Digital Commons Network^™

Understanding And Identifying Vulnerabilities Related To Architectural Security Tactics, Joanna Cecilia Da Silva Santos

Theses

To engineer secure software systems, software architects elicit the system's security requirements to adopt suitable architectural solutions. They often make use of architectural security tactics when designing the system's security architecture. Security tactics are reusable solutions to detect, resist, recover from, and react to attacks. Since security tactics are the building blocks of a security architecture, flaws in the adoption of these tactics, their incorrect implementation, or their deterioration during software maintenance activities can lead to vulnerabilities, which we refer to as "tactical vulnerabilities". Although security tactics and their correct adoption/implementation are crucial elements to achieve security, prior works have …

A Reinforcement Learning Approach To Vehicle Path Optimization In Urban Environments, Shamsa Abdulla Al Hassani

Theses

Road traffic management in metropolitan cities and urban areas, in general, is an important component of Intelligent Transportation Systems (ITS). With the increasing number of world population and vehicles, a dramatic increase in road traffic is expected to put pressure on the transportation infrastructure. Therefore, there is a pressing need to devise new ways to optimize the traffic flow in order to accommodate the growing needs of transportation systems. This work proposes to use an Artificial Intelligent (AI) method based on reinforcement learning techniques for computing near-optimal vehicle itineraries applied to Vehicular Ad-hoc Networks (VANETs). These itineraries are optimized based …

Assimilating Requirements Specification For Space Manned Missions: A Novel Approach, Khalfan Mohamed Al Remeithi

Theses

Aligned with the UAE Space Strategy 2117, which aims to establish the first inhabitable human on the Martian Surface by 2117, and with the current enthuse toward space tourism, the thesis proposes a novel framework to assimilate the process of requirement specification for a Manned Mission to Mars surface. Deep Space manned missions are unique and characterized by a set of specific requirements that should be elicited from different sources and stakeholders to ensure the missions’ success. In addition, these missions are highly dependent on the software components in the Command and Data Handling System (CDHS), which is used to …

Exploring Wireless Data Center Networks: Can They Reduce Energy Consumption While Providing Secure Connections?, Sayed Ashraf Mamun

Theses

Data centers have become the digital backbone of the modern world. To support the growing demands on bandwidth, Data Centers consume an increasing amount of power. A significant portion of that power is consumed by information technology (IT) equipment, including servers and networking components. Additionally, the complex cabling in traditional data centers poses design and maintenance challenges and increases the energy cost of the cooling infrastructure by obstructing the flow of chilled air. Hence, to reduce the power consumption of the data centers, we proposed a wireless server-to-server data center network architecture using millimeter-wave links to eliminate the need for …

Experimental Analysis Of Using Radar As An Extrinsic Sensor For Human-Robot Collaboration, Shravan Bhoopasamudram Krishna

Theses

Collaborative robots are expected to be an integral part of driving the fourth industrial revolution that is soon expected to happen. In human-robot collaboration, the robot and a human share a common workspace and work on a common task. Here the safety of a human working with the robot is of utmost importance. A collaborative robot usually consists of various sensors to ensure the safety of a human working with the robot. This research mainly focuses on establishing a safe environment for a human working alongside a robot by mounting an FMCW radar as an extrinsic sensor, through which the …

Rm-Net: Rasterizing Markov Signals To Images For Deep Learning, Kajal Gupta

Theses

Statistical machine learning approaches are quite famous for processing Markov signal data. They can model unobserved states and learn certain characteristics particular to a signal with good accuracy. However, with the advent of Deep learning the novice ways of solving a problem has shifted towards this more sophisticated algorithm, which is much better, powerful and more accurate. Specifically, Convolutional Neural Nets (CNN) have shown many promising results on images and videos. Here we illustrate how CNN can be applied to a 1D numeric signal using signal rasterization technique. We start by rasterizing a 1D numeric Markov signal into an image …

Iii-Nitride Ultraviolet Light-Emitting Diodes: Approaches For The Enhanced Efficiency, Moulik Patel

Theses

III-nitride ultraviolet (UV) light-emitting diodes (LEDs) offer marvelous potential for a wide range of applications, including air/water purification, surface disinfection, biochemical sensing, cancer cell elimination, and many more. III-nitride semiconductor alloys, especially AlGaN and AlInN, have drawn significant attention due to their significant advantages that include environmental-friendly material composition, compact in size, longer lifetime, low power consumption, and tunable optical emission. However, the performance of III-nitride UV LEDs in terms of efficiency and output power is still deficient. The presence of high defects and dislocations due to lattice-mismatched epilayers, polarization induced quantum-confined Stark effect, electron overflow with low hole injection …

Short Term Temperature Forecasting Using Lstms, And Cnn, Darshan Shah

Theses

Weather forecasting is a vital application in present times. We can use the predictions to minimize the weather related loss. Use of machine learning and deep learning algorithms for forecasting, can eliminate or reduce the necessity of big data and high computation dependent process of parameterization. Long Short-Term Memory (LSTM) is a widely used deep learning architecture for time series forecasting. In this paper, we aim to predict one day ahead average temperature using a 2-layer neural network consisting of one layer of LSTM and one layer of 1D convolution. The input is pre-processed using a smoothing technique and output …

Finite Element Modeling Of Underwater Acoustic Environments And Domain Decomposition Methods, General Ozochiawaeze

Theses

Underwater acoustic scattering problems have several important applications ranging from sonar imaging in target detection to providing information for sediment classification and geoacoustic inversion. This work presents numerical methods for time-harmonic acoustic scattering problems, specifically, finite element methods for the Helmholtz equation. Furthermore, an iterative domain decomposition formulation is introduced for acoustic scattering problems where the physical domain consists of multiple layers of different materials.

Assembly And Detection Of 3-D Qr Codes Through Additive Manufacturing And Terahertz Imaging, Patrick Dunn

Theses

Automatic identification and data capture, or AIDC, plays a substantial role in contemporary business, advertising, and military needs. The purpose of this study is to generate a potential alternative to current AIDC approaches by constructing three-dimensional plastic tags (or ‘3D QR codes’) using additive manufacturing techniques and interrogate them using Terahertz radiation. 3D Quick Response (QR) codes are designed in 3D computer-aided design software. The QR codes are 3D structures embedded in the printed plastic in which an air gap in the plastic (or an air gap filled in with another type of plastic) indicates a bit of information. Information …

Stationary Probability Distributions Of Stochastic Gradient Descent And The Success And Failure Of The Diffusion Approximation, William Joseph Mccann

Theses

In this thesis, Stochastic Gradient Descent (SGD), an optimization method originally popular due to its computational efficiency, is analyzed using Markov chain methods. We compute both numerically, and in some cases analytically, the stationary probability distributions (invariant measures) for the SGD Markov operator over all step sizes or learning rates. The stationary probability distributions provide insight into how the long-time behavior of SGD samples the objective function minimum.

A key focus of this thesis is to provide a systematic study in one dimension comparing the exact SGD stationary distributions to the Fokker-Planck diffusion approximation equations —which are commonly used in …

Time Series Forecasting With Applications To Finance, Viswapriya Misra

Theses

In finance, many phenomena are modeled as time series. This thesis investigates time series forecasting problems in finance, precisely the stock price prediction problem. We employ and compare traditional statistical algorithms like MA, ARIMA, and ARMA-GARCH with newly developed deep learning-based algorithms such RNNs, LSTMs, GRUs, TCNs, and bidirectional LSTMs and GRUs for predicting stock prices. We perform a comprehensive study and present all the experimental results on different datasets. We find that ARIMA and GRU perform better for single-step stock price prediction than other deep learning architectures. Adding market and economic indicators do not improve the performance of the …

Land Cover Image Segmentation Based On Individual Class Binary Segmentation, Sathyanarayanan Somasunder

Theses

Remote sensing techniques have been developed over the past decades to acquire data without being in contact of the target object or data source. Their application on land-cover image segmentation has attracted significant attention in recent years. With the help of satellites, scientists and researchers can collect and store high resolution image data that can be further processed, segmented, and classified. However, these research results have not yet been synthesized to provide coherent guidance on the effect of variant land-cover segmentation processes. In this paper, we present a novel model that augments segmentation using smaller networks to segment individual classes. …

Limitations Of Artificial Intelligence, Sahar Sultan

Theses

Artificial Intelligence is a groundbreaking technology that is now an established field. It is being used to mimic human capabilities such as speaking, listening, learning, and planning by using different algorithms to process data and produce results depending on the information provided by the user. Artificial Intelligence has been used in several industries when it comes to data processing and decision making. Artificial Intelligence has been invented to help decision and solutionmaking processes using a problem-solving approach. The development of Artificial Intelligence software provides efficiency and acceleration on different kinds of workflows, which will help organizations increase their profit and …

Intelligent Statcom Voltage Regulation Using Fuzzy Logic Control, Saleh Hussein

Theses

Reactive power compensation is a very important and challenging task in electrical power systems today. Future trends foreseen in power systems such as high interconnectivity and the integration of renewable energy resources produce even more issues related to power system control and stability. Flexible AC transmission systems are vastly used in power systems in order to mitigate several performance aspects found in typical power systems. One shunt connected device in particular, STATCOM, is very powerful and commonly used in voltage regulation at the power transmission level. STATCOM uses voltage sourced converters to inject or absorb reactive power from the power …

Port-All: Reproduction Of The Sense Of Companionship In A Long-Distance Relationship, Xincan Yang

Theses

The long-distance relationship is a common phenomenon in contemporary society. Nowadays with the development of the Internet, we have various instant messaging software which gives us an effective way to keep communication with distant others. But it also brings a series of new problems.

Due to the lack of physical contact, time difference, and high dependence on the Internet, people often experience negative emotions in long-distance relationships from delayed communication, suspicion, and misunderstanding of messages. Research shows that most couples feel tired and anxious for a long time in a long-distance relationship, and one of the core reasons is the …

Streaming Down The Stern-Brocot Tree: Finding And Expressing Solutions To Pell's Equation In Sl(2,Z), Marcus L. Shell

Theses

This paper explores and elaborates on a method of solving Pell’s equation as introduced by Norman Wildberger. In the first chapters of the paper, foundational topics are introduced in expository style including an explanation of Pell’s equation. An explanation of continued fractions and their ability to express quadratic irrationals is provided as well as a connection to the Stern-Brocot tree and a convenient means of representation for each in terms of 2×2 matrices with integer elements. This representation will provide a useful way of navigating the Stern-Brocot tree computationally and permit us a means of computing continued fractions without the …

Translating Macroscale Concepts To Microfluidic Devices, Nicole Hill

Theses

Electrokinetics represents an extremely versatile family of techniques that can be used to manipulate particles and fluid in microfluidic devices. This dissertation focused on taking techniques commonly used on a macroscale and developing microscale equivalents utilizing electrokinetics to effectively manipulate and separate microparticles. This analysis focuses on chromatography and separation trains as macroscale techniques translated to microfluidic insulator-based electrokinetic devices. The geometries of insulating post arrays embedded in microchannels were optimized using a combination of mathematical simulations and experimentally derived correction factors. Two particle separations were experimentally demonstrated: a separation based on differences in particle size and a separation based …

Business Data Analytics Dashboard Development For Performance Improvement Of Uae Government Service Centers, Laith Iyad Alawaysheh

Theses

His Highness Sheikh Mohammed bin Rashid Al Maktoum, The Vice President of UAE, The Prime Minister and Ruler of Dubai, once said that “Focusing on the happiness of various customers and enabling them to achieve an outstanding service experience, is a fundamental pillar for government development” and this quote was one of the main triggers for this project, which has a clear purpose to “enhance and improve the customer experience (CX) and service centers performance by implementing data analytics concept along with forecasting future demand of customers and benefit from it in the capacity planning of service centers’ resources”. Through …

Volume-Based Estimates Of Left Ventricular Blood Pool Volume And Ejection Fraction From Multi-Plane 2d Ultrasound Images, Dawei Liu

Theses

Accurate estimations of left ventricular (LV) blood pool volume and left ventricular ejection fraction (LVEF) are crucial for the clinical diagnosis of cardiac disease, patient management, or other therapeutic treatment decisions, especially given a patient’s LVEF often affects his or her candidacy for cardiovascular intervention. Ultrasound (US) imaging is the most common and least expensive imaging modalities used to non-invasively image the heart to estimate the LV blood pool volume and assess LVEF. Despite advances in 3D US imaging, 2D US images are routinely used by cardiologists to image the heart and their interpretation is inherently based on the 2D …

Automation And Advancement Of Non-Invasive Continuous Blood Glucose Measurements, Andrew Devries

Theses

Researching the RF application of noninvasive continuous, real time, blood glucose monitoring has been a persistent topic of interest for the research group at the electromagnetic theory and application (ETA) lab at RIT. The technique is based on the effects of glucose on the dielectric properties of blood. When the dielectric permittivity of the tissue changes due to glucose, the resonant frequency and input impedance of an antenna sensor can be related to the change in glucose level, as shown in [1] and [2]. The feasibility of this technique has been demonstrated successfully with one diabetic and one non-diabetic patient …

A Comparison Of Quantum Algorithms For The Maximum Clique Problem, Andrew R. Haverly

Theses

Two of the most promising computational models for quantum computing are the qubit-based model and the continuous variable model, which result in two different computational approaches, namely the qubit gate model and boson sampling. The qubit gate model is a universal form of quantum computation that relies heavily on the principles of superposition and entanglement to solve problems using qubits based on technologies ranging from magnetic fields created from superconducting materials to the spins of valence electrons in atoms. Boson sampling is a non-universal form of quantum computation that uses bosons as continuous-variable values for its computation. Both models show …

Predicting The Required Demand Flow To A Customer, Thani Almansoori

Theses

Yearly District Cooling Company (DCC) needs to upgrade the plants to meet customer requirements. Moreover, this project will help the company to find when the demand load of flow will reach above the plant's installed capacity and how much increase is expected. So, the dataset was provided by the company for previous years. By applying ML and Arima, KNN, and SVM algorithms, it was found that the best result was the KNN algorithm with an accuracy of 94%, and the maximum flow load will be reached in summer of upcoming years. Hence, the company needs to take further action to …

Heart Rhythm Classification From Static And Ecg Time-Series Data Using Hybrid Multimodal Deep Learning, Ahmad Abdulrazaq Abdulla Alnajjar

Theses

Cardiovascular arrhythmia diseases are considered as the most common diseases that cause death around the world. Abnormal arrhythmia diseases can be identified by analyzing heart rhythm using an electrocardiogram (ECG). However, this analysis is done manually by cardiologists, which may be subjective and susceptible to different cardiologist observations and experiences, as well as to noise and irregularities in those signals. This can lead to misdiagnosis. Motivated by this challenge, an automated heart rhythm diagnosis approach from ECG signals using Deep Learning has been proposed. In order to achieve this goal, three research problems have been addressed. First, recognize the role …

Technique To Reduce The Robbing Crime Rate In Dubai During The Event Of Expo 2020 By Analyzing Relevant Data., Abdulla Ahmed Kankzar

Theses

Dubai’s crime rate appears to be significantly lower. However, do not let this lull you into a false sense of security. Most of the crime occurs in areas populated primarily by lower-income, temporary laborers originating from other countries. Most crimes attributed to this group consist of petty theft, public offenses (e.g., fighting, public intoxication, and property damage), sexual harassment, and rare incidents of violent assault. Using advanced techniques to classify which category the crime belongs to; it will help the concerned authorities to tackle the major crime happening in the City and helpful to find out rare crimes in the …

Introducing Handwriting Into A Multimodal Latex Formula Editor, Yancarlos Diaz

Theses

Handwriting has been shown to be a useful input modality for math. However, math recognizers are imperfect, especially when recognizing complex expressions. Instead of improving the recognizer itself, we explore ways to best visualize the recognizer's output to help the user fix recognition mistakes more efficiently. To do this, we propose changes to the visual editing operations in MathDeck, a math-aware search engine and formula editor, as well as the addition of an n-best list of results for each symbol in the recognizer's output. We present two experiments to help us find good ways to help users fix errors in …

Examining Awareness And Identification Procedures Of Students With Specific Learning Disabilities In Uae Elementary Government Schools, Hana Aidrous Omar

Theses

Specific Learning Disability (SLD) is the most prevalent type of disability. Many students have been incorrectly identified as having SLD when, in fact, they have a different issue or disability. Other students with serious academic problems have been ignored and have not been evaluated. This study, therefore, examines the procedures used to identify students with SLD in UAE elementary government schools. The purpose of this study is twofold: (a) to examine the diagnostic procedures and steps that UAE elementary government schools follow to identify and place students with SLD and (b) to investigate school professionals’ awareness of SLD. A mixed …

Sustainability Of Modern Groundwater Pumping Technologies, Life Cycle Assessment, Hesham Mahmood Alshehabi

Theses

The sustainability of groundwater equipment systems is not well addressed in the Gulf Cooperation Council Countries (GCC). The typical technology practiced in the GCC is the borehole pumps coupled with asynchronous motors. This thesis is evaluating the sustainability of various alternatives for groundwater equipment through the three pillars of sustainability. Economic assessment seeking the Levelized cost of water given typically in $/m³ and main factors affecting the energy intensity through a statistical comparative analysis approach. Environmental evaluation through performing a life cycle assessment model for four pumping alternatives, and finally, societal impact assessment aiming to identify the best practices and …

Performance Of Ultrasound-Assisted Forward Osmosis Membrane Process In Desalination Of Seawater, Bara Awwad Al-Sakaji

Theses

The objective of this study was to investigate the effect of using ultrasound on water flux through forward osmosis membrane when applied for seawater desalination. A synthetically prepared solution simulating seawater characteristics was used. Parameters considered in the investigation included membrane cross-flow velocity (0.25 and 1.0 cm/s), flow configuration (co-current versus counter-current), direction of ultrasound waves relative to the membrane side (active layer versus support layer), and type of draw solution (NaCl versus MgCl₂). Furthermore, a two-level factorial design was considered in the analysis of the results obtained from the experimental work. This study revealed that applying a …

Mindful Consumption, Hind Ali Almualla

Theses

This study explores the impact of human behaviour on spaceship earth. It also explores the possibilities systems thinking offers to address complex problems such as climate change by influencing human behaviour. This study hypothesizes that the level of information the consumer knows about the ecological footprint of a product has an impact on his purchasing decisions in favour of the environment. The hypothesis was tested by running an experiment on an online shopping experience. Fourteen respondents completed the two phases of the experiment and answered two questionnaires. They were followed by 4 in-depth interviews. The analysis measured if there is …