Computer Engineering Commons^™

2012 (Fall) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department

ENSI Informer Magazine Archive

The ENSI Informer Magazine published in the fall of 2012.

Efficient Algorithms For Improving The Accuracy In Motifs Prediction, Jerlin C. Merlin

Master's Theses

Analysis of sequence homology has always played a major role in the understanding of biological factors such as protein domain identification, gene product relationships, and gene function determination. Short contiguous protein sequences that are conserved across proteins provide important information about such factors, and are of at most 15 residues in length. These segments of proteins are known as minimotifs. Identifying minimotifs has been of much use in the formulation of the hypothesis about the biological functions that otherwise might be uncharacterized. Mechanisms of motif predictions such as Minimotif Miner are widely used for predicting minimotifs. However, due to the …

Effects Of Architecture On Information Leakage Of A Hardware Advanced Encryption Standard Implementation, Eric A. Koziel

Theses and Dissertations

Side-channel analysis (SCA) is a threat to many modern cryptosystems. Many countermeasures exist, but are costly to implement and still do not provide complete protection against SCA. A plausible alternative is to design the cryptosystem using architectures that are known to leak little information about the cryptosystem's operations. This research uses several common primitive architectures for the Advanced Encryption Standard (AES) and assesses the susceptibility of the full AES system to side-channel attack for various primitive configurations. A combined encryption/decryption core is also evaluated to determine if variation of high-level architectures affects leakage characteristics. These different configurations are evaluated under …

Passive Synthetic Aperture Radar Imaging Using Commercial Ofdm Communication Networks, Jose R. Gutierrez Del Arroyo

Theses and Dissertations

Modern communication systems provide myriad opportunities for passive radar applications. OFDM is a popular waveform used widely in wireless communication networks today. Understanding the structure of these networks becomes critical in future passive radar systems design and concept development. This research develops collection and signal processing models to produce passive SAR ground images using OFDM communication networks. The OFDM-based WiMAX network is selected as a relevant example and is evaluated as a viable source for radar ground imaging. The monostatic and bistatic phase history models for OFDM are derived and validated with experimental single dimensional data. An airborne passive collection …

A Study Of Executable Model Based Systems Engineering From Dodaf Using Simulink, Weston J. Hanoka, Michael H. Ryan

Theses and Dissertations

Diagrams and visuals often cannot adequately capture a complex system’s architecture for analysis. The Department of Defense Architectural Framework (DoDAF), written to follow the Unified Modeling Language (UML), is a collection of mandated common architectural products for interoperability among the DoD components. In this study, DoDAF products from as-is Remotely Piloted Aircraft (RPA) Satellite Communication (SATCOM) systems have been utilized for the creation of executable architectures as part of an Executable Model Based Systems Engineering (EMBSE) process. EMBSE was achieved using Simulink, a software tool for modeling, simulating and analyzing dynamic systems.

This study has demonstrated that DoDAF products can …

Intelligent Behavioral Action Aiding For Improved Autonomous Image Navigation, Kwee Guan Eng

Theses and Dissertations

In egomotion image navigation, errors are common especially when traversing areas with few landmarks. Since image navigation is often used as a passive navigation technique in Global Positioning System (GPS) denied environments; egomotion accuracy is important for precise navigation in these challenging environments. One of the causes of egomotion errors is inaccurate landmark distance measurements, e.g., sensor noise. This research determines a landmark location egomotion error model that quantifies the effects of landmark locations on egomotion value uncertainty and errors. The error model accounts for increases in landmark uncertainty due to landmark distance and image centrality. A robot then uses …

Subwavelength Ripples Adjustment Based On Electron Dynamics Control By Using Shaped Ultrafast Laser Pulse Trains, Lan Jiang, Xuesong Shi, Xin Li, Yanping Yuan, Cong Wang, Yongfeng Lu

Department of Electrical and Computer Engineering: Faculty Publications

This study reveals that the periods, ablation areas and orientations of periodic surface structures (ripples) in fused silica can be adjusted by using designed femtosecond (fs) laser pulse trains to control transient localized electron dynamics and corresponding material properties. By increasing the pulse delays from 0 to 100fs, the ripple periods are changed from ~550nm to ~255nm and the orientation is rotated by 90°. The nearwavelength/subwavelength ripple periods are close to the fundamental/second-harmonic wavelengths in fused silica respectively. The subsequent subpulse of the train significantly impacts free electron distributions generated by the previous subpulse(s), which might influence the formation mechanism …

Fast Super-Resolution Using An Adaptive Wiener Filter With Robustness To Local Motion, Russell C. Hardie, Kenneth J. Barnard

Electrical and Computer Engineering Faculty Publications

We present a new adaptive Wiener filter (AWF) super-resolution (SR) algorithm that employs a global background motion model but is also robust to limited local motion. The AWF relies on registration to populate a common high resolution (HR) grid with samples from several frames. A weighted sum of local samples is then used to perform nonuniform interpolation and image restoration simultaneously. To achieve accurate subpixel registration, we employ a global background motion model with relatively few parameters that can be estimated accurately. However, local motion may be present that includes moving objects, motion parallax, or other deviations from the background …

Scalable Distributed Communication Architectures To Support Advanced Metering Infrastructure In Smart Grid, Jian Zhou, Rose Qingyang Hu, Yi Qian

Department of Electrical and Computer Engineering: Faculty Publications (to 2015)

In this paper, we investigate the scalability of three communication architectures for advanced metering infrastructure (AMI) in smart grid. AMI in smart grid is a typical cyber-physical system (CPS) example, in which large amount of data from hundreds of thousands of smart meters are collected and processed through an AMI communication infrastructure. Scalability is one of the most important issues for the AMI deployment in smart grid. In this study, we introduce a new performance metric, accumulated bandwidth distance product (ABDP), to represent the total communication resource usages. For each distributed communication architecture, we formulate an optimization problem and obtain …

Heuristic Algorithms For Optimization Of Task Allocation And Result Distribution In Peer-To-Peer Computing Systems, Grzegorz Chmaj, Krzysztof Walkowiak, Michal Tarnawski, Michal Kucharzak

Electrical & Computer Engineering Faculty Research

Recently, distributed computing system have been gaining much attention due to a growing demand for various kinds of effective computations in both industry and academia. In this paper, we focus on Peer-to-Peer (P2P) computing systems, also called public-resource computing systems or global computing systems. P2P computing systems, contrary to grids, use personal computers and other relatively simple electronic equipment (e.g., the PlayStation console) to process sophisticated computational projects. A significant example of the P2P computing idea is the BOINC (Berkeley Open Infrastructure for Network Computing) project. To improve the performance of the computing system, we propose to use the P2P …

Bayesian Speaker Adaptation Based On A New Hierarchical Probabilistic Model, Wen-Lin Zhang, Wei-Qiang Zhang, Bi-Cheng Li, Dan Qu, Michael T. Johnson

Electrical and Computer Engineering Faculty Research and Publications

In this paper, a new hierarchical Bayesian speaker adaptation method called HMAP is proposed that combines the advantages of three conventional algorithms, maximum a posteriori (MAP), maximum-likelihood linear regression (MLLR), and eigenvoice, resulting in excellent performance across a wide range of adaptation conditions. The new method efficiently utilizes intra-speaker and inter-speaker correlation information through modeling phone and speaker subspaces in a consistent hierarchical Bayesian way. The phone variations for a specific speaker are assumed to be located in a low-dimensional subspace. The phone coordinate, which is shared among different speakers, implicitly contains the intra-speaker correlation information. For a specific speaker, …

Noise Impacts From Professional Dog Grooming Forced-Air Dryers, Peter M. Scheifele, Michael T. Johnson, David C. Byrne, John G. Clark, Ashley Vandlik, Laura W. Kretschmer, Kristine E. Sonstrom

Electrical and Computer Engineering Faculty Research and Publications

This study was designed to measure the sound output of four commonly used brands of forced-air dryers used by dog groomers in the United States. Many dog groomers have questions about the effect of this exposure on their hearing, as well as on the hearing of the dogs that are being groomed. Readings taken from each dryer at 1 meter (the likely distance of the dryer from the groomer and the dog) showed average levels ranging from 105.5 to 108.3 dB SPL or 94.8 to 108.0 dBA. Using the 90 dBA criterion required by the US Occupational Safety and Health …

Active Storage And Ssd Caching In An Object Storage Environment, Michael T. Runde

Master's Theses

The advancing performance and lowering costs required to implement additional processing power on system peripherals such as disk drives are increasingly allowing additional computing ability to be located directly on individual drives. Active Storage attempts to take advantage of this excess by moving some computationally intensive applications directly to the disk drives. This can remove the bottlenecks seen through interconnects between the drives and the CPU of an initiating system as well as remove the need for systems to handle these applications.

The contributions of this thesis are in two areas. The first is the development of a framework designed …

Automation Of Landmark Selection For Rodent Brain Mri-Histology Registration Using Thin-Plate Splines, Ayan Sengupta

School of Computing: Dissertations, Theses, and Student Research

Image registration is the process of aligning two different images of the same object taken at different times, at different orientations or using different instruments. This is common in medical applications since multiple modalities are used to image different parts of the body. This is an important early step in many diagnostic procedures such as change detection, monitoring tumor or quantifying spread of a disease. The widely used landmark based registration approach is tedious, time consuming, inconsistent and error prone. Furthermore, the standard schemes based on rigid and affine transformation can only describe global geometric differences between the objects of …

Alignment, Clustering And Extraction Of Structured Motifs In Dna Promoter Sequences, Faisal Abdulmalek Alobaid

Electrical Engineering and Computer Science - Dissertations

A simple motif is a short DNA sequence found in the promoter region and believed to act as a binding site for a transcription factor protein. A structured motif is a sequence of simple motifs (boxes) separated by short sequences (gaps). Biologists theorize that the presence of these motifs play a key role in gene expression regulation. Discovering these patterns is an important step towards understanding protein-gene and gene-gene interaction thus facilitates the building of accurate gene regulatory network models. DNA sequence motif extraction is an important problem in bioinformatics. Many studies have proposed algorithms to solve the problem instance …

A Novel Dataset-Similarity-Aware Approach For Evaluating Stability Of Software Metric Selection Techniques, Taghi M. Khoshgoftaar, Huanjing Wang, Randall Wald, Amri Napolitano

Computer Science Faculty Publications

Software metric (feature) selection is an important preprocessing step before building software defect prediction models. Although much research has been done analyzing the classification performance of feature selection methods, fewer works have focused on their stability (robustness). Stability is important because feature selection methods which reliably produce the same results despite changes to the data are more trustworthy. Of the papers studying stability, most either compare the features chosen from different random subsamples of the dataset or compare each random subsample with the original dataset. These either result in an unknown degree of overlap between the subsamples, or comparing datasets …

Analyzing The Non-Functional Requirements In The Desharnais Dataset For Software Effort Estimation, Ali Bou Nassif, Luiz Fernando Capretz, Danny Ho

Electrical and Computer Engineering Publications

Studying the quality requirements (aka Non-Functional Requirements (NFR)) of a system is crucial in Requirements Engineering. Many software projects fail because of neglecting or failing to incorporate the NFR during the software life development cycle. This paper focuses on analyzing the importance of the quality requirements attributes in software effort estimation models based on the Desharnais dataset. The Desharnais dataset is a collection of eighty one software projects of twelve attributes developed by a Canadian software house. The analysis includes studying the influence of each of the quality requirements attributes, as well as the influence of all quality requirements attributes …

Simulation, Development And Deployment Of Mobile Wireless Sensor Networks For Migratory Bird Tracking, William P. Bennett Jr.

School of Computing: Dissertations, Theses, and Student Research

This thesis presents CraneTracker, a multi-modal sensing and communication system for monitoring migratory species at the continental level. By exploiting the robust and extensive cellular infrastructure across the continent, traditional mobile wireless sensor networks can be extended to enable reliable, low-cost monitoring of migratory species. The developed multi-tier architecture yields ecologists with unconventional behavior information not furnished by alternative tracking systems at such a large scale and for a low-cost. The simulation, development and implementation of the CraneTracker software system is presented. The system is shown effective through multiple proxy deployments on wildlife and has been operational for 10 months …

Node Filtering And Face Routing For Sensor Network, Umang Amatya

UNLV Theses, Dissertations, Professional Papers, and Capstones

Greedy forward routing and face routing algorithms have been extensively used for sending messages in sensor networks. In this thesis, we consider the problem of filtering redundant nodes in a sensor network as a pre-processing step for face routing. We propose two algorithms for identifying redundant nodes. We test the performance of proposed filtering algorithms on generated networks. The prototype algorithm for testing the proposed algorithms has been implemented in the Java programming language. Experimental investigation shows that the proposed filtering algorithms are effective in removing redundant nodes without compromising the network connectivity.

Characterization Of An Advanced Neuron Model, Christopher Echanique

HIM 1990-2015

This thesis focuses on an adaptive quadratic spiking model of a motoneuron that is both versatile in its ability to represent a range of experimentally observed neuronal firing patterns as well as computationally efficient for large network simulation. The objective of research is to fit membrane voltage data to the model using a parameter estimation approach involving simulated annealing. By manipulating the system dynamics of the model, a realizable model with linear parameterization (LP) can be obtained to simplify the estimation process. With a persistently excited current input applied to the model, simulated annealing is used to efficiently determine the …

Spectral Analysis Of Encrypted Chaotic Signals Using Fast Fourier Transforms And Laboratory Spectral Analyzers, Monish Ranjan Chatterjee, Abhinay Kundur

Electrical and Computer Engineering Faculty Publications

The use of acousto-optic chaos, as manifested via first-order feedback in an acousto-optic Bragg cell, in encrypting a message wave and subsequently recovering the message in the receiver using a chaotic heterodyne strategy, has been reported recently [1-3]. In examining the dynamical system analytically using computer simulation, (expected) modulated chaos waveforms are obtained within specified observation windows.

Because of the relatively random nature inherent in chaos waveforms, it is essentially impossible to ascertain from the visual display of the chaotic wave whether a given message signal has in fact modulated the chaotic "carrier". In fact, it has been observed from …

Measuring Merci: Exploring Data Mining Techniques For Examining Surgical Outcomes Of Stroke Patients, Matthew Ronald Mcnabb

Masters Theses and Doctoral Dissertations

Mechanical Embolus Removal in Cerebral Ischemia (MERCI) has been supported by medical trials as an improved method of treating ischemic stroke past the safe window of time for administering clot-busting drugs, and was released for medical use in 2004. The importance of analyzing real-world data collected from MERCI clinical trials is key to providing insights on the effectiveness of MERCI. Most of the existing data analysis on MERCI results has thus far employed conventional statistical analysis techniques. To the best of the knowledge acquired in preliminary research, advanced data analytics and data mining techniques have not yet been systematically applied. …

Non-Blocking Concurrent Operations On Heap, Mahesh Acharya

UNLV Theses, Dissertations, Professional Papers, and Capstones

We present a non-blocking implementation for the concurrent Heap data structure in the asynchronous shared memory system. The system may be a traditional one with a single processor with multiple threads, or it may be the one with multiple processors each possibly with multiple threads. Our implementation supports readMin, deleteMin, and insert operations on the heap. The deleteMin and insert operations are non-blocking operations, whereas the readMin is wait-free. One easy approach of using a heap in multi-threading environment could be by locking the entire heap before performing any operation. This would make the implementation very slow to have any …

Wavelets In Intelligent Transportation Systems: Data Compression And Incident Detection, Shaurya Agarwal

UNLV Theses, Dissertations, Professional Papers, and Capstones

Research show that wavelets can be used efficiently in denoising and feature extraction of a given signal. This thesis discusses about intelligent transportation systems(ITS), its requirement and benefits. We explore use of wavelets in intelligent transportation systems for knowledge discovery, compression and incident detection. In the first section of thesis, we focus on the following problems related to traffic matrix: data compression, retrieval and visualization. We propose a methodology using wavelet transform for data visualization and compression of traffic data. Aim is to research on the wavelet compression technique for the traffic data, come up with the performance of various …

Cpu Scheduling For Power/Energy Management On Heterogeneous Multicore Processors, Rajesh Patel

UNLV Theses, Dissertations, Professional Papers, and Capstones

Power and energy have become increasingly important concerns in the design and implementation of today's multicore/manycore chips. Many methods have been proposed to reduce a microprocessor's power usage and associated heat dissipation, including scaling a core's operating frequency. However, these techniques do not consider the dynamic performance characteristics of an executing process at runtime, the execution characteristics of the entire task to which this process belongs, the process's priority, the process's cache miss/cache reference ratio, the number of context switches and CPU migrations generated by the process, nor the system load. Also, many of the techniques that employ dynamic frequency …

Socialq&A: A Novel Approach To Notifiying The Correct Users In Question And Answering Systems, Nikhil Vithlani

All Theses

Question and Answering (Q&A) systems are currently in use by a large
number of Internet users. Q&A systems play a vital role in our daily life as
an important platform for information and knowledge sharing. Hence, much
research has been devoted to improving the performance of Q&A systems,
with a focus on improving the quality of answers provided by users, reducing
the wait time for users who ask questions, using a knowledge base to provide
answers via text mining, and directing questions to appropriate users. Due
to the growing popularity of Q&A systems, the number of questions in the
system …

Routing Over The Interplanetary Internet, Joyeeta Mukherjee

School of Computing: Dissertations, Theses, and Student Research

Future space exploration demands a Space Network that will be able to connect spacecrafts with one another and in turn with Earth's terrestrial Internet and hence efficiently transfer data back and forth. The feasibility of this technology would enable common people to directly access telemetric data from distant planets and satellites. The concept of an Interplanetary Internet (IPN) is only in its incubation stage and considerable amount of common standards and research is required before widespread deployment can occur to make IPN feasible.

We provide a comprehensive survey that presents a picture of the current space networking technologies and architectures. …

Statistical Software Properties: Definition, Inference And Monitoring, Javier A. Darsie

School of Computing: Dissertations, Theses, and Student Research

Software properties define how software systems should operate. Specifying correct properties, however, can be difficult and expensive as it requires deep knowledge of the system's expected behavior and the environment in which it operates. Automated analysis techniques to infer properties from code or code executions can mitigate that cost, but are still unable to go beyond state properties and the simplest patterns of temporal properties. This limitation renders properties that sacrifice fault detection power.

To address this problem, we introduce a new type of software properties called \textit{statistical properties}, which characterize significant statistical relationships among the values of variables across …

Ambient Habitat Noise And Vibration At The Georgia Aquarium, Peter M. Scheifele, Michael T. Johnson, Laura W. Kretschmer, John G. Clark, D. Kemper, G. Potty

Electrical and Computer Engineering Faculty Research and Publications

Underwater and in-air noise evaluations were completed in performance pool systems at Georgia Aquarium under normal operating conditions and with performance sound tracks playing. Ambient sound pressure levels at in-pool locations, with corresponding vibration measures from life support system (LSS) pumps, were measured in operating configurations, from shut down to full operation. Results indicate noise levels in the low frequency ranges below 100 Hz were the highest produced by the LSS relative to species hearing thresholds. The LSS had an acoustic impact of about 10 dB at frequencies up to 700 Hz, with a 20 dB re 1 μPa impact …

Data Mining Of Protein Databases, Christopher Assi

School of Computing: Dissertations, Theses, and Student Research

Data mining of protein databases poses special challenges because many protein databases are non-relational whereas most data mining and machine learning algorithms assume the input data to be a relational database. Protein databases are non-relational mainly because they often contain set data types. We developed new data mining algorithms that can restructure non-relational protein databases so that they become relational and amenable for various data mining and machine learning tools. We applied the new restructuring algorithms to a pancreatic protein database. After the restructuring, we also applied two classification methods, such as decision tree and SVM classifiers and compared their …