Computer Engineering Commons^™

A Graph-Based Reinforcement Learning Method With Converged State Exploration And Exploitation, Han Li, Tianding Chen, Hualiang Teng, Yingtao Jiang

Civil and Environmental Engineering and Construction Faculty Research

In any classical value-based reinforcement learning method, an agent, despite of its continuous interactions with the environment, is yet unable to quickly generate a complete and independent description of the entire environment, leaving the learning method to struggle with a difficult dilemma of choosing between the two tasks, namely exploration and exploitation. This problem becomes more pronounced when the agent has to deal with a dynamic environment, of which the configuration and/or parameters are constantly changing. In this paper, this problem is approached by first mapping a reinforcement learning scheme to a directed graph, and the set that contains all …

A Distributed Real-Time Short-Term Solar Irradiation Forecasting Network For Photovoltaic Systems, Michael Adelbert Gacusan

UNLV Theses, Dissertations, Professional Papers, and Capstones

Solar irradiation forecasting is essential for PV connected electrical grids to maintain reliability, stability, and effective matching of real-time demand to power distribution. This research paper develops and evaluates proposed forecasting methods using wireless sensor networks. Each node of the network is capable of monitoring illuminance data and communicate it through RF and/or WiFi. The nodes are calibrated with respect to irradiance data from an industry-standard pyranometer. Power consumption of each node type is also collected at different operating states. The proposed sensor network can estimate a cloud motion vector or a cloud shadow’s speed and direction from the data …

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 …

Design On High Performance Nanoscale Cmos Circuits With Low Temperature Sensitivity, Ming Zhu

UNLV Theses, Dissertations, Professional Papers, and Capstones

With the rapid development of integrated circuit (IC) design and manufacturing technology, the transistor size now can be shrunk into only couple of nanometers whereas billions of transistors can be squeezed into a square millimeter, providing unprecedented computation power. However, accompanied with continuous device miniaturization and increased integration density is the explosive growth of on-chip power dissipation and a wide range of temperature fluctuation, which can heavily and negatively affect the delay performance of the circuit, or in the worst case, the circuit may malfunction and the system can be unreliable. Therefore, improved performance resilience against temperature variations has become …

Automated Quantification Of White Blood Cells In Light Microscopic Images Of Injured Skeletal Muscle, Yang Jiao

UNLV Theses, Dissertations, Professional Papers, and Capstones

Muscle regeneration process tracking and analysis aim to monitor the injured muscle tissue section over time and analyze the muscle healing procedure. In this procedure, as one of the most diverse cell types observed, white blood cells (WBCs) exhibit dynamic cellular response and undergo multiple protein expression changes. The characteristics, amount, location, and distribution compose the action of cells which may change over time. Their actions and relationships over the whole healing procedure can be analyzed by processing the microscopic images taken at different time points after injury. The previous studies of muscle regeneration usually employ manual approach or basic …

Cyclist Detection, Tracking, And Trajectory Analysis In Urban Traffic Video Data, Farideh Foroozandeh Shahraki

UNLV Theses, Dissertations, Professional Papers, and Capstones

The major objective of this thesis work is examining computer vision and machine learning detection methods, tracking algorithms and trajectory analysis for cyclists in traffic video data and developing an efficient system for cyclist counting. Due to the growing number of cyclist accidents on urban roads, methods for collecting information on cyclists are of significant importance to the Department of Transportation. The collected information provides insights into solving critical problems related to transportation planning, implementing safety countermeasures, and managing traffic flow efficiently. Intelligent Transportation System (ITS) employs automated tools to collect traffic information from traffic video data. In comparison to …

Improving Pattern Recognition And Neural Network Algorithms With Applications To Solar Panel Energy Optimization, Ernesto Zamora Ramos

UNLV Theses, Dissertations, Professional Papers, and Capstones

Artificial Intelligence is a big part of automation and with today's technological advances, artificial intelligence has taken great strides towards positioning itself as the technology of the future to control, enhance and perfect automation. Computer vision includes pattern recognition and classification and machine learning. Computer vision is at the core of decision making and it is a vast and fruitful branch of artificial intelligence. In this work, we expose novel algorithms and techniques built upon existing technologies to improve pattern recognition and neural network training, initially motivated by a multidisciplinary effort to build a robot that helps maintain and optimize …

Analog And Mixed Signal Verification Using Satisfiability Solver On Discretized Models, Nikita Ramesh Wanjale

UNLV Theses, Dissertations, Professional Papers, and Capstones

With increasing demand of performance constraints and the ever reducing size of the IC chips, analog and mixed-signal designs have become indispensable and increasingly complex in modern CMOS technologies. This has resulted in the rise of stochastic behavior in circuits, making it important to detect all the corner cases and verify the correct functionality of the design under all circumstances during the earlier stages of the design process. It can be achieved by functional or formal verification methods, which are still widely unexplored for Analog and Mixed-Signal (AMS) designs.

Design Verification is a process to validate the performance of the …

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 …

Design And Implementation Of Benes/Clos On-Chip Interconnection Networks, Yikun Jiang

UNLV Theses, Dissertations, Professional Papers, and Capstones

Networks-on-Chip (NoCs) have emerged as the key on-chip communication architecture for multiprocessor systems-on-chip and chip multiprocessors. Single-hop non-blocking networks have the advantage of providing uniform latency and throughput, which is important for cachecoherent NoC systems. Existing work shows that Benes networks have much lower transistor count and smaller circuit area but longer delay than crossbars. To reduce the delay, we propose to design the Clos network built with larger size switches. Using less than half number of stages than the Benes network, the Clos network with 4x4 switches can significantly reduce the delay. This dissertation focuses on designing high performance …

Design, Fabrication And Testing Of Monolithic Low-Power Passive Sigma-Delta Analog-To-Digital Converters, Angsuman Roy

UNLV Theses, Dissertations, Professional Papers, and Capstones

Analog-to-digital converters are critically important in electronic systems. The

difficulty in meeting high performance parameters increases as integrated circuit design

process technologies advance into the deep nanometer region. Sigma-delta analog-todigital

converters are an attractive option to fulfill many data converter requirements.

These data converters offer high performance while relaxing requirements on the precision

of components within an integrated circuit. Despite this, the active integrators found within

sigma-delta analog-to-digital converters present two main challenges. These challenges are

the power consumption of the active amplifier and achieving gain-bandwidth necessary for

sigma-delta data converters in deep nanometer process technologies. Both of these

challenges …

Synthesis And Characterization Of Graphene, Ashok Em Sudhakar

UNLV Theses, Dissertations, Professional Papers, and Capstones

Graphene is an important nanoscale material with unique electronic and optical properties. Due to its many potential applications, grapheme was the subject of a Nobel Prize in physics 2010; Andre Geim and Kostya Novoselov of Manchester University received the Nobel Prize for demonstrating the ability to create single atom thick graphene layers from bulk graphite. Since then, many alternative synthesis techniques and device applications of graphene have been explored. An important and unique property of graphene is its excellent thermal properties. Graphene has a two dimensional structure and the thermal properties are significantly different than three dimensional bulk materials. Using …

Mcnp6 Computational-Based Sensitivity Propagation Analysis Of Continuous Neutron Cross-Sections Using The Godiva (Hmf-001) And The Godiver (Hmf-004) Benchmark Criticality Study Cases, Lawrence James Lakeotes

UNLV Theses, Dissertations, Professional Papers, and Capstones

There has been a reduction in funding for theoretical and applied research for improving the nation's database of continuous neutron cross-sections at BNL-NNDC. From 1940 through the late 1980s, research and applied development produced volumes of reliable neutron continuous cross-sections for many isotopes. Currently, the cross-section work has been mainly computational. The focus of this research is mainly centered on the requirements for improving thermal cross-sections to support reactor operations and fuel storage. The research efforts will also helpfully aid in the fast fission spectrum in order to support fast reactor designs for improving safety analysis and feedback coefficients.

This …

Efficient Algorithms For Clustering Polygonal Obstacles, Sabbir Kumar Manandhar

UNLV Theses, Dissertations, Professional Papers, and Capstones

Clustering a set of points in Euclidean space is a well-known problem having applications in pattern recognition, document image analysis, big-data analytics, and robotics. While there are a lot of research publications for clustering point objects, only a few articles have been reported for clustering a given distribution of obstacles. In this thesis we examine the development of efficient algorithms for clustering a given set of convex obstacles in the 2D plane. One of the methods presented in this work uses a Voronoi diagram to extract obstacle clusters. We also consider the implementation issues of point/obstacle clustering algorithms.

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 …

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 …

Practical Guidance For Integrating Data Management Into Long-Term Ecological Monitoring Projects, Robert D. Sutter, Susan Wainscott, John R. Boetsch, Craig Palmer, David J. Rugg

Library Faculty Research

Long-term monitoring and research projects are essential to understand ecological change and the effectiveness of management activities. An inherent characteristic of long-term projects is the need for consistent data collection over time, requiring rigorous attention to data management and quality assurance. Recent papers have provided broad recommendations for data management; however, practitioners need more detailed guidance and examples. We present general yet detailed guidance for the development of comprehensive, concise, and effective data management for monitoring projects. The guidance is presented as a graded approach, matching the scale of data management to the needs of the organization and the complexity …

Predicting Cross-Gaming Propensity Using E-Chaid Analysis, Eunju Suh, Matt Alhaery

UNLV Gaming Research & Review Journal

Cross-selling different types of games could provide an opportunity for casino operators to generate additional time and money spent on gaming from existing patrons. One way to identify the patrons who are likely to cross-play is mining individual players’ gaming data using predictive analytics. Hence, this study aims to predict casino patrons’ propensity to play both slots and table games, also known as cross-gaming, by applying a data-mining algorithm to patrons’ gaming data. The Exhaustive Chi-squared Automatic Interaction Detector (E-CHAID) method was employed to predict cross-gaming propensity. The E-CHAID models based on the gaming-related behavioral data produced actionable model accuracy …

Simulation, And Overload And Stability Analysis Of Continuous Time Sigma Delta Modulator, Kyung Kang

UNLV Theses, Dissertations, Professional Papers, and Capstones

The ever increasing demand for faster and more powerful digital applications requires high speed, high resolution ADCs. Currently, sigma delta modulators ADCs are extensively used in broadband telecommunication systems because they are an effective solution for high data-rate wireless communication systems that require low power consumption, high speed, high resolution, and large signal bandwidths.

Because mixed-signal integrated circuits such as Continuous Time sigma delta modulators contain both analog and digital circuits, mixed signal circuits are not as simple to model and simulate as all discrete or all analog systems. In this dissertation, the delta transform is used to simulate CT …

Designing A Biomimetic Testing Platform For Actuators In A Series-Elastic Co-Contraction System, Ryan Tyler Schroeder

UNLV Theses, Dissertations, Professional Papers, and Capstones

Actuators determine the performance of robotic systems at the most intimate of levels. As a result, much work has been done to assess the performance of different actuator systems. However, biomimetics has not previously been utilized as a pretext for tuning a series elastic actuator system with the purpose of designing an empirical testing platform. Thus, an artificial muscle tendon system has been developed in order to assess the performance of two distinct actuator types: (1) direct current electromagnetic motors and (2) ultrasonic rotary piezoelectric motors. Because the design of the system takes advantage of biomimetic operating principles such as …

Design And Implementation Of An Instruction Set Architecture And An Instruction Execution Unit For The Rez9 Coprocessor System, Daniel Spencer Anderson

UNLV Theses, Dissertations, Professional Papers, and Capstones

While the use of RNS has provided groundbreaking theory and progress in this field, the applications still lack viable testing platforms to test and verify the theory. This Thesis outlines the processing of developing an instruction set architecture (ISA) and an instruction execution unit (IEU) to help make the first residue based general processor a viable testing platform to address the mentioned problems.

Consider a 32-bit ripple adder. The delay on this device will be 32N where N is the delay for each adder to complete its operation. The delay of this process is due to the need to propagate …

A Novel Multimodal Image Fusion Method Using Hybrid Wavelet-Based Contourlet Transform, Yoonsuk Choi

UNLV Theses, Dissertations, Professional Papers, and Capstones

Various image fusion techniques have been studied to meet the requirements of different applications such as concealed weapon detection, remote sensing, urban mapping, surveillance and medical imaging. Combining two or more images of the same scene or object produces a better application-wise visible image. The conventional wavelet transform (WT) has been widely used in the field of image fusion due to its advantages, including multi-scale framework and capability of isolating discontinuities at object edges. However, the contourlet transform (CT) has been recently adopted and applied to the image fusion process to overcome the drawbacks of WT with its own advantages. …

Non-Learning Semantic Analysis For Context Discovery And Sentiment Estimation: Transportation Application, Himanshu Verma

UNLV Theses, Dissertations, Professional Papers, and Capstones

With enormous amount of linguistic data present on web, text analysis has become one of the major fields of interest today. This field includes sentiment analysis, information retrieval, text document classification, knowledge based modeling, content similarity measure, data clustering, words prediction/correction, decision making etc. Managing and processing such data has vital importance. The field being quite broad, our focus is mainly on transportation related social media(Twitter) data extraction, text categorization/classification which can be further sub-divided into concept discovery, word sense disambiguation and sentiment analysis to analyze performance of existing transportation system worldwide. Concept discovery is the method of extracting the …

Modeling And Development Of Human Interface For Pedestrian Simulator, Romesh Khaddar

UNLV Theses, Dissertations, Professional Papers, and Capstones

According to Traveler opinion and perception survey of 2005, 107.4 million Americans use walking as regular mode of travel, which amounts to 51% of American population. In 2009, 4092 pedestrian fatalities have been reported nationwide with a fatality rate of 1.33 which totals 59,000 crashes. Also, pedestrians are over represented in crash data by accounting more than 12% of fatalities but on 10.9% of trips. This makes a perfect case for understanding the causes behind such statistics, calling for a continuous research on pedestrians walking behavior and their interactions with surroundings.

Current research in pedestrian simulation focuses on surveys and …

Gate Monte Carlo Simulations In A Cloud Computing Environment, Blake Austin Rowedder

UNLV Theses, Dissertations, Professional Papers, and Capstones

The GEANT4-based GATE is a unique and powerful Monte Carlo (MC) platform, which provides a single code library allowing the simulation of specific medical physics applications, e.g. PET, SPECT, CT, radiotherapy, and hadron therapy. However, this rigorous yet flexible platform is used only sparingly in the clinic due to its lengthy calculation time. By accessing the powerful computational resources of a cloud computing environment, GATE's runtime can be significantly reduced to clinically feasible levels without the sizable investment of a local high performance cluster. This study investigated a reliable and efficient execution of GATE MC simulations using a commercial cloud …

An Energy-Efficient, Time-Constrained Scheduling Scheme In Local Mobile Cloud, Ting Shi

UNLV Theses, Dissertations, Professional Papers, and Capstones

Mobile devices have limited resource, such as computation performance and battery life. Mobile cloud computing is gaining popularity as a solution to overcome these resource limitations by sending heavy computation to resourceful servers and receiving the results from these servers. Local mobile clouds comprised of nearby mobile devices are proposed as a better solution to support real-time applications. Since network bandwidth and computational resource is shared among all the mobile devices, a scheduling scheme is needed to ensure that multiple mobile devices can efficiently offload tasks to local mobile clouds, satisfying the tasks' time constraint while keeping low-energy consumption. Two …

Co-Emulation Of Scan-Chain Based Designs Utilizing Sce-Mi Infrastructure, Bill Jason Pidlaoan Tomas

UNLV Theses, Dissertations, Professional Papers, and Capstones

Simulation times of complex System-on-Chips (SoC) have grown exponentially as designs reach the multi-million ASIC gate range. Verification teams have adopted emulation as a prominent methodology, incorporating high-level testbenches and FPGA/ASIC hardware for system-level testing (SLT). In addition to SLT, emulation enables software teams to incorporate software applications with cycle-accurate hardware early on in the design cycle. The Standard for Co-Emulation Modeling Interface (SCE-MI) developed by the Accelera Initiative, is a widely used communication protocol for emulation which has been accepted by major electronic design automation (EDA) companies.

Scan-chain is a design-for-test (DFT) methodology used for testing digital circuits. To …

The Construction And Characterization Of A Magneto-Optical Trap For Rubidium-87 And Electromagnetically-Induced Transparency In Rubidium-87 In A Vapor Cell, Yu Liu

Honors College Theses

Recent years have observed fast developments in neutral atomic vapor based quantum information storage technology. The technique utilizes light fields in the optical wavelength region as signal carrier and retriever and neutral atomic systems (e.g. single atoms, ensembles of atoms, atom-like defects in solids) as storage media. Photons are robust carriers of information due to their high velocity (c = 2.998 x 10⁸ m/s) and ease of transportation (they propagate rectilinearly with low loss). Their high mobility, however, makes it a challenging task to spatially localize and therefore store them. Atoms (or atom-like systems), on the other hand, can …

Computer-Based Stereoscopic Parts Recognition For Robotic Applications, Ahmad A. Fayed

UNLV Theses, Dissertations, Professional Papers, and Capstones

Most of robotic handling and assembly operations are based on sensors such as range and touch sensors. In certain circumstances, such as in the presence of ionizing radiation where most customary sensors will degrade over time due to radiation exposure, these sensors won't function properly. Utilizing two or more cameras (stereo vision) located outside the target zone and analyzing their images to identify location and dimensions of parts within the robot workspace is an alternative for using sensors. Object Recognition is affected by the light condition which oftentimes causes the gray-scale or red, green, and blue values to have a …