Electrical and Computer Engineering Commons^™

The Application Of Deep Learning Algorithms To Pediatric Vascular Anomalies Using A Limited Dataset, Briana I. Robertson

Honors Capstones

No abstract provided.

Evaluating Deep-Learning Models For Debris-Covered Glacier Mapping, Zhiyuan Xie, Vijayan K. Asari, Umesh K. Haritashya

Electrical and Computer Engineering Faculty Publications

In recent decades, mountain glaciers have experienced the impact of climate change in the form of accelerated glacier retreat and other glacier-related hazards such as mass wasting and glacier lake outburst floods. Since there are wide-ranging societal consequences of glacier retreat and hazards, monitoring these glaciers as accurately and repeatedly as possible is important. However, the accurate glacier boundary, especially the debriscovered glacier (DCG) boundary, which is one of the primary inputs in many glacier analyses, remains a challenge even after many years of research using conventional remote sensing methods or machine-learning methods. The GlacierNet, a deep-learning-based approach, utilized the …

Sigesn Light-Emitting Devices: From Optical To Electrical Injection, Yiyin Zhou

Graduate Theses and Dissertations

Si photonics is a fast-developing technology that impacts many applications such as data centers, 5G, Lidar, and biological/chemical sensing. One of the merits of Si photonics is to integrate electronic and photonic components on a single chip to form a complex functional system that features compact, low-cost, high-performance, and reliability. Among all building blocks, the monolithic integration of lasers on Si encountered substantial challenges. Si and Ge, conventional epitaxial material on Si, are incompetent for light emission due to the indirect bandgap. The current solution compromises the hybrid integration of III-V lasers, which requires growing on separate smaller size substrates …

Interplay Between The Lattice And Spin Degrees Of Freedom In Magnetoelectric And Magnetic Materials, Temuujin Bayaraa

Graduate Theses and Dissertations

This dissertation contains several investigations on the cross-coupling between structural and spin degrees of freedom in multiferroic and ferrimagnetic compounds by means of first-principles calculations and ab-initio-based Monte-Carlo simulations. We start with the reviews of magnetoelectricity, ferrimagnetism, strain engineering, followed by a brief introduction to first-principles computational methods, magnetic effective Hamiltonians, and other techniques that are utilized here. The results section of the dissertation can be divided into two parts. The first half focuses on magnetoelectric effects arising from different sources, while the second half is about the ferrimagnetic nature of materials. In the first part, we examine the epitaxial …

Study Of Thick Indium Gallium Nitride Graded Structures For Future Solar Cell Applications, Manal Abdullah Aldawsari

Graduate Theses and Dissertations

Indium gallium nitride (InxGa1-xN) materials have held great potential for the optoelectronic industry due to their electrical and optical properties. The tunable band gap that can span the solar spectrum was one of the most significant features that attracted researchers’ attention. The band gap can be varied continuously from 0.77 eV for InN to 3.42 eV for GaN, covering the solar spectrum from near infrared to near ultraviolet. Additionally, it has a high absorption coefficient on the order of ∼105 cm−1, a direct band gap, high radiation resistance, thermal stability, and so on. Nevertheless, the epitaxial growth of high quality …

Goes-16 Level 2 Land Surface Temperature Product-Filling For Cloud Masked Data, Guadalupe Ortega

Open Access Theses & Dissertations

The GOES-16 satellite ground segment team develops different levels of environmental products and makes them readily available to the public. The level 2 Land Surface Temperature (LST) product aims to provide a remote measurement of the Earth’s surface temperature every hour. LST is of fundamental importance to many aspects of the geosciences, for example, to study the Urban Heat Islands (UHI) effect. The product however, does not provide values for pixels where the satellite imager’s view is obstructed by clouds, as determined by a cloud mask intermediate product. The objective of this thesis is to estimate LST in the cloud …

Genome Annotation Using Average Mutual Information, Garin P. Newcomb

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Advancements in high-throughput DNA sequencing technologies and ambitious goals for their use are resulting in the generation of a deluge of unannotated sequenced genomes. This makes computational tools that can aid in annotation increasingly valuable.

Here, we provide a detailed exploration of the utility as well as the limitations of average mutual information (AMI) in several steps of genome annotation. For a genomic sequence, AMI is a measure of the information a base contains about the base separated by a fixed lag. A profile is constructed by calculating AMI at multiple lags. In addition to traditional AMI, we employ two …

Risk-Based Machine Learning Approaches For Probabilistic Transient Stability, Umair Shahzad

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Power systems are getting more complex than ever and are consequently operating close to their limit of stability. Moreover, with the increasing demand of renewable wind generation, and the requirement to maintain a secure power system, the importance of transient stability cannot be overestimated. Considering its significance in power system security, it is important to propose a different approach for enhancing the transient stability, considering uncertainties. Current deterministic industry practices of transient stability assessment ignore the probabilistic nature of variables (fault type, fault location, fault clearing time, etc.). These approaches typically provide a conservative criterion and can result in expensive …

Augmented Communications : A Solution For Overcoming High Spatial Correlation Of The Massive-Miso Vlc Channel, Monette Khadr

Legacy Theses & Dissertations (2009 - 2024)

A key challenge for future wireless networks is to come upon a riveting compromise between spectral efficiency, complexity, and energy efficiency. The challenge is also intensified due to the pace at which the Internet-of-Things (IoT) technology is arriving, causing an upheaval to pre-existing network infrastructures in terms of elevating spectrum scarcity. To keep pace with the exploding data demand forecasts, a circumvention is required. One realization is by utilizing the high-band spectrum and the rich body of knowledge on multiple-input multiple-output (MIMO) technologies. One of the prominent high frequency technologies is visible light communications (VLC). VLC provide a large unregulated …

Radio Direction Finding Implementing Music Algorithm With Usrp Node Arrays, Kevin Valdez

Open Access Theses & Dissertations

Direction Finding techniques are widely used across the fields of radar, telecommunications, geolocation systems, sonar, among many others to estimate the reference position of the incoming signal source. For this, the implementation of antenna arrays is essential as it allows the use of more advanced techniques in signal processing called spatial spectrum estimation [1]. This method of estimation is performed based on the antenna or sensor array response to the signal spatial parameters in every direction and estimate the location of the incoming signals. Algorithms have been developed for the purpose of spatial spectrum analysis, the most popular are MUSIC …

Acoustoelectric Amplification In Piezoelectric-Silicon Micromachined Lamb Wave Devices, Hakhamanesh Mansoorzare

Electronic Theses and Dissertations, 2020-2023

In this dissertation, heterostructured micro-acoustic devices are explored that leverage the interactions between acoustic phonons and electrons to enable radio frequency (RF) signal amplification or attenuation. Thin films of piezoelectric and semiconductor material are tailored into a heterostructure that allows for a strong acoustoelectric (AE) effect due to the combination of high electromechanical coupling and high electron drift velocity in said films respectively. In such devices, the relative electron drift and acoustic velocities could determine whether the RF signal undergoes AE gain or loss, rendering the device non-reciprocal. This is a highly sought-after property for building isolators and circulators which …

Temperature And Strain Sensing With Hybrid Interferometer, Lashari Ghulam Abbas, Zhou Ai, Farhan Mumtaz, Atta Muhammad, Yutang Dai, Rashda Parveen

Electrical and Computer Engineering Faculty Research & Creative Works

A hybrid interferometer for simultaneous measurement of strain and temperature is proposed and investigated experimentally. This hybrid design is composed of Fabry-Perot interferometer (FPI) and Michelson Interferometer (MI) cascaded with each other. It is developed by fusion splicing a single mode fiber (SMF), a multimode fiber (MMF), a dual side hole fiber (DSHF), a hollow core fiber (HCF) and a tapered-SMF. The tapered SMF was inserted into the HCF to form a reflection mirror for the FPI. The maximum temperature and strain sensitivity of the hybrid interferometer achieved through experiments is 11.6 pm/°C and 6.8 pm/mu varepsilon , respectively. The …

Approaching The Fundamental Limit Of Orbital-Angular-Momentum Multiplexing Through A Hologram Metasurface, Shuai S.A. Yuan, Jie Wu, Menglin L.N. Chen, Zhihao Lan, Liang Zhang, Sheng Sun, Zhixiang Huang, Xiaoming Chen, Shilie Zheng, Li (Lijun) Jun Jiang, Xianmin Zhang, Wei E.I. Sha

Electrical and Computer Engineering Faculty Research & Creative Works

Establishing and approaching the fundamental limit of orbital-angular-momentum (OAM) multiplexing are necessary and increasingly urgent for current multiple-input multiple-output research. In this work, we elaborate the fundamental limit in terms of independent scattering channels (or the degrees of freedom of scattered fields) through angular-spectral analysis, in conjunction with a rigorous Green's function method. The scattering-channel limit is universal for arbitrary spatial-mode multiplexing, which is launched by a planar electromagnetic device, such as antenna, metasurface, etc., with a predefined physical size. As a proof of concept, we demonstrate both theoretically and experimentally the limit by a phase-only metasurface hologram that transforms …

Numerical Green's Function-Based Method For Modeling Radiated Emission From Pcbs In Shielding Enclosures, Zi An Wang, Li (Lijun) Jun Jiang, Jun Fa Mao, Ping Li

Electrical and Computer Engineering Faculty Research & Creative Works

Due to stringent electromagnetic compatibility (EMC) regulations, all electronic devices need to go through rigorous radiated emission tests before launching to market. Thus, efficient, accurate, and cheap characterization approaches are quite of interest. Instead of utilizing the time-consuming and expensive direct far-field measurement, in this work, a novel methodology on the basis of numerical Green's function (NGF) is proposed to acquire the parasitic EM emissions from PCBs placed in a shielding enclosure with ventilation slots. Referring to Schelkunoff's equivalence principle, the whole modeling procedure can be decomposed into two steps in order to obtain the emissions in the entire space. …

Integrating Degradation Forecasting And Abatement Framework Into Advanced Distribution Management System, Huu Phuong Hoang

All Dissertations

Future distribution grids are expected to face an increasing penetration of heterogeneous distributed energy resources (DERs) and electric vehicles (EVs). This landscape change will pose challenges to the control and management of distribution grids because of the variability of renewable energy resources and EV charging. In addition, multiple DERs dispersed over networks can also challenge the grid operation and maintenance as various DERs at various locations are needed to be monitored and managed. However, customers will not be content with reductions in power quality, reliability, economy, safety, or security. To enhance the effectiveness of grid control and management, future grids …

Chess Piece Detection, Craig Reid Belshe

Electrical Engineering

This project determines the positions of each piece on a physical chessboard, so that a computer can record a game of chess by noting down the piece positions at the end of each turn. It determines each move so that the game can be replayed later without watching actual footage. The project allows for easy viewing of past games. An image of the chessboard is analyzed to detect each square on the board, and each piece's location. This is then done for each turn, so that the system can keep track of an entire game.

Ac/Dc Led Light Bulb Adaptor With Internal Rechargeable Batteries, Esteban A. Rubio, Matthew R. Delaby

Electrical Engineering

To make a sustainable product and provide a temporary source of lights on during emergencies, this project aims to create a small unit that can be attached to a light bulb of any variety and connect it to a socket. Within the device is a rechargeable battery that, when the device is not connected to an 120V AC, 240V AC, or 48V DC power source, will power the light for a short period of time. The battery can be charged during the standard operation of the device and can be powered by the US and EU standard outlet voltages as …

Directional Spectral Solar Energy For Building Performance: From Simulation To Cyber-Physical Prototype, Joseph Del Rocco

Electronic Theses and Dissertations, 2020-2023

The original research and development in this dissertation contributes to the field of building performance by actively harnessing a wider spectrum of directional solar radiation for use in buildings. Solar radiation (energy) is often grouped by wavelength measurement into the spectra ultraviolet (UV), visible (light), and short and long-wave infrared (heat) on the electromagnetic spectrum. While some of this energy is directly absorbed or deflected by our atmosphere, most of it passes through, scatters about, and collides with our planet. Modern building performance simulations, tools, and control systems often oversimplify this energy into scalar values for light and heat, when …

A Comprehensive Analysis Of Reward Function For Adaptive Traffic Signal Control, Abu Rafe Md Jamil, Naushin Nower

Knowledge Engineering and Data Science

Adaptive traffic control systems (ATCS) can play an essential role in reducing traffic congestion in urban areas. The main challenge for ATSC is to determine the proper signal timing. Recently, Deep Reinforcement Learning (DRL) has been used to determine proper signal timing. However, the success of the DRL algorithm depends on the appropriate reward function design. There exist various reward functions for ATSC in the existing research. This research presents a comprehensive analysis of the widely used reward function. The pros and cons of various reward algorithms were discussed, and experimental analysis shows that the multi-objective reward function enhances the …

Similarity Identification Of Large-Scale Biomedical Documents Using Cosine Similarity And Parallel Computing, Merlinda Wibowo, Christoph Quix, Nur Syahela Hussien, Herman Yuliansyah, Faisal Dharma Adhinata

Knowledge Engineering and Data Science

Document similarity computation is an important research topic in information retrieval, and it is a crucial issue for automatic document categorization. The similarity value is between 0 and 1, then the closest value to 1 is represented both documents is considered more relevant, vice versa. However, the large scale of textual information has created the problem of finding the relevance level between documents. Therefore, the relevance between mesh heading text in the PubMed documents is higher than the relevance of the abstract text in the PubMed documents. Furthermore, parallel computing is implemented to speed up the large-scale documents similarity identification …

Recognition Of Handwritten Javanese Script Using Backpropagation With Zoning Feature Extraction, Anik Nur Handayani, Heru Wahyu Herwanto, Katya Lindi Chandrika, Kohei Arai

Knowledge Engineering and Data Science

Backpropagation is part of supervised learning, in which the training process requires a target. The resulting error is transmitted back to the units below in its training process. Backpropagation can solve complicated problems because it consumes less memory than other algorithms. In addition, it also can produce solutions with a low error rate while executing less time. In image pattern recognition, backpropagation can be utilized for cultural preservation in many places worldwide, including Indonesia. It is used to recognize picture patterns in Javanese script writings. This study concluded that feature extraction approaches, zoning, and backpropagation could be utilized to distinguish …

Airspace Integration Of New Entrants And Safety Risk Management Models, Fadjimata Issoufou Anaroua

Doctoral Dissertations and Master's Theses

In recent years, the demand for airspace access of Unmanned Aerial Systems (UAS) increased significantly and is continuously increasing for different altitude-types UAS. A similar evolution is expected from Commercial Space Operations (CSO) in the next years. These aviation/aerospace systems will need to be seamlessly integrated into the National Airspace System (NAS), at their operational altitude levels, and accounted for from all perspectives, including proactively addressing their safety hazards. This thesis captures the requirements for the new entrants’ integration, and then identifies and analyzes the safety risks added to the NAS operations by its new entrants, the future omnipresent UAS …

Parallel Approach Of Adaptive Image Thresholding Algorithm On Gpu, Adhi Prahara, Andri Pranolo, Nuril Anwar, Yingchi Mao

Knowledge Engineering and Data Science

Image thresholding is used to segment an image into background and foreground using a given threshold. The threshold can be generated using a specific algorithm instead of a pre-defined value obtained from observation or experiment. However, the algorithm involves per pixel operation, histogram calculation, and iterative procedure to search the optimum threshold that is costly for high-resolution images. In this research, parallel implementations on GPU for three adaptive image thresholding methods, namely Otsu, ISODATA, and minimum cross-entropy, were proposed to optimize their computational times to deal with high-resolution images. The approach involves parallel reduction and parallel prefix sum (scan) techniques …

A Comparative Study Of Machine Learning-Based Approach For Network Traffic Classification, Kien Trang, An Hoang Nguyen

Knowledge Engineering and Data Science

Internet usage has increased rapidly and become an essential part of human life, corresponding to the rapid development of network infrastructure in recent years. Thus, protecting users’ confidential information when joining the global network becomes one of the most significant considerations. Even though multiple encryption algorithms and techniques have been applied in different parties, including internet providers, and web hosting, this situation also allows the hacker to attack the network system anonymously. Therefore, the significance of classifying network data streams to improve network system quality and security is attracting increasing study interests. This work introduces a machine learning-based approach to …

Cnn Based Face Recognition System For Patients With Down And William Syndrome, Endang Setyati, Suharyono Az, Subroto Prasetya Hudiono, Fachrul Kurniawan

Knowledge Engineering and Data Science

Down syndrome, also known as trisomy genetic condition, is a genetic disorder that affects many people. Williams syndrome is a hereditary disorder that can affect anyone at birth. It marks medical and cognitive issues, such as cardiovascular illness, developmental delays, and learning impairments. This is accompanied by exceptional verbal abilities, a gregarious attitude, and a passion for music. Down syndrome and William Syndrome are both genetic illnesses. However, it can be distinguished from the arrangement of chromosome 21. Down syndrome and William syndrome can also be identified by recognizing faces, or facial characteristics, such as observing particular facial features. Therefore, …

Melanoma Classification Based On Simulated Annealing Optimization Neural Network, Edi Jaya Kusuma, Ika Pantiawati, Sri Handayani

Knowledge Engineering and Data Science

Technology development in image processing and artificial intelligence leads to the high demand for smart systems, especially in the health sector. Cancer is one of the diseases with the highest mortality cases worldwide. Melanoma is one of the cancers commonly caused by high exposure to UV light. The earliest the melanoma is identified, the higher the patient's chance of recovering. Therefore, this study proposes melanoma detection based on BPNN optimized by a simulated annealing algorithm. This research utilizes PH2 dermoscopic image data containing 200 color digital images in BMP format. The data is processed using color feature extraction techniques to …

Performance Loss Rate And Temperature Modeling In Predictive Energy Yield Programs For Utility-Scale Solar Power Plants, Katelynn M. Dinius

Master's Theses

The Gold Tree Solar Farm, designed by REC Solar, has a rated output power of 4.5 MW and began operation in 2018 to provide electricity to Cal Poly’s campus. Gold Tree Solar Farm site terrain consists of rolling hills and uneven slopes. The uneven typography results in interrow shading, requiring a modified tracking control algorithm to maximize power production. Predicting a utility solar field’s lifetime energy yield is a critical step in assessing project feasibility and calculating project revenue. The MATLAB-based predictive power model developed for this field overpredicted power in the middle of the day. The purpose of this …

Investigation Of Optical And Structural Properties Of Gesn Heterostructures, Oluwatobi Gabriel Olorunsola

Graduate Theses and Dissertations

Silicon (Si)-based optoelectronics have gained traction due to its primed versatility at developing light-based technologies. Si, however, features indirect bandgap characteristics and suffers relegated optical properties compared to its III-V counterparts. III-Vs have also been hybridized to Si platforms but the resulting technologies are expensive and incompatible with standard complementary-metal-oxide-semiconductor processes. Germanium (Ge), on the other hand, have been engineered to behave like direct bandgap material through tensile strain interventions but are well short of attaining extensive wavelength coverage. To create a competitive material that evades these challenges, transitional amounts of Sn can be incorporated into Ge matrix to form …

Network Management, Optimization And Security With Machine Learning Applications In Wireless Networks, Mariam Nabil

Theses and Dissertations

Wireless communication networks are emerging fast with a lot of challenges and ambitions. Requirements that are expected to be delivered by modern wireless networks are complex, multi-dimensional, and sometimes contradicting. In this thesis, we investigate several types of emerging wireless networks and tackle some challenges of these various networks. We focus on three main challenges. Those are Resource Optimization, Network Management, and Cyber Security. We present multiple views of these three aspects and propose solutions to probable scenarios. The first challenge (Resource Optimization) is studied in Wireless Powered Communication Networks (WPCNs). WPCNs are considered a very promising approach towards sustainable, …

Additive Manufacturing Using Robotic Manipulators, Fdm, And Aerosol Jet Printers., Alexander Curry

Electronic Theses and Dissertations

Additive manufacturing has created countless new opportunities for fabrication of devices in the past few years. Advances in additive manufacturing continue to change the way that many devices are fabricated by simplifying processes and often lowering cost. Fused deposition modeling (FDM) is the most common form of 3D printing. It is a well-developed process that can print various plastic materials into three-dimensional structures. This technology is used in a lot of industries for rapid prototyping and sometimes small batch manufacturing. It is very inexpensive, and a prototype can be created in a few hours, rather than days. This is useful …