Large-Scale Flexible Membrane For Automatic Strain Monitoring Of Transportation Infrastructure, 2017 Iowa State University
Large-Scale Flexible Membrane For Automatic Strain Monitoring Of Transportation Infrastructure, Simon Laflamme, Venkata D. Kolipara, Hussam S. Saleem, Randall L. Geiger
Structural Health Monitoring (SHM) of transportation infrastructures is a complex task, typically conducted by visual inspection due to the technical and economical constrains of existing health monitoring technologies. It results that health monitoring is highly dependent on scheduling and on the judgment of the inspectors, which can be costly and ineffective. Thus, it is fundamental to automate the SHM process to allow timely inspection, maintenance, and management of transportation infrastructure. The authors propose a flexible membrane that can be deployed over large surfaces, at low cost, for automatic and continuous monitoring of strains. The membrane, termed sensing skin, is constituted ...
One-To-Cloud One-Time Pad Data Encryption: Introducing Virtual Prototyping With Pspice, 2017 Dublin Institute of Technology
One-To-Cloud One-Time Pad Data Encryption: Introducing Virtual Prototyping With Pspice, Paul Tobin, Lee Tobin, Roberto Gandia Blanquer Dr, Michael Mckeever, Jonathan Blackledge Professor
In this paper, we examine the design and application of a one-time pad encryption system for protecting data stored in the Cloud. Personalising security using a one-time pad generator at the client-end protects data from break-ins, side-channel attacks and backdoors in public encryption algorithms. The one-time pad binary sequences were obtained from modified analogue chaos oscillators initiated by noise and encoded client data locally. Specific ``one-to-Cloud'' storage applications returned control back to the end user but without the key distribution problem normally associated with one-time pad encryption. Development of the prototype was aided by ``Virtual Prototyping'' in the latest version ...
The Engineering Admissions Partnership Program: A Navigation Strategy For Community College Students Seeking A Pathway Into Engineering, Marcia R. Laugerman, Mack C. Shelley, Steven K. Mickelson, Diane T. Rover
This paper presents the evaluation of a program designed to improve transfer outcomes for community college students pursuing an engineering degree. The program, the Engineering Admissions Partnership Program (E-APP), was designed to improve the navigational success of community college transfer students through connections to the university. These connections include coordinated academic advising, peer-mentoring, campus visits, and online social and professional networks. The objective of the study is to determine the efficacy of the E-APP and its interventions, which will be measured by increased participation rates and increased university retention rates for E-APP participants. Outcome data for the students are analyzed ...
Slither.Io Deep Learning Bot, 2017 California Polytechnic State University, San Luis Obispo
Slither.Io Deep Learning Bot, James Caudill
Recent advances in deep learning and computer vision techniques and algorithms have inspired me to create a model application. The game environment used is Slither.io. The system has no previous understanding of the game and is able to learn its surroundings through feature detection and deep learning. Contrary to other agents, my bot is able to dynamically learn and react to its environment. It operates extremely well in early game, with little enemy encounters. It has difficulty transitioning to middle and late game due to limited training time. I will continue to develop this algorithm.
Daily Dose, 2017 California Polytechnic State University, San Luis Obispo
Daily Dose, Ken H. Yasui, Joey M. Angeja
The project goal is to develop a medication and vitamin management device that will sort and dispense pre-configured amounts of pills at designated times . The main clientele of this device is the elderly community with a secondary client base of the general public. The entire system is designed from scratch, powered by US standard line voltage. The main functionalities of the device are the ability to store multiple types of pills and the ability to accurately handle user input and data transfer. The two engineering specifications that were not met included the desired pill pick up rate and dimensions of ...
Sublimesurf, 2017 California Polytechnic State University, San Luis Obispo
Sublimesurf, Nathan Sfard, Karis Russell
Surf conditions change rapidly day to day and location to location, which forces modern day surfers to utilize online forecasts and obtain a detailed knowledge of the places they want to surf. To ease this pain, we are developing SublimeSurf, an iOS application that will keep track of the current surf conditions and allow users to rate aspects of the surf. We plan to use this rating data in combination with surf forecast data available online to notify a user when conditions look favorable, based on their previous ratings. We also intend to mine the data submitted by all users ...
Farmbot Rfid Integration, 2017 California Polytechnic State University, San Luis Obispo
Farmbot Rfid Integration, Laura R. Swart
The purpose of this project is to assist the company FarmBot improve their product by adding RFID tracking to the FarmBot robot. RFID tracking will allow the robot to select and pick up tool heads without any user interference.
Underwater Computer Vision - Fish Recognition, 2017 California Polytechnic State University, San Luis Obispo
Underwater Computer Vision - Fish Recognition, Spencer Chang, Austin Otto
The Underwater Computer Vision – Fish Recognition project includes the design and implementation of a device that can withstand staying underwater for a duration of time, take pictures of underwater creatures, such as fish, and be able to identify certain fish. The system is meant to be cheap to create, yet still able to process the images it takes and identify the objects in the pictures with some accuracy. The device can output its results to another device or an end user.
Multispectral Identification Array, 2017 California Polytechnic State University, San Luis Obispo
Multispectral Identification Array, Zachary D. Eagan
The Multispectral Identification Array is a device for taking full image spectroscopy data via the illumination of a subject with sixty-four unique spectra. The array combines images under the illumination spectra to produce an approximate reflectance graph for every pixel in a scene. Acquisition of an entire spectrum allows the array to differentiate objects based on surface material. Spectral graphs produced are highly approximate and should not be used to determine material properties, however the output is sufficiently consistent to allow differentiation and identification of previously sampled subjects. While not sufficiently advanced for use as a replacement to spectroscopy the ...
Cpu Db Data Visualization, 2017 California Polytechnic State University, San Luis Obispo
Cpu Db Data Visualization, Ruchita Patel, Marek Moreno
Given the CPU database from Stanford, we wanted to create something that portrayed the data in a more visually pleasing way. The CPU database website wanted a web page that would allow users to create graphs based on the processor data from the database. The web page would allow users to select different data from the database and create the graphs they wanted to gain insight into the decades of processor data.
A Survey Of Addictive Software Design, 2017 California Polytechnic State University at San Luis Obispo
A Survey Of Addictive Software Design, Chauncey J. Neyman
The average smartphone owner checks their phone more than 150 times per day. As of 2015, 62% of smartphone users had used their phone to look up information about a health condition, while 57% had used their phone to do online banking. Mobile platforms have become the dominant medium of human-computer interaction. So how have these devices established themselves as our go to connection to the Internet? The answer lies in addictive design. Software designers have become well versed in creating software that captivates us at a primal level. In this article, we survey addictive software design strategies, their bases ...
Gridiron-Gurus Final Report: Fantasy Football Performance Prediction, 2017 California Polytechnic State University, San Luis Obispo
Gridiron-Gurus Final Report: Fantasy Football Performance Prediction, Kyle Tanemura, Michael Li, Erica Dorn, Ryan Mckinney
Gridiron Gurus is a desktop application that allows for the creation of custom AI profiles to help advise and compete against in a Fantasy Football setting. Our AI are capable of performing statistical prediction of players on both a season long and week to week basis giving them the ability to both draft and manage a fantasy football team throughout a season.
Djukebox: A Mobile Application Senior Project, 2017 California Polytechnic State University, San Luis Obispo
Djukebox: A Mobile Application Senior Project, Alexander M. Mitchell
I’m going to discuss the process used to research, design, and develop a mobile application to handle song requests from patrons to disc jockeys. The research phase was completed in the first half of the project, during CSC-491, along with much of the design. The rest of the design and all of the development was completed during CSC-492. Once development began there were times when reverting back to the design phase was needed, which became apparent as more was learned about the mobile platform chosen for development, Android, and the backend server utilized, Google Firebase. Ultimately the project was ...
Real Time Learning Level Assessment Using Eye Tracking, 2017 Florida Atlantic University
Real Time Learning Level Assessment Using Eye Tracking, Saurin S. Parikh, Hari Kalva
E-Learning is emerging as a convenient and effective learning tool. However, the challenge with eLearning is the lack of effective tools to assess levels of learning. Ability to predict difficult content in real time enables eLearning systems to dynamically provide supplementary content to meet learners’ needs. Recent developments have made possible low-cost eye trackers, which enables a new class of applications based on eye response. In comparison to past attempts using bio-metrics in learning assessments, with eye tracking, we can have access to the exact stimulus that is causing the response. A key aspect of the proposed approach is the ...
Classification Of Images Based On Pixels That Represent A Small Part Of The Scene. A Case Applied To Microaneurysms In Fundus Retina Images, Pablo F. Ordonez, Pablo F. Ordonez
Master of Science in Computer Science Theses
Convolutional Neural Networks (CNNs), the state of the art in image classification, have proven to be as effective as an ophthalmologist, when detecting Referable Diabetic Retinopathy (RDR). Having a size of less than 1\% of the total image, microaneurysms are early lesions in DR that are difficult to classify. The purpose of this thesis is to improve the accuracy of detection of microaneurysms using a model that includes two CNNs with different input image sizes, 60x60 and 420x420 pixels. These models were trained using the Kaggle and Messidor datasets and tested independently against the Kaggle dataset, showing a sensitivity of ...
Hospital Readmission And Social Risk Factors Identified From Physician Notes, 2017 University of Pennsylvania
Hospital Readmission And Social Risk Factors Identified From Physician Notes, Amol Navathe, Feiran Zhong, Victor J. Lei, Frank Y. Chang, Margarita Sordo, Maxim Topaz, Shamkant B. Navathe, Roberto A. Rocha, Li Zhou
No abstract provided.
A Study Of Activation Functions For Neural Networks, 2017 University of Arkansas, Fayetteville
A Study Of Activation Functions For Neural Networks, Meenakshi Manavazhahan
Computer Science and Computer Engineering Undergraduate Honors Theses
Artificial neural networks are function-approximating models that can improve themselves with experience. In order to work effectively, they rely on a nonlinearity, or activation function, to transform the values between each layer. One question that remains unanswered is, “Which non-linearity is optimal for learning with a particular dataset?” This thesis seeks to answer this question with the MNIST dataset, a popular dataset of handwritten digits, and vowel dataset, a dataset of vowel sounds. In order to answer this question effectively, it must simultaneously determine near-optimal values for several other meta-parameters, including the network topology, the optimization algorithm, and the number ...
Uncovering Exceptional Predictions Using Exploratory Analysis Of Second Stage Machine Learning., 2017 University of Louisville
Uncovering Exceptional Predictions Using Exploratory Analysis Of Second Stage Machine Learning., Aneseh Alvanpour
Electronic Theses and Dissertations
Nowadays, algorithmic systems for making decisions are widely used to facilitate decisions in a variety of fields such as medicine, banking, applying for universities or network security. However, many machine learning algorithms are well-known for their complex mathematical internal workings which turn them into black boxes and makes their decision-making process usually difficult to understand even for experts. In this thesis, we try to develop a methodology to explain why a certain exceptional machine learned decision was made incorrectly by using the interpretability of the decision tree classifier. Our approach can provide insights about potential flaws in feature definition or ...
Feature Selection And Improving Classification Performance For Malware Detection, 2017 Kennesaw State University
Feature Selection And Improving Classification Performance For Malware Detection, Carlos A. Cepeda Mora
Master of Science in Computer Science Theses
The ubiquitous advance of technology has been conducive to the proliferation of cyber threats, resulting in attacks that have grown exponentially. Consequently, researchers have developed models based on machine learning algorithms for detecting malware. However, these methods require significant amount of extracted features for correct malware classification, making that feature extraction, training, and testing take significant time; even more, it has been unexplored which are the most important features for accomplish the correct classification.
In this Thesis, it is created and analyzed a dataset of malware and clean files (goodware) from the static and dynamic features provided by the online ...
An Inductive Ethnographic Study In Elderly Woman Technology Adoption And The Role Of Her Children, 2017 Portland State University
An Inductive Ethnographic Study In Elderly Woman Technology Adoption And The Role Of Her Children, Noshad Rahimi, Antonie J, Jetter, Charles M. Weber
Antonie J. Jetter
Elderly woman strives to have a streamlined life surrounded by ease and familiarity. As she is aging, her desire for simplicity grows, her self-efficacy weakens, her prudency intensifies and her overall inclination toward status quo strengthens. As a result, she delays, or refuses, making any decision that might bring complexity and disrupt the continuity in her life, particularly new and unfamiliar technologies (which often bring complexity, before providing ease). Consequently, her technology adoption has a much lower rate than that of other demographics. To open the black box of elderly woman technology adoption process, this study focuses on the role ...