Other Electrical and Computer Engineering Commons^™

Hvac Fan Control Using Modicon M580, Anthony Tyler, Kevin Shipp

Electrical Engineering

This project is the start of a lab experiment for the Cal Poly San Luis Obispo Electrical Engineering department’s new lab focusing on Programmable Logic Controller's (PLCs). The primary focus is to create a lab where students control a Heating, Ventilation, and Air conditioning (HVAC) system controlled by the Modicon M580 PLC, donated by Schneider Electric. The experiment contains a heat source, which the PLC monitors with a temperature sensor, and a cooling source with multiple fans. Students will learn to use function block diagrams to program the PLC, controlling fan output and regulating the system temperature. The experiment specifications …

Pulsed Electric Field System Development For Algae Biofuel Extraction, Juan David Gonzalez Aguayo, Aspyn Bessler

Electrical Engineering

The search for sustainable alternatives to fossil fuels proves necessary due to the effects fossil fuels have on Earth’s environment. These alternatives must have a minimum ecological footprint and cause no long-term harm to the environment. An environmentally friendly fuel is necessary to usher in a generation of renewable green energy.

The production of algae refined biofuels becomes a possible solution to this growing issue. Algae absorb CO2from the atmosphere during their reproduction and growth cycles, yielding a positive environmental impact. As the biofuel is refined and becomes suitable for use, the combustion of the finished fuel generates an equal …

Polyone Smartphone, Joshua Zalmanowitz, Chi Nguyen, Gerome Cacho, Chris Lim

Electrical Engineering

The Poly One Smartphone is a student designed smartphone built to explore the implementation of 5G, provide a hardware solution to ensure personal information security and privacy, and provide longer battery life. The key features of this smartphone include but are not limited to a main cpu, some form of network connectivity in the form of Wi-fi or Cellular Data, calling functionality, a rechargeable battery that works with common power connection protocols, and compatibility with popular applications.

Design And Development Of Laboratory Single-Axis Pv Module Tracker, Helen A. Rice, Delaney Berger, Avishek Maitra

Electrical Engineering

Solar energy is an integral part of the renewable energy industry. Advanced solar farms actively track solar movement and update solar panel angles to maximize the system’s output power. Cal Poly boasts its own Solar Farm that features a single-axis tracking system. Single-axis tracking aims to get panels as close to perpendicular as possible given the panel arrangements and given the time of year. Single-axis tracking is a more robust measurement and tracking option. Single-axis tracking systems usually only have East-West panel arc movement, following the sun’s rotation. Dual-axis trackers have both East-West and North-South panel arc movements. Dual-axis systems …

Post-Quantum Encryption Benchmark, Jordan David Churi

Electrical Engineering

Recent advancements in quantum computing bring the weaknesses in modern RSA encryption to the foreground. Shor's algorithm, though not implementable on today's quantum computers, shows that RSA asymmetric key encryption is not secure for the coming future. This flaw in the security has prompted the National Institute of Standards and Technology (NIST) to start a search for a new post-quantum encryption algorithm that will be resistant to future quantum computers. There are several implementations of preforming this encryption scheme. One promising technique is using lattices in an application called ring Learning with Errors (rLWE). Several algorithms have been submitted to …

Dc Treasure Box, Michael A. Derrenbacher

Electrical Engineering

An all in one DC resource would enable electronics students to prototype circuits for labs and projects without the need for the lab equipment present on campus. The labs on campus can be physically far, closed, or overcrowded, preventing students from accessing the equipment. Roughly 75% of upper division electrical engineering students do not own power supplies, with even fewer students owning a source measurement unit (SMU). There is a significant need for a product capable of providing standard lab equipment functionality. The functionally this project provides are positive and negative DC power supplies, 4-Quadrant SMU, analog inputs and outputs, …

Wildland Fire Location Management System (Wflms), Robert G. Goldie, Jack A. Gallegos

Electrical Engineering

Wildland firefighters work in complex, dangerous environments where effective communication is key to developing situational awareness. Currently, the only communication firefighters have is with Very High Frequency (VHF) 160 MHz band analog radios. While digital radio protocols could potentially allow location data and commands to be sent to field crews, the technology is primarily for voice communication. This project presents a new system that frees up voice channels and uses LoRa transceivers for robust communication. The system allows for emergency and location reports to be sent to a dispatcher via an airborne repeater. The entire system is software-defined, so it …

Sweep-N-Go 3.0, Maria Cortelyou Pieroni

Electrical Engineering

This project improves the current performance of the Sweep-N-Go LabVIEW program used in Cal Poly electrical engineering laboratories. Sweep-N-Go expedites the laboratory data collection process through automated testing. The new version of the program (Sweep-N-Go Version 3.0) reduces user debugging time, improves sustainability, increases efficiency, and considers all new lab bench equipment. Sweep-N-Go Version 3.0 includes an enhanced Graphical User Interface (GUI) to optimize user-efficiency and user-friendliness according to student survey feedback. To further achieve usability, this program has been well documented online, outlining LabVIEW functions, such as how to open the program in LabVIEW, how to run an executable …

Raysun's Infrared Raisin Dryer, Lucas Kensinger, Saraith Aispuro, Joe Vanacore

General Engineering

The RaySuns senior project team was tasked with lowering the drying costs of raisins for River Ranch Raisins. In doing so, we explored several options for cutting costs: utilizing automation and exploring new drying technologies were our primary focus. We eventually planned a modular infrared heating mechanism which would be easy to automate in future projects. After manufacturing and testing an infrared heating mechanism, it was found that infrared drying could significantly cut costs versus the previous natural gas fired dryer tunnels while leaving room for automation. The infrared dryer was also shown to have the potential to create high-quality …

Electrical Measurement Of Sram Cell Variation And Sensitivity To Singe-Event Upsets By Low-Energy Protons, James M. Cannon

Macalester Journal of Physics and Astronomy

With the rise of the transistor in the 1970s, electronics shifted from analog circuitry, where values are stored on a continuum, to digital, in which ones and zeros are the law of the land. Transistors, as a class circuit element, can be affected by radiation and cosmic rays which then cause temporary or permanent failures, depending on the specifics of the situation. On Earth, this poses little risk with all electronics shielded by the magnetosphere, however for space bound electronics, the risks from these extraterrestrial particles are not so negligible. The first step in designing a mission to be able …

Ml-Medic: A Preliminary Study Of An Interactive Visual Analysis Tool Facilitating Clinical Applications Of Machine Learning For Precision Medicine, Laura Stevens, David Kao, Jennifer Hall, Carsten Görg, Kaitlyn Abdo, Erik Linstead

Engineering Faculty Articles and Research

Accessible interactive tools that integrate machine learning methods with clinical research and reduce the programming experience required are needed to move science forward. Here, we present Machine Learning for Medical Exploration and Data-Inspired Care (ML-MEDIC), a point-and-click, interactive tool with a visual interface for facilitating machine learning and statistical analyses in clinical research. We deployed ML-MEDIC in the American Heart Association (AHA) Precision Medicine Platform to provide secure internet access and facilitate collaboration. ML-MEDIC’s efficacy for facilitating the adoption of machine learning was evaluated through two case studies in collaboration with clinical domain experts. A domain expert review was also …

Deep Learning And Polar Transformation To Achieve A Novel Adaptive Automatic Modulation Classification Framework, Pejman Ghasemzadeh

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

Automatic modulation classification (AMC) is an approach that can be leveraged to identify an observed signal's most likely employed modulation scheme without any a priori knowledge of the intercepted signal. Of the three primary approaches proposed in literature, which are likelihood-based, distribution test-based, and feature-based (FB), the latter is considered to be the most promising approach for real-world implementations due to its favorable computational complexity and classification accuracy. FB AMC is comprised of two stages: feature extraction and labeling. In this thesis, we enhance the FB approach in both stages. In the feature extraction stage, we propose a new architecture …

Towards Hybrid Quantum-Classical Ciphersuite Primitives, H. Shelton Jacinto

Boise State University Theses and Dissertations

With the dawn of quantum computing in scale, current secure classical primitives are at risk. Protocols with immediate risk of breach are those built on the advanced encryption standard (AES) and Rivest-Shamir-Adleman (RSA) algorithms. To secure classical data against a quantum adversary, a secure communications ciphersuite must be developed. The ciphersuite developed in this work contains components that do not necessarily rely on quantum key distribution (QKD), due to recent insecurities found when a QKD-based protocol is faced with a quantum eavesdropper.

A set of quantum-classical ciphersuite primitives were developed using less common mathematical methods where a quantum adversary will …

Low-Cost Test And Characterization Platform For Memristors, Lyle Jones

Boise State University Theses and Dissertations

The electrical Testing and Characterization of the devices built under research conditions on silicon wafers, diced wafers, or package parts have hampered research since the beginning of integrated circuits. The challenges of performing electrical characterization on devices are to acquire useful and accurate data, the ease of use of the test platform, the portability of the test equipment, the ability to automate quickly, to allow modifications to the platform, the ability to change the configuration of the Device Under Test (DUT) or the Memristor Based Design (MBD), and to do this within budget. The devices that this research is focused …

Ensemble Malware Classification System Using Deep Neural Networks, Barath Narayanan Narayanan, Venkata Salini Priyamvada Davuluru

Electrical and Computer Engineering Faculty Publications

With the advancement of technology, there is a growing need of classifying malware programs that could potentially harm any computer system and/or smaller devices. In this research, an ensemble classification system comprising convolutional and recurrent neural networks is proposed to distinguish malware programs. Microsoft's Malware Classification Challenge (BIG 2015) dataset with nine distinct classes is utilized for this study. This dataset contains an assembly file and a compiled file for each malware program. Compiled files are visualized as images and are classified using Convolutional Neural Networks (CNNs). Assembly files consist of machine language opcodes that are distinguished among classes using …

Heuristic-Based Threat Analysis Of Register-Transfer-Level Hardware Designs, Wesley Layton Ellington

Electrical Engineering Theses and Dissertations

The development of globalized semiconductor manufacturing processes and supply chains has lead to an increased interest in hardware security as new types of hardware based attacks, called hardware Trojans, are being observed in industrial and military electronics. To combat this, a technique was developed to help analyze hardware designs at the register-transfer-level (RTL) and locate points of interest within a design that might be vulnerable to attack. This method aims to eventually enable the creation of an end-to-end design hardening solution that analyzes existing designs and suggests countermeasures for potential Trojan attacks. The method presented in this work uses a …

Supporting Self-Regulation Of Children With Adhd Using Wearables: Tensions And Design Challenges, Franceli L. Cibrian, Kimberley D. Lakes, Arya Tavakoulnia, Kayla Guzman, Sabrina Schuck, Gillian R. Hayes

Engineering Faculty Articles and Research

The design of wearable applications supporting children with Attention Deficit Hyperactivity Disorders (ADHD) requires a deep understanding not only of what is possible from a clinical standpoint but also how the children might understand and orient towards wearable technologies, such as a smartwatch. Through a series of participatory design workshops with children with ADHD and their caregivers, we identified tensions and challenges in designing wearable applications supporting the self-regulation of children with ADHD. In this paper, we describe the specific challenges of smartwatches for this population, the balance between self-regulation and co-regulation, and tensions when receiving notifications on a smartwatch …

Comparison Of Visual Simultaneous Localization And Mapping Methods For Fixed-Wing Aircraft Using Slambench2, Patrick R. Latcham

Theses and Dissertations

Visual Simultaneous Localization and Mapping (VSLAM) algorithms have evolved rapidly in the last few years, however there has been little research evaluating current algorithm's effectiveness and limitations when applied to tracking the position of a fixed-wing aerial vehicle. This research looks to evaluate current monocular VSLAM algorithms' performance on aerial vehicle datasets using the SLAMBench2 benchmarking suite. The algorithms tested are MonoSLAM, PTAM, OKVIS, LSDSLAM, ORB-SLAM2, and SVO, all of which are built into the SLAMBench2 software. The algorithms' performance is evaluated using simulated datasets generated in the AftrBurner Engine. The datasets were designed to test the quality of each …

Learning In The Machine: To Share Or Not To Share?, Jordan Ott, Erik Linstead, Nicholas Lahaye, Pierre Baldi

Engineering Faculty Articles and Research

Weight-sharing is one of the pillars behind Convolutional Neural Networks and their successes. However, in physical neural systems such as the brain, weight-sharing is implausible. This discrepancy raises the fundamental question of whether weight-sharing is necessary. If so, to which degree of precision? If not, what are the alternatives? The goal of this study is to investigate these questions, primarily through simulations where the weight-sharing assumption is relaxed. Taking inspiration from neural circuitry, we explore the use of Free Convolutional Networks and neurons with variable connection patterns. Using Free Convolutional Networks, we show that while weight-sharing is a pragmatic optimization …

Effects Of Long-Term Evolution Waveform On Synthetic Aperture Radar Image Quality Metrics, Blake M. Colson

Theses and Dissertations

As a greater demand by the private sector for bandwidth drives spectrum allocations away from defense, new methods for coexistence in the spectrum are being explored. One of the prominent areas in defense for this coexistence is passive radar. This mode of radar system allows for data collection by referencing signals already established in the environment of interest. Some of the most prolific signals currently available are those used for mobile communication networks. In particular, Long- Term Evolution (LTE) is a common waveform that could be leveraged for discrete collection of image intelligence. Seeking to build a base of knowledge, …

Electricity Price Forecasting Using A Convolutional Neural Network, Elliott Winicki

Master's Theses

Many methods have been used to forecast real-time electricity prices in various regions around the world. The problem is difficult because of market volatility affected by a wide range of exogenous variables from weather to natural gas prices, and accurate price forecasting could help both suppliers and consumers plan effective business strategies. Statistical analysis with autoregressive moving average methods and computational intelligence approaches using artificial neural networks dominate the landscape. With the rise in popularity of convolutional neural networks to handle problems with large numbers of inputs, and convolutional neural networks conspicuously lacking from current literature in this field, convolutional …

Dual-Axis Solar Tracker, Bryan Kennedy

All Undergraduate Projects

Renewable energies, and fuels that are not fossil fuel-based, are one of the prolific topics of debate in modern society. With climate change now becoming a primary focus for scientists and innovators of today, one of the areas for the largest amount of potential and growth is that of the capturing and utilization of Solar Energy. This method involves using a mechanical system to track the progression of the sun as it traverses the sky throughout the day. A dual-axis solar tracker such as the one designed and built for this project, can follow the sun both azimuthally and in …

Ensemble Lung Segmentation System Using Deep Neural Networks, Redha A. Ali, Russell C. Hardie, Hussin K. Ragb

Electrical and Computer Engineering Faculty Publications

Lung segmentation is a significant step in developing computer-aided diagnosis (CAD) using Chest Radiographs (CRs). CRs are used for diagnosis of the 2019 novel coronavirus disease (COVID-19), lung cancer, tuberculosis, and pneumonia. Hence, developing a Computer-Aided Detection (CAD) system would provide a second opinion to help radiologists in the reading process, increase objectivity, and reduce the workload. In this paper, we present the implementation of our ensemble deep learning model for lung segmentation. This model is based on the original DeepLabV3+, which is the extended model of DeepLabV3. Our model utilizes various architectures as a backbone of DeepLabV3+, such as …

Deep Siamese Neural Networks For Facial Expression Recognition In The Wild, Wassan Hayale

Electronic Theses and Dissertations

The variation of facial images in the wild conditions due to head pose, face illumination, and occlusion can significantly affect the Facial Expression Recognition (FER) performance. Moreover, between subject variation introduced by age, gender, ethnic backgrounds, and identity can also influence the FER performance. This Ph.D. dissertation presents a novel algorithm for end-to-end facial expression recognition, valence and arousal estimation, and visual object matching based on deep Siamese Neural Networks to handle the extreme variation that exists in a facial dataset. In our main Siamese Neural Networks for facial expression recognition, the first network represents the classification framework, where we …

Application Of Quantum Cryptography To Cybersecurity And Critical Infrastructures In Space Communications, Rita Meraz, Linda Vahala

OUR Journal: ODU Undergraduate Research Journal

As society becomes more dependent on technology and the internet, critical infrastructure, which provides the fundamental services that millions of people depend on, becomes more vulnerable to cyber threats. This paper presents the importance of cybersecurity in critical infrastructure addressing the communications sector which is prevailed by space systems. It gives an overview of laser communications via satellite, and it argues the utility that quantum cryptography can provide to secure the data transmitted between communication satellites and ground stations from cyber attacks. Common encryption algorithms are briefly introduced as well as a review on quantum computing. Quantum cryptography is still …

Corrections To ‘‘Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping’’, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel

Electrical and Computer Engineering Faculty Publications

In the above article [1], Figure 2 was incorrect. Unfortunately, we mixed the color label of "CONV $\to $ BN $\to $ ReLu" and "Unpooling" in the CNN structure section of Figure 2. The color label of "CONV $\to $ BN $\to $ ReLu" should be orange while the color label of "Unpooling" should be green. Also, the word "Decoder" is misspelled. That same figure with the same error is also used for the graphic abstract. The corrected figure is given here. None of the sections in the figure is modified. The only change is in the color label of …

Accurate Range-Based Indoor Localization Using Pso-Kalman Filter Fusion, Paul Bupe Jr

College of Graduate Studies: Theses & Dissertations

Accurate indoor localization often depends on infrastructure support for distance estimation in range-based techniques. One can also trade off accuracy to reduce infrastructure investment by using relative positions of other nodes, as in range-free localization. Even for range-based methods where accurate Ultra-WideBand (UWB) signals are used, non line-of-sight (NLOS) conditions pose significant difficulty in accurate indoor localization. Existing solutions rely on additional measurements from sensors and typically correct the noise using a Kalman filter (KF). Solutions can also be customized to specific environments through extensive profiling. In this work, a range-based indoor localization algorithm called PSO - Kalman Filter Fusion …

Analysis Of Antenna Designs For The Maximum Power Transmission, Lauryn P. Smith

College of Graduate Studies: Theses & Dissertations

Since Nikola Tesla discovered wireless power transmission, it has become a very interesting topic of study in the antennas and wireless propagation community. Various aspects and applications for wireless power transmission are studied today, a few of which are investigated in this work. First, various antenna geometries are analyzed for radiative near-field wireless power transfer in terms of electrical field strength. It is determined that the meander antenna is ideal for maximum power transfer in its radiative near-field region, contrary to its far-field behavior. Next, in the application of radio frequency identification, a directive, UHF RFID tag antenna is designed …

Reliable Navigation For Suas In Complex Indoor Environments, Andrew J. Fabian

Theses and Dissertations

Indoor environments are a particular challenge for Unmanned Aerial Vehicles (UAVs). Effective navigation through these GPS-denied environments require alternative localization systems, as well as methods of sensing and avoiding obstacles while remaining on-task. Additionally, the relatively small clearances and human presence characteristic of indoor spaces necessitates a higher level of precision and adaptability than is common in traditional UAV flight planning and execution. This research blends the optimization of individual technologies, such as state estimation and environmental sensing, with system integration and high-level operational planning.

The combination of AprilTag visual markers, multi-camera Visual Odometry, and IMU data can be used …

Deep Learning Towards Intelligent Vehicle Fault Diagnosis, Mohammed Al-Zeyadi, Javier Andreu-Perez, Hani Hagras, Chris Royce, Darren Smith, Piotr Rzonsowski, Ali Malik

Conference papers

Recently, the rapid development of automotive industries has given rise to large multidimensional datasets both in the production sites and after-sale services. Fault diagnostic systems are one of the services that the automotive industries provide. As a consequence of the rapid development of cars features, traditional rule-based diagnostic systems became very limited. Therefore, more sophisticated AI approaches need to be investigated towards more efficient solutions. In this paper, we focus on utilising deep learning so as to build a diagnostic system that is able to estimate the required services in an efficient and effective way. We propose a new model, …