Engineering Commons^™

Machine Learning Techniques For Network Analysis, Irfan Lateef

Dissertations

The network's size and the traffic on it are both increasing exponentially, making it difficult to look at its behavior holistically and address challenges by looking at link level behavior. It is possible that there are casual relationships between links of a network that are not directly connected and which may not be obvious to observe. The goal of this dissertation is to study and characterize the behavior of the entire network by using eigensubspace based techniques and apply them to network traffic engineering applications.

A new method that uses the joint time-frequency interpretation of eigensubspace representation for network statistics …

Iii-Nitride Nanostructures: Photonics And Memory Device Applications, Barsha Jain

Dissertations

III-nitride materials are extensively studied for various applications. Particularly, III-nitride-based light-emitting diodes (LEDs) have become the major component of the current solid-state lighting (SSL) technology. Current III-nitride-based phosphor-free white color LEDs (White LEDs) require an electron blocking layer (EBL) between the device active region and p-GaN to control the electron overflow from the active region, which has been identified as one of the primary reasons to adversely affect the hole injection process. In this dissertation, the effect of electronically coupled quantum well (QW) is investigated to reduce electron overflow in the InGaN/GaN dot-in-a-wire phosphor-free white LEDs and to improve the …

On Resource-Efficiency And Performance Optimization In Big Data Computing And Networking Using Machine Learning, Wuji Liu

Dissertations

Due to the rapid transition from traditional experiment-based approaches to large-scale, computational intensive simulations, next-generation scientific applications typically involve complex numerical modeling and extreme-scale simulations. Such model-based simulations oftentimes generate colossal amounts of data, which must be transferred over high-performance network (HPN) infrastructures to remote sites and analyzed against experimental or observation data on high-performance computing (HPC) facility. Optimizing the performance of both data transfer in HPN and simulation-based model development on HPC is critical to enabling and accelerating knowledge discovery and scientific innovation. However, such processes generally involve an enormous set of attributes including domain-specific model parameters, network transport …

Experimental And Computational Studies Of Functionalized Carbon Nanotubes For Use In Energy Storage Devices And Membranes, Emine S. Karaman

Dissertations

Electrolytes with good interfacial stability are a crucial component of any electrochemical device. The development of novel gel polymer electrolytes (GEs) with good interface stability and better manufacturability is important for the development of the next generation electrochemical devices. Gel electrolytes are hybrid electrolyte materials, combining benefits of both liquid and solid systems. Compared with liquid and solid electrolytes, GEs open new design opportunities and do not require rigorous encapsulation methods. In this dissertation, studies on functionalized carbon nanotubes (fCNTs) and graphene oxide (GO) doped polyvinyl alcohol (PVA) based gel electrolytes (GEs) are reported. The ionic conductivity and mechanical strength …

Development Of Sensor, Sensory System And Signal Processing Algorithm For Intelligent Sensing Applications, Xingzhe Zhang

Dissertations

Sensors have been receiving significant attention in the last decade and the demand for sensory systems has increased in recent years due to the rapid growth in the field of artificial intelligence (AI). Sensors can improve people’s awareness by providing them with real-time information on the environment and their immediate health conditions. This dissertation presents the fulfilment of three main projects and focuses on the development of a sensor, a sensory system, and a sensor signal recognition system for AI applications by employing printed electronics, analog circuit design, and digital signal processing techniques.

In the first project, a multi-channel stethograph …

Simple Procedure For Calculating Parameters Of Permanent Magnet Linear Generator And Methods For Maximizing Power Absorption Using Less Dependent Mathematical Model / Low Computationally Cost Controllers In Wave Energy Converters, Bisni Fahad Mon

Dissertations

The study comprises of designing permanent magnet linear generator (PMLG) for wave energy converters (WECs) and method for maximizing power absorption using less dependent mathematical model or low computationally cost controllers. There are three proposed controller methods: the damping control using maximum power point tracking (MPPT), the reactive control using MPPT, and finite control set model predictive control (FCSMPC).

The first part of the thesis is started with the design and testing of a laboratory scale test-rig for wave energy converters (WECs). The main element of the test-rig is a double-sided permanent magnet linear generator (PMLG). In this study, detailed …

Colloidal Quantum Dot (Cqd) Based Mid-Wavelength Infrared Optoelectronics, Shihab Bin Hafiz

Dissertations

Colloidal quantum dot (CQD) photodetectors are a rapidly emerging technology with a potential to significantly impact today’s infrared sensing and imaging technologies. To date, CQD photodetector research is primarily focused on lead-chalcogenide semiconductor CQDs which have spectral response fundamentally limited by the bulk bandgap of the constituent material, confining their applications to near-infrared (NIR, 0.7-1.0 um) and short-wavelength infrared (SWIR, 1-2.5 um) spectral regions. The overall goal of this dissertation is to investigate a new generation of CQD materials and devices that advances the current CQD photodetector research toward the technologically important thermal infrared region of 3-5 ?m, known as …

Learning Of Radar System For Target Detection, Wei Jiang

Dissertations

In this dissertation, the problem of data-driven joint design of transmitted waveform and detector in a radar system is addressed. Two novel learning-based approaches to waveform and detector design are proposed based on end-to-end training of the radar system. The first approach consists of alternating supervised training of the detector for a fixed waveform and reinforcement learning of the transmitter for a fixed detector. In the second approach, the transmitter and detector are trained simultaneously. Various operational waveform constraints, such as peak-to-average-power ratio (PAR) and spectral compatibility, are incorporated into the design. Unlike traditional radar design methods that rely on …

Intelligent System For Laparoscopic Surgery Suturing Skill Assessment, Mohammed Yasser Al-Gailani

Dissertations

In laparoscopic surgery, which is also referred to as minimally invasive surgery (MIS), surgeons carry out surgical procedures with the assistance of a video camera and several surgical instruments. Laparoscopic surgeons should possess excellent eye-hand coordination capabilities, strong cognitive knowledge, case and problem management, and manual dexterity skills. Such skills can be acquired through simulation using a basic, low-fidelity setup, such as the surgical box-trainer. General surgeons must pass a set of tests on a Fundamentals of Laparoscopic Surgery (FLS) Trainer device.

One pivotal skill for a successful operation is developing a sense of the applied forces on the tissue …

Optimized Insulation Design Of Power Transformer Windings Under Fast Voltage Pulses, Juan Manuel Villanueva Ramirez

Dissertations

Power transformers are essential electrical power system devices. Using the principle of electromagnetic induction, they can transfer electric energy between two otherwise isolated circuits, as well as reduce or increase voltage levels without modifying the frequency. This allows reduction of power losses when electric energy is transferred between power plants and consumers. Because of their importance and widespread use, transformers failures can have a severe economic impact due to the temporary interruption of electric service.

The insulation design of power transformers is performed by considering the maximum values of voltage or current to which the device will be exposed during …

Optical Engineering Of Iii-Nitride Nanowire Light-Emitting Diodes And Applications, Ha Quoc Thang Bui

Dissertations

Applications of III-nitride nanowires are intensively explored in different emerging technologies including light-emitting diodes (LEDs), laser diodes, photodiodes, biosensors, and solar cells. The synthesis of the III-nitride nanowires by molecular beam epitaxy (MBE) is investigated with significant achievements. III-nitride nanowires can be grown on dissimilar substrates i.e., silicon with nearly dislocation free due to the effective strain relaxation. III-nitride nanowires, therefore, are perfectly suited for high performance light emitters for cost-effective fabrication of the advanced photonic-electronic integrated platforms. This dissertation addresses the design, fabrication, and characterization of III-nitride nanowire full-color micro-LED (µLED) on silicon substrates for µLED display technologies, high-efficient …

Selective Neural Stimulation By Leveraging Electrophysiological Diversity And Using Alternative Stimulus Waveforms, Bemin Ghobreal

Dissertations

Efforts on finding the principle mechanism for selective neural stimulation have concentrated on segregating the neurons based on their size and other geometric factors. However, neuronal subtypes found in different parts of the nervous system also differ in their electrophysiological properties. The primary objective of this study is to investigate the feasibility of selective activation of neurons by leveraging the diversity seen in passive and active membrane properties.

Using both a local membrane model and an axon model based on the CRRSS, the diversity of electrophysiological properties is simulated by varying four model parameters (membrane leakage-Gleak and capacitance-Cm, temperature coefficient-Ktemp, …

Intelligent And Secure Fog-Aided Internet Of Drones, Jingjing Yao

Dissertations

Internet of drones (IoD), which utilize drones as Internet of Things (IoT) devices, deploys several drones in the air to collect ground information and send them to the IoD gateway for further processing. Computing tasks are usually offloaded to the cloud data center for intensive processing. However, many IoD applications require real-time processing and event response (e.g., disaster response and virtual reality applications). Hence, data processing by the remote cloud may not satisfy the strict latency requirement. Fog computing attaches fog nodes, which are equipped with computing, storage and networking resources, to IoD gateways to assume a substantial amount of …

Controlled Reduction Of Graphene Oxide And Graphene Oxide-Carbon Nanotube Hybrids And Their Applications, Samar Azizighannad

Dissertations

Graphene and graphene derivatives are widely used in diverse research and industrial applications. Graphene production on a large scale is carried out by exfoliating graphite oxide and producing graphene oxide (GO), which comprises of graphene sheets with different oxygen-containing functional groups such as hydroxyl, carboxyl, and carbonyl. GO is reduced to reduced graphene oxide (rGO), which has properties that are closer to graphene. Properties of GO and rGO depend upon the oxygen content, and the effect of reducing oxygen content on the aqueous behavior of rGOs is not well understood.

In an effort to understand how properties of rGO change …

Machine Learning For Auditory Hierarchy, William Coleman

Dissertations

Coleman, W. (2021). Machine Learning for Auditory Hierarchy. This dissertation is submitted for the degree of Doctor of Philosophy, Technological University Dublin. Audio content is predominantly delivered in a stereo audio file of a static, pre-formed mix. The content creator makes volume, position and effects decisions, generally for presentation in stereo speakers, but has no control ultimately over how the content will be consumed. This leads to poor listener experience when, for example, a feature film is mixed such that the dialogue is at a low level relative to the sound effects. Consumers can complain that they must turn …

Study Of Mm-Wave Fixed Beam And Frequency Beam-Scanning Antenna Arrays, Zeeshan Ahmed

Dissertations

Millimeter-wave frequencies are anticipated to be widely adapted for future wireless communication systems to resolve the demand of high data-rate and capacity issues. The millimeter-wave frequency range offers wide spectrum and a shift for most newly developing technologies as the microwave and lower frequency bands are becoming overcrowded and congested. These high frequency bands offer short wavelengths which has enabled the researchers to design and implement compact and adaptable antenna solutions. This research focuses on the implementation, transformation and modification of antenna structures used in lower frequency bands to millimeter-wave applications with high gain and multi-band and wideband performances.

The …

Cough Monitoring Through Audio Analysis, Thomas Snella

Dissertations

The detection of cough events in audio recordings requires the analysis of a significant amount of data as cough is typically monitored continuously over several hours to capture naturally occurring cough events. The recorded data is mostly composed of undesired sound events such as silence, background noise, and speech. To reduce computational costs and to address the ethical concerns raised from the collection of audio data in public environments, the data requires pre-processing prior to any further analysis.

Current cough detection algorithms typically use pre-processing methods to remove undesired audio segments from the collected data but do not preserve the …

Analysis Of Power Quality Constrained Consumer-Friendly Demand Response In Low Voltage Distributions Network, Chittesh Veni Chandran

Dissertations

Load management using demand response (DR) in a low voltage distribution network (LVDN) offers an economically profitable business platform with peak load management. However, the inconvenience caused to the consumer in depriving their devices and the low levels of associated incentive have contributed to lower consumer acceptance for DR programs in the community. However, with the increasing number of controllable consumer loads, a residential-level DR program is highly plausible in the short to medium term. Further, additional DR capabilities (including ancillary services) are likely to improve the remuneration potential for participants in DR. Considering the perspective of a distribution network …