Open Access. Powered by Scholars. Published by Universities.®

Computer Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Electronic Theses and Dissertations

Discipline
Institution
Keyword
Publication Year
File Type

Articles 1 - 30 of 218

Full-Text Articles in Computer Engineering

Leveraging The Intrinsic Switching Behaviors Of Spintronic Devices For Digital And Neuromorphic Circuits, Steven Pyle May 2019

Leveraging The Intrinsic Switching Behaviors Of Spintronic Devices For Digital And Neuromorphic Circuits, Steven Pyle

Electronic Theses and Dissertations

With semiconductor technology scaling approaching atomic limits, novel approaches utilizing new memory and computation elements are sought in order to realize increased density, enhanced functionality, and new computational paradigms. Spintronic devices offer intriguing avenues to improve digital circuits by leveraging non-volatility to reduce static power dissipation and vertical integration for increased density. Novel hybrid spintronic-CMOS digital circuits are developed herein that illustrate enhanced functionality at reduced static power consumption and area cost. The developed spin-CMOS D Flip-Flop offers improved power-gating strategies by achieving instant store/restore capabilities while using 10 fewer transistors than typical CMOS-only implementations. The spin-CMOS Muller C-Element ...


An Explainable Sequence-Based Deep Learning Predictor With Applications To Song Recommendation And Text Classification., Khalil Damak May 2019

An Explainable Sequence-Based Deep Learning Predictor With Applications To Song Recommendation And Text Classification., Khalil Damak

Electronic Theses and Dissertations

Streaming applications are now the predominant tools for listening to music. What makes the success of such software is the availability of songs and especially their ability to provide users with relevant personalized recommendations. State of the art music recommender systems mainly rely on either Matrix factorization-based collaborative filtering approaches or deep learning architectures. Deep learning models usually use metadata for content-based filtering or predict the next user interaction (listening to a song) using a memory-based deep learning structure that learns from temporal sequences of user actions. Despite advances in deep learning models for song recommendation systems, none has taken ...


Value-Of-Information Based Data Collection In Underwater Sensor Networks, Fahad Khan May 2019

Value-Of-Information Based Data Collection In Underwater Sensor Networks, Fahad Khan

Electronic Theses and Dissertations

Underwater sensor networks are deployed in marine environments, presenting specific challenges compared to sensor networks deployed in terrestrial settings. Among the major issues that underwater sensor networks face is communication medium limitations that result in low bandwidth and long latency. This creates problems when these networks need to transmit large amounts of data over long distances. A possible solution to address this issue is to use mobile sinks such as autonomous underwater vehicles (AUVs) to offload these large quantities of data. Such mobile sinks are called data mules. Often it is the case that a sensor network is deployed to ...


Development Of Enhanced Weed Detection System With Adaptive Thresholding, K-Means And Support Vector Machine, Dheeman Saha Jan 2019

Development Of Enhanced Weed Detection System With Adaptive Thresholding, K-Means And Support Vector Machine, Dheeman Saha

Electronic Theses and Dissertations

This paper proposes a sophisticated classification process to segment the leaves of carrots from weeds (mostly Chamomile). In the early stages, of the plants’ development, both weeds and carrot leaves are intermixed with each other and have similar color texture. This makes it difficult to identify without the help of the domain experts. Therefore, it is essential to remove the weed regions so that the carrot plants can grow without any interruptions. The process of identifying the weeds become more challenging when both plant and weed regions overlap (inter-leaves). The proposed system addresses this problem by creating a sophisticated means ...


Hydrogen Fuel Cell Gasket Handling And Sorting With Machine Vision Integrated Dual Arm Robot, Devin C. Fowler Jan 2019

Hydrogen Fuel Cell Gasket Handling And Sorting With Machine Vision Integrated Dual Arm Robot, Devin C. Fowler

Electronic Theses and Dissertations

Recently demonstrated robotic assembling technologies for fuel cell stacks used fuel cell components manually pre-arranged in stacks (presenters), all oriented in the same position. Identifying the original orientation of fuel cell components and loading them in stacks for a subsequent automated assembly process is a difficult, repetitive work cycle which if done manually, deceives the advantages offered by automated fabrication technologies of fuel cell components and by robotic assembly processes. We present an innovative robotic technology which enables the integration of automated fabrication processes of fuel cell components with robotic assembly of fuel cell stacks into a fully automated fuel ...


Design And Development Of A Testbed Prototype For Cognitive Radio Transmission Over Tv White Space, Dewan Md Ariful Hassan Jan 2019

Design And Development Of A Testbed Prototype For Cognitive Radio Transmission Over Tv White Space, Dewan Md Ariful Hassan

Electronic Theses and Dissertations

Considering the ever-increasing demand and the associated high costs of wireless electromagnetic spectrum, technologies that can facilitate efficient spectrum utilization are of utmost importance. Cognitive radio (CR), in conjunction with TV White Spaces (TVWS), can be a viable solution, where unlicensed or secondary users can opportunistically use the not-currently-in-use, aka idle, TV channels registered to licensed or primary users. This thesis focuses on the design and development of a testbed prototype for real-time testing of secondary user transmission in TVWS. Once an unused TV channel has been identified, our system uses that idle channel for transmitting and receiving signals. The ...


Development Of Semantic Scene Conversion Model For Image-Based Localization At Night, Dongyoun Kim Jan 2019

Development Of Semantic Scene Conversion Model For Image-Based Localization At Night, Dongyoun Kim

Electronic Theses and Dissertations

Developing an autonomous vehicle navigation system invariant to illumination change is one of the biggest challenges in vision-based localization field due to the fact that the appearance of an image becomes inconsistent under different light conditions even with the same location. In particular, the night scene images have greatest change in appearance compared to the according day scenes. Moreover, the night images do not have enough information in Image-based localization. To deal with illumination change, image conversion methods have been researched. However, these methods could lose the detail of objects and add fake objects into the output images. In this ...


Automated Synthesis Of Unconventional Computing Systems, Amad Ul Hassen Jan 2019

Automated Synthesis Of Unconventional Computing Systems, Amad Ul Hassen

Electronic Theses and Dissertations

Despite decades of advancements, modern computing systems which are based on the von Neumann architecture still carry its shortcomings. Moore's law, which had substantially masked the effects of the inherent memory-processor bottleneck of the von Neumann architecture, has slowed down due to transistor dimensions nearing atomic sizes. On the other hand, modern computational requirements, driven by machine learning, pattern recognition, artificial intelligence, data mining, and IoT, are growing at the fastest pace ever. By their inherent nature, these applications are particularly affected by communication-bottlenecks, because processing them requires a large number of simple operations involving data retrieval and storage ...


Modeling And Simulation Methodologies For Spinal Cord Stimulation., Saliya Kumara Kirigeeganage Dec 2018

Modeling And Simulation Methodologies For Spinal Cord Stimulation., Saliya Kumara Kirigeeganage

Electronic Theses and Dissertations

The use of neural prostheses to improve health of paraplegics has been a prime interest of neuroscientists over the last few decades. Scientists have performed experiments with spinal cord stimulation (SCS) to enable voluntary motor function of paralyzed patients. However, the experimentation on the human spinal cord is not a trivial task. Therefore, modeling and simulation techniques play a significant role in understanding the underlying concepts and mechanics of the spinal cord stimulation. In this work, simulation and modeling techniques related to spinal cord stimulation were investigated. The initial work was intended to visualize the electric field distribution patterns in ...


A Transfer Learning Approach For Sentiment Classification., Omar Abdelwahab Dec 2018

A Transfer Learning Approach For Sentiment Classification., Omar Abdelwahab

Electronic Theses and Dissertations

The idea of developing machine learning systems or Artificial Intelligence agents that would learn from different tasks and be able to accumulate that knowledge with time so that it functions successfully on a new task that it has not seen before is an idea and a research area that is still being explored. In this work, we will lay out an algorithm that allows a machine learning system or an AI agent to learn from k different domains then uses some or no data from the new task for the system to perform strongly on that new task. In order ...


Autonomous Discovery And Maintenance Of Mobile Frees-Space-Optical Links, Mahmudur Khan Aug 2018

Autonomous Discovery And Maintenance Of Mobile Frees-Space-Optical Links, Mahmudur Khan

Electronic Theses and Dissertations

Free-Space-Optical (FSO) communication has the potential to play a significant role in future generation wireless networks. It is advantageous in terms of improved spectrum utilization, higher data transfer rate, and lower probability of interception from unwanted sources. FSO communication can provide optical-level wireless communication speeds and can also help solve the wireless capacity problem experienced by the traditional RF-based technologies. Despite these advantages, communications using FSO transceivers require establishment and maintenance of line-of-sight (LOS). We consider autonomous mobile nodes (Unmanned Ground Vehicles or Unmanned Aerial Vehicles), each with one FSO transceiver mounted on a movable head capable of scanning in ...


Spam Elimination And Bias Correction : Ensuring Label Quality In Crowdsourced Tasks., Lingyu Lyu Aug 2018

Spam Elimination And Bias Correction : Ensuring Label Quality In Crowdsourced Tasks., Lingyu Lyu

Electronic Theses and Dissertations

Crowdsourcing is proposed as a powerful mechanism for accomplishing large scale tasks via anonymous workers online. It has been demonstrated as an effective and important approach for collecting labeled data in application domains which require human intelligence, such as image labeling, video annotation, natural language processing, etc. Despite the promises, one big challenge still exists in crowdsourcing systems: the difficulty of controlling the quality of crowds. The workers usually have diverse education levels, personal preferences, and motivations, leading to unknown work performance while completing a crowdsourced task. Among them, some are reliable, and some might provide noisy feedback. It is ...


How Gpu Rendering Affects Image Processing And Scientific Calculation Speed, Power And Energy On A Raspberry Pi, Qihao He May 2018

How Gpu Rendering Affects Image Processing And Scientific Calculation Speed, Power And Energy On A Raspberry Pi, Qihao He

Electronic Theses and Dissertations

In this thesis, we explore the speed, power, and energy performance of the same data process on the central processing unit (CPU) with and without the acceleration of the Graphics Processing Unit (GPU) on the microcomputer Raspberry Pi (RPI). We tested on the RPI in two different fields. The first was comparing the speed, power, and energy usage with and without GPU acceleration in the image processing impacts on RPI model B+. The second was comparing speed, power, energy usage, and accuracy for scientific calculation with and without GPU acceleration on RPI model B+ and 3B.

We used a novel ...


Robust Fuzzy Clustering For Multiple Instance Regression., Mohamed Trabelsi May 2018

Robust Fuzzy Clustering For Multiple Instance Regression., Mohamed Trabelsi

Electronic Theses and Dissertations

Multiple instance regression (MIR) operates on a collection of bags, where each bag contains multiple instances sharing an identical real-valued label. Only few instances, called primary instances, contribute to the bag labels. The remaining instances are noise and outliers observations. The goal in MIR is to identify the primary instances within each bag and learn a regression model that can predict the label of a previously unseen bag. In this thesis, we introduce an algorithm that uses robust fuzzy clustering with an appropriate distance to learn multiple linear models from a noisy feature space simultaneously. We show that fuzzy memberships ...


Machine Learning For Omics Data Analysis., Ameni Trabelsi May 2018

Machine Learning For Omics Data Analysis., Ameni Trabelsi

Electronic Theses and Dissertations

In proteomics and metabolomics, to quantify the changes of abundance levels of biomolecules in a biological system, multiple sample analysis steps are involved. The steps include mass spectrum deconvolution and peak list alignment. Each analysis step introduces a certain degree of technical variation in the abundance levels (i.e. peak areas) of those molecules. Some analysis steps introduce technical variations that affect the peak areas of all molecules equally while others affect the peak areas of a subset of molecules with varying degrees. To correct these technical variations, some existing normalization methods simply scale the peak areas of all molecules ...


End-To-End Learning Framework For Circular Rna Classification From Other Long Non-Coding Rnas Using Multi-Modal Deep Learning., Mohamed Chaabane May 2018

End-To-End Learning Framework For Circular Rna Classification From Other Long Non-Coding Rnas Using Multi-Modal Deep Learning., Mohamed Chaabane

Electronic Theses and Dissertations

Over the past two decades, a circular form of RNA (circular RNA) produced from splicing mechanism has become the focus of scientific studies due to its major role as a microRNA (miR) ac tivity modulator and its association with various diseases including cancer. Therefore, the detection of circular RNAs is a vital operation for continued comprehension of their biogenesis and purpose. Prediction of circular RNA can be achieved by first distinguishing non-coding RNAs from protein coding gene transcripts, separating short and long non-coding RNAs (lncRNAs), and finally pre dicting circular RNAs from other lncRNAs. However, available tools to distinguish circular ...


Horse Racing Prediction Using Graph-Based Features., Mehmet Akif Gulum May 2018

Horse Racing Prediction Using Graph-Based Features., Mehmet Akif Gulum

Electronic Theses and Dissertations

This thesis presents an applied horse racing prediction using graph based features on a set of horse races data. We used artificial neural network and logistic regression models to train then test to prediction without graph based features and with graph based features. This thesis can be explained in 4 main parts. Collect data from a horse racing website held from 2015 to 2017. Train data to using predictive models and make a prediction. Create a global directed graph of horses and extract graph-based features (Core Part) . Add graph based features to basic features and train to using same predictive ...


A Framework For Cardio-Pulmonary Resuscitation (Cpr) Scene Retrieval From Medical Simulation Videos Based On Object And Activity Detection., Anju Panicker Madhusoodhanan Sathik May 2018

A Framework For Cardio-Pulmonary Resuscitation (Cpr) Scene Retrieval From Medical Simulation Videos Based On Object And Activity Detection., Anju Panicker Madhusoodhanan Sathik

Electronic Theses and Dissertations

In this thesis, we propose a framework to detect and retrieve CPR activity scenes from medical simulation videos. Medical simulation is a modern training method for medical students, where an emergency patient condition is simulated on human-like mannequins and the students act upon. These simulation sessions are recorded by the physician, for later debriefing. With the increasing number of simulation videos, automatic detection and retrieval of specific scenes became necessary. The proposed framework for CPR scene retrieval, would eliminate the conventional approach of using shot detection and frame segmentation techniques. Firstly, our work explores the application of Histogram of Oriented ...


Network Science Algorithms For Mobile Networks., Heba Mohamed Elgazzar May 2018

Network Science Algorithms For Mobile Networks., Heba Mohamed Elgazzar

Electronic Theses and Dissertations

Network Science is one of the important and emerging fields in computer science and engineering that focuses on the study and analysis of different types of networks. The goal of this dissertation is to design and develop network science algorithms that can be used to study and analyze mobile networks. This can provide essential information and knowledge that can help mobile networks service providers to enhance the quality of the mobile services. We focus in this dissertation on the design and analysis of different network science techniques that can be used to analyze the dynamics of mobile networks. These techniques ...


Maintainability Analysis Of Mining Trucks With Data Analytics., Abdulgani Kahraman May 2018

Maintainability Analysis Of Mining Trucks With Data Analytics., Abdulgani Kahraman

Electronic Theses and Dissertations

The mining industry is one of the biggest industries in need of a large budget, and current changes in global economic challenges force the industry to reduce its production expenses. One of the biggest expenditures is maintenance. Thanks to the data mining techniques, available historical records of machines’ alarms and signals might be used to predict machine failures. This is crucial because repairing machines after failures is not as efficient as utilizing predictive maintenance. In this case study, the reasons for failures seem to be related to the order of signals or alarms, called events, which come from trucks. The ...


Detailed Power Measurement With Arm Embedded Boards, Yanxiang Mao Apr 2018

Detailed Power Measurement With Arm Embedded Boards, Yanxiang Mao

Electronic Theses and Dissertations

Power and energy are becoming important considerations in today's electronic equipment. The amount of power required to run a supercomputer for an hour could supply an ordinary household for many months. The need for low-power computing also extends to smaller devices, such as mobile phones, laptops and embedded devices.

In order to optimize power usage of electronic equipment, we need to collect information on the power consumption of these devices. Unfortunately it is not easy to do this on modern computing systems. Existing measuring equipment is often expensive, inaccurate, and difficult to operate. The main goal of this project ...


Acceleration Of K-Nearest Neighbor And Srad Algorithms Using Intel Fpga Sdk For Opencl, Liyuan Liu Mar 2018

Acceleration Of K-Nearest Neighbor And Srad Algorithms Using Intel Fpga Sdk For Opencl, Liyuan Liu

Electronic Theses and Dissertations

Field Programmable Gate Arrays (FPGAs) have been widely used for accelerating machine learning algorithms. However, the high design cost and time for implementing FPGA-based accelerators using traditional HDL-based design methodologies has discouraged users from designing FPGA-based accelerators. In recent years, a new CAD tool called Intel FPGA SDK for OpenCL (IFSO) allowed fast and efficient design of FPGA-based hardware accelerators from high level specification such as OpenCL. Even software engineers with basic hardware design knowledge could design FPGA-based accelerators. In this thesis, IFSO has been used to explore acceleration of k-Nearest-Neighbour (kNN) algorithm and Speckle Reducing Anisotropic Diffusion (SRAD) simulation ...


Force-Canceling Mixer Algorithm For Vehicles With Fully-Articulated Radially-Symmetric Thruster Arrays, Joseph Nicholas Casabona Jan 2018

Force-Canceling Mixer Algorithm For Vehicles With Fully-Articulated Radially-Symmetric Thruster Arrays, Joseph Nicholas Casabona

Electronic Theses and Dissertations

A new type of fully-holonomic aerial vehicle is identified and developed that can optionally utilize automatic cancellation of excessive thruster forces to maintain precise control despite little or no throttle authority. After defining the physical attributes of the new vehicle, a flight control mixer algorithm is defined and presented. This mixer is an input/output abstraction that grants a flight control system (or pilot) full authority of the vehicle's position and orientation by means of an input translation vector and input torque vector. The mixer is shown to be general with respect to the number of thrusters in the ...


Development Of A Locomotion And Balancing Strategy For Humanoid Robots, Emile Bahdi Jan 2018

Development Of A Locomotion And Balancing Strategy For Humanoid Robots, Emile Bahdi

Electronic Theses and Dissertations

The locomotion ability and high mobility are the most distinguished features of humanoid robots. Due to the non-linear dynamics of walking, developing and controlling the locomotion of humanoid robots is a challenging task. In this thesis, we study and develop a walking engine for the humanoid robot, NAO, which is the official robotic platform used in the RoboCup Spl. Aldebaran Robotics, the manufacturing company of NAO provides a walking module that has disadvantages, such as being a black box that does not provide control of the gait as well as the robot walk with a bent knee. The latter disadvantage ...


Developing An Affect-Aware Rear-Projected Robotic Agent, Ali Mollahosseini Jan 2018

Developing An Affect-Aware Rear-Projected Robotic Agent, Ali Mollahosseini

Electronic Theses and Dissertations

Social (or Sociable) robots are designed to interact with people in a natural and interpersonal manner. They are becoming an integrated part of our daily lives and have achieved positive outcomes in several applications such as education, health care, quality of life, entertainment, etc. Despite significant progress towards the development of realistic social robotic agents, a number of problems remain to be solved. First, current social robots either lack enough ability to have deep social interaction with human, or they are very expensive to build and maintain. Second, current social robots have yet to reach the full emotional and social ...


Studying Facial Expression Recognition And Imitation Ability Of Children With Autism Spectrum Disorder In Interaction With A Social Robot, Farzaneh Askari Jan 2018

Studying Facial Expression Recognition And Imitation Ability Of Children With Autism Spectrum Disorder In Interaction With A Social Robot, Farzaneh Askari

Electronic Theses and Dissertations

Children with Autism Spectrum Disorder (ASD) experience limited abilities in recognizing non-verbal elements of social interactions such as facial expressions [1]. They also show deficiencies in imitating facial expressions in social situations. In this Master thesis, we focus on studying the ability of children with ASD in recognizing facial expressions and imitating the expressions using a rear-projected expressive humanoid robot, called Ryan. Recent studies show that social robots such as Ryan have great potential for autism therapy. We designed and developed three studies, first to evaluate the ability of children with ASD in recognizing facial expressions that are presented to ...


Bridging The Gap Between Application And Solid-State-Drives, Jian Zhou Jan 2018

Bridging The Gap Between Application And Solid-State-Drives, Jian Zhou

Electronic Theses and Dissertations

Data storage is one of the important and often critical parts of the computing system in terms of performance, cost, reliability, and energy. Numerous new memory technologies, such as NAND flash, phase change memory (PCM), magnetic RAM (STT-RAM) and Memristor, have emerged recently. Many of them have already entered the production system. Traditional storage optimization and caching algorithms are far from optimal because storage I/Os do not show simple locality. To provide optimal storage we need accurate predictions of I/O behavior. However, the workloads are increasingly dynamic and diverse, making the long and short time I/O prediction ...


Low Power Wide Area Networks (Lpwan): Technology Review And Experimental Study On Mobility Effect, Dhaval Patel Jan 2018

Low Power Wide Area Networks (Lpwan): Technology Review And Experimental Study On Mobility Effect, Dhaval Patel

Electronic Theses and Dissertations

In the past decade, we have witnessed explosive growth in the number of low-power embedded and Internet-connected devices, reinforcing the new paradigm, Internet of Things (IoT). IoT devices like smartphones, home security systems, smart electric meters, garage parking indicators, etc., have penetrated deeply into our daily lives. These IoT devices are increasingly attached and operated in mobile objects like unmanned vehicles, trains, airplanes, etc. The low power wide area network (LPWAN), due to its long-range, low-power and low-cost communication capability, is actively considered by academia and industry as the future wireless communication standard for IoT. However, despite the increasing popularity ...


A Scale Space Local Binary Pattern (Sslbp) – Based Feature Extraction Framework To Detect Bones From Knee Mri Scans, Jinyeong Mun Jan 2018

A Scale Space Local Binary Pattern (Sslbp) – Based Feature Extraction Framework To Detect Bones From Knee Mri Scans, Jinyeong Mun

Electronic Theses and Dissertations

The medical industry is currently working on a fully autonomous surgical system, which is considered a novel modality to go beyond technical limitations of conventional surgery. In order to apply an autonomous surgical system to knees, one of the primarily responsible areas for supporting the total weight of human body, accurate segmentation of bones from knee Magnetic Resonance Imaging (MRI) scans plays a crucial role. In this paper, we propose employing the Scale Space Local Binary Pattern (SSLBP) feature extraction, a variant of local binary pattern extractions, for detecting bones from knee images. The proposed methods consist of two phases ...


Wi-Fi Finger-Printing Based Indoor Localization Using Nano-Scale Unmanned Aerial Vehicles, Appala Narasimha Raju Chekuri Jan 2018

Wi-Fi Finger-Printing Based Indoor Localization Using Nano-Scale Unmanned Aerial Vehicles, Appala Narasimha Raju Chekuri

Electronic Theses and Dissertations

Explosive growth in the number of mobile devices like smartphones, tablets, and smartwatches has escalated the demand for localization-based services, spurring development of numerous indoor localization techniques. Especially, widespread deployment of wireless LANs prompted ever increasing interests in WiFi-based indoor localization mechanisms. However, a critical shortcoming of such localization schemes is the intensive time and labor requirements for collecting and building the WiFi fingerprinting database, especially when the system needs to cover a large space. In this thesis, we propose to automate the WiFi fingerprint survey process using a group of nano-scale unmanned aerial vehicles (NAVs). The proposed system significantly ...