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Electrical and Computer Engineering

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Articles 991 - 1020 of 7209

Full-Text Articles in Computer Engineering

Quantum Computing And Resilient Design Perspectives For Cybersecurity Of Feedback Systems, Keshav Kasturi Rangan, Jihan Abou Halloun, Henrique Oyama, Samantha Cherney, Ilham Azali Assoumani, Nazir Jairazbhoy, Helen Durand, Simon Ka Ng Jun 2022

Quantum Computing And Resilient Design Perspectives For Cybersecurity Of Feedback Systems, Keshav Kasturi Rangan, Jihan Abou Halloun, Henrique Oyama, Samantha Cherney, Ilham Azali Assoumani, Nazir Jairazbhoy, Helen Durand, Simon Ka Ng

Chemical Engineering and Materials Science Faculty Research Publications

Cybersecurity of control systems is an important issue in next-generation manufac- turing that can impact both operational objectives (safety and performance) as well as process designs (via hazard analysis). Cyberattacks differ from faults in that they can be coordinated efforts to exploit system vulnerabilities to create otherwise unlikely hazard scenarios. Because coordination and targeted process manipulation can be characteristics of attacks, some of the tactics previously analyzed in our group from a control system cybersecurity perspective have incorporated randomness to attempt to thwart attacks. The underlying assumption for the generation of this randomness has been that it can be achieved …


Barrier Knockdown Test Control System For The Cal Poly Kinesiology Department, Regina M. Chapuis Jun 2022

Barrier Knockdown Test Control System For The Cal Poly Kinesiology Department, Regina M. Chapuis

Computer Engineering

The goal of this project is to design and implement a new control system for the LEDs and buttons on an existing Barrier Knockdown setup in the Cal Poly Kinesiology department. The Barrier Knockdown test is a testing apparatus in which subjects knock down a series of mechanical barriers in one of three patterns. The computer system times their reaction and movement time, and the test as a whole provides students with data to study the phenomenon of Contextual Interference. This system was previously controlled by an old computer setup that ultimately crashed. This project recreates the logic and user …


Dual-Axis Precision Imager, Gary Huarng Jun 2022

Dual-Axis Precision Imager, Gary Huarng

Computer Engineering

The Dual-Axis Precision Imager (DAPI) is a drawing robot that processes images and draws them on a whiteboard. The system has two modes: a Sobel filter mode that finds the edges of the input image with a Sobel filter, and a tri-tone grayscale mode that approximates the shading of the input image with the colors white, gray, and black. The DAPI consists of an Arduino-controlled XY gantry system with a pen mounted on the gantry head, and a Processing IDE program that processes the original image, converts the processed image into gantry instructions, and sends them to the Arduino for …


Imnets: Deep Learning Using An Incremental Modular Network Synthesis Approach For Medical Imaging Applications, Redha A. Ali, Russell C. Hardie, Barath Narayanan Narayanan, Temesguen Messay Jun 2022

Imnets: Deep Learning Using An Incremental Modular Network Synthesis Approach For Medical Imaging Applications, Redha A. Ali, Russell C. Hardie, Barath Narayanan Narayanan, Temesguen Messay

Electrical and Computer Engineering Faculty Publications

Deep learning approaches play a crucial role in computer-aided diagnosis systems to support clinical decision-making. However, developing such automated solutions is challenging due to the limited availability of annotated medical data. In this study, we proposed a novel and computationally efficient deep learning approach to leverage small data for learning generalizable and domain invariant representations in different medical imaging applications such as malaria, diabetic retinopathy, and tuberculosis. We refer to our approach as Incremental Modular Network Synthesis (IMNS), and the resulting CNNs as Incremental Modular Networks (IMNets). Our IMNS approach is to use small network modules that we call SubNets …


A Nano-Drone Safety Architecture, Connor J. Sexton Jun 2022

A Nano-Drone Safety Architecture, Connor J. Sexton

Master's Theses

As small-form factor drones grow more intelligent, they increasingly require more sophisticated capabilities to record sensor data and system state, ensuring safe and improved operation. Already regulations for black boxes, electronic data recorders (EDRs), for determining liabilities and improving the safety of large-form factor autonomous vehicles are becoming established. Conventional techniques use hardened memory storage units that conserve all sensor (visual) and system operational state; and N-way redundant models for detecting uncertainty in system operation. For small-form factor drones, which are highly limited by weight, power, and computational resources, these techniques become increasingly prohibitive. In this paper, we propose a …


Poster: Indoor Navigation For Visually Impaired People With Vertex Colored Graphs, Pei Du, Nirupama Bulusu Jun 2022

Poster: Indoor Navigation For Visually Impaired People With Vertex Colored Graphs, Pei Du, Nirupama Bulusu

Electrical and Computer Engineering Faculty Publications and Presentations

Visually impaired people face many daily encumbrances. Traditional visual enhancements do not suffice to navigate indoor environments. In this paper, we explore path finding algorithms such as Dijkstra and A* combined with graph coloring to find a safest and shortest path for visual impaired people to navigate indoors. Our mobile application is based on a database which stores the locations of several spots in the building and their corresponding label. Visual impaired people select the start and destination when they want to find their way, and our mobile application will show the appropriate path which guarantees their safety.


Mars Prototype Rover Environmental Measurement System, James A. Renick Jun 2022

Mars Prototype Rover Environmental Measurement System, James A. Renick

Computer Engineering

In my senior project, the problem I am trying to solve is how to efficiently design, create, and install an original library onto a Mars prototype rover operating system and to further use that library to integrate a new weather measurement sensor device into the rover system with the necessary software and hardware implementations. This is an important and highly valued problem as many aerospace and other engineering companies utilize rovers and other autonomous systems for important research, explorations, and reconnaissance missions and goals. In solving this problem, I utilized many resources that were available to me such as advisors, …


Developing A Miniature Smart Boat For Marine Research, Michael Isaac Eirinberg Jun 2022

Developing A Miniature Smart Boat For Marine Research, Michael Isaac Eirinberg

Computer Engineering

This project examines the development of a smart boat which could serve as a possible marine research apparatus. The smart boat consists of a miniature vessel containing a low-cost microcontroller to live stream a camera feed, GPS telemetry, and compass data through its own WiFi access point. The smart boat also has the potential for autonomous navigation. My project captivated the interest of several members of California Polytechnic State University, San Luis Obispo’s (Cal Poly SLO) Marine Science Department faculty, who proposed a variety of fascinating and valuable smart boat applications.


Machine Learning Fmri Autism Classifier, Nicholas Luckenbach Jun 2022

Machine Learning Fmri Autism Classifier, Nicholas Luckenbach

Interdisciplinary Design Senior Theses

Autism Spectrum Disorder (ASD) is typically understood by observing patient behaviors. Advances in neuroimaging research and data collection have made it possible to investigate the neurobiological basis for ASD, and differences between subjects with ASD and healthy controls (HC) have been found using a variety of methods. Functional magnetic resonance imaging (fMRI) in particular has provided evidence for and against certain cognitive models of ASD based on measuring the functional connectivity of subjects’ brains. Various techniques have been explored for applying machine learning (ML) to fMRI data in order to find unique patterns and differences between ASD and HC subjects. …


Total Sky Imager Project, Ryan D. Maier, Benjamin Jack Forest, Kyle X. Mcgrath Jun 2022

Total Sky Imager Project, Ryan D. Maier, Benjamin Jack Forest, Kyle X. Mcgrath

Mechanical Engineering

Solar farms like the Gold Tree Solar Farm at Cal Poly San Luis Obispo have difficulty delivering a consistent level of power output. Cloudy days can trigger a significant drop in the utility of a farm’s solar panels, and an unexpected loss of power from the farm could potentially unbalance the electrical grid. Being able to predict these power output drops in advance could provide valuable time to prepare a grid and keep it stable. Furthermore, with modern data analysis methods such as machine learning, these predictions are becoming more and more accurate – given a sufficient data set. The …


Smartphone Control Of Rc Cars, Weston R. Fitzgerald Jun 2022

Smartphone Control Of Rc Cars, Weston R. Fitzgerald

Electrical Engineering

The smartphone-controlled RC (remote-controlled) car is an inexpensive remote-controlled car designed to be fast and portable. Instead of manufacturing, packaging, and shipping a separate controller, the remote control is implemented in a phone application, which saves time and money in both the design process and the manufacturing process. Utilizing the user’s smartphone is more cost-effective since mobile devices are a common recurrence, and packaging fewer devices results in overall better portability of the product.

This smartphone-controlled car is speedy and intuitive to learn for typical smartphone users. The user can change the car’s speed and direction wirelessly using their phone; …


Runtime Energy Savings Based On Machine Learning Models For Multicore Applications, Vaibhav Sundriyal, Masha Sosonkina Jun 2022

Runtime Energy Savings Based On Machine Learning Models For Multicore Applications, Vaibhav Sundriyal, Masha Sosonkina

Electrical & Computer Engineering Faculty Publications

To improve the power consumption of parallel applications at the runtime, modern processors provide frequency scaling and power limiting capabilities. In this work, a runtime strategy is proposed to maximize energy savings under a given performance degradation. Machine learning techniques were utilized to develop performance models which would provide accurate performance prediction with change in operating core-uncore frequency. Experiments, performed on a node (28 cores) of a modern computing platform showed significant energy savings of as much as 26% with performance degradation of as low as 5% under the proposed strategy compared with the execution in the unlimited power case.


Outdoor Operations Of Multiple Quadrotors In Windy Environment, Deepan Lobo May 2022

Outdoor Operations Of Multiple Quadrotors In Windy Environment, Deepan Lobo

Dissertations

Coordinated multiple small unmanned aerial vehicles (sUAVs) offer several advantages over a single sUAV platform. These advantages include improved task efficiency, reduced task completion time, improved fault tolerance, and higher task flexibility. However, their deployment in an outdoor environment is challenging due to the presence of wind gusts. The coordinated motion of a multi-sUAV system in the presence of wind disturbances is a challenging problem when considering collision avoidance (safety), scalability, and communication connectivity. Performing wind-agnostic motion planning for sUAVs may produce a sizeable cross-track error if the wind on the planned route leads to actuator saturation. In a multi-sUAV …


Rechargeable Multi-Cell Battery, Wei Qiao, Taesic Kim, Liyan Qu May 2022

Rechargeable Multi-Cell Battery, Wei Qiao, Taesic Kim, Liyan Qu

Department of Electrical and Computer Engineering: Faculty Publications

A method for power management of a multi - cell battery includes identifying a desired power value and voltage value , determining a battery voltage value and a battery current value for a battery , determining a number of battery banks from a plurality of battery banks to use for the battery , where each battery bank includes one or more battery cells ( or battery modules ) , checking availability of each of the one or more battery cells ( or battery modules ) , selecting one or more battery banks from the plurality of battery banks , where …


A High-Density Theta Burst Paradigm Enhances The Aftereffects Of Transcranial Magnetic Stimulation: Evidence From Focal Stimulation Of Rat Motor Cortex, Qinglei Meng, Hieu Nguyen, Antonia Vrana, Simone Baldwin, Charlotte Qiong Li, Antonia Giles, Jun Wang, Yihong Yang, Hanbing Lu May 2022

A High-Density Theta Burst Paradigm Enhances The Aftereffects Of Transcranial Magnetic Stimulation: Evidence From Focal Stimulation Of Rat Motor Cortex, Qinglei Meng, Hieu Nguyen, Antonia Vrana, Simone Baldwin, Charlotte Qiong Li, Antonia Giles, Jun Wang, Yihong Yang, Hanbing Lu

Department of Electrical and Computer Engineering: Faculty Publications

Background: Theta burst stimulation (TBS) is an efficient noninvasive neuromodulation paradigm that has been widely adopted, clinically. However, the efficacy of TBS treatment remains similarly modest as conventional 10 Hz repetitive transcranial magnetic stimulation (rTMS).

Objective/hypothesis: To develop a new TBS paradigm that enhances the effects of TMS administration while maintaining high time-efficiency.

Methods: We describe here a new TMS paradigm, named High-Density Theta Burst Stimulation (hdTBS). This paradigm delivers up to 6 pulses per burst, as opposed to only 3 in conventional TBS, while maintaining the inter-burst interval of 200 ms (or 5 Hz) - a …


Project Metamorphosis: Designing A Dynamic Framework For Converting Musical Compositions Into Paintings, Rao Hamza Ali, Grace Fong, Erik Linstead May 2022

Project Metamorphosis: Designing A Dynamic Framework For Converting Musical Compositions Into Paintings, Rao Hamza Ali, Grace Fong, Erik Linstead

Engineering Faculty Articles and Research

The authors present an automated, rule-based system for converting piano compositions into paintings. Using a color-note association scale presented by Edward Maryon in 1919, which correlates 12-tone scale with 12 hues of the color circle, the authors present a simple approach for extracting colors associated with each note played in a piano composition. The authors also describe the color extraction and art generation process in detail, as well as the process for creating “moving art,” which imitates the progression of a musical piece in real time. They share and discuss artworks generated for four well-known piano compositions.


Chapter 28: Quantum Phase Estimation, Hiu Yung Wong May 2022

Chapter 28: Quantum Phase Estimation, Hiu Yung Wong

Faculty Research, Scholarly, and Creative Activity

No abstract provided.


Chapter 3: Basis, Basis Vectors, And Inner Product, Hiu Yung Wong May 2022

Chapter 3: Basis, Basis Vectors, And Inner Product, Hiu Yung Wong

Faculty Research, Scholarly, and Creative Activity

No abstract provided.


Chapter 27: Bloch Sphere And Single-Qubit Arbitrary Unitary Gate, Hiu Yung Wong May 2022

Chapter 27: Bloch Sphere And Single-Qubit Arbitrary Unitary Gate, Hiu Yung Wong

Faculty Research, Scholarly, and Creative Activity

No abstract provided.


Graph-Based Heuristic Solution For Placing Distributed Video Processing Applications On Moving Vehicle Clusters, Kanika Sharma, Bernard Butler, Brendan Jennings May 2022

Graph-Based Heuristic Solution For Placing Distributed Video Processing Applications On Moving Vehicle Clusters, Kanika Sharma, Bernard Butler, Brendan Jennings

Articles

Vehicular fog computing (VFC) is envisioned as an extension of cloud and mobile edge computing to utilize the rich sensing and processing resources available in vehicles. We focus on slow-moving cars that spend a significant time in urban traffic congestion as a potential pool of onboard sensors, video cameras, and processing capacity. For leveraging the dynamic network and processing resources, we utilize a stochastic mobility model to select nodes with similar mobility patterns. We then design two distributed applications that are scaled in real-time and placed as multiple instances on selected vehicular fog nodes. We handle the unstable vehicular environment …


Ml-Based Online Traffic Classification For Sdns, Mohammed Nsaif, Gergely Kovasznai, Mohammed Abboosh, Ali Malik, Ruairí De Fréin May 2022

Ml-Based Online Traffic Classification For Sdns, Mohammed Nsaif, Gergely Kovasznai, Mohammed Abboosh, Ali Malik, Ruairí De Fréin

Articles

Traffic classification is a crucial aspect for Software-Defined Networking functionalities. This paper is a part of an on-going project aiming at optimizing power consumption in the environment of software-defined datacenter networks. We have developed a novel routing strategy that can blindly balance between the power consumption and the quality of service for the incoming traffic flows. In this paper, we demonstrate how to classify the network traffic flows so that the quality of service of each flow-class can be guaranteed efficiently. This is achieved by creating a dataset that encompasses different types of network traffic such as video, VoIP, game …


Automotive Sensor Fusion Systems For Traffic Aware Adaptive Cruise Control, Jonah T. Gandy May 2022

Automotive Sensor Fusion Systems For Traffic Aware Adaptive Cruise Control, Jonah T. Gandy

Theses and Dissertations

The autonomous driving (AD) industry is advancing at a rapid pace. New sensing technology for tracking vehicles, controlling vehicle behavior, and communicating with infrastructure are being added to commercial vehicles. These new automotive technologies reduce on road fatalities, improve ride quality, and improve vehicle fuel economy. This research explores two types of automotive sensor fusion systems: a novel radar/camera sensor fusion system using a long shortterm memory (LSTM) neural network (NN) to perform data fusion improving tracking capabilities in a simulated environment and a traditional radar/camera sensor fusion system that is deployed in Mississippi State’s entry in the EcoCAR Mobility …


Design Of Hardware To Aid Smartphone-Based Oscilloscope App, Riddock Moran May 2022

Design Of Hardware To Aid Smartphone-Based Oscilloscope App, Riddock Moran

Honors Program: Senior Projects (Public)

A smartphone-based oscilloscope improves on traditional lab oscilloscopes in accessibility and portability but faces several performance limitations compared to traditional oscilloscopes. Among these, an oscilloscope app that uses the phone’s audio to read voltage signals will have a sampling rate and voltage bottlenecked by the capabilities of the audio codec, which will rarely exceed a rate of 48 kHz and 1 volt, respectively. Additionally, smartphones lack the ability to read line-in audio, allowing only one channel input through the microphone. Direct connections to an audio source may not be possible due to requiring an audio jack connection, and different poles …


Automated Robotic Light Bulb Testing Platform, Agha I. Akram, Muhammad Ali Ummy May 2022

Automated Robotic Light Bulb Testing Platform, Agha I. Akram, Muhammad Ali Ummy

Publications and Research

The main purpose of this project is to create a functional prototype of a multilayered system that incorporates aspects of electrical, mechanical, and computer engineering technology. The main objective of the system is to be able to determine whether a light bulb is working or not. The building blocks of this system are a robotic arm that is able to slide along a rail (for added mobility), a conveyor belt, and an electromechanical device that holds and tests light bulbs. Initially, the robot arm picks up a light bulb and places it into the holder which then tests it. A …


Probing Myosin Ensemble Mechanics In Actin Filament Bundles Using Optical Tweezers, Omayma Al Azzam, Janie C. Watts, Justin E. Reynolds, Juliana E. Davis, Dana N. Reinemann May 2022

Probing Myosin Ensemble Mechanics In Actin Filament Bundles Using Optical Tweezers, Omayma Al Azzam, Janie C. Watts, Justin E. Reynolds, Juliana E. Davis, Dana N. Reinemann

Faculty and Student Publications

Myosins are motor proteins that hydrolyze ATP to step along actin filament (AF) tracks and are essential in cellular processes such as motility and muscle contraction. To understand their force-generating mechanisms, myosin II has been investigated both at the single-molecule (SM) level and as teams of motors in vitro using biophysical methods such as optical trapping. These studies showed that myosin force-generating behavior can differ greatly when moving from the single-molecule level in a three-bead arrangement to groups of motors working together on a rigid bead or coverslip surface in a gliding arrangement. However, these assay constructions do not permit …


Improving Intelligent Transportation Safety And Reliability Through Lowering Costs, Integrating Machine Learning, And Studying Model Sensitivity, Cavender Holt May 2022

Improving Intelligent Transportation Safety And Reliability Through Lowering Costs, Integrating Machine Learning, And Studying Model Sensitivity, Cavender Holt

All Theses

As intelligent transportation becomes increasingly prevalent in the domain of transportation, it is essential to understand the safety, reliability, and performance of these systems. We investigate two primary areas in the problem domain. The first area concerns increasing the feasibility and reducing the cost of deploying pedestrian detection systems to intersections in order to increase safety. By allowing pedestrian detection to be placed in intersections, the data can be better utilized to create systems to prevent accidents from occurring. By employing a dynamic compression scheme for pedestrian detection, we show the reduction of network bandwidth improved by 2.12× over the …


Control, Decision-Making, And Learning Approaches For Connected And Autonomous Driving Systems With Humans-In-The-Loop, Fangjian Li May 2022

Control, Decision-Making, And Learning Approaches For Connected And Autonomous Driving Systems With Humans-In-The-Loop, Fangjian Li

All Dissertations

By virtue of vehicular connectivity and automation, the vehicle becomes increasingly intelligent and self-driving capable. However, no matter what automation level the vehicle can achieve, humans will still be in the loop despite their roles. First, considering the manual driving car as a disturbance to the connected and autonomous vehicles (CAVs), a novel string stability is proposed for mixed traffic platoons consisting of both autonomous and manual driving cars to guarantee acceptable motion fluctuation and platoon safety. Furthermore, humans are naturally considered as the rider in the passenger vehicle. A human-centered cooperative adaptive cruise control (CACC) is designed to improve …


Interval Observer-Based Supervision Of Nonlinear Networked Control Systems, Afef Najjar, Thach Ngoc Dinh, Messaoud Amairi, Tarek Raissi May 2022

Interval Observer-Based Supervision Of Nonlinear Networked Control Systems, Afef Najjar, Thach Ngoc Dinh, Messaoud Amairi, Tarek Raissi

Turkish Journal of Electrical Engineering and Computer Sciences

Networked control system (NCS) is a multidisciplinary area that attracts increasing attention today. In this paper, we deal with remote supervision of a nonlinear networked control systems class subject to network imperfections. Different from many existing researches that consider only the problem of small and/or constant communication delays, we focus on large and time-varying network delays problem in both measurement and control channels. The proposed method is a set-membership estimation-based predictor approach computing a guaranteed set of admissible state values when the uncertainties (i.e. measurement noises and system disturbances) are considered unknown but bounded with a priori known bounds. The …


An Efficient End-To-End Deep Neural Network For Interstitial Lung Disease Recognition And Classification, Masum Shah Junayed, Afsana Ahsan Jeny, Md Baharul Islam, Ikhtiar Ahmed, Afm Shahen Shah May 2022

An Efficient End-To-End Deep Neural Network For Interstitial Lung Disease Recognition And Classification, Masum Shah Junayed, Afsana Ahsan Jeny, Md Baharul Islam, Ikhtiar Ahmed, Afm Shahen Shah

Turkish Journal of Electrical Engineering and Computer Sciences

The automated Interstitial Lung Diseases (ILDs) classification technique is essential for assisting clinicians during the diagnosis process. Detecting and classifying ILDs patterns is a challenging problem. This paper introduces an end-to-end deep convolution neural network (CNN) for classifying ILDs patterns. The proposed model comprises four convolutional layers with different kernel sizes and Rectified Linear Unit (ReLU) activation function, followed by batch normalization and max-pooling with a size equal to the final feature map size well as four dense layers. We used the ADAM optimizer to minimize categorical cross-entropy. A dataset consisting of 21328 image patches of 128 CT scans with …


Evaluating The Role Of Carbon Quantum Dots Covered Silica Nanofillers On The Partial Discharge Performance Of Transformer Insulation, Kasi Viswanathan Palanisamy, Chandrasekar Subramaniam, Balaji Sakthivel May 2022

Evaluating The Role Of Carbon Quantum Dots Covered Silica Nanofillers On The Partial Discharge Performance Of Transformer Insulation, Kasi Viswanathan Palanisamy, Chandrasekar Subramaniam, Balaji Sakthivel

Turkish Journal of Electrical Engineering and Computer Sciences

The article presents the experimental results on the role of carbon quantum dots (CQD) covered silica nanofillers on the partial discharge (PD) properties of transformer oil insulation. The improvement in PD performance of nanofiller blend oil is tested with increased voltage gradient and nanofiller concentration. PD of nanoblend oils for various concentrations of modified silica ranging from 0 to 0.1%wt was measured. PD activity of the test samples is simulated in the laboratory with needle, rod and plane electrode geometry combinations. The facets of PD signals such as PD magnitude, PD inception and time duration of PD extracted from phase-resolved …