Computer Engineering Commons^™

Video Stream Adaptation In Computer Vision Systems, Yousef Sharrab Sharrab

Wayne State University Dissertations

Computer Vision (CV) has been deployed recently in a wide range of applications, including surveillance and automotive industries. According to a recent report, the market for CV technologies will grow to $33.3 billion by 2019. Surveillance and automotive industries share over 20% of this market. This dissertation considers the design of real-time CV systems with live video streaming, especially those over wireless and mobile networks. Such systems include video cameras/sensors and monitoring stations. The cameras should adapt their captured videos based on the events and/or available resources and time requirement. The monitoring station receives video streams from all cameras and …

Integrative Pathway Analysis Pipeline For Mirna And Mrna Data, Diana Mabel Diaz Herrera

Wayne State University Theses

The identification of pathways that are involved in a particular phenotype helps us understand the underlying biological processes. Traditional pathway analysis techniques aim to infer the impact on individual pathways using only mRNA levels. However, recent studies showed that gene expression alone is unable to capture the whole picture of biological phenomena. At the same time, MicroRNAs (miRNAs) are newly discovered gene regulators that have shown to play an important role in diagnosis, and prognosis for different types of diseases. Current pathway analysis techniques do not take miRNAs into consideration. In this project, we investigate the effect of integrating miRNA …

Analysis Of Cross-Layer Optimization Of Facial Recognition In Automated Video Surveillance, Loren Garavaglia

Wayne State University Theses

Interest in automated video surveillance systems has grown dramatically and with that so too has research on the topic. Recent approaches have begun addressing the issues of scalability and cost. One method aimed to utilize cross-layer information for adjusting bandwidth allocated to each video source. Work on this topic focused on using distortion and accuracy for face detection as an adjustment metric, utilizing older, less efficient codecs. The framework was shown to increase accuracy in face detection by interpreting dynamic network conditions in order to manage application rates and transmission opportunities for video sources with the added benefit of reducing …

Smart Ev Charging For Improved Sustainable Mobility, Ashutosh Shivakumar

Browse all Theses and Dissertations

The landscape of energy generation and utilization is witnessing an unprecedented change. We are at the threshold of a major shift in electricity generation from utilization of conventional sources of energy like coal to sustainable and renewable sources of energy like solar and wind. On the other hand, electricity consumption, especially in the field of transportation, due to advancements in the field of battery research and exponential technologies like vehicle telematics, is seeing a shift from carbon based to Lithium based fuel. Encouraged by 1. Decrease in the cost of Li – ion based batteries 2. Breakthroughs in battery chemistry …

A New Approach To Pulse Deinterleaving Based On Adaptive Thresholding, Mostafa Bagheri, Mohammad Hossein Sedaaghi

Turkish Journal of Electrical Engineering and Computer Sciences

Since histogram-based methods are formed by some simple differences, they are very desirable for deinterleaving. However, their main imperfection concerns recognizing complex pulse repetition interval (PRI) patterns like jittered and staggered ones.In this paper, we present new thresholds to detect jittered and staggered PRI from histogram-based methods even in complex circumstances such as noisy time of arrival (TOA), complex PRI patterns, and large missing pulses. Simulation results demonstrate that our method can detect and extract constant, jittered, and staggered PRI correctly. Moreover, the method is proved to be considerably robust and reliable at a missing pulses rate up to 30%.

3d Body Tracking Using Deep Learning, Qingguo Xu

Theses and Dissertations--Computer Science

This thesis introduces a 3D body tracking system based on neutral networks and 3D geometry, which can robustly estimate body poses and accurate body joints. This system takes RGB-D data as input. Body poses and joints are firstly extracted from color image using deep learning approach. The estimated joints and skeletons are further translated to 3D space by using camera calibration information. This system is running at the rate of 3 4 frames per second. It can be used to any RGB-D sensors, such as Kinect, Intel RealSense [14] or any customized system with color depth calibrated. Comparing to the …

Autonomous Quadrotor Collision Avoidance And Destination Seeking In A Gps-Denied Environment, Thomas C. Kirven

Theses and Dissertations--Mechanical and Aerospace Engineering

This thesis presents a real-time autonomous guidance and control method for a quadrotor in a GPS-denied environment. The quadrotor autonomously seeks a destination while it avoids obstacles whose shape and position are initially unknown. We implement the obstacle avoidance and destination seeking methods using off-the-shelf sensors, including a vision-sensing camera. The vision-sensing camera detects the positions of points on the surface of obstacles. We use this obstacle position data and a potential-field method to generate velocity commands. We present a backstepping controller that uses the velocity commands to generate the quadrotor's control inputs. In indoor experiments, we demonstrate that the …

Towards High-Efficiency Data Management In The Next-Generation Persistent Memory System, Xunchao Chen

Electronic Theses and Dissertations

For the sake of higher cell density while achieving near-zero standby power, recent research progress in Magnetic Tunneling Junction (MTJ) devices has leveraged Multi-Level Cell (MLC) configurations of Spin-Transfer Torque Random Access Memory (STT-RAM). However, in order to mitigate the write disturbance in an MLC strategy, data stored in the soft bit must be restored back immediately after the hard bit switching is completed. Furthermore, as the result of MTJ feature size scaling, the soft bit can be expected to become disturbed by the read sensing current, thus requiring an immediate restore operation to ensure the data reliability. In this …

End To End Brain Fiber Orientation Estimation Using Deep Learning, Nandakishore Puttashamachar

Electronic Theses and Dissertations

In this work, we explore the various Brain Neuron tracking techniques, one of the most significant applications of Diffusion Tensor Imaging. Tractography is a non-invasive method to analyze underlying tissue micro-structure. Understanding the structure and organization of the tissues facilitates a diagnosis method to identify any aberrations which can occur within tissues due to loss of cell functionalities, provides acute information on the occurrences of brain ischemia or stroke, the mutation of certain neurological diseases such as Alzheimer, multiple sclerosis and so on. Under all these circumstances, accurate localization of the aberrations in efficient manner can help save a life. …

Energy-Aware Data Movement In Non-Volatile Memory Hierarchies, Navid Khoshavi Najafabadi

Electronic Theses and Dissertations

While technology scaling enables increased density for memory cells, the intrinsic high leakage power of conventional CMOS technology and the demand for reduced energy consumption inspires the use of emerging technology alternatives such as eDRAM and Non-Volatile Memory (NVM) including STT-MRAM, PCM, and RRAM. The utilization of emerging technology in Last Level Cache (LLC) designs which occupies a signifcant fraction of total die area in Chip Multi Processors (CMPs) introduces new dimensions of vulnerability, energy consumption, and performance delivery. To be specific, a part of this research focuses on eDRAM Bit Upset Vulnerability Factor (BUVF) to assess vulnerable portion of …

Novel Approaches For Efficient Stochastic Computing, Ramu Seva

Masters Theses

"This thesis is comprised of two papers, where the first paper presents a novel approach for parallel implementation of SC using FPGA (Field Programmable Gate Array). This paper makes use of the distributed memory elements of FPGAs (i.e., look-up-tables -LUTs) to achieve this. An attempt has been made to build the stochastic number generators (SNGs) by using the proposed LUT approach. The construction of these SNGs has been influenced by the Quasi-random number sequences, which provide the advantage of reducing the random fluctuations present in the pseudo-random number generators such as LFSR (Linear Feedback Shift Register) as well as the …

Heuristic Algorithm-Based Estimation Of Rotor Resistance Of An Induction Machine By Slot Parameters With Experimental Verification, Mehmet Çelebi̇, Murat Tören

Turkish Journal of Electrical Engineering and Computer Sciences

The estimations of induction machine equivalent circuit parameters are still being widely used in the analysis and in determining the characteristics of the machine. Since the most important part of the machine is the rotor where torque is produced, the calculation of rotor resistance correctly will directly affect all other data. Almost all parameters belonging to the stator side can easily be determined through external measurements. However, due to the formulation of the rotor as a closed box, estimating rotor resistance and the rotor's slot shape by heuristic algorithms, without damaging the rotor physically, and comparing it with its actual …

Distinct Degradation Processes In Zno Varistors: Reliability Analysis And Modeling With Accelerated Ac Tests, Hadi Yadavari, Mustafa Altun

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we investigate different degradation mechanisms of zinc oxide (ZnO) varistors. We propose a model that shows how Vv (defined as DC varistor voltage when a 1-mA DC current is applied) changes with time for different stress levels. For this purpose, accelerated degradation tests are applied for different AC current levels and voltage values are then measured. Different from the common practice in the literature that considers degradation with only decreasing Vv values, we demonstrate either an increasing or a decreasing trend in the Vv parameter. The tests show a decreasing trend in Vv for current levels above …

Ego-Localization Navigation For Intelligent Vehicles Using 360° Lidar Sensor For Point Cloud Mapping, Tyler Naes

College of Graduate Studies: Theses & Dissertations

With its prospects of reducing vehicular accidents and traffic in highly populated urban areas by taking the human error out of driving, the future in automobiles is leaning towards autonomous navigation using intelligent vehicles. Autonomous navigation via Light Detection And Ranging (LIDAR) provides very accurate localization within a predefined, a priori, point cloud environment that is not possible with Global Positioning System (GPS) and video camera technology. Vehicles may be able to follow paths in the point cloud environment if the baseline paths it must follow are known in that environment by referencing objects detected in the point cloud …

Using Natural Language Processing And Machine Learning Techniques To Characterize Configuration Bug Reports: A Study, Wei Wen

Theses and Dissertations--Computer Science

In this study, a tool is developed that achieves two purposes: (1) given bug reports, it identifies configuration bug reports from non-configuration bug reports; (2) once a bug report is identified to be a configuration bug report, the tool finds out what specific configuration option the bug report is associated.

This study starts with a review of related works that used machine learning tools to solve software bug and bug report related issues. It then discusses the natural language processing and machine learning techniques. Afterwards, the development process of the proposed tool is described in detail, including the motivation, the …

Contributions To Edge Computing, Vernon K. Bumgardner

Theses and Dissertations--Computer Science

Efforts related to Internet of Things (IoT), Cyber-Physical Systems (CPS), Machine to Machine (M2M) technologies, Industrial Internet, and Smart Cities aim to improve society through the coordination of distributed devices and analysis of resulting data. By the year 2020 there will be an estimated 50 billion network connected devices globally and 43 trillion gigabytes of electronic data. Current practices of moving data directly from end-devices to remote and potentially distant cloud computing services will not be sufficient to manage future device and data growth.

Edge Computing is the migration of computational functionality to sources of data generation. The importance of …

Modeling Faceted Browsing With Category Theory For Reuse And Interoperability, Daniel R. Harris

Theses and Dissertations--Computer Science

Faceted browsing (also called faceted search or faceted navigation) is an exploratory search model where facets assist in the interactive navigation of search results. Facets are attributes that have been assigned to describe resources being explored; a faceted taxonomy is a collection of facets provided by the interface and is often organized as sets, hierarchies, or graphs. Faceted browsing has become ubiquitous with modern digital libraries and online search engines, yet the process is still difficult to abstractly model in a manner that supports the development of interoperable and reusable interfaces. We propose category theory as a theoretical foundation for …

Underwater Cave Mapping And Reconstruction Using Stereo Vision, Nicholas Weidner

Theses and Dissertations

This work presents a systematic approach for 3-D mapping and reconstruction of underwater caves. Exploration of underwater caves is very important for furthering our understanding of hydrogeology, managing efficiently water resources, and advancing our knowledge in marine archaeology. Underwater cave exploration by human divers however, is a tedious, labor intensive, extremely dangerous operation, and requires highly skilled people. As such, it is an excellent fit for robotic technology. The proposed solution employs a stereo camera and a video-light. The approach utilizes the intersection of the cone of video-light with the cave boundaries resulting in the construction of a wire frame …

Towards Improving Visqol (Virtual Speech Quality Objective Listener) Using Machine Learning Techniques, Joseph Mcnally

Dissertations

Vast amounts of sound data are transmitted every second over digital networks. VoIP services and cellular networks transmit speech data in increasingly greater volumes. Objective sound quality models provide an essential function to measure the quality of this data in real-time. However, these models can suffer from a lack of accuracy with various degradations over networks. This research uses machine learning techniques to create one support vector regression and three neural network mapping models for use with ViSQOLAudio. Each of the mapping models (including ViSQOL and ViSQOLAudio) are tested against two separate speech datasets in order to comparatively study accuracy …

Critical Comparison Of The Classification Ability Of Deep Convolutional Neural Network Frameworks With Support Vector Machine Techniques In The Image Classification Process, Robert Kelly

Dissertations

Recently, a number of new image classification models have been developed to diversify the number of options available to prospective machine learning classifiers, such as Deep Learning. This is particularly important in the field of medical image classification as a misdiagnosis could have a severe impact on the patient. However, an assessment on the level to which a deep learning based Convolutional Neural Network can outperform a Support Vector Machine has not been discussed. In this project, the use of CNN and SVM classifiers is used on a dataset of approx. 55,000 images. This dataset was used to assess the …

Benchmarking Javascript Frameworks, Carl Lawrence Mariano

Dissertations

JavaScript programming language has been in existence for many years already and is one of the most widely known, if not, the most used front-end programming language in web development. However, JavaScript is still evolving and with the emergence of JavaScript Frameworks (JSF), there has been a major change in how developers develop software nowadays. Developers these days often use more than one framework in order to fulfil their job which has given rise to the problem for developers when it comes to choosing the right JavaScript framework to develop software which is partly due to the availability of countless …

An Exploration Study Of Using The Universities Performance And Enrolments Features For Predicting The International Quality, Aeshah Althagafi

Dissertations

Quality ranking systems are crucial in the assessment of the academic performance of an institution because these assessment systems give details about how different learning institutions deliver their services. Education quality is also of paramount importance to the students because it is through quality education that these students develop skills that are needed in the job market. Besides, education enhances a student's academic and reasoning capacities. When universities are subjected to ranking systems, they are likely to improve their quality to be ranked high in the system. When the university administrators are exposed to ranking, competition gears up. Through competition, …

Exploring The Factors That Affect Secondary Student’S Mathematics And Portuguese Performance In Portugal, Lulu Cheng

Dissertations

Secondary education provides not only knowledge and skills, but also inculcates values, training of instincts, fostering right attitude and habits to enable adolescents to move into tertiary education or to ensure a workplace for students who decided to terminate their secondary schooling. Without secondary education to guide the development of young people through their adolescence, they will be ill prepared for tertiary education or for workplace, moreover, the possibility of juvenile delinquency and teenage pregnancy becomes higher. These negative effects will increase the pressures and expenditures on society and socio-economic. In 2006, Portugal was reported having the higher school-leaving rate …

The Influence Of Sensor-Based Intelligent Traffic Light Control On Traffic Flow In Dublin, Katja Rademacher

Dissertations

With growing cities and the increased use of vehicles for transportation purposes, there is a demand to make the traffic management in cities smarter. An intelligent traffic light control that dynamically adapts to the existing traffic conditions can help reduce traffic congestion and CO2 emissions. This thesis reviews the popular traffic light control approaches - static, actuated and adaptive – based on their influences on recorded traffic conditions in Dublin. The Irish capital relies heavily on busses for public transport adding to the number of already moving vehicles in the city centre. Using vehicle count data from inductive loop detectors …

Comparison Study Of The Most Common Virtual Machine Load Balancing Algorithms In Large-Scale Cloud Environment Using Cloud Simulator, Rowaa Filimban

Dissertations

This is era of internet. There is barely any field where internet do not play important role. Nowadays, CloudComputing links to the internet that has rebelled the whole universe. CloudComputing is a rapid enlarging domain in computing industry and research. Three main services offered by the cloud are SaaS, PaaS and IaaS. With the technology advancement of the CloudComputing, there are many new chances pioneer on how applications can be developed and how several services can be provided to the end user throughout Virtualization, on the internet. What's more, there are cloud service providers who offer and provide large-scaled computing …

Physical Human Activity Recognition Using Machine Learning Algorithms, Haritha Vellampalli

Dissertations

With the rise in ubiquitous computing, the desire to make everyday lives smarter and easier with technology is on the increase. Human activity recognition (HAR) is the outcome of a similar motive. HAR enables a wide range of pervasive computing applications by recognizing the activity performed by a user. In order to contribute to the multi facet applications that HAR is capable to offer, predicting the right activity is of utmost importance. Simplest of the issues as the use of incorrect data manipulation or utilizing a wrong algorithm to perform prediction can hinder the performance of a HAR system. This …

Application Of Supervised Machine Learning To Predict The Mortality Risk In Elderly Using Biomarkers, Priyanka Sonkar

Dissertations

The idea of long-term survival amongst older individuals has been a major medical and social concern. A wide range of biomarkers have been identified to prospectively predict disability, morbidity, and mortality outcomes in older adult populations. The machine learning techniques applied with clinically relevant biomarkers provide new ways of understanding diseases and solutions to tackle challenges to the health of the aging population. This paper describes two supervised machine learning techniques, Logistic Regression (LR) and Support Vector Machine (SVM) which are used in the prediction of the mortality in elderly people. LR is one of the traditionally used predictive modeling …

Modeling Mortgage Assessment With Computational Argumentation Theory And Defeasible Reasoning, Henrik Szucs

Dissertations

In the mortgage lending business of a bank, a key focus area is risk analysis, which supports the mortgage awarding process and the prediction of the risk of defaulting (repayment issues). The standard risk assessment method at most banks is a scorecard calculation. A new way of predicting the defaulting is proposed using Defeasible Reasoning (DR) and computational Argumentation Theory (AT), areas of interdisciplinary research, in the discipline of Articial Intelligence (AI). Argumentation is formalised by reasoning models which are inspired by human reasoning. For a more realistic representation AT employs DR which is a non-monotonic reasoning process, meaning that …

Predicting The Impact Of Data Corruption On The Operation Of Cyber-Physical Systems, Erik David Burgdorf

Masters Theses

"Cyber-physical systems, where computing and communication are used to fortify and streamline the operation of a physical infrastructure, now comprise the foundation of much of modern critical infrastructure. These systems are typically large in scale and highly interconnected, and span application domains from power and water distribution to autonomous vehicle control and collaborative robotics. Intelligent decision support in these systems is heavily reliant on the availability of sufficient and sufficiently correct data. Failure or malfunction of these systems can have devastating consequences in terms of public safety, financial losses, or both.

The research described in this thesis aims to predict …

Analysis Of Outsourcing Data To The Cloud Using Autonomous Key Generation, Mortada Abdulwahed Aman

Masters Theses

"Cloud computing, a technology that enables users to store and manage their data at a low cost and high availability, has been emerging for the past few decades because of the many services it provides. One of the many services cloud computing provides to its users is data storage. The majority of the users of this service are still concerned to outsource their data due to the integrity and confidentiality issues, as well as performance and cost issues, that come along with it. These issues make it necessary to encrypt data prior to outsourcing it to the cloud. However, encrypting …