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Full-Text Articles in Computer Engineering

Instructor Activity Recognition Using Smartwatch And Smartphone Sensors, Zayed Uddin Chowdhury Jan 2020

Instructor Activity Recognition Using Smartwatch And Smartphone Sensors, Zayed Uddin Chowdhury

Electronic Theses and Dissertations

During a classroom session, an instructor performs several activities, such as writing on the board, speaking to the students, gestures to explain a concept. A record of the time spent in each of these activities could be valuable information for the instructors to virtually observe their own style of instruction. It can help in identifying activities that engage the students more, thereby enhancing teaching effectiveness and efficiency. In this work, we present a preliminary study on profiling multiple activities of an instructor in the classroom using smartwatch and smartphone sensor data. We use 2 benchmark datasets to test out the ...


Applying Artificial Intelligence To Medical Data, Shaikh Shiam Rahman Jan 2020

Applying Artificial Intelligence To Medical Data, Shaikh Shiam Rahman

Electronic Theses and Dissertations

Machine learning, data mining, and deep learning has become the methodology of choice for analyzing medical data and images. In this study, we implemented three different machine learning techniques to medical data and image analysis. Our first study was to implement different log base entropy for a decision tree algorithm. Our results suggested that using a higher log base for the dataset with mostly categorical attributes with three or more categories for each attribute can obtain a higher accuracy. For the second study, we analyzed mental health data tuning the parameters of the decision tree (splitting method, depth and entropy ...


Quantitative Performance Assessment Of Lidar-Based Vehicle Contour Estimation Algorithms For Integrated Vehicle Safety Applications, David M. Mothershed Jan 2020

Quantitative Performance Assessment Of Lidar-Based Vehicle Contour Estimation Algorithms For Integrated Vehicle Safety Applications, David M. Mothershed

Electronic Theses and Dissertations

Many nations and organizations are committing to achieving the goal of `Vision Zero' and eliminate road traffic related deaths around the world. Industry continues to develop integrated safety systems to make vehicles safer, smarter and more capable in safety critical scenarios. Passive safety systems are now focusing on pre-crash deployment of restraint systems to better protect vehicle passengers. Current commonly used bounding box methods for shape estimation of crash partners lack the fidelity required for edge case collision detection and advanced crash modeling. This research presents a novel algorithm for robust and accurate contour estimation of opposing vehicles. The presented ...


Kernel-Controlled Dqn Based Cnn Pruning For Model Compression And Acceleration, Romancha Khatri Jan 2020

Kernel-Controlled Dqn Based Cnn Pruning For Model Compression And Acceleration, Romancha Khatri

Electronic Theses and Dissertations

Apart from the accuracy, the size of convolutional neural networks (CNN) models is another principal factor for facilitating the deployment of models on memory, power and budget constrained devices. However, conventional model compression techniques require human experts to setup parameters to explore the design space which is suboptimal and time consuming. Various pruning techniques are implemented to gain compression, trading off speed and accuracy. Given a CNN model [11], we propose an automated deep reinforcement learning [9] based model compression technique that can effectively turned off kernels on each layer by observing its significance on decision making. By observing accuracy ...


Semantic Segmentation Using Modified U-Net Architecture For Crack Detection, Michael Sun Jan 2020

Semantic Segmentation Using Modified U-Net Architecture For Crack Detection, Michael Sun

Electronic Theses and Dissertations

The visual inspection of a concrete crack is essential to maintaining its good condition during the service life of the bridge. The visual inspection has been done manually by inspectors, but unfortunately, the results are subjective. On the other hand, automated visual inspection approaches are faster and less subjective. Concrete crack is an important deficiency type that is assessed by inspectors. Recently, various Convolutional Neural Networks (CNNs) have become a prominent strategy to spot concrete cracks mechanically. The CNNs outperforms the traditional image processing approaches in accuracy for the high-level recognition task. Of them, U-Net, a CNN based semantic segmentation ...


Past To Present (P2p): Road Thermal Image Colorization, Yuseong Park Jan 2020

Past To Present (P2p): Road Thermal Image Colorization, Yuseong Park

Electronic Theses and Dissertations

Thermal image colorization into realistic RGB image is a challenging task. Thermal cameras are easily to detect objects in particular situation (e.g. darkness and fog) that the human eyes cannot detect. However, it is difficult to interpret the thermal image with human eyes. Enhancing thermal image colorization is an important task to improve these areas. The results of the existing colorization method still have color ambiguities, distortion, and blurriness problems. This paper focused on thermal image colorization using pix2pix network architecture based on Generative Adversarial Net (GAN). Pix2pix is a model that transforms thermal image into RGB image, but ...


Cognitive Satellite Communications And Representation Learning For Streaming And Complex Graphs., Wenqi Liu Aug 2019

Cognitive Satellite Communications And Representation Learning For Streaming And Complex Graphs., Wenqi Liu

Electronic Theses and Dissertations

This dissertation includes two topics. The first topic studies a promising dynamic spectrum access algorithm (DSA) that improves the throughput of satellite communication (SATCOM) under the uncertainty. The other topic investigates distributed representation learning for streaming and complex networks. DSA allows a secondary user to access the spectrum that are not occupied by primary users. However, uncertainty in SATCOM causes more spectrum sensing errors. In this dissertation, the uncertainty has been addressed by formulating a DSA decision-making process as a Partially Observable Markov Decision Process (POMDP) model to optimally determine which channels to sense and access. Large-scale networks have attracted ...


An Explainable Recommender System Based On Semantically-Aware Matrix Factorization., Mohammed Sanad Alshammari Aug 2019

An Explainable Recommender System Based On Semantically-Aware Matrix Factorization., Mohammed Sanad Alshammari

Electronic Theses and Dissertations

Collaborative Filtering techniques provide the ability to handle big and sparse data to predict the ratings for unseen items with high accuracy. Matrix factorization is an accurate collaborative filtering method used to predict user preferences. However, it is a black box system that recommends items to users without being able to explain why. This is due to the type of information these systems use to build models. Although rich in information, user ratings do not adequately satisfy the need for explanation in certain domains. White box systems, in contrast, can, by nature, easily generate explanations. However, their predictions are less ...


Formally Designing And Implementing Cyber Security Mechanisms In Industrial Control Networks., Mehdi Sabraoui Aug 2019

Formally Designing And Implementing Cyber Security Mechanisms In Industrial Control Networks., Mehdi Sabraoui

Electronic Theses and Dissertations

This dissertation describes progress in the state-of-the-art for developing and deploying formally verified cyber security devices in industrial control networks. It begins by detailing the unique struggles that are faced in industrial control networks and why concepts and technologies developed for securing traditional networks might not be appropriate. It uses these unique struggles and examples of contemporary cyber-attacks targeting control systems to argue that progress in securing control systems is best met with formal verification of systems, their specifications, and their security properties. This dissertation then presents a development process and identifies two technologies, TLA+ and seL4, that can be ...


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 ...


Segmentation And Classification Of Lung Nodules From Thoracic Ct Scans : Methods Based On Dictionary Learning And Deep Convolutional Neural Networks., Mohammad Mehdi Farhangi May 2019

Segmentation And Classification Of Lung Nodules From Thoracic Ct Scans : Methods Based On Dictionary Learning And Deep Convolutional Neural Networks., Mohammad Mehdi Farhangi

Electronic Theses and Dissertations

Lung cancer is a leading cause of cancer death in the world. Key to survival of patients is early diagnosis. Studies have demonstrated that screening high risk patients with Low-dose Computed Tomography (CT) is invaluable for reducing morbidity and mortality. Computer Aided Diagnosis (CADx) systems can assist radiologists and care providers in reading and analyzing lung CT images to segment, classify, and keep track of nodules for signs of cancer. In this thesis, we propose a CADx system for this purpose. To predict lung nodule malignancy, we propose a new deep learning framework that combines Convolutional Neural Networks (CNN) and ...


Optimal Design And Planning Of Hybrid Ac/Dc Microgrid, Hossein Lotfi Jan 2019

Optimal Design And Planning Of Hybrid Ac/Dc Microgrid, Hossein Lotfi

Electronic Theses and Dissertations

The traditional approach for microgrid design and deployment has been mainly focused on AC systems. DC microgrids, however, are gaining attention due to numerous advantages they provide over AC microgrids, such as removing the need for synchronization and frequency adjustment as well as appropriateness in supporting DC loads and distributed energy resources (DERs). Moreover, considering that both AC and DC DERs are utilized in microgrids, hybrid microgrids would provide viable and economic solutions as they can potentially eliminate the need for AC-to-DC or DC-to-AC voltage conversions. This dissertation focuses on a hybrid microgrid planning model with the objective of minimizing ...


Improvements Of And Extensions To Fsmweb: Testing Mobile Apps, Ahmed Fawzi Al Haddad Jan 2019

Improvements Of And Extensions To Fsmweb: Testing Mobile Apps, Ahmed Fawzi Al Haddad

Electronic Theses and Dissertations

A mobile application is a software program that runs on mobile device. In 2017, 178.1 billion mobile apps downloaded and the number is expected to grow to 258.2 billion app downloads in 2022 [19]. The number of app downloads poses a challenge for mobile application testers to find the right approach to test apps. This dissertation extends the FSMWeb approach for testing web applications [50] to test mobile applications (FSMApp). During the process of analyzing FSMWeb how it could be extended to test Mobile Apps, a number of shortcomings were detected which we improved upon. We discuss these ...


Protection Of High-Voltage Transformer Bushings And Other Brittle Structures Against Impact, Christine Nichole Henderson Jan 2019

Protection Of High-Voltage Transformer Bushings And Other Brittle Structures Against Impact, Christine Nichole Henderson

Electronic Theses and Dissertations

This dissertation contributes unique approaches to improve the fundamental understanding of the impact behavior of porcelain high-voltage (HV) transformer bushings under high-velocity impact, with a focus on their protection with feasible methods which could be quickly applied in service to prevent vandalism and other undesirable impact situations. The bushings are brittle and pressurized; prone to explosive damage when hit by a high-velocity projectile. Damaged bushings can destroy transformers and entire substations in complex fashions. This can put the power grid at risk for cascading failures and electrical blackouts, affecting consumers. Therefore, suggesting practical approaches which could be used to protect ...


3d Formation Control In Multi-Robot Teams Using Artificial Potential Fields, Sanjana Reddy Mohan Jan 2019

3d Formation Control In Multi-Robot Teams Using Artificial Potential Fields, Sanjana Reddy Mohan

Electronic Theses and Dissertations

Multi-robot teams find applications in emergency response, search and rescue operations, convoy support and many more. Teams of autonomous aerial vehicles can also be used to protect a cargo of airplanes by surrounding them in some geometric shape. This research develops a control algorithm to attract UAVs to one or a set of bounded geometric shapes while avoiding collisions, re-configuring in the event of departure or addition of UAVs and maneuvering in mission space while retaining the configuration. Using potential field theory, weighted vector fields are described to attract UAVs to a desired formation. In order to achieve this, three ...


Application Of Microgrids In Supporting The Utility Grid, Alireza Majzoobi Jan 2019

Application Of Microgrids In Supporting The Utility Grid, Alireza Majzoobi

Electronic Theses and Dissertations

Distributed renewable energy resources have attracted significant attention in recent years due to the falling cost of the renewable energy technology, extensive federal and state incentives, and the application in improving load-point reliability. This growing proliferation, however, is changing the traditional consumption load curves by adding considerable levels of variability and further challenging the electricity supply-demand balance. In this dissertation, the application of microgrids in effectively capturing the distribution network net load variability, caused primarily by the prosumers, is investigated. Microgrids provide a viable and localized solution to this challenge while removing the need for costly investments by the electric ...


A Policy Mechanism For Federal Recommendation Of Security Standards For Mobile Devices That Conduct Transactions, Ariel Huckabay Jan 2019

A Policy Mechanism For Federal Recommendation Of Security Standards For Mobile Devices That Conduct Transactions, Ariel Huckabay

Electronic Theses and Dissertations

The proliferation of mobile devices in the BRIC countries has prompted them to develop policies to manage the security of these devices. In China, mobile devices are a primary tool for payments. As a result, China instituted in 2017 a cyber security policy that applies to mobile devices giving China broad authority to manage cyber threats. The United States has a similar need for a cyber policy. Mobile devices are likely to become a primary payment tool in the United States soon. DHS has also identified a need for more effective security policy in mobile devices for government operations. This ...


Building A Classification Model Using Affinity Propagation, Christopher R. Klecker Jan 2019

Building A Classification Model Using Affinity Propagation, Christopher R. Klecker

Electronic Theses and Dissertations

Regular classification of data includes a training set and test set. For example for Naïve Bayes, Artificial Neural Networks, and Support Vector Machines, each classifier employs the whole training set to train itself. This thesis will explore the possibility of using a condensed form of the training set in order to get a comparable classification accuracy. The technique explored in this thesis will use a clustering algorithm to explore with data records can be labeled as exemplar, or a quality of multiple records. For example, is it possible to compress say 50 records into one single record? Can a single ...


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 ...


Eaglebot: A Chatbot Based Multi-Tier Question Answering System For Retrieving Answers From Heterogeneous Sources Using Bert, Muhammad Rana Jan 2019

Eaglebot: A Chatbot Based Multi-Tier Question Answering System For Retrieving Answers From Heterogeneous Sources Using Bert, Muhammad Rana

Electronic Theses and Dissertations

This paper proposes to tackle Question Answering on a specific domain by developing a multi-tier system using three different types of data storage for storing answers. For testing our system on University domain we have used extracted data from Georgia Southern University website. For the task of faster retrieval we have divided our answer data sources into three distinct types and utilized Dialogflow's Natural Language Understanding engine for route selection. We compared different word and sentence embedding techniques for making a semantic question search engine and BERT sentence embedding gave us the best result and for extracting answer from ...


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 ...


Instance Segmentation And Object Detection In Road Scenes Using Inverse Perspective Mapping Of 3d Point Clouds And 2d Images, Chungyup Lee Jan 2019

Instance Segmentation And Object Detection In Road Scenes Using Inverse Perspective Mapping Of 3d Point Clouds And 2d Images, Chungyup Lee

Electronic Theses and Dissertations

The instance segmentation and object detection are important tasks in smart car applications. Recently, a variety of neural network-based approaches have been proposed. One of the challenges is that there are various scales of objects in a scene, and it requires the neural network to have a large receptive field to deal with the scale variations. In other words, the neural network must have deep architectures which slow down computation. In smart car applications, the accuracy of detection and segmentation of vehicle and pedestrian is hugely critical. Besides, 2D images do not have distance information but enough visual appearance. On ...


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 ...


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 ...


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 ...


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 ...


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 ...


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 ...


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 ...