Computer Engineering Commons^™

Video Annotation By Crowd Workers With Privacy-Preserving Local Disclosure, Apeksha Dipak Kumavat

Open Access Theses

Advancements in computer vision are still not reliable enough for detecting video content including humans and their actions. Microtask crowdsourcing on task markets such as Amazon Mechnical Turk and Upwork can bring humans into the loop. However, engaging crowd workers to annotate non-public video footage risks revealing the identities of people in the video who may have a right to anonymity.

This thesis demonstrates how we can engage untrusted crowd workers to detect behaviors and objects, while robustly concealing the identities of all faces. We developed a web-based system that presents obfuscated videos to crowd workers, and provides them with …

Liquid Metal Particle Popping: Nanoscale To Macroscale, Trevor R. Lear

Open Access Theses

Liquid metal nanoparticles can be used to produce stretchable electronic devices. Understanding the mechanical properties of liquid metal nanoparticles is crucial to optimizing their use in various applications, especially printing of flexible, stretchable electronics. Smaller nanoparticles are desired for high-resolution printing and compatibility with existing scalable manufacturing methods; however, they contain less liquid metal and are more difficult to rupture than larger particles, making them less desirable for post-processing functionality. This study investigates the mechanics of liquid metal particle rupture as a function of particle size. We employ compression of particle films to characterize the composition of the particle core …

Improving Programmability And Performance For Scientific Applications, Chenyang Liu

Open Access Dissertations

With modern advancements in hardware and software technology scaling towards new limits, our compute machines are reaching new potentials to tackle more challenging problems. While the size and complexity of both the problems and solutions increases, the programming methodologies must remain at a level that can be understood by programmers and scientists alike. In our work, this problem is encountered when developing an optimized framework to best exploit the semantic properties of a finite-element solver. In efforts to address this problem, we explore programming and runtime models which decouple algorithmic complexity, parallelism concerns, and hardware mapping. We build upon these …

What Broke Where For Distributed And Parallel Applications — A Whodunit Story, Subrata Mitra

Open Access Dissertations

Detection, diagnosis and mitigation of performance problems in today's large-scale distributed and parallel systems is a difficult task. These large distributed and parallel systems are composed of various complex software and hardware components. When the system experiences some performance or correctness problem, developers struggle to understand the root cause of the problem and fix in a timely manner. In my thesis, I address these three components of the performance problems in computer systems. First, we focus on diagnosing performance problems in large-scale parallel applications running on supercomputers. We developed techniques to localize the performance problem for root-cause analysis. Parallel applications, …

Approximate Computing: An Integrated Cross-Layer Framework, Swagath Venkataramani

Open Access Dissertations

A new design approach, called approximate computing (AxC), leverages the flexibility provided by intrinsic application resilience to realize hardware or software implementations that are more efficient in energy or performance. Approximate computing techniques forsake exact (numerical or Boolean) equivalence in the execution of some of the application’s computations, while ensuring that the output quality is acceptable. While early efforts in approximate computing have demonstrated great potential, they consist of ad hoc techniques applied to a very narrow set of applications, leaving in question the applicability of approximate computing in a broader context.

The primary objective of this thesis is to …

Psychophysiological Analysis Of A Pedagogical Agent And Robotic Peer For Individuals With Autism Spectrum Disorders., Mohammad Nasser Saadatzi

Electronic Theses and Dissertations

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by ongoing problems in social interaction and communication, and engagement in repetitive behaviors. According to Centers for Disease Control and Prevention, an estimated 1 in 68 children in the United States has ASD. Mounting evidence shows that many of these individuals display an interest in social interaction with computers and robots and, in general, feel comfortable spending time in such environments. It is known that the subtlety and unpredictability of people’s social behavior are intimidating and confusing for many individuals with ASD. Computerized learning environments and robots, however, prepare a predictable, …

Coyotelab - Linux Containers For Educational Use, Michael D. Korcha

Electronic Theses, Projects, and Dissertations

CoyoteLab is an exploration in the use of Linux container technology as a means to simplify the way students in computing fields access and complete laboratory work in their educational career. This project provides two main benefits: creating a simple way for students to log in and access their coursework without anything more than their web browser, and providing course instructors a way to verify that assigned work is completed successfully. Thanks to advances in container technology and the advent of WebSockets, this becomes a middle layer between a WebSocket opened up on the client’s browser and the SSH daemon …

A Reduced Labeled Samples (Rls) Framework For Classification Of Imbalanced Concept-Drifting Streaming Data., Elaheh Arabmakki

Electronic Theses and Dissertations

Stream processing frameworks are designed to process the streaming data that arrives in time. An example of such data is stream of emails that a user receives every day. Most of the real world data streams are also imbalanced as is in the stream of emails, which contains few spam emails compared to a lot of legitimate emails. The classification of the imbalanced data stream is challenging due to the several reasons: First of all, data streams are huge and they can not be stored in the memory for one time processing. Second, if the data is imbalanced, the accuracy …

Analog Spiking Neuromorphic Circuits And Systems For Brain- And Nanotechnology-Inspired Cognitive Computing, Xinyu Wu

Boise State University Theses and Dissertations

Human society is now facing grand challenges to satisfy the growing demand for computing power, at the same time, sustain energy consumption. By the end of CMOS technology scaling, innovations are required to tackle the challenges in a radically different way. Inspired by the emerging understanding of the computing occurring in a brain and nanotechnology-enabled biological plausible synaptic plasticity, neuromorphic computing architectures are being investigated. Such a neuromorphic chip that combines CMOS analog spiking neurons and nanoscale resistive random-access memory (RRAM) using as electronics synapses can provide massive neural network parallelism, high density and online learning capability, and hence, paves …

Cal Poly Engineering Photobot: Final Design Review, Samantha Clements, Carlos Esquivel, Kassandra Rodriguez, Aubrey Russell

Mechanical Engineering

The purpose of this project was to create a remotely controlled camera device; the PhotoBot captures images and videos of various plants and perhaps animals for biological analysis. The features for such a device allows a user to capture images and videos from various angles and heights with minimal outside assistance. Furthermore, the device is designed for users that do not wish to spend an extensive amount of time and effort taking pictures and videos in the rainforest. The key constraints of the device includes safety, versatility, ease of use, and durability. Ultimately, this project was completed for Dr. Cris …

Vulnerability Analysis And Security Framework For Zigbee Communication In Iot, Charbel Azzi

UNLV Theses, Dissertations, Professional Papers, and Capstones

Securing IoT (Internet of Things) systems in general, regardless of the communication technology used, has been the concern of many researchers and private companies. As for ZigBee security concerns, much research and many experiments have been conducted to better predict the nature of potential security threats. In this research we are addressing several ZigBee vulnerabilities by performing first hand experiments and attack simulations on ZigBee protocol. This will allow us to better understand the security issues surveyed and find ways to mitigate them. Based on the attack simulations performed and the survey conducted, we have developed a ZigBee IoT framework …

An Emg-Based Patient Monitoring System Using Zynq Soc Device, Farhad Fallahlalehzari

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis describes the design, development, and testing of an EMG-based patient monitoring system using the Zynq device. Zynq is a system on chip device designed by Xilinx which consists of an ARM dual cortex-A9 processor as well as an FPGA integrated into one chip. This work also analyzes the performance of image-processing algorithms on this system and compares that performance to more traditional PC-based systems. Image processing algorithms, such as Sobel edge detection, dilation and erosion, could be used in conjunction with a camera for the patient monitoring purposes. These algorithms often perform sub-optimally on processors because of their …

A Multi-Value Sequence Generated By Power Residue Symbol And Trace Function Over Odd Characteristic Field, Yasuyuki Nogami, Satoshi Uehara, Kazuyoshi Tsuchiya, Nasima Begum, Hiroto Ino, Robert Morelos-Zaragoza

Faculty Publications

This paper proposes a new multi-value sequence generated by utilizing primitive element, trace, and power residue symbol over odd characteristic finite field. In detail, let p and k be an odd prime number as the characteristic and a prime factor of p-1, respectively. Our proposal generates k-value sequence T={ti | ti=fk(Tr(ωi)+A)}, where ω is a primitive element in the extension field $\F{p}{m}$, Tr(⋅) is the trace function that maps $\F{p}{m} \rightarrow \f{p}$, A is a non-zero scalar in the prime field $\f{p}$, and fk(⋅) is a certain mapping function based on k-th power residue symbol. Thus, the proposed sequence has …

Design Of A Flexible Control Platform And Miniature In Vivo Robots For Laparo-Endoscopic Single-Site Surgeries, Lou P. Cubrich

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Minimally-invasive laparoscopic procedures have proven efficacy for a wide range of surgical procedures as well as benefits such as reducing scarring, infection, recovery time, and post-operative pain. While the procedures have many advantages, there are significant shortcomings such as limited instrument motion and reduced dexterity. In recent years, robotic surgical technology has overcome some of these limitations and has become an effective tool for many types of surgeries. These robotic platforms typically have an increased workspace, greater dexterity, improved ergonomics, and finer control than traditional laparoscopic methods. This thesis presents the designs of both a four degree-of-freedom (DOF) and 5-DOF …

Unsupervised Feature Selection For Outlier Detection By Modelling Hierarchical Value-Feature Couplings, Guansong Pang, Longbing Cao, Ling Chen, Huan Liu

Research Collection School Of Computing and Information Systems

Proper feature selection for unsupervised outlier detection can improve detection performance but is very challenging due to complex feature interactions, the mixture of relevant features with noisy/redundant features in imbalanced data, and the unavailability of class labels. Little work has been done on this challenge. This paper proposes a novel Coupled Unsupervised Feature Selection framework (CUFS for short) to filter out noisy or redundant features for subsequent outlier detection in categorical data. CUFS quantifies the outlierness (or relevance) of features by learning and integrating both the feature value couplings and feature couplings. Such value-to-feature couplings capture intrinsic data characteristics and …

Sensor Placement With Time-To-Detection Guarantees, Saif Eddin Jabari, Laura Wynter

Research Collection School Of Computing and Information Systems

We present a novel and effective method for determining the placement of sensors so as to be able to satisfy probabilistic constraints on the time-to-detection of an incident. Indeed, with the wealth of real-time traffic data available today, an important new goal of intelligent traffic management systems is incident detection with time-to-detection guarantees, in particular on expressways with large distances between sensors. This goal drives investment decisions in new sensor deployment, hence making the topic a pressing need for traffic management. The method we provide makes use of a probabilistic formulation of traffic behavior and incident localization to determine the …

Hashtag Recommendation With Topical Attention-Based Lstm, Yang Li, Ting Liu, Jing Jiang, Liang Zhang

Research Collection School Of Computing and Information Systems

Microblogging services allow users to create hashtags to categorize their posts. In recent years,the task of recommending hashtags for microblogs has been given increasing attention. However,most of existing methods depend on hand-crafted features. Motivated by the successful use oflong short-term memory (LSTM) for many natural language processing tasks, in this paper, weadopt LSTM to learn the representation of a microblog post. Observing that hashtags indicatethe primary topics of microblog posts, we propose a novel attention-based LSTM model whichincorporates topic modeling into the LSTM architecture through an attention mechanism. Weevaluate our model using a large real-world dataset. Experimental results show that …

From Footprint To Evidence: An Exploratory Study Of Mining Social Data For Credit Scoring, Guangming Guo, Feida Zhu, Enhong Chen, Qi Liu, Le Wu, Chu Guan

Research Collection School Of Computing and Information Systems

With the booming popularity of online social networks like Twitter and Weibo, online user footprints are accumulating rapidly on the social web. Simultaneously, the question of how to leverage the large-scale user-generated social media data for personal credit scoring comes into the sight of both researchers and practitioners. It has also become a topic of great importance and growing interest in the P2P lending industry. However, compared with traditional financial data, heterogeneous social data presents both opportunities and challenges for personal credit scoring. In this article, we seek a deep understanding of how to learn users’ credit labels from social …

Investigation Of Polymer–Plasticizer Blends As Sh-Saw Sensor Coatings For Detection Of Benzene In Water With High Sensitivity And Long-Term Stability, Pintu Adhikari, Laura Jeanne Alderson, Florian Bender, Antonio J. Ricco, Fabien Josse

Electrical and Computer Engineering Faculty Research and Publications

We report the first-ever direct detection of benzene in water at concentrations below 100 ppb (parts per billion) using acoustic wave (specifically, shear-horizontal surface acoustic wave, SH-SAW) sensors with plasticized polymer coatings. Two polymers and two plasticizers were studied as materials for sensor coatings. For each polymer–plasticizer combination, the influence of the mixing ratio of the blend on the sensitivity to benzene was measured and compared to commercially available polymers that were used for BTEX (benzene, toluene, ethylbenzene, and xylene) detection in previous work. After optimizing the coating parameters, the highest sensitivity and lowest detection limit for benzene were found …

Harmonic Scale Transformations, John H. Chalmers

The Transdisciplinary STEAM+ Journal

My artwork derives from a project to delineate the transformations certain types of harmonic musical scales undergo as the sizes of their generating intervals vary over the space of the octave.

Overview Of Lte Spectrum Sharing Technologies, Yun Ye, Dalei Wu, Zhihui Shu, Yi Qian

Department of Electrical and Computer Engineering: Faculty Publications

Long-Term Evolution (LTE) communication systems feature advanced frequency reuse and interference coordination techniques providing faster and more secured mobile services. However, the network capacity in licensed spectrum is still behind market demands. Dynamic spectrum access or spectrum sharing in other frequently vacant or unlicensed frequency bands is considered an effective means to boost system throughput. Different from operations in licensed spectrum with exclusive access, LTE deployment needs to take into account the distinct regulations on channel access to each shared frequency band, in order to avoid interference to incumbent users, and to maintain fair play with peer operators in heterogeneous …

On The Origin Of Synthetic Life: Attribution Of Output To A Particular Algorithm, Roman V. Yampolskiy

Faculty and Staff Scholarship

With unprecedented advances in genetic engineering we are starting to see progressively more original examples of synthetic life. As such organisms become more common it is desirable to gain an ability to distinguish between natural and artificial life forms. In this paper, we address this challenge as a generalized version of Darwin's original problem, which he so brilliantly described in On the Origin of Species. After formalizing the problem of determining the samples' origin, we demonstrate that the problem is in fact unsolvable. In the general case, if computational resources of considered originator algorithms have not been limited and priors …

Mesh Addition Based On The Depth Image (Mabdi), Lucas E. Chavez

Mechanical Engineering ETDs

Many robotic applications utilize a detailed map of the world and the algorithm used to produce such a map must take into consideration real-world constraints such as computational and memory costs. Traditional mesh-based environmental mapping algorithms receive data from the sensor, create a mesh surface from the data, and then append the surface to a growing global mesh. These algorithms do not provide a computationally efficient mechanism for reducing redundancies in the global mesh. MABDI is able to leverage the knowledge contained in the global mesh to find the difference between what we expect our sensor to see and what …

Towards Concolic Testing For Hybrid Systems, Pingfan Kong, Yi Li, Xiaohong Chen, Jun Sun, Meng Sun, Jingyi Wang

Research Collection School Of Computing and Information Systems

Hybrid systems exhibit both continuous and discrete behavior. Analyzing hybrid systems is known to be hard. Inspired by the idea of concolic testing (of programs), we investigate whether we can combine random sampling and symbolic execution in order to effectively verify hybrid systems. We identify a sufficient condition under which such a combination is more effective than random sampling. Furthermore, we analyze different strategies of combining random sampling and symbolic execution and propose an algorithm which allows us to dynamically switch between them so as to reduce the overall cost. Our method has been implemented as a web-based checker named …

Towards Learning And Verifying Invariants Of Cyber-Physical Systems By Code Mutation, Yuqi Chen, Christopher M. Poskitt, Jun Sun

Research Collection School Of Computing and Information Systems

Cyber-physical systems (CPS), which integrate algorithmic control with physical processes, often consist of physically distributed components communicating over a network. A malfunctioning or compromised component in such a CPS can lead to costly consequences, especially in the context of public infrastructure. In this short paper, we argue for the importance of constructing invariants (or models) of the physical behaviour exhibited by CPS, motivated by their applications to the control, monitoring, and attestation of components. To achieve this despite the inherent complexity of CPS, we propose a new technique for learning invariants that combines machine learning with ideas from mutation testing. …

Rapid Deployment Indoor Localization Without Prior Human Participation, Han Xu, Zimu Zhou, Longfei Shangguan

Research Collection School Of Computing and Information Systems

In this work, we propose RAD, a RApid Deployment localization framework without human sampling. The basic idea of RAD is to automatically generate a fingerprint database through space partition, of which each cell is fingerprinted by its maximum influence APs. Based on this robust location indicator, fine-grained localization can be achieved by a discretized particle filter utilizing sensor data fusion. We devise techniques for CIVD-based field division, graph-based particle filter, EM-based individual character learning, and build a prototype that runs on commodity devices. Extensive experiments show that RAD provides a comparable performance to the state-of-the-art RSSbased methods while relieving it …

Open Source Database And Website To Provide Free And Open Access To Inactive U.S. Patents In The Public Domain, Yuenyong Nilsiam, Joshua M. Pearce

Department of Materials Science and Engineering Publications

Although theoretically the patent system is meant to bolster innovation, the current United States Patent and Trademark Office (USPTO) is cumbersome and involves a significant time investment to locate inactive patents less than 20 years old. This article reports on the development of an open source database to find these public domain ideas. First, a search strategy is explained. Then the operation and use of free and open source software are detailed to meet the needs of open hardware innovators. Finally, a case study is presented to demonstrate the utility of the approach with 3-D printing. The results showed how …

An M-Learning Maturity Model For Universities And Higher Educational Institutes, Luiz Fernando Capretz, Muasaad Alrasheedi, Arif Raza

Electrical and Computer Engineering Publications

An m-learning maturity model is put forward in this research to assess the mobile technology adoption rates in universities and higher educational institutes. The model is derived from Capability Maturity Model (CMM), which has been widely used in organizations to gauge the adoption of various new processes. Five levels of m-learning maturity are specified including preliminary, established, defined, structured, and continuous improvement. Each of these maturity levels is gauged through nine critical success factors (CSFs) in assessment questionnaires. The CSFs used in measuring instrument of the model are adopted from three of our previous empirical studies. Using an assessment questionnaire …

Behavioral Modeling And Fpga Synthesis Of Ieee 802.11n Orthogonal Frequency Division Multiplexing (Ofdm) Scheme, Ragahv Sharma

USF Tampa Graduate Theses and Dissertations

In the field of communications, a high data rate and low multi-path fading is required for efficient information exchange. Orthogonal Frequency Division Multiplexing (OFDM) is a widely accepted IEEE 802.11n (and many others) standard for usage in communication systems operating in fading dispersive channels. In this thesis, we modeled the OFDM algorithm at the behavioral level in VHDL/Verilog that was successfully synthesized/verified on an FPGA. Due to rapid technology scaling, FPGAs have become popular and are low-cost and high performance alternatives to (semi-) custom ASICs. Further, due to reprogramming flexibility, FPGAs are useful in rapid prototyping. As per the IEEE …

Formal Performance Guarantees For Behavior-Based Localization Missions, Damian Lyons, Ron Arkin, Shu Jiang, Matt O'Brien, Feng Tang, Peng Tang

Faculty Publications

Abstract— Localization and mapping algorithms can allow a robot to navigate well in an unknown environment. However, whether such algorithms enhance any specific robot mission is currently a matter for empirical validation. In this paper we apply our MissionLab/VIPARS mission design and verification approach to an autonomous robot mission that uses probabilistic localization software.

Two approaches to modeling probabilistic localization for verification are presented: a high-level approach, and a sample-based approach which allows run-time code to be embedded in verification. Verification and experimental validation results are presented for two different missions, each using each method, demonstrating the accuracy …