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Articles 1 - 30 of 80
Full-Text Articles in Computer Engineering
Radiomic Features To Predict Overall Survival Time For Patients With Glioblastoma Brain Tumors Based On Machine Learning And Deep Learning Methods, Lina Chato
UNLV Theses, Dissertations, Professional Papers, and Capstones
Machine Learning (ML) methods including Deep Learning (DL) Methods have been employed in the medical field to improve diagnosis process and patient’s prognosis outcomes. Glioblastoma multiforme is an extremely aggressive Glioma brain tumor that has a poor survival rate. Understanding the behavior of the Glioblastoma brain tumor is still uncertain and some factors are still unrecognized. In fact, the tumor behavior is important to decide a proper treatment plan and to improve a patient’s health. The aim of this dissertation is to develop a Computer-Aided-Diagnosis system (CADiag) based on ML/DL methods to automatically estimate the Overall Survival Time (OST) for …
Modeling And Analysis Of Subcellular Protein Localization In Hyper-Dimensional Fluorescent Microscopy Images Using Deep Learning Methods, Yang Jiao
UNLV Theses, Dissertations, Professional Papers, and Capstones
Hyper-dimensional images are informative and become increasingly common in biomedical research. However, the machine learning methods of studying and processing the hyper-dimensional images are underdeveloped. Most of the methods only model the mapping functions between input and output by focusing on the spatial relationship, whereas neglect the temporal and causal relationships. In many cases, the spatial, temporal, and causal relationships are correlated and become a relationship complex. Therefore, only modeling the spatial relationship may result in inaccurate mapping function modeling and lead to undesired output. Despite the importance, there are multiple challenges on modeling the relationship complex, including the model …
Tinyml For Gait Stride Classification, Priyanka Rajendra
Tinyml For Gait Stride Classification, Priyanka Rajendra
UNLV Theses, Dissertations, Professional Papers, and Capstones
Human gait classification and analysis become very important when a person has been diagnosed with a neurological disorder or has suffered an injury which has affected their ability to walk correctly. Gait strides are an important parameter to be studied as it helps the doctor to diagnose any underlying gait condition and evaluate what type of treatment suits the best for the patient’s recovery. Studying gait strides also helps athletes to improve their performance.In today’s world, machine learning has emerged as one of the most widely used technology for classification and analysis of gait characteristics. TinyML is a field of …
Analysis Of Microscopic Objects Using Computer Vision Methods, Yuan Dao
Analysis Of Microscopic Objects Using Computer Vision Methods, Yuan Dao
UNLV Theses, Dissertations, Professional Papers, and Capstones
As an essential and powerful tool to observe living organisms, three-dimensional fluorescence microscopy is widely used in biological research and diagnosis. The 4D fluorescence microscopy data can be obtained using time-lapsed videos of 3D images. To analyze and extract useful information from the increasingly large and complex biological image dataset, efficient and effective computational tools are in need but still lagging behind. In analyzing biological data, two major challenges are faced. First, time-lapsed fluorescence microscopic images typically have a low SNR. Second, biological objects often change their morphology and internal structure frequently. As such, conventional image processing methods may not …
Forecasting Pedestrian Trajectory Using Deep Learning, Arsal Syed
Forecasting Pedestrian Trajectory Using Deep Learning, Arsal Syed
UNLV Theses, Dissertations, Professional Papers, and Capstones
In this dissertation we develop different methods for forecasting pedestrian trajectories. Complete understanding of pedestrian motion is essential for autonomous agents and social robots to make realistic and safe decisions. Current trajectory prediction methods rely on incorporating historic motion, scene features and social interaction to model pedestrian behaviors. Our focus is to accurately understand scene semantics to better forecast trajectories. In order to do so, we leverage semantic segmentation to encode static scene features such as walkable paths, entry/exits, static obstacles etc. We further evaluate the effectiveness of using semantic maps on different datasets and compare its performance with already …
A Circle Hough Transform Implementation Using High-Level Synthesis, Carlos Lemus
A Circle Hough Transform Implementation Using High-Level Synthesis, Carlos Lemus
UNLV Theses, Dissertations, Professional Papers, and Capstones
Circle Hough Transform (CHT) has found applications in biometrics, robotics, and imageanalysis. In this work, the focus is the development of a Field Programmable Gate Array (FPGA) based accelerator that performs a series of procedures and results in circle detection. The design is performed using Vivado High-Level Synthesis (HLS) tools and targeted for a Zynq UltraScale+ ZCU106. The implementation includes the following procedures: Gaussian filter, Sobel edge operator, thresholding, and finally the CHT algorithm. The performance is evaluated based on the execution time as compared to the software (Python code) execution and the analysis tools provided by Vivado HLS tool. …
A Multi-Channel Mcp-Pmt Based Readout Integrated Circuit For Lidar Applications, Sachin Purushothaman Namboodiri
A Multi-Channel Mcp-Pmt Based Readout Integrated Circuit For Lidar Applications, Sachin Purushothaman Namboodiri
UNLV Theses, Dissertations, Professional Papers, and Capstones
Photon counting techniques are becoming more critical in fields such as LiDAR, high energy physics (HEP), and positron emission tomography (PET). For space-based aerosol-cloud-ocean (ACO) LiDAR, the total aggregate photon flux signal has a very high dynamic range, from a single-photon up to giga-photons per second for a single channel. This dissertation focuses on the design of a multichannel, photon counting readout circuit that can interface with MCP-PMTs for high dynamic range, space-based LiDAR applications. Chapter 2 presents the conventional current mode approach that has been employed to realize a photon counting circuit. A transimpedance amplifier, a 6-bit delay line …
Water Quality Prediction Based On Machine Learning Techniques, Zhao Fu
Water Quality Prediction Based On Machine Learning Techniques, Zhao Fu
UNLV Theses, Dissertations, Professional Papers, and Capstones
Water is one of the most important natural resources for all living organisms on earth. The monitoring of treated wastewater discharge quality is vitally important for the stability and protection of the ecosystem. Collecting and analyzing water samples in the laboratory consumes much time and resources. In the last decade, many machine learning techniques, like multivariate linear regression (MLR) and artificial neural network (ANN) model, have been proposed to address the problem. However, simple linear regression analysis cannot accurately forecast water quality because of complicated linear and nonlinear relationships in the water quality dataset. The ANN model also has shortcomings …
The Dynamic Control Platform: Reinventing The Wheel, One Leg At A Time, Angel Javier Solis
The Dynamic Control Platform: Reinventing The Wheel, One Leg At A Time, Angel Javier Solis
UNLV Theses, Dissertations, Professional Papers, and Capstones
Upright bipedal walking is a complex balance of forces and actions that is almost taken for granted. How this system is modeled, how it affects a prosthesis, and how it can be implemented in the real world are topics that the proposed Dynamic Control Platform aims to address.
The Dynamic Control Platform (DCP) is a bipedal robot designed to test bio-inspired control algorithms with the aim to smooth out the walking experience for prosthetic legs. The main control paradigm that the DCP centers on the principle of orthogonal constraint, which aims to enforce a perpendicular relationship between the center of …
The Affective Perceptual Model: Enhancing Communication Quality For Persons With Pimd, Jadin Tredup
The Affective Perceptual Model: Enhancing Communication Quality For Persons With Pimd, Jadin Tredup
UNLV Theses, Dissertations, Professional Papers, and Capstones
Methods for prolonged compassionate care for persons with Profound Intellectual and Multiple Disabilities (PIMD) require a rotating cast of import people in the subjects life in order to facilitate interaction with the external environment. As subjects continue to age, dependency on these people increases with complexity of communications while the quality of communication decreases. It is theorized that a machine learning (ML) system could replicate the attuning process and replace these people to promote independence. This thesis extends this idea to develop a conceptual and formal model and system prototype.
The main contributions of this thesis are: (1) proposal of …
Analysis Of Bitcoin Cryptocurrency And Its Mining Techniques, Suman Ghimire
Analysis Of Bitcoin Cryptocurrency And Its Mining Techniques, Suman Ghimire
UNLV Theses, Dissertations, Professional Papers, and Capstones
Bitcoin is a peer-to-peer digital, decentralized cryptocurrency created by an individual under pseudonym Satoshi Nakamoto. In fact, it is the first digital, decentralized currency. Several developers and organizations have explored the importance of digital cryptocurrency and the concept of the blockchain. Bitcoin is assumed to be one of the secure and comfortable payment methods that can be used in the upcoming days. The backbone of Bitcoin mining is the concept of the blockchain, which is assumed to beone of the ingenious invention of this century. The blockchain is the collection of blocks that are linked together in such a way …
A Distributed Real-Time Short-Term Solar Irradiation Forecasting Network For Photovoltaic Systems, Michael Adelbert Gacusan
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 …
Design On High Performance Nanoscale Cmos Circuits With Low Temperature Sensitivity, Ming Zhu
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 …
Cyclist Detection, Tracking, And Trajectory Analysis In Urban Traffic Video Data, Farideh Foroozandeh Shahraki
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 …
Automated Quantification Of White Blood Cells In Light Microscopic Images Of Injured Skeletal Muscle, Yang Jiao
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 …
Analog And Mixed Signal Verification Using Satisfiability Solver On Discretized Models, Nikita Ramesh Wanjale
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
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
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
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
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
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
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 …
Performance Analysis Of Hybrid Algorithms For Lossless Compression Of Climate Data, Bharath Chandra Mummadisetty
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 …
Compression Of Climate Data Through Artificial Neural Networks, Astha Puri
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 …
Simulation, And Overload And Stability Analysis Of Continuous Time Sigma Delta Modulator, Kyung Kang
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 …
Design And Implementation Of An Instruction Set Architecture And An Instruction Execution Unit For The Rez9 Coprocessor System, Daniel Spencer Anderson
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 …
Non-Learning Semantic Analysis For Context Discovery And Sentiment Estimation: Transportation Application, Himanshu Verma
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 …
A Novel Multimodal Image Fusion Method Using Hybrid Wavelet-Based Contourlet Transform, Yoonsuk Choi
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. …
Modeling And Development Of Human Interface For Pedestrian Simulator, Romesh Khaddar
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 …
An Energy-Efficient, Time-Constrained Scheduling Scheme In Local Mobile Cloud, Ting Shi
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 …