Digital Commons Network^™

Data-Driven Porosity Prediction For Directed Energy Deposition, Georgia E. Kaufman

Electrical and Computer Engineering ETDs

Stochastic flaw formation leading to poor print quality is a major obstacle to the utility of directed energy deposition (DED), a laser and metal powder-based additive manufacturing technology for construction and repair of custom metal parts. While melt pool temperature variability is known to be a major factor in flaw formation, control schemes to decrease flaw formation are limited by a lack of physics-based models that fully and accurately describe DED. In this work, a stochastic reachability analysis with a data-driven model based on thermal images of the melt pool was conducted to determine the likelihood of violating melt pool …

Exploring The Impact Of Students Demographic Attributes On Performance Prediction Through Binary Classification In The Kdp Model, Issah Iddrisu, Peter Appiahene, Obed Appiah, Inusah Fuseini

Knowledge Engineering and Data Science

During the course of this research, binary classification and the Knowledge Discovery Process (KDP) were used. The experimental and analytical capabilities of Rapid Miner's 9.10.010 instructional environment are supported by five different classifiers. Included in the analysis were 2334 entries, 17 characteristics, and one class variable containing the students' average score for the semester. There were twenty experiments carried out. During the studies, 10-fold cross-validation and ratio split validation, together with bootstrap sampling, were used. It was determined whether or not to use the Random Forest (RF), Rule Induction (RI), Naive Bayes (NB), Logistic Regression (LR), or Deep Learning (DL) …

High Performance Scene Generator For Testing Of Imaging Sensors, Austin Modoff

Electrical Engineering Theses and Dissertations

Since the invention of modern solid-state imaging sensors in the 1980s, considerable advancements have been made, improving aspects such as frequency response, dynamic range, resolution, and wavelength diversity, as well as inventing many different types of sensor architectures such as framing sensors and event sensors. While considerable improvements in this field are evolving every day, the methods by which to test and validate these systems remain unchanged. Many of these test platforms require specialized designs to test only one or two specific qualities. For example, a spinning disk in front of a black body source to measure the frequency response …

Optimization Of Ultrawide Bandgap Semiconductor Materials For Heterostructure Field Effect Transistors (Hfets), Mohi Uddin Jewel

Theses and Dissertations

Ultra-wide bandgap (UWBG) gallium oxide (Ga2O3), and aluminum gallium oxide (Al_xGa_1-x)₂O₃ materials with bandgap E_G ≥ 4.8 eV are promising for heterostructure field effect transistors (HFETs) with high breakdown voltage and operating at high temperatures. Despite some initial breakthroughs in good quality β-Ga₂O₃ thin films growth on (001), (100), (010), and (201) β-Ga₂O₃ substrates, and promising results on β- (Al_xGa_1-x)₂O₃/β-Ga₂O₃ HFETs fabricated on (010) β-Ga₂O₃ substrates, heat dissipation in Ga2O3 materials and …

Resilience Model For Teams Of Autonomous Unmanned Aerial Vehicles (Uav) Executing Surveillance Missions, Robert Koeneke

Doctoral Dissertations and Master's Theses

Teams of low-cost Unmanned Aerial Vehicles (UAVs) have gained acceptance as an alternative for cooperatively searching and surveilling terrains. These UAVs are assembled with low-reliability components, so unit failures are possible. Losing UAVs to failures decreases the team's coverage efficiency and impacts communication, given that UAVs are also communication nodes. Such is the case of a Flying Ad Hoc Network (FANET), where the failure of a communication node may isolate segments of the network covering several nodes. The main goal of this study is to develop a resilience model that would allow us to analyze the effects of individual UAV …

Design Of A Burst Mode Ultra High-Speed Low-Noise Cmos Image Sensor, Xin Yue

Dartmouth College Ph.D Dissertations

Ultra-high-speed (UHS) image sensors are of interest for studying fast scientific phenomena and may also be useful in medicine. Several published studies have recently achieved frame rates of up to millions of frames per second (Mfps) using advanced processes and/or customized processes.

This thesis presents a burst-mode (108 frames) UHS low-noise CMOS image sensor (CIS) based on charge-sweep transfer gates in an unmodified, standard 180 nm front-side-illuminated CIS process. By optimizing the photodiode geometry, the 52.8 μm pitch pixels with 20x20 μm^2 of active area, achieve a charge-transfer time of less than 10 ns. A proof-of-concept CIS was designed and …

Ant Colony Optimization For Resistor Color Code Detection, Slamet Wibawanto, Kartika Candra Kirana, Hani Ramadhan

Knowledge Engineering and Data Science

In the early stages of learning resistors, introducing color-based values is needed. Moreover, some combinations require a resistor trip analysis to identify. Unfortunately, a resistor body color is considered a local solution, which often confuses resistor coloration. Ant Colony Optimization (ACO) is a heuristic algorithm that can recognize problems with traveling a group of ants. ACO is proposed to select commercial matrix values to be computed without preventing local solutions. In this study, each explores the matrix based on pheromones and heuristic information to generate local solutions. Global solutions are selected based on their high degree of similarity with other …

Maximum Marginal Relevance And Vector Space Model For Summarizing Students' Final Project Abstracts, Gunawan Gunawan, Fitria Fitria, Esther Irawati Setiawan, Kimiya Fujisawa

Knowledge Engineering and Data Science

Automatic summarization is reducing a text document with a computer program to create a summary that retains the essential parts of the original document. Automatic summarization is necessary to deal with information overload, and the amount of data is increasing. A summary is needed to get the contents of the article briefly. A summary is an effective way to present extended information in a concise form of the main contents of an article, and the aim is to tell the reader the essence of a central idea. The simple concept of a summary is to take an essential part of …

Optimizing Random Forest Algorithm To Classify Player's Memorisation Via In-Game Data, Akmal Vrisna Alzuhdi, Harits Ar Rosyid, Mohammad Yasser Chuttur, Shah Nazir

Knowledge Engineering and Data Science

Assessment of a player's knowledge in game education has been around for some time. Traditional evaluation in and around a gaming session may disrupt the players' immersion. This research uses an optimized Random Forest to construct a non-invasive prediction of a game education player's Memorization via in-game data. Firstly, we obtained the dataset from a 3-month survey to record in-game data of 50 players who play 4-15 game stages of the Chem Fight (a test case game). Next, we generated three variants of datasets via the preprocessing stages: resampling method (SMOTE), normalization (min-max), and a combination of resampling and normalization. …

A Non-Line-Of-Sight Mitigation Method For Indoor Ultra-Wideband Localization With Multiple Walls, Mengyao Dong, Yihong Qi, Xianbin Wang, Yiming Liu

Electrical and Computer Engineering Faculty Research & Creative Works

Ultra-wideband (UWB) ranging techniques can provide accurate distance measurement under line-of-sight (LOS) conditions. However, various walls and obstacles in indoor non-LOS (NLOS) environments, which obstruct the direct propagation of UWB signals, can generate significant ranging errors. Due to the complex through-wall UWB signal propagation, most conventional studies simplify the ranging error model by assuming that the incidence angle is zero or the relative permittivity's for different walls are the same to improve the through-wall UWB localization performance. Considering walls are different in realistic settings, this article presents a through-multiple-wall NLOS mitigation method for UWB indoor positioning. First, spatial geometric equilibrium …

Asset Cueing Nuclear Radiation Anomaly Detection Using An Embedded Neural Network Resource, April Inamura

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

Nuclear radiation detection is inherently a challenging task, coupled with a high background variation or increase in anomalies, the accuracy for detection can plummet. A key factor in the success of nuclear detection hinges on the sensor’s ability to generalize its model and directly leads to the model’s robustness. The goal of this project is to develop algorithms suitable for use on the University of Nebraska-Lincoln’s Pingora chip, a low-power, system-on-chip device with an active neural processing unit (NPU) made for nuclear radiation detection. The thesis aims to improve Pingora’s overall generalization ability in nuclear radiation source detection. A multiphase …

Intellectualization Of The Process Of Monitoring Of Complex Technological Productions, Dmitry Semenovich Karpovich, Umidjon Abdimajitovich Ruziev

Chemical Technology, Control and Management

The article deals with the creation of intelligent monitoring systems for complex technological processes. The methods and models of the intellectualization of information processing systems are analyzed. The advantages of using intelligent measuring instruments in monitoring systems are given, which allow obtaining reliable information necessary for the effective control of complex technological processes. The issues of using intelligent measuring instruments in monitoring systems are considered. A block diagram of intelligent monitoring of signal processing of complex production processes has been proposed. An algorithm for parametric correction of intelligent measuring instruments in monitoring systems has been developed. A model of a …

Modeling And Dynamic Correction Of The Thermal Radiation Fluxes Measuring System, Olexander Alekseevich Sytnik, Fatima Mirazizovna Sagatova

Chemical Technology, Control and Management

Temperature measurements are currently an integral part of modern production, in particular, energy, aviation, instrumentation, etc. Therefore, the need to improve the accuracy of measurement, control and regulation of temperature largely determines the technical and economic efficiency of production. The development of reliable methods for temperature control under various conditions and the creation of specific devices is one of the most important tasks of modern instrumentation. The article deals with the issues of solving the problems of modeling and correcting the dynamic characteristics of a system for measuring thermal radiation fluxes using the integral method of signal recovery. For computer …

Current Issues Of The Use Of Artificial Intelligence In The Activities Of Customs Authorities, Jasur Usmonovich Sevinov, Gayrat Rustamovich Khamroev

Chemical Technology, Control and Management

Presents effective methods and solutions to eliminate errors caused by the “human factor” (fatigue, neglect, etc.) as a result of the creation and improvement of automated systems based on artificial intelligence, distinguishing features such as commodity group, weight, dimensions, etc. in relation to goods under customs control. The use of artificial intelligence in customs activities allows: to increase the speed of performing tasks set before customs authorities by increasing productivity, without attracting additional personnel; to eliminate errors caused by the “human factor” (fatigue, neglect, etc.); to free employees from everyday activities and transfer it to solving mainly analytical tasks; to …

Synthesis Of Control Systems With Multilayer Neural Networks Based On Velocity Gradient Methods, Oxunjon Boborayimov, Okyay Kaynak

Chemical Technology, Control and Management

In this manuscripts, the synthesis of control systems with multilayer neural networks based on the speed gradient methods is given. For adjusting the weight coefficients of the base processor element, the gradient method of minimizing the learning criterion is used. A procedure for the synthesis of neural network control systems based on the velocity gradient methods has been developed. This guarantees the stabilization of the system under external limited disturbances that are inaccessible to direct measurement. Taking into account the state vector of the control object in the network learning function ensures the consistency of the processes of setting the …

Scanning Photoelectrochemical Microscopic Study In Photoinduced Electron Transfer Of Supramolecular Sensitizers-Tio2 Thin Films Systems, Sheng-Ya Zhang, Min Yao, Ze Wang, Tian-Jiao Liu, Rong-Fang Zhan, Hui-Qin Ye, Yan-Jun Feng, Xiao-Quan Lu

Journal of Electrochemistry

Crafting charge transfer channels at titanium dioxide (TiO₂) based photoanodes remain a pressing bottleneck in solar-to-chemical conversion technology. Despite the tremendous attempts, TiO₂ as the promising photoanode material still suffers from sluggish charge transport kinetics. Herein, we propose an assembly strategy that involves the axial coordination grafting metalloporphyrin-based photosensitizer molecules (MP) onto the surface-modified TiO₂ nanorods (NRs) photoanode, forming the composite MP/TiO₂ NRs photoelectrode. As expected, the resulted unique MP_B/TiO₂ NRs photoelectrode displays significantly improved photocurrent density as compared to TiO₂ NRs alone and MP_A/TiO₂ NRs photoelectrode. Scanning …

Development Of Attack Resistant Cybersecurity Framework For Digital Health Systems, Sridevi A

Theses and Dissertations

The emerging cyber landscape demands the data to be protected by CIA triad which comprises Confidentiality, Integrity and Availability(CIA). For the swift diagnosis process, a standard patient data representation in the form of EHR (Electronic Health Record) plays a significant role. There exists a necessity to protect this EHR through the information security mechanisms namely encryption, watermarking and intrusion detection system for ensuring application and network layer security. Implementation of medical data protection solution on a reconfigurable hardware platform can further strengthen EHR security. This research work effectively achieves the CIA triad for healthcare cybersecurity at data, application and network …

Optimal Estimation Inversion Of Ionospheric Electron Density From Gnss-Pod Limb Measurements: Part I-Algorithm And Morphology, Dong L. Wu, Nimalan Swarnalingam, Cornelius C. J. H. Salinas, Daniel J. Emmons, Tyler C. Summers, Robert Gardiner-Garden

Faculty Publications

GNSS-LEO radio links from Precise Orbital Determination (POD) and Radio Occultation (RO) antennas have been used increasingly in characterizing the global 3D distribution and variability of ionospheric electron density (Ne). In this study, we developed an optimal estimation (OE) method to retrieve Ne profiles from the slant total electron content (hTEC) measurements acquired by the GNSS-POD links at negative elevation angles (ε < 0°). Although both OE and onion-peeling (OP) methods use the Abel weighting function in the Ne inversion, they are significantly different in terms of performance in the lower ionosphere. The new OE results can overcome the large Ne oscillations, sometimes negative values, seen in the OP retrievals in the E-region ionosphere. In the companion paper in this Special Issue, the HmF2 and NmF2 from the OE retrieval are validated against ground-based ionosondes and radar observations, showing generally good agreements in NmF2 from all sites. Nighttime hmF2 measurements tend to agree better than the daytime when the ionosonde heights tend to be slightly lower. The OE algorithm has been applied to all GNSS-POD data acquired from the COSMIC-1 (2006–2019), COSMIC-2 (2019–present), and Spire (2019–present) constellations, showing a consistent ionospheric Ne morphology. The unprecedented spatiotemporal sampling of the ionosphere from these constellations now allows a detailed analysis of the frequency–wavenumber spectra for the Ne variability at different heights. In the lower ionosphere (~150 km), we found significant spectral power in DE1, DW6, DW4, SW5, and SE4 wave components, in addition to well-known DW1, SW2, and DE3 waves. In the upper ionosphere (~450 km), additional wave components are still present, including DE4, DW4, DW6, SE4, and SW4. The co-existence of eastward- and westward-propagating wave4 components implies the presence of a stationary wave4 (SPW4), as suggested by other earlier studies. Further improvements to the OE method are proposed, including a tomographic inversion technique that leverages the asymmetric sampling about the tangent point associated with GNSS-LEO links.

A Flexible Ot Testbed For Evaluating On-Device Implementations Of Iec-61850 Goose, Matthew Boeding, Michael Hempel, Hamid Sharif, Juan Lopez Jr., Kalyan Perumalla

Department of Electrical and Computer Engineering: Faculty Publications

The growing convergence of Information Technology and Operational Technology has enhanced communication and visibility across power grids. This, coupled with the growing use of Distributed Energy Resources in power grids, has enhanced the grid capabilities while also creating a larger attack surface for malicious actors. A common protocol vulnerable to these attacks is the IEC-61850 GOOSE protocol due to its low-latency requirements, multicast packet delivery method, and lack of encryption. In this paper, we evaluate the security implications of different hardware implementations of this protocol by contrasting device response and recovery of two commercial off-the-shelf Intelligent Electronic Devices from separate …

Stochastic Worst-Case Test Vectors For Asic Devices In Single Event Environment, Mostafa Hemeda

Theses and Dissertations

Charged particles and energetic particles can impact the integrated circuit, referred to as single event effects (SEE). Nuclear reactors and space radiation can produce these particles. These effects can negatively affect the reliability and performance of electronics. When SEE occurs, a transient current is created, which can cause electronic devices to have incorrect outputs and ultimately fail. As a result, ensuring the reliability of ASIC circuits is a significant concern.

This thesis discusses the different fault types, then discuss the soft error and, in particular, the Single Event Transient (SET) and its causes and models. Then, this thesis proposes a …

Crazyflie 2.1 Quadcopter Nonlinear System Identification, Nhat V. Nguyen, Hope Storro, John Plimpton

2023 Symposium

Quadcopters (quad) are used widely in many industries with crucial applications such as infrastructure inspection or package delivery. The Crazyflie 2.1 quad from Bitcraze provides an excellent platform for research and development. In this project, our goal is to perform system identification on the Crazyflie to propose a complete model. A gray box method is explored, which includes leveraging the parameters that are already known, to develop a set of equations. Through theory, simulations, and measurements, a complete quadcopter model is developed.

Model-Driven Analysis Of Ecg Using Reinforcement Learning, Christian O'Reilly, Sai Durga Rithvik Oruganti, Deepa Tilwani, Jessica Bradshaw

Publications

Modeling is essential to better understand the generative mechanisms responsible for experimental observations gathered from complex systems. In this work, we are using such an approach to analyze the electrocardiogram (ECG). We present a systematic framework to decompose ECG signals into sums of overlapping lognormal components. We use reinforcement learning to train a deep neural network to estimate the modeling parameters from an ECG recorded in babies from 1 to 24 months of age. We demonstrate this model-driven approach by showing how the extracted parameters vary with age. From the 751,510 PQRST complexes modeled, 82.7% provided a signal-to-noise ratio that …

Adversary Aware Continual Learning, Muhammad Umer

Theses and Dissertations

Continual learning approaches are useful as they help the model to learn new information (classes) sequentially, while also retaining the previously acquired information (classes). However, these approaches are adversary agnostic, i.e., they do not consider the possibility of malicious attacks. In this dissertation, we have demonstrated that continual learning approaches are extremely vulnerable to the adversarial backdoor attacks, where an intelligent adversary can introduce small amount of misinformation to the model in the form of imperceptible backdoor pattern during training to cause deliberate forgetting of a specific class at test time. We then propose a novel defensive framework to counter …

A General Model For Noisy Labels In Machine Learning, Glenn Dawson

Theses and Dissertations

Machine learning is an ever-growing and increasingly pervasive presence in every-day life; we entrust these models, and systems built on these models, with some of our most sensitive information and security applications. However, for all of the trust that we place in these models, it is essential to recognize the fact that such models are simply reflections of the data and labels on which they are trained. To wit, if the data and labels are suspect, then so too must be the models that we rely on—yet, as larger and more comprehensive datasets become standard in contemporary machine learning, it …

Design Of Hybrid Inverters Using Wideband Gap Semiconductors For Microgrid Application, Luca Gacy

Electronic Theses and Dissertations

As the world becomes more reliant on renewable energy sources such as solar and wind power, the need for high efficiency high power inverters connected to homes is more relevant than ever. Connecting these renewable energy sources (RES) coupled with an energy storage system (ESS) to the grid through a hybrid inverter, with the highest efficiency and grid stability, is quickly becoming a necessity for the near future. This thesis explores the integration of wide band gap semiconductors for the power stage in these systems, along with the analysis of hybrid inverter topologies and structures. The goal of this thesis …

Programmable And Modular Dc-Dc Converter, Joshua C. Hutchinson, Elijah M. Gordon

Electrical Engineering

This project considers the design, implementation, and testing of an open-source dc-dc converter for microgrid prototyping. Unlike conventional dc-dc converters that are proprietary and require specialist knowledge, and are usually designed for a single function, the proposed dc-dc converter will comprise of a programmable MCU and a Raspberry Pi (RPi) interface to allow less-skilled consumers to monitor and modify a power converting system. We will develop an open-source library that contains voltage control, current control, maximum power point tracking, and battery charge control profiles. Each library will be easy to implement through a GUI on the Raspberry Pi and will …

Tank Level Controller Plc Lab, Siddhi Upadhyaya, Teghvir Grewal

Electrical Engineering

The California Polytechnic State University San Luis Obispo’s Electrical Engineering Department is currently developing lab experiments for the new EE435 (Industrial Power Control and Automation) class. In order to support these efforts, fourth year Cal Poly students are expected to develop laboratory experiments that will be conducted during this new class for the semester system. The lab experiment focused on in this project is called the Tank Level Controller. This experiment will introduce EE 435 students to Schneider Electric Programmable Logic Controller (PLC) hardware and software, which is prominent in the automation industry.
This experiment will require students to develop …

Hvac Fan Cooling System Using Modicon M580, Ogbonnaya Okoronkwo Okorie, Nicolas Jens Fache

Electrical Engineering

A common problem that many devices have when operating is overheating. Whether it is operating at full capacity or idle, those devices that we use exert heat to some type of extent. The physical and electronic components of the device can only withstand so much heat before the component becomes damaged. This product provides a method of preventing overheating by being a cooling system for your device. A solution for preventing overheating of the components in these electronic devices is by having some sort of cooling system. Our product’s cooling system will be based on energy efficiency, which means that …

Current Source Dc-Dc Converter For Undersea Fiber Optic Sensors, Richard Anthony Esplana Kwan, John Charles Rodinec, Andrew Armstrong

Electrical Engineering

Today, there are nearly 400 cable networks spanning roughly 750,000 miles to connect our world together. With thousands of miles of cable already lying on the ocean floor, with thousands more to come, many have recognized a unique opportunity in using this cable infrastructure as an attachment point for sensors to help study and monitor the ocean. Placing sensors onto a submarine cable is not a simple task; the sensors will require power that they receive from a transmission cable, from a battery, or from the submarine cable itself. Unfortunately, the existing power feed configuration for submarine cables typically only …

Cybersecurity In Industrial Automation Lab Design For Ee 435, Jules Khalil Emile Hajjar, Emily Zhou

Electrical Engineering

This project involves the creation of an instructional laboratory aimed at teaching cybersecurity for industrial automation applications. Specifically tailored for Electrical Engineering students at Cal Poly, the experiment focuses on configuring the Modicon M580, a PLC from Schneider Electric, and serves to introduce students to relevant cybersecurity protocols and techniques. This project will be implemented into the EE435 (Industrial Power Control and Automation) course curriculum upon Cal Poly’s transition to the semester system.