Electrical and Computer Engineering Commons^™

Enhancing Telecom Churn Prediction: Adaboost With Oversampling And Recursive Feature Elimination Approach, Long Dinh Tran

Master's Theses

Churn prediction is a critical task for businesses to retain their valuable customers. This paper presents a comprehensive study of churn prediction in the telecom sector using 15 approaches, including popular algorithms such as Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, and AdaBoost.

The study is segmented into three sets of experiments, each focusing on a different approach to building the churn prediction model. The model is constructed using the original training set in the first set of experiments. The second set involves oversampling the training set to address the issue of imbalanced data. Lastly, the third set …

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 …

Investigation Of Green Strawberry Detection Using R-Cnn With Various Architectures, Daniel W. Rivers

Master's Theses

Traditional image processing solutions have been applied in the past to detect and count strawberries. These methods typically involve feature extraction followed by object detection using one or more features. Some object detection problems can be ambiguous as to what features are relevant and the solutions to many problems are only fully realized when the modern approach has been applied and tested, such as deep learning.

In this work, we investigate the use of R-CNN for green strawberry detection. The object detection involves finding regions of interest (ROIs) in field images using the selective segmentation algorithm and inputting these regions …

An Analysis Of Camera Configurations And Depth Estimation Algorithms For Triple-Camera Computer Vision Systems, Jared Peter-Contesse

Master's Theses

The ability to accurately map and localize relevant objects surrounding a vehicle is an important task for autonomous vehicle systems. Currently, many of the environmental mapping approaches rely on the expensive LiDAR sensor. Researchers have been attempting to transition to cheaper sensors like the camera, but so far, the mapping accuracy of single-camera and dual-camera systems has not matched the accuracy of LiDAR systems. This thesis examines depth estimation algorithms and camera configurations of a triple-camera system to determine if sensor data from an additional perspective will improve the accuracy of camera-based systems. Using a synthetic dataset, the performance of …

First Order Self-Oscillating Class-D Circuit With Triangular Wave Injection, Matthew J. Carroll

Master's Theses

An investigation into performance improvements to the modulator stage of a class-D amplifier is conducted in this thesis. Two of the standard topologies, namely class-D open-loop pulse-width modulation (PWM), and the improved self-oscillating feedback system are benchmarked against a topology which includes both a hysteretic comparator in a feedback loop and triangle wave injection. Circuit performance is analyzed by comparing how the triangle injection circuit handles known issues with open-loop and self-oscillating circuits. Using this analysis, it is shown that the triangle injection topology offers an improved power supply rejection ratio relative to open-loop PWM and reduces distortion generated by …

Biological Semantic Segmentation On Ct Medical Images For Kidney Tumor Detection Using Nnu-Net Framework, Andres Bergsneider

Master's Theses

Healthcare systems are constantly challenged with bottlenecks due to human-reliant operations, such as analyzing medical images. High precision and repeatability is necessary when performing a diagnostics on patients with tumors. Throughout the years an increasing number of advancements have been made using various machine learning algorithms for the detection of tumors helping to fast track diagnosis and treatment decisions. “Black Box” systems such as the complex deep learning networks discussed in this paper rely heavily on hyperparameter optimization in order to obtain the most ideal performance. This requires a significant time investment in the tuning of such networks to acquire …

Boost Converter Inductor Sizing Effects On The Performance Of Mppt Algorithms, Alan Nonaka

Master's Theses

With solar power and other renewables set to take over the market in the coming decades, maximum power point tracking will be essential to optimizing power output. One underserved topic of research is the effect of inductor current ripple on performance of Maximum Power Point Tracking (MPPT) algorithms. Many new topologies are focused on decreasing the ripple from PV source to increase efficiency and power output. However, not much has been done to show ripple degrading performance of MPPT algorithms. This study uses a boost converter topology to test the performance of constant duty cycle step Perturb and Observe (PO), …

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 …

Performance Enhancement And Characterization Of An Electromagnetic Railgun, Paul M. Gilles

Master's Theses

Collision with orbital debris poses a serious threat to spacecraft and astronauts. Hypervelocity impacts resulting from collisions mean that objects with a mass less than 1g can cause mission-ending damage to spacecraft. A means of shielding spacecraft against collisions is necessary. A means of testing candidate shielding methods for their efficacy in mitigating hypervelocity impacts is therefore also necessary. Cal Poly’s Electromagnetic Railgun was designed with the goal of creating a laboratory system capable of simulating hypervelocity (≥ 3 km/s) impacts. Due to several factors, the system was not previously capable of high-velocity (≥ 1 km/s) tests. A deficient projectile …

Utilizing Trajectory Optimization In The Training Of Neural Network Controllers, Nicholas Kimball

Master's Theses

Applying reinforcement learning to control systems enables the use of machine learning to develop elegant and efficient control laws. Coupled with the representational power of neural networks, reinforcement learning algorithms can learn complex policies that can be difficult to emulate using traditional control system design approaches. In this thesis, three different model-free reinforcement learning algorithms, including Monte Carlo Control, REINFORCE with baseline, and Guided Policy Search are compared in simulated, continuous action-space environments. The results show that the Guided Policy Search algorithm is able to learn a desired control policy much faster than the other algorithms. In the inverted pendulum …

Development Of A Myoelectric Detection Circuit Platform For Computer Interface Applications, Nickolas Andrew Butler

Master's Theses

Personal computers and portable electronics continue to rapidly advance and integrate into our lives as tools that facilitate efficient communication and interaction with the outside world. Now with a multitude of different devices available, personal computers are accessible to a wider audience than ever before. To continue to expand and reach new users, novel user interface technologies have been developed, such as touch input and gyroscopic motion, in which enhanced control fidelity can be achieved. For users with limited-to-no use of their hands, or for those who seek additional means to intuitively use and command a computer, novel sensory systems …

Logging, Visualization, And Analysis Of Network And Power Data Of Iot Devices, Neal Huynh Nguyen

Master's Theses

There are approximately 23.14 billion IoT(Internet of Things) devices currently in use worldwide. This number is projected to grow to over 75 billion by 2025. Despite their ubiquity little is known about the security and privacy implications of IoT devices. Several large-scale attacks against IoT devices have already been recorded.

To help address this knowledge gap, we have collected a year’s worth of network traffic and power data from 16 common IoT devices. From this data, we show that we can identify different smart speakers, like the Echo Dot, from analyzing one minute of power data on a shared power …

Iris Biometric Identification Using Artificial Neural Networks, Kevin Joseph Haskett

Master's Theses

A biometric method is a more secure way of personal identification than passwords. This thesis examines the iris as a personal identifier with the use of neural networks as the classifier. A comparison of different feature extraction methods that include the Fourier transform, discrete cosine transform, the eigen analysis method, and the wavelet transform, is performed. The robustness of each method, with respect to distortion and noise, is also studied.

Developing, Evaluating, And Demonstrating An Open Source Gateway And Mobile Application For The Smartfarm Decision Support System, Caleb D. Fink

Master's Theses

The purpose of this research is to design, develop, evaluate, and demonstrate an open source gateway and mobile application for the SmartFarm open source decision support system to improve agricultural stewardship, environmental conservation, and provide farmers with a system that they own. There are very limited options for an open source gateway for collecting data on the farm. The options available are: expensive, require professional maintenance, are not portable between systems, improvements are made only by the manufacturer, limited in customization options, difficult to operate, and data is owned by the company rather than the farmer. The gateway is designed …

Towards A Strawberry Harvest Prediction System Using Computer Vision And Pattern Recognition, Andreas M. Apitz

Master's Theses

Farmers require advance notice when a harvest is approaching, so they can allocate resources and hire workers as efficiently as possible. Existing methods are subjective and labor intensive, and require the expertise of a professional forecaster. Cal Poly’s EE department has been collaborating with the Cal Poly Strawberry Center to investigate the potential in using digital imaging processing to predict harvests more reliably. This paper shows the progress of that ongoing project, as well as what aspects could still be improved. Three main blocks comprise this system: data acquisition, which obtains and catalogues images of the strawberry plants; computer vision, …

Computer-Aided Diagnoses (Cad) System: An Artificial Neural Network Approach To Mri Analysis And Diagnosis Of Alzheimer's Disease (Ad), Berizohar Padilla Cerezo

Master's Theses

Alzheimer’s disease (AD) is a chronic and progressive, irreversible syndrome that deteriorates the cognitive functions. Official death certificates of 2013 reported 84,767 deaths from Alzheimer’s disease, making it the 6th leading cause of death in the United States. The rate of AD is estimated to double by 2050. The neurodegeneration of AD occurs decades before symptoms of dementia are evident. Therefore, having an efficient methodology for the early and proper diagnosis can lead to more effective treatments.

Neuroimaging techniques such as magnetic resonance imaging (MRI) can detect changes in the brain of living subjects. Moreover, medical imaging techniques are the …

Workplace Posture Assessment And Biofeedback With Kinect, Matthew Crussell

Master's Theses

With the prevalence of computing, many workers today are confined to desk within an office. By sitting in these positions for long periods of time, workers are prone to develop one of many musculoskeletal disorders (MSDs), such as carpal tunnel syndrome. In order to prevent MSDs in the long term, workers must employ good sitting habits. One promising method to ensure good workplace posture is through camera monitoring. To date, camera systems have been used in determining posture in a clean environment. However, an occluded and cluttered background, which is typical in an office setting, imposes a great challenge for …

Scaled Synthetic Aperture Rader Development, Jason Garvey Schray

Master's Theses

Several previous Cal Poly thesis projects involve synthetic aperture radar (SAR), automatic target recognition (ATR), and tracking. SAR data was either accessed from a publicly available database or generated using complex computer modeling software. The motivation for this dual thesis project is to design and construct a scaled SAR system to support Cal Poly radar projects. Ideally this is a low-cost, high resolution SAR architecture that produces raw range Doppler data for any desired target area. To that end, a scaled SAR system was successfully designed, built, and tested. The current SAR system, however, does not perform azimuthal compression and …

Oceanographic Instrument Simulator, Amy Chen

Master's Theses

The Monterey Bay Aquarium Research Institute (MBARI) established the Free Ocean Carbon Enrichment (FOCE) experiment to study the long-term effects of decreased ocean pH levels by developing in-situ platforms [1]. Deep FOCE (dpFOCE) was the first platform, which was deployed in 950 meters of water in Monterey Bay. After the conclusion of dpFOCE, MBARI developed an open source shallow water FOCE (swFOCE) platform located at around 250 meter of water to facilitate worldwide shallow water experiments on FOCE [1][2]. A shallow water platform can be more ubiquitous than a deep-water platform as shallow water instruments are less expensive (as it …

Automated Multi-Modal Search And Rescue Using Boosted Histogram Of Oriented Gradients, Matthew A. Lienemann

Master's Theses

Unmanned Aerial Vehicles (UAVs) provides a platform for many automated tasks and with an ever increasing advances in computing, these tasks can be more complex. The use of UAVs is expanded in this thesis with the goal of Search and Rescue (SAR), where a UAV can assist fast responders to search for a lost person and relay possible search areas back to SAR teams. To identify a person from an aerial perspective, low-level Histogram of Oriented Gradients (HOG) feature descriptors are used over a segmented region, provided from thermal data, to increase classification speed. This thesis also introduces a dataset …

Sweep Stability Characterization Of A Vernier-Tuned Distributed Bragg Reflector (Vt-Dbr) All-Semiconductor Tunable Swept Laser System At 1550 Nm For Sensing Applications, Roric Christian Martens Biersach

Master's Theses

The short-term jitter and longer-term wander of the frequency sweep profile of a Vernier-Tuned Distributed Bragg Reflector (VT-DBR) laser at 1550 nm used in optical coherence tomography (OCT) and other sensing applications is characterized in this work. The VT-DBR has demonstrated success in source-swept OCT (SSOCT), performing both intensity and phase-sensitive OCT.

The purpose of this paper is to investigate one of the unique aspects of the VT-DBR laser that makes it successful in OCT: the stability of the linear optical frequency sweep. A highly stable linear optical frequency sweep implies benefits for further fiber sensing applications including fiber Bragg …

Atrengine: An Orientation-Based Algorithm For Automatic Target Recognition, Justin Ting-Jeuan Kuo

Master's Theses

Automatic Target Recognition (ATR) is a subject involving the use of sensor data to develop an algorithm for identifying targets of significance. It is of particular interest in military applications such as unmanned aerial vehicles and missile tracking systems. This thesis develops an orientation-based classification approach from previous ATR algorithms for 2-D Synthetic Aperture Radar (SAR) images. Prior work in ATR includes Chessa Guilas’ Hausdorff Probabilistic Feature Analysis Approach in 2005 and Daniel Cary’s Optimal Rectangular Fit in 2007.

A system incorporating multiple modules performing different tasks is developed to streamline the data processing of previous algorithms. Using images from …

Mos Current Mode Logic (Mcml) Analysis For Quiet Digital Circuitry And Creation Of A Standard Cell Library For Reducing The Development Time Of Mixed Signal Chips, David Marusiak

Master's Theses

Many modern digital systems use forms of CMOS logical implementation due to the straight forward design nature of CMOS logic and minimal device area since CMOS uses fewer transistors than other logic families. To achieve high-performance requirements in mixed-signal chip development and quiet, noiseless circuitry, this thesis provides an alternative toCMOSin the form of MOS Current Mode Logic (MCML). MCML dissipates constant current and does not produce noise during value changing in a circuit CMOS circuits do. CMOS logical networks switch during clock ticks and with every device switching, noise is created on the supply and ground to deal with …

A Comparison Of Image Processing Techniques For Bird Detection, Elsa Reyes

Master's Theses

Orchard fruits and vegetable crops are vulnerable to wild birds and animals. These wild birds and animals can cause critical damage to the produce. Traditional methods of scaring away birds such as scarecrows are not long-term solutions but short-term solutions. This is a huge problem especially near areas like San Luis Obispo where there are vineyards. Bird damage can be as high as 50% for grapes being grown in vineyards. The total estimated revenue lost annually in the 10 counties in California due to bird and rodent damage to 22 selected crops ranged from $168 million to $504 million (in …

Active Storage And Ssd Caching In An Object Storage Environment, Michael T. Runde

Master's Theses

The advancing performance and lowering costs required to implement additional processing power on system peripherals such as disk drives are increasingly allowing additional computing ability to be located directly on individual drives. Active Storage attempts to take advantage of this excess by moving some computationally intensive applications directly to the disk drives. This can remove the bottlenecks seen through interconnects between the drives and the CPU of an initiating system as well as remove the need for systems to handle these applications.

The contributions of this thesis are in two areas. The first is the development of a framework designed …

A Resistance Based Structural Health Monitoring System For Composite Structure Applications, Dennis N. Boettcher

Master's Theses

This research effort explored the possibility of using interwoven conductive and nonconductive fibers in a composite laminate for structural health monitoring (SHM). Traditional SHM systems utilize fiber optics, piezoelectrics, or detect defects by nondestructive test methods by use of sonar graphs or x-rays. However, these approaches are often expensive, time consuming and complicated.

The primary objective of this research was to apply a resistance based method of structural health monitoring to a composite structure to determine structural integrity and presence of defects.

The conductive properties of fiber such as carbon, copper, or constantan - a copper-nickel alloy - can be …

Touchspice: Physical-Virtual Circuit Emulator, Kevin Christopher Peters

Master's Theses

This thesis involves the creation of a system of embedded touchscreen devices called touchSPICE to aid in the learning of basic circuits. Traditionally, circuit theory is taught to students in two different methods, lectures and laboratory exercises. Lectures focus on auditory and visual learning and are largely passive learning. Lab experiments allow students to physically interact with the circuits, and learn visually through viewing output waveforms from simulators or on measurement devices. The goal of the touchSPICE project is to develop a physical system for virtual, real-time SPICE simulation that mimics the laboratory experience. In touchSPICE, touchscreen devices act as …

Linear Power-Efficient Rf Amplifier With Partial Positive Feedback, Matthew E. King

Master's Theses

Over the last decade, the number of mobile wireless devices on the market has increased substantially. New “multi-carrier” modulation schemes, such as OFDM, WCDMA, and WiMAX, have been developed to accommodate the increasing number of wireless subscribers and the demand for faster data rates within the limited commercial frequency spectrum. These complex modulation schemes create signals with high peak-to-average power ratios (PAPR), exhibiting rapid changes in the signal magnitude. To accommodate these high-PAPR signals, RF power amplifiers in mobile devices must operate under backed-off gain conditions, resulting in poor power efficiency. Various efficiency-enhancement solutions have been realized for backed-off devices …

Development And Prototyping Of A Ground Fault Circuit Interrupter For 3-Phase 480 Volt Systems, Matthew R. Norlander

Master's Theses

Ground Fault Circuit Interrupter (GFCI) technology was first introduced in the NEC in 1971, yet four decades later the technology has not been introduced to a great extent outside of the home environment. This thesis introduces the difficulties encountered in low-voltage three phase ground fault current detection, and adopts a previously patented tripping scheme to develop and prototype a digital relay for 3-phase 480 volt systems capable of the sensitivity and speed required for personnel safety. Results demonstrate the feasibility of the concept and suggest commercial development should be pursued. The prototype is capable of mA sensitivity and reliably detects …

Face Detection And Lip Localization, Benafsh Nadir Husain

Master's Theses

Integration of audio and video signals for automatic speech recognition has become an important field of study. The Audio-Visual Speech Recognition (AVSR) system is known to have accuracy higher than audio-only or visual-only system. The research focused on the visual front end and has been centered around lip segmentation. Experiments performed for lip feature extraction were mainly done in constrained environment with controlled background noise. In this thesis we focus our attention to a database collected in the environment of a moving car which hampered the quality of the imagery.

We first introduce the concept of illumination compensation, where we …