Electrical and Computer Engineering Commons^™

Integration Of Blockchain Technology Into Automobiles To Prevent And Study The Causes Of Accidents, John Kim

Electronic Theses, Projects, and Dissertations

Automobile collisions occur daily. We now live in an information-driven world, one where technology is quickly evolving. Blockchain technology can change the automotive industry, the safety of the motoring public and its surrounding environment by incorporating this vast array of information. It can place safety and efficiency at the forefront to pedestrians, public establishments, and provide public agencies with pertinent information securely and efficiently. Other industries where Blockchain technology has been effective in are as follows: supply chain management, logistics, and banking. This paper reviews some statistical information regarding automobile collisions, Blockchain technology, Smart Contracts, Smart Cities; assesses the feasibility …

Classifying Electrocardiogram With Machine Learning Techniques, Hillal Jarrar

Master's Theses

Classifying the electrocardiogram is of clinical importance because classification can be used to diagnose patients with cardiac arrhythmias. Many industries utilize machine learning techniques that consist of feature extraction methods followed by Naive- Bayesian classification in order to detect faults within machinery. Machine learning techniques that analyze vibrational machine data in a mechanical application may be used to analyze electrical data in a physiological application. Three of the most common feature extraction methods used to prepare machine vibration data for Naive-Bayesian classification are the Fourier transform, the Hilbert transform, and the Wavelet Packet transform. Each machine learning technique consists of …

Indoor Positioning Using Synchronized Ultrasonic Ofdma Signals, Julian Bartolone

Master's Theses

This paper proposes a method of short-range indoor localization using differential phase measurements of synchronized two-tone ultrasonic signals in an Orthogonal Frequency Multiple Access (OFDMA) scheme. This indoor positioning system (IPS) operates at an ultrasonic frequency of approximately 40kHz and synchronizes using an infrared signal. The OFDMA scheme allows for a receiver to process the signals from multiple transmitters continuously without the signals interfering with each other. The phases of the signals are measured using Goertzel Filters, allowing for low-complexity frequency content analysis. A MATLAB simulation using the proposed localization method is performed using four transmitter nodes in the corners …

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 …

Spatiotemporal Pattern Detection With Neuromorphic Circuits, Robert C. Ivans

Boise State University Theses and Dissertations

In this dissertation, neuromorphic circuits are used to implement spiking neural networks in order to detect spatiotemporal patterns. Unsupervised training and detection-by-design techniques were used to attain the appropriate connectomes and perform pattern detection.

Unsupervised training was performed by feeding random digital spikes with a repeating embedded spatiotemporal pattern to a spiking neural network composed of leaky integrate-and-fire neurons and memristor-R(t) element circuits which implement spike-timing-dependent plasticity learning rules.

Detection-by-design was achieved using neuromporphic circuits and digital logic gates. When detection-by-design was achieved using both neuromorphic circuits and digital logic gates, a network was created of spatiotemporal pattern detector circuits, …

Roi-Aware Content-Adaptive Video Streaming System For Power Savings, William Oswald

Graduate Theses and Dissertations (2019 - present)

The demand for mobile video streams is constantly increasing. With this demand comes a need for mobile devices to receive more videos at ever increasing quality. However, due to the large size of video data and intensive computational requirements, video streaming requires frequent memory access that consumes a substantial amount of mobile device power; as a result, the battery life of mobile devices is limited. In this thesis, a video content-adaptable Region-of-Interest (ROI)-aware video storage technique that promotes power savings is presented. During the video encoding process on the transmitting server, based on the macroblock variance and ROI characterization, the …

Development Of Metaheuristic Algorithms For The Efficient Allocation Of Power Flow Control Devices, Eduardo Jose Castillo Fatule

Open Access Theses & Dissertations

Modern energy grids have become extremely complex systems, requiring more variable and active flow control. As a remedy to this, Distributed Flexible AC Transmission Systems (D-FACTS) are cost-efficient devices used to mitigate power flow congestion and integrate renewable energies. The objective of this research is then to propose an efficient multiple objective evolutionary algorithm to solve a stochastic model for D-FACTS allocation, which aims to optimize various objectives related to cost, grid health, and environmental impacts. The model was implemented on a modified RTS-96 test system, and the results show that optimally allocating D-FACTS modules using the proposed model can …

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 …

A Double-Sided Stack Low-Inductance Wire-Bondless Sic Power Module With A Ceramic Interposer, Si Huang

Graduate Theses and Dissertations

The objective of this dissertation research is to develop a novel three-dimensional (3-D) wire bondless power module package for silicon carbide (SiC) power devices to achieve a low parasitic inductance and an improved thermal performance. A half-bridge module consisting of 900-V SiC MOSFETs is realized to minimize stray parasitic inductance as well as to provide both vertical and horizontal cooling paths to maximize heat dissipation. The proposed 3-D power module package was designed, simulated, fabricated and tested. In this module, low temperature co-fired ceramic (LTCC) substrate with vias is utilized as an interposer of which both top and bottom sides …

Deep Learning Based Speech Enhancement And Its Application To Speech Recognition, Ju Lin

All Dissertations

Speech enhancement is the task that aims to improve the quality and the intelligibility of a speech signal that is degraded by ambient noise and room reverberation. Speech enhancement algorithms are used extensively in many audio- and communication systems, including mobile handsets, speech recognition, speaker verification systems and hearing aids. Recently, deep learning has achieved great success in many applications, such as computer vision, nature language processing and speech recognition. Speech enhancement methods have been introduced that use deep-learning techniques, as these techniques are capable of learning complex hierarchical functions using large-scale training data. This dissertation investigates the deep learning …

Dual Multivector Model Predictive Control For The Power Converters Of A Floating Owc Wec, Marcos Blanco, Dionisio Ramirez, Mohammad Ebrahim Zarei, Mahima Gupta

Electrical and Computer Engineering Faculty Publications and Presentations

Oscillating Water Column (OWC) is one of the most well-known wave energy converter (WEC). Typically, OWCs are installed in rocky shores or in custom-built breakwaters. However, since the wave profile is more favorable in an open sea, it can also be installed in a point absorber in order to increase the energy extraction.

This paper presents the development of a new dual Multivector Model Predictive Control (MMPC) for the power converters of a floating OWC WEC. The fast dynamic response featured by the proposed MMPC has proven to be very suitable to deal with the highly variable torque and velocity …

Nevr: Learning Continuous Neural Video Representation With Local Feature Codes For Video Interpolation, Wentao Shangguan

McKelvey School of Engineering Graduate Student Theses & Dissertations

Video frame interpolation aims to synthesis a non-exists intermediate frame guided by two successive frames. Recently, some work shows excellent results in learning continuous representation of temporally-varying 3D objects with neural field (NF), which could be used for interpolating the original video. However, these methods require several videos from different viewing angles, the information of camera poses, learning for each specific scene, and achieving sub-optimal results for video frame interpolation. To this end, we propose a new learning neural field representation-based model, Neural Video Representation (NeVR) to learn a continuous representation of videos for high-quality video interpolation. Unlike the traditional …

Roadway-Embedded Transmitters And Multi-Pad Receivers For High Power Dynamic Wireless Power Transfer, Benny J. Varghese

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Electric vehicles (EVs) offer considerable economic and environmental benefits to society. Despite the decreasing vehicle costs and increasing range of newer EVs, the problem of range anxiety still exists. Range anxiety, at its core, is an issue of charging speeds rather than a concern about the driving range. Dynamic wireless charging of EVs is seen as a potential solution to this issue of range anxiety. Further, wireless charging technology also helps the push towards level 5 autonomy and opens new opportunities for how an EV can be utilized.

Dynamic wireless power transfer (DWPT) systems typically require a high initial investment …

Low Power Reconfigurable Antenna With Continuous Beam Steering Capability, Glendyn Darryn King

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Each year, the number of wireless devices increases, and the size of the devices’ data is increases, 8k video streaming, for example. More and more bandwidth is needed for wireless networks to meet these growing demands. Higher frequencies allow for more bandwidth; however, using higher frequencies comes with some trade-offs. The higher the wireless signal frequency, the shorter the distance it can travel before the signal strength becomes too weak for the receiver to pick it up. One solution might be to increase the power of the signal provider, but that would waste a lot of energy. Most antennas radiate …

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 …

Collaborative Human-Machine Interfaces For Mobile Manipulators., Shamsudeen Olawale Abubakar

Electronic Theses and Dissertations

The use of mobile manipulators in service industries as both agents in physical Human Robot Interaction (pHRI) and for social interactions has been on the increase in recent times due to necessities like compensating for workforce shortages and enabling safer and more efficient operations amongst other reasons. Collaborative robots, or co-bots, are robots that are developed for use with human interaction through direct contact or close proximity in a shared space with the human users. The work presented in this dissertation focuses on the design, implementation and analysis of components for the next-generation collaborative human machine interfaces (CHMI) needed for …

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 …

Erratum: Physicochemical Insights Of Irradiation-Enhanced Hydroxyl Radical Generation From Zno Nanoparticles(Toxicology Research Doi: 10.1039/C5tx00384a), Qingbo Yang, Tien Sung Lin, Casey Burton, Sungho Park, Yinfa Ma

Electrical and Computer Engineering Faculty Research & Creative Works

In the originally published version of this manuscript, the fourth author's name is incorrect. The name should read "Sungho Park", instead of "Sung-Ho Park". These details have been corrected only in this corrigendum to preserve the published version of record.

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 …

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 …

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, …

Multifunctional Programmable Self-Assembled Nanoparticles In Nanomedicine, Yoshie Sakamaki

Graduate Theses and Dissertations

Developing methodologies to control the architecture of nanoparticles (NPs) at the atomic level prevents their inhomogeneity and leads to a variety of expected functions. Rationally designed nanoparticles can either be programmed or crystallized structures into pre-determined structures achieving tunable particle pore size and physiochemistry. In this dissertation, two broad classes of multifunctional nanoparticles are developed, metal-organic frameworks and DNA-NP aggregates.

Metal-organic frameworks are a novel class of highly porous crystalline materials built from organic linkers and metal cluster-based secondary building units. However, applications in bioremediation have not been developed very well especially in applications regarding drug delivery systems (DDS). 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 …

Incorporation Of Zinc In Pre-Alloyed Cuin[Zn]S2/Zns Quantum Dots, Jean Carlos Morales Orocu

Graduate Theses and Dissertations

Since the early 2000s heavy-metal-free quantum dots (QDs) such as CuInS2/ZnS have attempted to replace CdSe, their heavy-metal-containing counterparts. CuInS2/ZnS is synthesized in a two-step process that involves the fabrication of CuInS2 (CIS) nanocrystals (NCs) followed by the addition of zinc precursors. Instead of the usual core/shell architecture often exhibited by binary QDs, coating CIS QDs results in alloyed and/or partially alloyed cation-exchange (CATEX) QDs. The effect that zinc has on the properties of CIS NCs was studied by incorporating zinc during the first step of the synthesis. Different In:Cu:Zn ratios were employed in this study, maintaining a constant 4:1 …

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 …

Automated Flight Controller Adaptive Compensation For Actuator Failures In Transport Type Aircraft, Daniel James Fresella

Graduate Theses and Dissertations

Aircraft operate over a wide range of conditions including atmospheric, weight, and center ofgravity changes. This presents a substantial challenge to automatic control system designers. When these operating conditions are merged with a partial or full control surface failure, automatic flight control is near impossible with conventional controllers. Additionally, when pilots experience control failure emergencies during flight, workload and fatigue increase drastically. The continued research of automatic flight control systems that can seamlessly adapt to unmodelled failures will enable a new generation of robust aircraft control. In this paper a 9th order 6 degree of freedom aircraft model is used …

Design, Extraction, And Optimization Tool Flows And Methodologies For Homogeneous And Heterogeneous Multi-Chip 2.5d Systems, Md Arafat Kabir

Graduate Theses and Dissertations

Chip and packaging industries are making significant progress in 2.5D design as a result of increasing popularity of their application. In advanced high-density 2.5D packages, package redistribution layers become similar to chip Back-End-of-Line routing layers, and the gap between them scales down with pin density improvement. Chiplet-package interactions become significant and severely affect system performance and reliability. Moreover, 2.5D integration offers opportunities to apply novel design techniques. The traditional die-by-die design approach neither carefully considers these interactions nor fully exploits the cross-boundary design opportunities.

This thesis presents chiplet-package cross-boundary design, extraction, analysis, and optimization tool flows and methodologies for high-density …

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 …