Computer Engineering Commons^™

Performance Analysis Of Hybrid Algorithms For Lossless Compression Of Climate Data, Bharath Chandra Mummadisetty

UNLV Theses, Dissertations, Professional Papers, and Capstones

Climate data is very important and at the same time, voluminous. Every minute a new entry is recorded for different climate parameters in climate databases around the world. Given the explosive growth of data that needs to be transmitted and stored, there is a necessity to focus on developing better transmission and storage technologies. Data compression is known to be a viable and effective solution to reduce bandwidth and storage requirements of bulk data. So, the goal is to develop the best compression methods for climate data.

The methodology used is based on predictive analysis. The focus is to implement …

Estimation On Gibbs Entropy For An Ensemble, Lekhya Sai Sake

Electronic Theses, Projects, and Dissertations

In this world of growing technology, any small improvement in the present scenario would create a revolution. One of the popular revolutions in the computer science field is parallel computing. A single parallel execution is not sufficient to see its non-deterministic features, as same execution with the same data at different time would end up with a different path. In order to see how non deterministic a parallel execution can extend up to, creates the need of the ensemble of executions. This project implements a program to estimate the Gibbs Entropy for an ensemble of parallel executions. The goal is …

A Game-Based Learning Model, Fatmah Mohamed Ali Ramsi

Theses

The purpose of this research is to design a conceptual model and develop an implementation as a proof of concept of game-based learning (GBL)to support linguistic skills acquisition. Our model lays the foundations of game-based learning by defining methods, processes, and procedures to support the development of game-based learning systems. Integration of learning and gameplay raises various issues, among them the learning process, learning content, and game characteristics. Language competency is fundamental to academic and social success. Vocabulary acquisition is a primary basis for language competency. Word lists and dictionaries have been used as a resource to enrich vocabulary. The …

Novel Software Defined Radio Architecture With Graphics Processor Acceleration, Lalith Narasimhan

Dissertations

Wireless has become one of the most pervasive core technologies in the modern world. Demand for faster data rates, improved spectrum efficiency, higher system access capacity, seamless protocol integration, improved security and robustness under varying channel environments has led to the resurgence of programmable software defined radio (SDR) as an alternative to traditional ASIC based radios. Future SDR implementations will need support for multiple standards on platforms with multi-Gb/s connectivity, parallel processing and spectrum sensing capabilities. This dissertation implemented key technologies of importance in addressing these issues namely development of cost effective multi-mode reconfigurable SDR and providing a framework to …

A Platform For Fast Detection Of Let-7 Micro Rna Using Polyaniline Fluorescence And Image Analysis Techniques, Partha P. Sengupta

Master's Theses

The project describes a new strategy for transducing hybridization events through modulating intrinsic properties of the electroconductive polymer polyaniline (PANI). When DNA based probes electrostatically interact with PANI, its fluorescence properties are increased, a phenomenon that can be enhanced by UV irradiation. Hybridization of target nucleic acids results in dissociation of probes causing PANI fluorescence to return to basal levels. By monitoring restoration of base PANI fluorescence as little as 10^-11 M (10 pM) of target oligonucleotides could be detected within 15 minutes of hybridization. Detection of complementary oligos was specific, with introduction of a single mismatch failing to …

Microcontroller Application For Linear And Rotational Motion Sensing, Zachary Mintzer

Computer Engineering

No abstract provided.

Computer Aided Brain Tumor Edge Extraction Using Morphological Operations, Warqaa Shaher Alazawee

Masters Theses

Detecting the precise boundary of the area containing a recognized brain tumor is a complex problem and must be addressed since it applies to many medical modalities and tumor types. The objective of this thesis is to provide an efficient algorithm for detecting edges of brain tumors to help neurosurgeons identify the border of the critical area and distinguish the precise margin of the tumor from the rest of the brain tissue during the surgery. This thesis work exploits MRI brain tumor images as a tool to aid surgeons. MRI image segmentation is an essential step as a preliminary process …

An Integrated Framework For Cardiac Sounds Diagnosis, Zichun Tong

Masters Theses

The Phonocardiogram (PCG) signal contains valuable information about the cardiac condition and is a useful tool in recognizing dysfunction and heart failure. By analyzing the PCG, early detection and diagnosis of heart diseases can be accomplished since many pathological conditions of the cardiovascular system cause murmurs or abnormal heart sounds. This thesis presents an algorithm to classify normal and abnormal heart sound signals using PCG. The proposed analysis is based on a framework composed of several statistical signal analysis techniques such as wavelet based de-noising, energy-based segmentation, Hilbert-Huang transform based feature extraction, and Support Vector Machine based classification. The MATLAB …

Morphology Based Framework For Improved Driver's Visibility In Inclement Weather Conditions, Saleem Farhood Hussein

Masters Theses

The U.S. Department of Transportation reports that on average there are 5,870,000 vehicle accidents each year. Twenty-three percent (23%) of these accidents are attributed to weather conditions with an annual average of more than 6,000 people are killed and 480,000 people are injured. Weather-related accidents occur mainly because of the low visibility on the roads under inclement conditions such as snow, rain and fog. While these conditions can be predictable and individuals try to avoid driving in inclement weather, there are circumstances that require driving in such conditions such as emergency responders or when the severity of the storm has …

Detecting Occlusions Of Automobile Parts Being Inspected By A Camera System During Manufacturing Assembly, Jayadevan Puthumanappilly

All Theses

This thesis considers the problem of detecting occlusions in automobile parts on a moving assembly line in an automotive manufacturing plant. This work builds on the existing ``Visual Inspector'' (VI) system developed as a joint research project between Clemson University and the BMW Spartanburg manufacturing plant. The goal is to develop a method that can successfully detect occlusions in real-time. VI is a detector and classifier system that uses video cameras to determine the correct installation of a part in the assembly line. In the current version of VI, an occluded part is flagged simply as `not OK' - as …

A Lidar Based Semi-Autonomous Collision Avoidance System And The Development Of A Hardware-In-The-Loop Simulator To Aid In Algorithm Development And Human Studies, Thomas F. Stevens

Master's Theses

In this paper, the architecture and implementation of an embedded controller for a steering based semi-autonomous collision avoidance system on a 1/10^th scale model is presented. In addition, the development of a 2D hardware-in-the-loop simulator with vehicle dynamics based on the bicycle model is described. The semi-autonomous collision avoidance software is fully contained onboard a single-board computer running embedded GNU/Linux. To eliminate any wired tethers that limit the system’s abilities, the driver operates the vehicle at a user-control-station through a wireless Bluetooth interface. The user-control-station is outfitted with a game-controller that provides standard steering wheel and pedal controls along …

A Time-Efficient Strategy For Relay Selection And Link Scheduling In Wireless Communication Networks, Chenxi Qiu

All Dissertations

Despite the unprecedented success and proliferation of wireless communication, sustainable reliability and stability among wireless users are still considered important issues in the underlying link protocols. Existing link-layer protocols, like ARQ [44] or HARQ [57,67] approaches are designed to achieve this goal by discarding a corrupted packet at the receiver and performing one or more retransmissions until the packet is successfully decoded or a maximum number of retransmission attempts is reached. These strategies suffer from degradation of throughput and overall system instability since packets need to be en/decode in every hop, leading to high burden for relay nodes especially when …

Computational Capacity And Energy Consumption Of Complex Resistive Switch Networks, Jens Bürger, Alireza Goudarzi, Darko Stefanovic, Christof Teuscher

Electrical and Computer Engineering Faculty Publications and Presentations

Resistive switches are a class of emerging nanoelectronics devices that exhibit a wide variety of switching characteristics closely resembling behaviors of biological synapses. Assembled into random networks, such resistive switches produce emerging behaviors far more complex than that of individual devices. This was previously demonstrated in simulations that exploit information processing within these random networks to solve tasks that require nonlinear computation as well as memory. Physical assemblies of such networks manifest complex spatial structures and basic processing capabilities often related to biologically-inspired computing. We model and simulate random resistive switch networks and analyze their computational capacities. We provide a …

Face Recognition With Multi-Stage Matching Algorithms, Xianming Chen

Dissertations

For every face recognition method, the primary goal is to achieve higher recognition accuracy and spend less computational costs. However, as the gallery size increases, especially when one probe image corresponds to only one training image, face recognition becomes more and more challenging. First, a larger gallery size requires more computational costs and memory usage. Meanwhile, that the large gallery sizes degrade the recognition accuracy becomes an even more significant problem to be solved.

A coarse parallel algorithm that equally divides training images and probe images into multiple processors is proposed to deal with the large computational costs and huge …

Free2play, Corey Lee Wilson

Computer Engineering

Free2Play is a website based upon the wildly popular PC video game League of Legends created by Riot Gaming. The website contains helpful information for new and old players of the game, such as articles containing the latest League of Legends new, a rune calculator, and recommended item builds for characters. The website uses HTML5, jquery, node.js, MySQL, and PHP to pull data from Riot’s web API and Champion.gg’s website.

Bep: Bit Error Pattern Measurement And Analysis In Ieee 802.11, Jiayue Li, Zimu Zhou, Chen Zhang, Liang Yin, Lionel M. Ni

Research Collection School Of Computing and Information Systems

The IEEE 802.11 is a set of Media Access Control (MAC) and Physical Layer (PHY) specifications which concern the Wireless Local Area Network (WLAN) service. However, most IEEE 802.11 WLAN services are easily affected by external elements, such as the homogeneous interference caused by the high-density deployment of IEEE 802.11 devices, the attenuation effect caused by complicated indoor obstacles, and the heterogeneous interference caused by other devices which operate out of unlicensed 2.4GHz ISM bands. In this paper, we first present a method to capture IEEE 802.11n Bit Error Patterns (BEP) under the network effect such as the homogeneous interference …

Adaptive Scaling Of Cluster Boundaries For Large-Scale Social Media Data Clustering, Lei Meng, Ah-Hwee Tan, Donald C. Wunsch

Research Collection School Of Computing and Information Systems

The large scale and complex nature of social media data raises the need to scale clustering techniques to big data and make them capable of automatically identifying data clusters with few empirical settings. In this paper, we present our investigation and three algorithms based on the fuzzy adaptive resonance theory (Fuzzy ART) that have linear computational complexity, use a single parameter, i.e., the vigilance parameter to identify data clusters, and are robust to modest parameter settings. The contribution of this paper lies in two aspects. First, we theoretically demonstrate how complement coding, commonly known as a normalization method, changes the …

Adaptive Duty Cycling In Sensor Networks With Energy Harvesting Using Continuous-Time Markov Chain And Fluid Models, Ronald Wai Hong Chan, Pengfei Zhang, Ido Nevat, Sai Ganesh Nagarajan, Alvin Cerdena Valera, Hwee Xian Tan

Research Collection School Of Computing and Information Systems

The dynamic and unpredictable nature of energy harvesting sources available for wireless sensor networks, and the time variation in network statistics like packet transmission rates and link qualities, necessitate the use of adaptive duty cycling techniques. Such adaptive control allows sensor nodes to achieve long-run energy neutrality, where energy supply and demand are balanced in a dynamic environment such that the nodes function continuously. In this paper, we develop a new framework enabling an adaptive duty cycling scheme for sensor networks that takes into account the node battery level, ambient energy that can be harvested, and application-level QoS requirements. We …

Cockpit Video Recorder & Streaming For Training Purposes, Ruthvik Adloori

Theses and Dissertations

This paper is my Master's Thesis which is based on Cockpit Voice and Video Recorder which is an enhancement to the current Cockpit Voice Recorder. The main aim of my project is to use the system for training of pilots about cockpit functions and different in flight scenarios. The key factors for efficient Human-Machine systems such as situation awareness, decision making, risk management are studied in this thesis. The complexity in the design and the way to override such complexity is also demonstrated in this paper. A g1 impse of understanding through emotions is also discussed as an advantage in …

On Reliability Of Smart Grid Neighborhood Area Networks, Shengjie Xu, Yi Qian, Rose Qingyang Hu

Department of Electrical and Computer Engineering: Faculty Publications

With the integration of the advanced computing and communication technologies, smart grid system is dedicated to enhance the efficiency and the reliability of future power systems greatly through renewable energy resources, as well as distributed communication intelligence and demand response. Along with advanced features of smart grid, the reliability of smart grid communication system emerges to be a critical issue, since millions of smart devices are interconnected through communication networks throughout critical power facilities, which has an immediate and direct impact on the reliability of the entire power infrastructure. In this paper, we present a comprehensive survey of reliability issues …

Transforming C Openmp Programs For Verification In Civl, Michael Rogers

School of Computing: Dissertations, Theses, and Student Research

There are numerous way to express parallelism which can make it challenging for developers to verify these programs. Many tools only target a single dialect but the Concurrency Intermediate Verification Language (CIVL) targets MPI, Pthreads, and CUDA. CIVL provides a general concurrency model that can represent pro- grams in a variety of concurrency dialects. CIVL includes a front-end that support all of the dialects mentioned above. The back-end is a verifier that uses model checking and symbolic execution to check standard properties.

In this thesis, we have designed and implemented a transformer that will take C OpenMP programs and transform …

Using Software-Defined Networking To Improve Campus, Transport And Future Internet Architectures, Adrian Lara

School of Computing: Dissertations, Theses, and Student Research

Software-defined Networking (SDN) promises to redefine the future of networking. Indeed, SDN-based networks have unique capabilities such as centralized control, flow abstraction, dynamic updating of forwarding rules and software-based traffic analysis. SDN-based networks decouple the data plane from the control plane, migrating the latter to a software controller. By adding a software layer between network devices and applications, features such as network virtualization and automated management are simpler to achieve.

In this dissertation, we show how SDN-based deployments simplify network management at multiple scales such as campus and transport networks, as well as future Internet architectures. First, we propose OpenSec, …

Signage Recognition Based Wayfinding System For The Visually Impaired, Abdullah Khalid Ahmed

Masters Theses

Persons of visual impairment make up a growing segment of modern society. To cater to the special needs of these individuals, society ought to consider the design of special constructs to enable them to fulfill their daily necessities. This research proposes a new method for text extraction from indoor signage that will help persons of visual impairment maneuver in unfamiliar indoor environments, thus enhancing their independence and quality of life.

In this thesis, images are acquired through a video camera mounted on glasses of the walking person. Frames are then extracted and used in an integrated framework that applies Maximally …

Design Of A New Digital Relay For Transmission Line Fault Detection, Classification And Localization Based On A New Composite Relay And Artificial Neural Network Approach, Ahmed Sabri Altaie

Masters Theses

This thesis focuses on new approach to detect, classify, and localize the fault in transmission line. Firstly, fault detection was carried out using the New Composite Relay (CR) which, has different characteristics and the ability to detect any type of fault including series faults. Secondly, fault classification was conducted using the Feed Forward Artificial Neural Network (FFANN). In addition, the fault classification led to the investigation of the best use of the FFANN. The data used come from MATLAB/SIMULINK three phase series compensated network. The results obtained using FFANN, were compared with the type of the fault that have been …

Design Of Digital Down Converter Chain For Software Defined Radio Systems On Fpga, Nagarjun Marappa

Masters Theses

Modern communication systems have increasingly attempted to trade off the digital signal processing for analog circuitry. In performing this tradeoff, advanced algorithms have been implemented in both custom programmable hardware and in software; such systems are commonly called Software Defined Radios (SDR). Advanced software defined radios consist of highly configurable hardware and computers used as digital signal processing (DSP) platforms that provide the technology for realizing current and future generations of digital wireless communication infrastructure. Many sophisticated signal processing tasks are performed in SDR, including compression algorithms, channel estimation, equalization, forward error correction and protocol management. This research has focused …

A High Performance Architecture For An Exact Match Short-Read Aligner Using Burrows-Wheeler Aligner On Fpgas, Dana Abdul Qader

Masters Theses

Due to modern DNA sequencing technologies vast amount of short DNA sequences known as short-reads is generated. Biologists need to be able to align the short-reads to a reference genome to be able to make scientific use of the data. Fast and accurate short-read aligner programs are needed to keep up with the pace at which this data is generated. Field Programmable Gate Arrays have been widely used to accelerate many data-intensive bioinformatics applications.

Burrows-Wheeler Transform has been used in the theory of string matching which has led to the development of many short-read alignment programs. This thesis presents a …

Parking Lot Monitoring System Using An Autonomous Quadrotor Uav, Venkataraman Ganesh

All Theses

The main goal of this thesis is to develop a drone-based parking lot monitoring system using low-cost hardware and open-source software. Similar to wall-mounted surveillance cameras, a drone-based system can monitor parking lots without affecting the flow of traffic while also offering the mobility of patrol vehicles. The Parrot AR Drone 2.0 is the quadrotor drone used in this work due to its modularity and cost efficiency. Video and navigation data (including GPS) are communicated to a host computer using a Wi-Fi connection. The host computer analyzes navigation data using a custom flight control loop to determine control commands to …

Compression Of Climate Data Through Artificial Neural Networks, Astha Puri

UNLV Theses, Dissertations, Professional Papers, and Capstones

Lately, there has been a tremendous increase in the number of climate monitoring

stations in various parts of the country producing abundant climate data. Among climate data parameters, humidity and temperature are the two parameters influencing hydrological and agricultural processes, weather monitoring, and having critical effect on living organisms. As more data is being generated over time, there is a strong need to develop compression methods for efficient transfer and storage of this data.

The main goal of this thesis is to perform compression of humidity and temperature

data via prediction. As these are critical components of climate, it is …

Learning Query And Image Similarities With Ranking Canonical Correlation Analysis, Ting Yao, Tao Mei, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

One of the fundamental problems in image search is to learn the ranking functions, i.e., similarity between the query and image. The research on this topic has evolved through two paradigms: feature-based vector model and image ranker learning. The former relies on the image surrounding texts, while the latter learns a ranker based on human labeled query-image pairs. Each of the paradigms has its own limitation. The vector model is sensitive to the quality of text descriptions, and the learning paradigm is difficult to be scaled up as human labeling is always too expensive to obtain. We demonstrate in this …

Communication Between Virtual Emulation System And Plc Modbus/Tcp Protocol, Huang Benjamin Huang

Morehead State Theses and Dissertations

A thesis presented to the faculty of the College of Science and Technology at Morehead State University in partial fulfillment of the requirements for the Degree of Master of Science by Huang (Benjamin) Huang on November 20, 2015.