent agent, one-way communication is used between the adjacent DGs, and the reactive power sharing is equivalent to a problem of reactive power current consensus. It has been proven that the system is asymptotically stable under the …

Prototype Of A Fish Inspired Swimming Silk Robot, Cassandra M. Donatelli, Sarah A. Bradner, Juanita Mathews, Erin Sanders, Casey R. Culligan, David Kaplan, Eric D. Tytell

Engineering Faculty Articles and Research

Elongate fishes have evolved hundreds of times throughout the tree of life. They occupy many aquatic environments, from streams and ponds to the deepest parts of the ocean. Due to their long body and numerous vertebrae, they are also highly flexible animals, which makes them useful as bioinspiration for designs in the field of soft robotics. We present a biodegradable soft robot prototype, inspired by elongate fishes. The robot's body is primarily composed of a silk hydrogel with embedded fibers to mimic the structure of natural fish skin. When actuated at the front, the flexible gel prototype mimics the undulatory …

Moving Target Defense For Securing Scada Communications, Vahid Heydari

College of Science & Mathematics Departmental Research

In this paper, we introduce a framework for building a secure and private peer to peer communication used in supervisory control and data acquisition networks with a novel Mobile IPv6-based moving target defense strategy. Our approach aids in combating remote cyber-attacks against peer hosts by thwarting any potential attacks at their reconnaissance stage. The IP address of each host is randomly changed at a certain interval creating a moving target to make it difficult for an attacker to find the host. At the same time, the peer host is updated through the use of the binding update procedure (standard Mobile …