Computer Engineering Commons^™

An Approach To Solving The Incoming Target Based On Uncertain Time Series, Jing Yang, Minghua Lu, Xingchen Hu, Jinping Wu

Journal of System Simulation

The traditional solution method for the incoming attacking target in water lacks the time series characteristics mining on multi-dimensional and uncertain observation data. Aiming at the time series prediction with high complexity and missing data, a method based on adaptive window interpolation and deep variable weight long-term and short-term memory network model for missing time series observation data with multiple sampling frequencies is proposed, which is compared and verified on the simulation data and public test data set.Aiming at the random missing problem caused by the inconsistency of sampling frequency of multi-source observation information, an adaptive window imputation method …

Golden Eagle Optimizer Algorithm Combining Levy Flight And Brownian Motion, Jiaxin Deng, Damin Zhang, Qing He, Jianping Zhao

Journal of System Simulation

Aiming at the slow attenuation and low convergence precision of golden eagle optimization algorithm, a new algorithm combining Levy fight and Brownian motion is proposed.In order to increase the diversity, Fuch chaotic map is introduced to initialize the golden eagle individuals. Levy flight mechanism and Brownian motion mechanism are introduced into the position update formula of golden eagle individual to improve the search accuracy and help to the jump out of local optimum. The reduction factor is introduced into the overall position update formula of the golden eagle individual to improve the convergence speed. Compared with 9 original …

Particle Swarm Optimization For New Energy Truck Scheduling In Network Environment, Chuanchao Zhao, Rui Zheng, Li Gong, Xiaolu Ma

Journal of System Simulation

In V2X intelligent network environment, the dispatching system of new energy trucks needs real-time dynamic information.The system under traditional particle swarm scheduling method is prone to fall into local optimum and low solution efficienty.An improved particle swarm scheduling method for new energy trucks is proposed on the basis of multi-objective optiminaztion research. The inertia weight update method is improvedso that the inertia weight decreases non-linearly, andthe risk of the system falling into local optimum is reduced.A priori path encoding method is designed and optimized,the solution efficiency of the algorithm is improved, …

Research On Application Of Monarch Butterfly Optimization Particle Filter In Slam, Zhiqiang Chen, Menglong Cao, Wenbin Zhao

Journal of System Simulation

In traditional particle filter resampling, weight degradation and loss of particle diversity are prone to occur, which leads to the decrease in filtering accuracy and result in inaccurate robot positioning and inaccurate mapping. An optimized particle filter algorithm based on the improved monarch butterfly algorithm is proposed.The algorithm replaces the particle individual with the monarch butterfly individual, and integrates the migration operator and adjustment operator in the monarch butterfly algorithm into the particle filter algorithm. The adaptive genetic parameters are introduced to the iterative update process of the monarch butterfly, and the linear combination optimization resampling method is used …

A Uav Target Tracking And Control Algorithm Based On Siamrpn, Songming Jiao, Hui Ding, Yufei Zhong, Xin Yao, Jiahao Jiahao Zheng

Journal of System Simulation

Aiming at the requirement of autonomously tracking land moving targets of rotary-wing UAVs, an autonomous and stable UAV tracking and control system that can adapt to the common interference environments such as scale changes, occlusions, and attitude changes is constructed.The system extracts the imaging position of the target in airborne camera through the twin network based on deep learning, and obtains the relative pose of the target. The image processing algorithm is designed to process the icons in the tracking frame, and the yaw angle of UAV relative to the tracking target is obtained, Kalman filter is introduced to …

Capturing The Social Experience Of Scu Campus Housing Options In Virtual Tours, Eva Stenberg, Kian Malakooti, Matthew Gates

Computer Science and Engineering Senior Theses

For incoming students at Santa Clara University, it can be challenging and stressful to choose which campus housing to live in. Is it a social dorm or a quiet one? What types of students live here? Will we get along? Will I feel comfortable in the place I’ll call home for the next nine months? Santa Clara University offers very limited resources for choosing campus housing. With the overhead 2D room layouts and the “selfie stick” dorm tours that focus more on the resident director than the rooms, it is hard to discern the sociality of each space which is …

Forecasting Migration To The United States From Hong Kong And India, Priyanka [email protected]

Dissertations and Theses

This study investigates the forecasting of migration from India and Hong Kong to the United States. To study this, quantitative design is employed so numerical data can be used. The proposed research strategy uses the post-positivism approach, as this method can help with looking for explanations via numerical data. The data collection is through using archived data available from the Department of Homeland Security’s website, which is analyzed using descriptive and inferential analysis. The results show how migration trends increase for India but slowly decrease for Hong Kong, along with the best models used to forecast migration.

Dreamtemp: A Platform For Sleep Monitoring And Improvement, Michelle Lim, Kyle Pedersen, Will Cockrum

Interdisciplinary Design Senior Theses

With 70 million Americans suffering from chronic sleep disorders and only 7500 board-certified sleep physicians, a clear logistical problem exists that technological solutions may be able to address. The proliferation of IoT devices in homes and on our person presents a unique opportunity to improve sleep quality by leveraging the data they produce, and the control they provide to us over our everyday lives. DreamTemp is a platform for sleep monitoring and improvement that aims to improve an individual’s quality of sleep by dynamically adjusting the room temperature based on the user’s sleep cycle using a smart wearable and thermostat. …

A Digital Twin Of The Scu Campus: Telling Immersive Stories About Student Life, Marianne Yamazaki Dorr, Hasmik Galstyan, Venus Li, Trisha Nguyen

Computer Science and Engineering Senior Theses

This senior design project aims to explore the use of digital twins of physical spaces to capture the social feel of a space and in the process turning that space into a place, in order to truly convey ‘what it’s like’ to be somewhere. However, existing digital twins of physical spaces often fail to capture the social meaning and behaviors that turn a space into a place. This project aims to address this problem by using spatial capture technology to create a 3D model digital twin of the Santa Clara University campus and using it as a foundation for exploring …

Obujulizi Share - Enabling Voices For Rural Ugandan Communities, Aastha Khare, Sravani Polkampalli

Computer Science and Engineering Senior Theses

Rural communities in Uganda currently lack proper technical infrastructure to effectively communicate their issues and find support within their communities. For our project, we collaborated with Rose Academies, a nonprofit organization that aims to empower and aid impoverished communities in Sub-Saharan Africa. We intend to help them by creating a centralized, secure, and accessible system that allows members of the communities they serve to share their experiences. Our project consisted of three parts: an interview application, where Rose Academies’ creative team can take and record interviews, a content managing application to allow the creative team to select compelling interviews and …

Wyclef: A Rational Reconstruction Of Versu Social Engine, James Dameris, Rosaura Hemandez

Computer Science and Engineering Senior Theses

Video games often lack an accurate representation of the person playing the game, causing a disconnect between the player and the character’s story. With Versu, a proprietary social simulation engine, not only did choices become more connected to the player, but the player could choose to take the place of any of the characters present in the story. This allows the player to find themselves in the story, while also giving vast replayability to the game. Wyclef is an open source, rational reconstruction of Versu providing increased authoring speed of stories and availability of the social engine to more people. …

Developing An Open-Source Tool For Systematic App Reviews For Non-Technical Researchers, Lauren Xie, David Truong, Tino Theodoropoulos, Jason Vu

Computer Science and Engineering Senior Theses

Researchers in many fields, from psychology to privacy studies, want to understand the mobile app ecosystem. The process of reviewing mobile apps is called a ’systematic app review’ (SAR). In a systematic app review, researchers analyze app metadata (e.g., the description, user reviews of the app, the app’s permissions list) and/or the experience of the app itself (e.g., the user interface, the content it contains). Unfortunately, this process does not yet have clearly defined best practices and the process of scraping data from app stores is costly, challenging, and time-consuming for researchers, especially ones without a technical background. Researchers lack …

Insect Classification And Explainability From Image Data Via Deep Learning Techniques, Tanvir Hossain Bhuiyan

USF Tampa Graduate Theses and Dissertations

Since the dawn of the Industrial Revolution, humanity has always tried to make labor more efficient and automated, and this trend is only continuing in the modern digital age. With the advent of artificial intelligence (AI) techniques in the latter part of the 20th century, the speed and scale with which AI has been leveraged to automate tasks defy human imagination. Many people deeply entrenched in the technology field are genuinely intrigued and concerned about how AI may change many of the ways in which humans have been living for millennia. Only time will provide the answers. This dissertation is …

Safehome, Meryem Esa, Siddarth Raj

Interdisciplinary Design Senior Theses

The SafeHome app was developed to address the significant communication challenges in refugee camps, where outdated methods such as flyers and intercoms limit the efficiency and reliability of information dissemination. Through extensive research and user-centric design, we developed a dual-interface application on the Firebase platform, featuring a web-based portal for camp administrators and a mobile application for refugees. The results showed effective functionality and enhanced communication, with refugees now able to receive timely updates, access crucial resources, and store personal documents securely. The successful implementation of SafeHome underscores the potential of leveraging technology to solve real-world challenges and enhance the …

A Hardware Platform For Wireless Beehive Monitoring, Erik Wrysinski, Jonathan Stock, Collin Paiz, Daniel Blanc

Computer Science and Engineering Senior Theses

Traditional beehive monitoring systems suffer from many challenges. These monitoring devices are expensive to set up, difficult to implement, and lack cross compatibility with each other. Preexisting beehive monitoring solutions face all of these shortcomings. Our beehive monitoring platform aims to overcome these issues by using inexpensive, off-theshelf, open-source hardware paired with a computer vision machine learning model to accurately monitor the ingress and egress of bees into and out of the hive. This data is presented to the beekeeper in a simple GUI which allows them to track hive activity over time, and by extension, the overall health of …

A Study Of Processing Beehive Monitoring Data In Edge And Cloud, Yen-Jung Lu, Jason Fong, Cheng Zhang, Chan Nam Tieu

Computer Science and Engineering Senior Theses

Bees are vital pollinators for numerous crops and plants, playing an essential role in maintaining the world’s ecosystem and food security. Without bees, the global food supply would be threatened, potentially leading to food shortages and increased food prices. Current beehive monitoring solutions in the market are often prohibitively expensive, some commercial beehive monitoring solutions can cost upwards of thousands of dollars. This makes them inaccessible to many small-scale beekeepers. To help protect bee health and ensure the survival of thousands of plant species worldwide, this project aims to create an accessible solution for individuals to monitor the health and …

Automated Retail Checkout By Computer Vision: Arc-Ai, Griffin Ellis

Computer Science and Engineering Senior Theses

There is some opportunity to apply AI and computer vision techniques to the problems in the retail industry. This paper presents a possible solution to the problem of accurate automated check-out in a retail store setting, a difficult problem due to the possibility of occlusion of hand-held products by the customer and the possible similarity of different products. This solution will identify objects being purchased frame-by-frame, propose tracks that follow individual objects across multiple frames, then determine when and where the object was brought over the region of interest, which will be determined at the start of the task. At …

Flowview: A Web Application For Hydrologic Predictions, Marcus Chavez, Sean Leininger, Joseph Pham Nguyen

Computer Science and Engineering Senior Theses

The Santa Clara Valley Water District, or Valley Water, provides water management resources to the two million residents in Santa Clara County. A few of their services include supplying safe water, ownership of streams, and flood protection. However, given the evolving conditions of the climate throughout the state of California, Valley Water seeks to include machine learning analytics as part of its water management services. Additionally, the increased access to the Internet has expanded the use of web applications, which provide a flexible platform to integrate the

predictions of machine learning models. In this paper, we design and implement a …

Warn: Wi-Fi Attack Recognizer And Notifier, Sudhish Sewpaul, Roshan Sevalia, Jaden Ngo, Tate Musante

Computer Science and Engineering Senior Theses

The Wi-Fi Attack Recognizer and Notifier (WARN) aims to establish a wireless network monitoring system for detection of attacks on Wi-Fi IoT devices. Millions of homes use smart home devices, and many of these are for security. However, these devices are vulnerable to attacks that can disable them or compromise their data confidentiality. WARN is capable of detecting two of these attacks: deauthentication and key reinstallation (KRACK). Deauthentication attacks hoax devices into disconnecting themselves from a network, and KRACK manipulates the authentication protocol of Wi-Fi devices to see unencrypted data. WARN uses Raspberry Pis equipped with long range Wi-Fi antennas …

Avalanche Predictions Based On Ml, William Olson, Matthew Davenport, Ben Airola

Computer Science and Engineering Senior Theses

Our Avalanche Prediction Model utilizes machine learning to analyze weather and climate data in order to provide users in the Northern California back-country with accurate probabilities of avalanche occurrences. Snow forecasts only provide information relating to how much snow will fall. Current avalanche danger ratings only provide the potential level for injury there is if an avalanche will occur. Our system, Avy Safe ML, let’s users survey geographic terrain and see direct probability indicators for precise geo-locations of mountain faces and ranges. These indicators are represented as variably-shaded geo-polygons that indicate avalanche risk classifications. Our data visualization allows access to …

Twigeenglish, Brian Burnett, Jillian Coveney, Kristin Tong, Nanki Sekhon

Computer Science and Engineering Senior Theses

TwigeEnglish is an educational platform aimed to teach English in a fun and interactive way. It comprises a mobile application for students and a web application for pre-determined administrators. The mobile application offers three key features which include: a pictionary-like game, a dictionary flash card game, and a user-friendly interface for uploading photos to be used in both games. The web application will primarily focus on providing administrators with an interface to manage the student-photo database. With moderation powers, administrators can seamlessly review and make decisions to approve or deny the inclusion of photos in the active pictionary and dictionary …

Round Trip Time Measurement Over Microgrid Power Network, Yasin Emir Kutlu, Ruairí De Fréin, Malabika Basu, Ali Malik

Conference papers

A focus of the Power Systems and Networking communities is the design and deployment of Microgrid (MG) integration systems that ensure that quality of service targets are met for load sharing systems at different endpoints. This paper presents an integrated Microgrid testbed that allows Microgrids endpoints to share their current, voltage and power values using a Network Published Shared Variable (NPSV) approach. We present Round Trip Time (RTT) measurements for time sensitive Microgrid control traffic in the presence of varying background traffic as an example quality of service measurement. Numerical results are presented using a range of different background traffic …

Whether-Weather, Lucas Voron, Graham Purvis, Malcolm Weaver, Josh Kelleran

Computer Science and Engineering Senior Theses

The WhetherWeather project is a comprehensive weather and traffic forecasting system that provides real-time insights and predictions. It utilizes Python programming language and various data sources, including Inrix data for traffic information and weather data from Meteostat. The system employs machine learning techniques, specifically XGBoost, to train models on historical data. Once trained, the models can accurately forecast traffic conditions based on weather data. To visualize the results, a Flask API is available, allowing users to access the system's functionalities through a web interface. For more information and to access the WhetherWeather website, visit WhetherWeather.org.

Singular Value Decomposition And Transformer-Based Image Super Resolution, Andy Qin, Chen Zhang, Timothy Cui

Computer Science and Engineering Senior Theses

Image super-resolution (ISR) is a prominent field in computer vision that aims to enhance the quality and resolution of low-resolution images. It finds widespread applications in various domains, including surveillance, satellite imagery, medical imaging, and media. The primary objective of ISR is to improve the visual quality and level of detail in low-resolution images. In this paper, we propose the Singular Value Decomposition and Transformer-based Image Super Resolution (SVDTIR) model, which combines both traditional and deep learning approaches to achieve image super-resolution. The SVDTIR model consists of three stages: image pre-processing, which employs the singular-value decomposition (SVD) algorithm to decompose …

Climate Cloud, Atiyut Khemkhon, Dylan Lin

Computer Science and Engineering Senior Theses

The increasing frequency and intensity of drastic climate change events have underscored the urgency for a comprehensive understanding of climate dynamics and the development of effective mitigation and adaptation strategies. In this context, our thesis addresses the critical issue of drought category prediction in Western America using machine learning techniques. We recognize the interconnectedness of efforts aimed at combating climate change and strive to make a meaningful contribution to the broader understanding of climate change, even if our impact may seem comparatively smaller. By leveraging the power of machine learning algorithms and utilizing a wide range of climatic and environmental …

Underwater Robot Path Planning In An Intermittent Communication System, Hunter Gallant

Dartmouth College Master’s Theses

Sunflower, a novel cross-medium localization system between an aerial drone and an underwater robot, has not yet been implemented in a multi-robot exploration system. This project’s aim was to simulate various configurations of multi-robot systems, and to create an algorithm, called AdjustPath, to improve exploration and avoid inter- robot collisions. With three, five, seven, and ten simulated underwater robots, there was significant improvement when the AdjustPath algorithm was used. Knowing this, future hardware using the Sunflower system could use this proposed algorithm to increase efficiency and avoid more collisions.

Ai-Powered Iot Monitoring And Security For Smart Homes, Paul Boldyrev, Timothy Hradil, Matthew Ding

Computer Science and Engineering Senior Theses

Smart home devices are becoming increasingly popular across the United States. Unfortunately, in order to keep the cost of these devices down, manufacturers tend to place cybersecurity measures lower on their list of priorities. As a result, these devices have become targets for security breaches like the Mirai Botnet and distributed denial of service (DDoS) attacks. The cybersecurity solutions currently available on the market are either expensive, difficult to set up, or follow a static set of rules for attack detection. In this thesis, we propose a novel approach to detecting attacks on Internet of Things (IoT) devices through the …

Cometrics: A New Software Tool For Behavior‑Analytic Clinicians And Machine Learning Researchers, Walker S. Arce, Seth G. Walker, Morgan L. Hurtz

Department of Electrical and Computer Engineering: Faculty Publications

Cometrics is a Microsoft Windows compatible clinical tool for the collection and recording of frequency- and duration-based target behaviors, physiological signals, and video data. This software package is designed to record in-vivo observational and physiological data. In addition, we have included features that allow observers to capture video from real-time camera feeds and import saved video for retroactive data collection. By using Microsoft Excel-based spreadsheets, also called keystroke files, assessment and treatment sessions are exported into a single document using the click of a button. Integrated interobserver agreement metrics allow comparisons across primary and reliability observers, with the output exported …

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 …

Poly-Gan: Regularizing Polygons With Generative Adversarial Networks, Lasith Niroshan, James Carswell

Conference Papers

Regularizing polygons involves simplifying irregular and noisy shapes of built environment objects (e.g. buildings) to ensure that they are accurately represented using a minimum number of vertices. It is a vital processing step when creating/transmitting online digital maps so that they occupy minimal storage space and bandwidth. This paper presents a data-driven and Deep Learning (DL) based approach for regularizing OpenStreetMap building polygon edges. The study introduces a building footprint regularization technique (Poly-GAN) that utilises a Generative Adversarial Network model trained on irregular building footprints and OSM vector data. The proposed method is particularly relevant for map features …