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Full-Text Articles in Engineering

Design And Implementation Of Anomaly Detections For User Authentication Framework, Iman Abu Sulayman Dec 2019

Design And Implementation Of Anomaly Detections For User Authentication Framework, Iman Abu Sulayman

Electronic Thesis and Dissertation Repository

Anomaly detection is quickly becoming a very significant tool for a variety of applications such as intrusion detection, fraud detection, fault detection, system health monitoring, and event detection in IoT devices. An application that lacks a strong implementation for anomaly detection is user trait modeling for user authentication purposes. User trait models expose up-to-date representation of the user so that changes in their interests, their learning progress or interactions with the system are noticed and interpreted. The reason behind the lack of adoption in user trait modeling arises from the need of a continuous flow of high-volume data, that is ...


A Wearable Mechatronic Device For Hand Tremor Monitoring And Suppression: Development And Evaluation, Yue Zhou Dec 2019

A Wearable Mechatronic Device For Hand Tremor Monitoring And Suppression: Development And Evaluation, Yue Zhou

Electronic Thesis and Dissertation Repository

Tremor, one of the most disabling symptoms of Parkinson's disease (PD), significantly affects the quality of life of the individuals who suffer from it. These people live with difficulties with fine motor tasks, such as eating and writing, and suffer from social embarrassment. Traditional medicines are often ineffective, and surgery is highly invasive and risky. The emergence of wearable technology facilitates an externally worn mechatronic tremor suppression device as a potential alternative approach for tremor management. However, no device has been developed for the suppression of finger tremor that has been validated on a human.

It has been reported ...


Exploitation Of Robust Aoa Estimation And Low Overhead Beamforming In Mmwave Mimo System, Yuyan Zhao Nov 2019

Exploitation Of Robust Aoa Estimation And Low Overhead Beamforming In Mmwave Mimo System, Yuyan Zhao

Electronic Thesis and Dissertation Repository

The limited spectral resource for wireless communications and dramatic proliferation of new applications and services directly necessitate the exploitation of millimeter wave (mmWave) communications. One critical enabling technology for mmWave communications is multi-input multi-output (MIMO), which enables other important physical layer techniques, specifically beamforming and antenna array based angle of arrival (AoA) estimation. Deployment of beamforming and AoA estimation has many challenges. Significant training and feedback overhead is required for beamforming, while conventional AoA estimation methods are not fast or robust. Thus, in this thesis, new algorithms are designed for low overhead beamforming, and robust AoA estimation with significantly reduced ...


Machine Learning Classification Of Interplanetary Coronal Mass Ejections Using Satellite Accelerometers, Kelsey Doerksen Oct 2019

Machine Learning Classification Of Interplanetary Coronal Mass Ejections Using Satellite Accelerometers, Kelsey Doerksen

Electronic Thesis and Dissertation Repository

Space weather phenomena is a complex area of research as there are many different variables and signatures that are used to identify the occurrence of solar storms and Interplanetary Coronal Mass Ejections (ICMEs), with inconsistencies between databases and solar storm catalogues. The identification of space weather events is important from a satellite operation point of view, as strong geomagnetic storms can cause orbit perturbations to satellites in low-earth orbit. The Disturbance storm time (Dst) and the Planetary K-index (Kp) are common indices used to identify the occurrence of geomagnetic storms caused by ICMEs, among several other signatures that are not ...


Schrödinger Filtering: A Novel Technique For Removing Gradient Artifact From Electroencephalography Data Acquired During Functional Magnetic Resonance Imaging, Gabriel Bruno Benigno Sep 2019

Schrödinger Filtering: A Novel Technique For Removing Gradient Artifact From Electroencephalography Data Acquired During Functional Magnetic Resonance Imaging, Gabriel Bruno Benigno

Electronic Thesis and Dissertation Repository

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are complementary modalities commonly acquired simultaneously to study brain function with high spatial and temporal resolution. The time-varying gradient fields from fMRI induce massive-amplitude artifacts (GRAs) that overlap in time and frequency with EEG, making GRA removal a challenge for which no satisfactory solution yet exists. We present a new GRA removal method termed Schrödinger filtering (SF). SF is based on semi-classical signal analysis in which a signal is decomposed into a series of energy-based components using the discrete spectrum of the Schrödinger operator. Using a publicly available dataset, we compared our ...


A Heterogeneous Patient-Specific Biomechanical Model Of The Lung For Tumor Motion Compensation And Effective Lung Radiation Therapy Planning, Parya Jafari Sep 2019

A Heterogeneous Patient-Specific Biomechanical Model Of The Lung For Tumor Motion Compensation And Effective Lung Radiation Therapy Planning, Parya Jafari

Electronic Thesis and Dissertation Repository

Radiation therapy is a main component of treatment for many lung cancer patients. However, the respiratory motion can cause inaccuracies in radiation delivery that can lead to treatment complications. In addition, the radiation-induced damage to healthy tissue limits the effectiveness of radiation treatment. Motion management methods have been developed to increase the accuracy of radiation delivery, and functional avoidance treatment planning has emerged to help reduce the chances of radiation-induced toxicity. In this work, we have developed biomechanical model-based techniques for tumor motion estimation, as well as lung functional imaging. The proposed biomechanical model accurately estimates lung and tumor motion ...


Height Measurement Of Basil Crops For Smart Irrigation Applications In Greenhouses Using Commercial Sensors, Leila Bahman Sep 2019

Height Measurement Of Basil Crops For Smart Irrigation Applications In Greenhouses Using Commercial Sensors, Leila Bahman

Electronic Thesis and Dissertation Repository

Plant height is a key phenotypic attribute that directly represents how well a plant grows. It can also be a useful parameter in computing other important features such as yield and biomass. As the number of greenhouses increase, the traditional method of measuring plant height requires more time and labor, which increases demand for developing a reliable and affordable method to perform automated height measurements of plants. This research is aimed to develop a solution to automatically measure plant height in greenhouses using low cost sensors and computer vision techniques. For this purpose, the performance of various depth sensing technologies ...


Data Analytics And Performance Enhancement In Edge-Cloud Collaborative Internet Of Things Systems, Tianqi Yu Aug 2019

Data Analytics And Performance Enhancement In Edge-Cloud Collaborative Internet Of Things Systems, Tianqi Yu

Electronic Thesis and Dissertation Repository

Based on the evolving communications, computing and embedded systems technologies, Internet of Things (IoT) systems can interconnect not only physical users and devices but also virtual services and objects, which have already been applied to many different application scenarios, such as smart home, smart healthcare, and intelligent transportation. With the rapid development, the number of involving devices increases tremendously. The huge number of devices and correspondingly generated data bring critical challenges to the IoT systems. To enhance the overall performance, this thesis aims to address the related technical issues on IoT data processing and physical topology discovery of the subnets ...


Optimal Decentralized Coordination Of Sources In Islanded And Grid-Connected Microgrids, Mithun Mallick Jul 2019

Optimal Decentralized Coordination Of Sources In Islanded And Grid-Connected Microgrids, Mithun Mallick

Electronic Thesis and Dissertation Repository

Rising climate change concerns in recent years have instigated the emergence of sustainable sources to reduce dependence on high-emission, isolated bulk generation systems. The microgrid framework relies on integrating these distributed energy resources (DERs) to achieve regional energy independence that leads to a reliable and environment-friendly power grid. In this work, highly granular and decentralized coordination schemes are proposed that will enable fast computation of source dispatch set-points, thereby appropriately accounting for frequent changes in regional load-supply configuration of a microgrid. The mathematical models utilized in the study sufficiently represent the steady-state electrical interdependencies and feasibility limits in islanded or ...


Adaptation Of A Deep Learning Algorithm For Traffic Sign Detection, Jose Luis Masache Narvaez Jul 2019

Adaptation Of A Deep Learning Algorithm For Traffic Sign Detection, Jose Luis Masache Narvaez

Electronic Thesis and Dissertation Repository

Traffic signs detection is becoming increasingly important as various approaches for automation using computer vision are becoming widely used in the industry. Typical applications include autonomous driving systems, mapping and cataloging traffic signs by municipalities. Convolutional neural networks (CNNs) have shown state of the art performances in classification tasks, and as a result, object detection algorithms based on CNNs have become popular in computer vision tasks. Two-stage detection algorithms like region proposal methods (R-CNN and Faster R-CNN) have better performance in terms of localization and recognition accuracy. However, these methods require high computational power for training and inference that make ...


Nonlinear Attitude And Pose Filters With Superior Convergence Properties, Hashim Abdellah Hashim Mohamed Jul 2019

Nonlinear Attitude And Pose Filters With Superior Convergence Properties, Hashim Abdellah Hashim Mohamed

Electronic Thesis and Dissertation Repository

In this thesis, several deterministic and stochastic attitude filtering solutions on the special orthogonal group SO(3) are proposed. Firstly, the attitude estimation problem is approached on the basis of nonlinear deterministic filters on SO(3) with guaranteed transient and steady-state measures. The second solution to the attitude estimation problem considers nonlinear stochastic filters on SO(3) with superior convergence properties with two filters being developed in the sense of Ito, and one in the sense of Stratonovich.

This thesis also presents several deterministic and stochastic pose filtering solutions developed on the special Euclidean group SE(3). The first solution ...


Analysis, Design And Demonstration Of Control Systems Against Insider Attacks In Cyber-Physical Systems, Xirong Ning Jun 2019

Analysis, Design And Demonstration Of Control Systems Against Insider Attacks In Cyber-Physical Systems, Xirong Ning

Electronic Thesis and Dissertation Repository

This dissertation aims to address the security issues of insider cyber-physical attacks and provide a defense-in-depth attack-resilient control system approach for cyber-physical systems.

Firstly, security analysis for cyber-physical systems is investigated to identify potential risks and potential security enhancements. Vulnerabilities of the system and existing security solutions, including attack prevention, attack detection and attack mitigation strategies are analyzed.

Subsequently, a methodology to analyze and mathematically characterize insider attacks is developed. An attack pattern is introduced to represent key features in an insider cyber-physical attack, which includes attack goals, resources, constraints, modes, as well as probable attack paths. Patterns for such ...


Gabor Filter Initialization And Parameterization Strategies In Convolutional Neural Networks, Long Pham Apr 2019

Gabor Filter Initialization And Parameterization Strategies In Convolutional Neural Networks, Long Pham

Electronic Thesis and Dissertation Repository

Convolutional neural networks (CNN) have been widely known in literature to be extremely effective for classifying images. Some of the filters learned during training of the first layer of a CNN resemble the Gabor filter. Gabor filters are extremely good at extracting features within an image. We have taken this as an incentive by replacing the first layer of a CNN with the Gabor filter to increase speed and accuracy for classifying images. We created two simple 5-layer AlexNet-like CNNs comparing grid-search to random-search for initializing the Gabor filter bank. We trained on MNIST, CIFAR-10, and CIFAR-100 as well as ...


Autonomous And Real Time Rock Image Classification Using Convolutional Neural Networks, Alexis David Pascual Feb 2019

Autonomous And Real Time Rock Image Classification Using Convolutional Neural Networks, Alexis David Pascual

Electronic Thesis and Dissertation Repository

Autonomous image recognition has numerous potential applications in the field of planetary science and geology. For instance, having the ability to classify images of rocks would allow geologists to have immediate feedback without having to bring back samples to the laboratory. Also, planetary rovers could classify rocks in remote places and even in other planets without needing human intervention. In 2017, Shu et. al. used a Support Vector Machine (SVM) classification algorithm to classify 9 different types of rock images using a with the image features extracted autonomously. Through this method, they achieved a test accuracy of 96.71%. Within ...


Electroacoustic Assessment Of Hearing Aids And Psaps, Manan Sheel Dec 2018

Electroacoustic Assessment Of Hearing Aids And Psaps, Manan Sheel

Electronic Thesis and Dissertation Repository

Hearing aids and personal sound amplification products (PSAPs) are commonly used assistive devices for treating hearing loss. Due to the diversity in the hardware and signal processing algorithms in these devices, comprehensive verification of their performance is essential. Existing standards for assistive hearing devices are primarily used for quality control purposes and do not quantify their performance in a perceptually-relevant manner. This thesis developed a comprehensive electroacoustic testing toolbox for hearing devices that encompasses both quality control and perceptually-relevant measures. In particular, a test sequence was developed to assess the effectiveness of noise reduction feature in assistive hearing devices. Several ...


Objective Assessment Of Machine Learning Algorithms For Speech Enhancement In Hearing Aids, Krishnan Parameswaran Dec 2018

Objective Assessment Of Machine Learning Algorithms For Speech Enhancement In Hearing Aids, Krishnan Parameswaran

Electronic Thesis and Dissertation Repository

Speech enhancement in assistive hearing devices has been an area of research for many decades. Noise reduction is particularly challenging because of the wide variety of noise sources and the non-stationarity of speech and noise. Digital signal processing (DSP) algorithms deployed in modern hearing aids for noise reduction rely on certain assumptions on the statistical properties of undesired signals. This could be disadvantageous in accurate estimation of different noise types, which subsequently leads to suboptimal noise reduction. In this research, a relatively unexplored technique based on deep learning, i.e. Recurrent Neural Network (RNN), is used to perform noise reduction ...


Performance Enhancement Of Ieee 802.11ax In Ultra-Dense Wireless Networks, Jiyang Bai Dec 2018

Performance Enhancement Of Ieee 802.11ax In Ultra-Dense Wireless Networks, Jiyang Bai

Electronic Thesis and Dissertation Repository

IEEE 802.11ax, which is one emerging WLAN standard, aims at providing highly efficient communication in ultra-dense wireless networks. However, due to a large number of stations (STAs) in dense deployment scenarios and diverse services to be supported, there are many technical challenges to be overcome. Firstly, the potential high packet collision rate significantly degrades the network efficiency of WLAN. In this thesis, we propose an adaptive station (STA) grouping scheme to overcome this challenge in IEEE 802.11ax using Uplink OFDMA Random Access (UORA). In order to achieve optimal utilization efficiency of resource units (RUs), we first analyze the ...


Current Implementation Of The Flooding Time Synchronization Protocol In Wireless Sensor Networks, Asma Khalil Dec 2018

Current Implementation Of The Flooding Time Synchronization Protocol In Wireless Sensor Networks, Asma Khalil

Electronic Thesis and Dissertation Repository

Time synchronization is an issue that affects data accuracy within wireless sensor networks (WSNs). This issue is due to the complex nature of the wireless medium and can be mitigated with accurate time synchronization. This research focuses on the Flooding Time Synchronization Protocol (FTSP) since it is considered as the gold standard for accuracy in WSNs. FTSP minimizes the synchronization error by executing an algorithm that creates a unified time for the network reporting micro-second accuracy. Most synchronization protocols use the FTSP implementation as a benchmark for comparison. The current and only FTSP implementation runs on the TinyOS platform and ...


Continuous Monitoring Of Neutral Grounding Resistors And Reactors, Rahim Jafari Nov 2018

Continuous Monitoring Of Neutral Grounding Resistors And Reactors, Rahim Jafari

Electronic Thesis and Dissertation Repository

Electrical power system components are designed three-phase balanced and symmetric with the internal connection of wye or delta. The common point of the wye-connected equipment, which is called neutral, is impedance grounded for many reasons such as fault ride through by controlling transient overvoltages, and limiting the ground overcurrents. Depending on the application, different neutral impedance grounding methods exist that employ resistors or reactors with/without neutral grounding transformers. These apparatuses are known as Neutral Grounding Devices (NGD). The most well-known sort of NGDsarethe Neutral Grounding Resistor (NGR) and Neutral Grounding Reactor (NGL) which are the main focus of this ...


Spectral And Energy Efficient Communication Systems And Networks, Abdulbaset Hamed Oct 2018

Spectral And Energy Efficient Communication Systems And Networks, Abdulbaset Hamed

Electronic Thesis and Dissertation Repository

In this thesis, design and analysis of energy- and spectral-efficient communication and cellular systems in micro wave and millimeter wave bands are considered using the following system performance metrics: i) Energy efficiency; ii) Spectral efficiency; iii) Spatial spectral efficiency; iv) Spatial energy efficiency, and v) Bit error rate. Statistical channel distributions, Nakagami-m and Generalized-K, and path loss models, Line of Sight (LOS) and Non-Line of Sight (NLOS), are used to represent the propagation environment in these systems. Adaptive M-QAM and M-CPFSK communication systems are proposed to enhance their efficiency metrics as a function of Signal-to-Noise Ratio (SNR) over the channel ...


Generalized Scattering-Based Stabilization Of Nonlinear Interconnected Systems, Anastasiia Usova Oct 2018

Generalized Scattering-Based Stabilization Of Nonlinear Interconnected Systems, Anastasiia Usova

Electronic Thesis and Dissertation Repository

The research presented in this thesis is aimed at development of new methods and techniques for stability analysis and stabilization of interconnections of nonlinear systems, in particular, in the presence of communication delays. Based on the conic systems' formalism, we extend the notion of conicity for the non-planar case where the dimension of the cone's central subspace may be greater than one. One of the advantages of the notion of non-planar conicity is that any dissipative system with a quadratic supply rate can be represented as a non-planar conic system; specifically, its central subspace and radius can be calculated ...


A Biomechanical And Physiological Signal Monitoring System For Four Degrees Of Upper Limb Movement, Allison R. Goldman Sep 2018

A Biomechanical And Physiological Signal Monitoring System For Four Degrees Of Upper Limb Movement, Allison R. Goldman

Electronic Thesis and Dissertation Repository

A lack of adherence to prescribed physical therapy regimens in improper healing results in poor outcomes for those affected by musculoskeletal disorders (MSDs) of the upper limb. Societal and psychological barriers to proper adherence can be addressed through the system presented in this work consisting of the following components: an ambulatory biosignal acquisition sleeve, an electromyography (EMG) based motion repetition detection algorithm, and the design of a compatible capacitive EMG acquisition module.

The biosignal acquisition sleeve was untethered, unobtrusive to motion, contained only modular components, and collected biomechanical and physiological sensor data to form full motion profiles of the following ...


Non-Pilot Protection Of The Inverter-Dominated Ac Microgrid, Houman Lahiji Sep 2018

Non-Pilot Protection Of The Inverter-Dominated Ac Microgrid, Houman Lahiji

Electronic Thesis and Dissertation Repository

The main objective of this research is to develop reliable non-pilot protection and control strategies for the inverter-dominated microgrid. First, an improved Proportional-Derivative (PD) droop control strategy is proposed for enhanced disturbance response of the inverter-dominated AC microgrid. The proposed strategy significantly improves microgrid dynamic response and stability without requiring communication between distributed energy resources. Moreover, the impacts of large startup currents of induction motors on the stability and power quality of the inverter-dominated microgrid are investigates and recommendations for minimizing the associated adverse effects are made.

Subsequently, a fast, selective, and reliable protection strategy for the inverter-dominated microgrid is ...


New Algorithms For Locating Faults In Series Capacitive Compensated Transmission Lines, Tirath Bains Sep 2018

New Algorithms For Locating Faults In Series Capacitive Compensated Transmission Lines, Tirath Bains

Electronic Thesis and Dissertation Repository

The precise location of the fault in a series capacitive compensated transmission line (SCCTL) plays an integral part in limiting the maintenance time following its tripping due to the occurrence of a permanent fault. Since, an SCCTL acts as a huge corridor of power, its outage will result in huge monetary losses which are directly proportion to the time it remains out of service. In worst case scenario, the tripping of an SCCTL might lead to the cascaded tripping of the parallel transmission lines due to overloading. Therefore, the need for an accurate and robust fault location algorithm for the ...


Automatic Recall Of Lessons Learned For Software Project Managers, Tamer Mohamed Abdellatif Mohamed Aug 2018

Automatic Recall Of Lessons Learned For Software Project Managers, Tamer Mohamed Abdellatif Mohamed

Electronic Thesis and Dissertation Repository

Lessons learned (LL) records constitute a software organization’s memory of successes and failures. LL are recorded within the organization repository for future reference to optimize planning, gain experience, and elevate market competitiveness. However, manually searching this repository is a daunting task, so it is often overlooked. This can lead to the repetition of previous mistakes and missing potential opportunities, which, in turn, can negatively affect the organization’s profitability and competitiveness. In this thesis, we present a novel solution that provides an automatic process to recall relevant LL and to push them to project managers. This substantially reduces the ...


Recurrent Neural Network Architectures Toward Intrusion Detection, Wafaa Anani Aug 2018

Recurrent Neural Network Architectures Toward Intrusion Detection, Wafaa Anani

Electronic Thesis and Dissertation Repository

Recurrent Neural Networks (RNN) show a remarkable result in sequence learning, particularly in architectures with gated unit structures such as Long Short-term Memory (LSTM). In recent years, several permutations of LSTM architecture have been proposed mainly to overcome the computational complexity of LSTM. In this dissertation, a novel study is presented that will empirically investigate and evaluate LSTM architecture variants such as Gated Recurrent Unit (GRU), Bi-Directional LSTM, and Dynamic-RNN for LSTM and GRU specifically on detecting network intrusions. The investigation is designed to identify the learning time required for each architecture algorithm and to measure the intrusion prediction accuracy ...


Development Of Image-Based Surgical Planning Software For Bone-Conduction Implants, Carlos D. Salgado Aug 2018

Development Of Image-Based Surgical Planning Software For Bone-Conduction Implants, Carlos D. Salgado

Electronic Thesis and Dissertation Repository

The BONEBRIDGE bone-conduction device is used to treat conductive and mixed hearing losses. The size of its floating mass transducer (FMT) can preclude implantation in certain anatomies, necessitating comprehensive surgical planning. Current techniques are time consuming and difficult to transfer to the operating room. The objective of this thesis was to develop software for calculating skull thickness to the dura mater to find locations for the FMT and to the first air cells which guarantee sufficient bone for the implant screws to grasp. Temporal bone computed tomography (CT) images were segmented and processed and custom Matlab code was written to ...


Development Of An Emg-Based Muscle Health Model For Elbow Trauma Patients, Emma Farago Aug 2018

Development Of An Emg-Based Muscle Health Model For Elbow Trauma Patients, Emma Farago

Electronic Thesis and Dissertation Repository

Musculoskeletal (MSK) conditions are a leading cause of pain and disability worldwide. Rehabilitation is critical for recovery from these conditions and for the prevention of long-term disability. Robot-assisted therapy has been demonstrated to provide improvements to stroke rehabilitation in terms of efficiency and patient adherence. However, there are no wearable robot-assisted solutions for patients with MSK injuries. One of the limiting factors is the lack of appropriate models that allow the use of biosignals as an interface input. Furthermore, there are no models to discern the health of MSK patients as they progress through their therapy.

This thesis describes the ...


Signal Identification In Discrete-Time Based On Internal-Model-Principle, Jie Chen Aug 2018

Signal Identification In Discrete-Time Based On Internal-Model-Principle, Jie Chen

Electronic Thesis and Dissertation Repository

This work presents an implementation of a signal identification algorithm which is based on the internal model principle. By using several internal models in feedback with a tuning function, this algorithm can decompose a signal into narrow-band signals and identify the frequencies, amplitudes and relative phases. A desired band-pass filter response can be achieved by selecting appropriate coefficients of the controllers and tuning functions, which can reject the noise and improve the performance. To achieve a result with fast transient characteristics, this system is then modified by adding a low-pass filter. This work is based on the previous work in ...


Real-Time Intrusion Detection Using Multidimensional Sequence-To-Sequence Machine Learning And Adaptive Stream Processing, Gobinath Loganathan Aug 2018

Real-Time Intrusion Detection Using Multidimensional Sequence-To-Sequence Machine Learning And Adaptive Stream Processing, Gobinath Loganathan

Electronic Thesis and Dissertation Repository

A network intrusion is any unauthorized activity on a computer network. There are host-based and network-based Intrusion Detection Systems (IDS's), of which there are each signature-based and anomaly-based detection methods. An anomalous network behavior can be defined as an intentional violation of the expected sequence of packets. In a real-time network-based IDS, incoming packets are treated as a stream of data. A stream processor takes any stream of data or events and extracts interesting patterns on the fly. This representation allows applying statistical anomaly detection using sequence prediction algorithms as well as using a stream processor to perform signature-based ...