Computer Engineering Commons^™

Predictive Analysis Of Ethanol Prices With Machine Learning, Benjamin Schilling

Student Academic Conference

Overview of a predictive analysis regression developed using machine learning alongside ETL process techniques.

Estimating The Tempo Of Audio Files, Parker Ostertag

Student Academic Conference

On the market today, there exists a multitude of software that allows for the detection and prediction of beats per minute (BPM) contained in audio files. There are both free and monetized versions of these programs, but there is one thing that they all have in common: they are inaccurate. This is simply because the science behind beat detection is unfinished, and may never be. In this project, I decided to use a method of audio peak detection to help me detect the tempo that may exist in any audio file. I started by researching existing programs and the science …

Analysis And Design Of A Soft Switching Z-Source Boost Dc-Dc Converter, Mahdi Rezvanyvardom, Amin Mirzaei

Emirates Journal for Engineering Research

This paper proposes a high step-up fully soft switched Z-source Boost DC-DC converter, which uses two resonant paths to create soft switching conditions for switches and diodes and also increases the voltage gain. The proposed converter only has one switch, so it has a simple structure. Furthermore, its control circuit remains pulse width modulation. Since soft switching conditions are provided for all switching elements, the converter efficiency is very high. This converter also has all advantages of Z-source converters. The converter is analyzed and simulated in PSPICE software. The results confirm the aforementioned advantages and features of the proposed converter

Less-Java, More Type Safety: Type Inference And Static Analysis In Less-Java, Charles D. Hines

Senior Honors Projects, 2020-current

Less-Java is an object-oriented programming language whose primary goal is to help new programmers learn programming. Some of the features of Less-Java that might make it better for beginners are static typing, implicit typing, low verbosity, and built-in support for unit testing. The primary focus of this project is on improving type inference (especially with regards to object-oriented programming) and adding static analysis in the Less-Java compiler.

Methods To Detect Forgeries In Static Signatures, Jennifer Lauriello

Honors Theses

Statistical and machine learning approaches to forgery detection in offline sig- natures are attempted and evaluated. Offline signatures are static signatures found on physical media, mainly a piece of paper. A dataset of 330 signatures for 33 people is used, containing five genuine and five forged signatures for each person. The statistical analysis approach proves more successful than a machine learning approach, likely due to the size of the dataset.

Implementation Of A Computer-Vision System As A Supportive Diagnostic Tool For Parkinson’S Disease, Diego Machado Reyes

Honors Theses

Parkinson’s disease is the second most common neurodegenerative disorder, affecting nearly 1 million people in the US and it is predicted that the number will keep increasing. Parkinson’s disease is difficult to diagnose due to its similarity with other diseases that share the parkinsonian symptoms and the subjectivity of its assessment, thus increasing the probabilities of misdiagnosis. Therefore, it is relevant to develop diagnostic tools that are quantitatively based and monitoring tools to improve the patient’s quality of life. Computer-based assessment systems have shown to be successful in this field through diverse approaches that can be classified into two main …

Empirical Evaluation Of Vehicle Detection, Tracking And Recognition Algorithms Operating On Real Time Video Feeds, Yunik Tamrakar

Honors Theses

A traffic surveillance camera system is an important part of an intelligent transportation system.(Zhang et al., 2013) This system is capable of performing useful object detections on the incoming feed. These detected objects can then be used for tracking purposes which forms the basis for monitoring important traffic data such as collisions, vehicle count, pedestrian count and so on. Furthermore, other additional information such as the weather conditions, time of day as well as date can also be extracted from a live feed. (Sun et al., 2004) Different algorithms can yield different results for any given video input. Not only …

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 …

Artificial Stupidity: Data We Need To Make Machines Our Equals, Michaël Trazzi, Roman V. Yampolskiy

Faculty and Staff Scholarship

AI must understand human limitations to provide good service and safe interactions. Standardized data on human limits would be valuable in many domains but is not available. The data science community has to work on collecting and aggregating such data in a common and widely available format, so that any AI researcher can easily look up the applicable limit measurements for their latest project. AI must understand human limitations to provide good service and safe interactions. Standardized data on human limits would be valuable in many domains but is not available. Data science community has to work on collecting and …

Elicitation And Aggregation Of Data In Knowledge Intensive Crowdsourcing, Dohoon Kim

All Computer Science and Engineering Research

With the significant advance of internet and connectivity, crowdsourcing gained more popularity and various crowdsourcing platforms emerged. This project focuses on knowledge-intensive crowdsourcing, in which agents are presented with the tasks that require certain knowledge in domain. Knowledge-intensive crowdsourcing requires agents to have experiences on the specific domain. With the constraint of resources and its trait as sourcing from crowd, platform is likely to draw agents with different levels of expertise and knowledge and asking same task can result in bad performance. Some agents can give better information when they are asked with more general question or more knowledge-specific task …

Zenneck Waves In Decision Agriculture: An Empirical Verification And Application In Em-Based Underground Wireless Power Transfer, Usman Raza, Abdul Salam

Computer Information Technology Faculty Publications

In this article, the results of experiments for the observation of Zenneck surface waves in sub GHz frequency range using dipole antennas are presented. Experiments are conducted over three different soils for communications distances of up to 1 m. This empirical analysis confirms the existence of Zenneck waves over the soil surface. Through the power delay profile (PDP) analysis, it has been shown that other subsurface components exhibit rapid decay as compared to the Zenneck waves. A potential application of the Zenneck waves for energy transmission in the area of decision agriculture is explored. Accordingly, a novel wireless through-the-soil power …

Campuspartner: An Assistive Technology For Pedestrians With Mobility Impairments, Cynthia R. Zastudil

Senior Honors Projects, 2020-current

Route-planning applications such as Google Maps and Apple Maps are used by millions of people each month. However, these mapping applications are optimized for vehicle navigation, and although they provide pedestrian routing, the route customization options aren’t sufficient for pedestrian users, especially those with mobility impairments. CampusPartner is an assistive mobile application that was designed with the purpose of supporting people with mobility impairments in planning and previewing their walking routes. By viewing routes in advance, users can see an overview and detailed information about them as well as turn-by-turn instructions. CampusPartner integrates existing services, GraphHopper, OpenStreetMap, and Mapbox, to …

A Virtual 4d Ct Scanner, Xiwen Li

All Computer Science and Engineering Research

4D CT scan is widely used in medical imaging. Images are acquired through phases. In this case, we can track the motion of organs such as heart. However, it also introduces motion artifacts. A lot of research focuses on remove these artifacts. It is difficult to acquire artifact data by a real CT scanner. In this project, we implement a virtual CT machine to simulate the real 4D CT scan. we also conduct experi- ments to check its clinical reality with respect to respiratory and heart motion parameters.

Centrality Of Blockchain, Zixuan Li

All Computer Science and Engineering Research

Decentralization is widely recognized as the property and one of most important advantage of blockchain over legacy systems. However, decentralization is often discussed on the consensus layer and recent research shows the trend of centralization on several subsystem of blockchain. In this project, we measured centralization of Bitcoin and Ethereum on source code, development eco-system, and network node levels. We found that the programming language of project is highly centralized, code clone is very common inside Bitcoin and Ethereum community, and developer contribution distribution is highly centralized. We further discuss how could these centralizations lead to security issues in blockchain. …

Solving Disappearance At Gastech With Visual Analytic Techniques, Saulet Yskak

All Computer Science and Engineering Research

We are living in a society, where images and charts speak louder than words. Therefore, information visualization plays a major role in solving complex problems since it provides a visual summary of data that makes it easier to identify trends and patterns.

In this master project, I propose a web – based visual analytics tool that enables to analyze complex email and time based / event series data. The visual analytics framework uses test data from IEEE VAST Challenge 2014: Mini challenge 1 that concentrated on the disappearance of employees of a fictional GAStech company, but the tool allows users …

Small Mode Volume Plasmonic Film-Coupled Nanostar Resonators, Negar Charchi, Ying Li, Margaret Huber, Elyahb Allie Kwizera, Xiaohua Huang, Christos Argyropoulos, Thang Hoang

Department of Electrical and Computer Engineering: Faculty Publications

Confining and controlling light in extreme subwavelength scales are tantalizing tasks. In this work, we report a study of individual plasmonic film-coupled nanostar resonators where polarized plasmonic optical modes are trapped in ultrasmall volumes. Individual gold nanostars, separated from a flat gold film by a thin dielectric spacer layer, exhibit a strong light confinement between the sub-10 nm volume of the nanostar's tips and the film. Through dark field scattering measurements of many individual nanostars, a statistical observation of the scattered spectra is obtained and compared with extensive simulation data to reveal the origins of the resonant peaks. We observe …

Understanding Eye Gaze Patterns In Code Comprehension, Jonathan Saddler

School of Computing: Dissertations, Theses, and Student Research

Program comprehension is a sub-field of software engineering that seeks to understand how developers understand programs. Comprehension acts as a starting point for many software engineering tasks such as bug fixing, refactoring, and feature creation. The dissertation presents a series of empirical studies to understand how developers comprehend software in realistic settings. The unique aspect of this work is the use of eye tracking equipment to gather fine-grained detailed information of what developers look at in software artifacts while they perform realistic tasks in an environment familiar to them, namely a context including both the Integrated Development Environment (Eclipse or …

Using Taint Analysis And Reinforcement Learning (Tarl) To Repair Autonomous Robot Software, Damian Lyons, Saba Zahra

Faculty Publications

It is important to be able to establish formal performance bounds for autonomous systems. However, formal verification techniques require a model of the environment in which the system operates; a challenge for autonomous systems, especially those expected to operate over longer timescales. This paper describes work in progress to automate the monitor and repair of ROS-based autonomous robot software written for an a-priori partially known and possibly incorrect environment model. A taint analysis method is used to automatically extract the data-flow sequence from input topic to publish topic, and instrument that code. A unique reinforcement learning approximation of MDP utility …

Ahead: Automatic Holistic Energy-Aware Design Methodology For Mlp Neural Network Hardware Generation In Proactive Bmi Edge Devices, Nan-Sheng Huang, Yi-Chung Chen, Jørgen Christian Larsen, Poramate Manoonpong

Electrical and Computer Engineering Faculty Research

The prediction of a high-level cognitive function based on a proactive brain–machine interface (BMI) control edge device is an emerging technology for improving the quality of life for disabled people. However, maintaining the stability of multiunit neural recordings is made difficult by the nonstationary nature of neurons and can affect the overall performance of proactive BMI control. Thus, it requires regular recalibration to retrain a neural network decoder for proactive control. However, retraining may lead to changes in the network parameters, such as the network topology. In terms of the hardware implementation of the neural decoder for real-time and low-power …

A Capacitive Sensing Gym Mat For Exercise Classification & Tracking, Adam Goertz

Computer Science and Computer Engineering Undergraduate Honors Theses

Effective monitoring of adherence to at-home exercise programs as prescribed by physiotherapy protocols is essential to promoting effective rehabilitation and therapeutic interventions. Currently physical therapists and other health professionals have no reliable means of tracking patients' progress in or adherence to a prescribed regimen. This project aims to develop a low-cost, privacy-conserving means of monitoring at-home exercise activity using a gym mat equipped with an array of capacitive sensors. The ability of the mat to classify different types of exercises was evaluated using several machine learning models trained on an existing dataset of physiotherapy exercises.