One-To-Cloud One-Time Pad Data Encryption: Introducing Virtual Prototyping With Pspice,
2017
Technological University Dublin
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
Conference papers
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 …
Multiple-Phase Modeling Of Degradation Signal For Condition Monitoring And Remaining Useful Life Prediction,
2017
Chapman University
Multiple-Phase Modeling Of Degradation Signal For Condition Monitoring And Remaining Useful Life Prediction, Yuxin Wen, Jianguo Wu, Yuan Yuan
Engineering Faculty Articles and Research
Remaining useful life prediction plays an important role in ensuring the safety, availability, and efficiency of various engineering systems. In this paper, we propose a flexible Bayesian multiple-phase modeling approach to characterize degradation signals for prognosis. The priors are specified with a novel stochastic process and the multiple-phase model is formulated to a novel state-space model to facilitate online monitoring and prediction. A particle filtering algorithm with stratified sampling and partial Gibbs resample-move strategy is developed for online model updating and residual life prediction. The advantages of the proposed method are demonstrated through extensive numerical studies and real case studies.
A Survey Of Addictive Software Design,
2017
California Polytechnic State University at San Luis Obispo
A Survey Of Addictive Software Design, Chauncey J. Neyman
Computer Science and Software Engineering
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 …
Djukebox: A Mobile Application Senior Project,
2017
California Polytechnic State University, San Luis Obispo
Djukebox: A Mobile Application Senior Project, Alexander M. Mitchell
Computer Science and Software Engineering
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 purely …
Slither.Io Deep Learning Bot,
2017
California Polytechnic State University, San Luis Obispo
Slither.Io Deep Learning Bot, James Caudill
Computer Engineering
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.
Diy Grip Tape Website,
2017
California Polytechnic State University, San Luis Obispo
Diy Grip Tape Website, Jason E. Krein
Computer Science and Software Engineering
The goal of this senior project was to create an easy to use website that will allow people to design and order their own custom skateboard grip tape. Custom skateboard decks are a large business, however the top, more visible, part of the board is largely ignored by custom shops. With the help of a local entrepreneur, I aim to enable skateboarders the ability to get custom grip tape shapes that they can stick on their board to spice it up from the normal black tape that everyone uses. The website was completed over the course of 4 months, in …
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
Computer Science and Software Engineering
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.
Underwater Computer Vision - Fish Recognition,
2017
California Polytechnic State University, San Luis Obispo
Underwater Computer Vision - Fish Recognition, Spencer Chang, Austin Otto
Computer Engineering
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
Computer Engineering
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 …
Sublimesurf,
2017
California Polytechnic State University, San Luis Obispo
Sublimesurf, Nathan Sfard, Karis Russell
Computer Engineering
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 …
Design And Implementation Of An Archetype Based Interoperable Knowledge Eco-System For Data Buoys,
2017
Institute of Technology, Blanchardstown
Design And Implementation Of An Archetype Based Interoperable Knowledge Eco-System For Data Buoys, Paul Stacey, Damon Berry
Conference papers
This paper describes the ongoing work of the authors in translating two-level system design techniques used in Health Informatics to the Earth Systems Science domain. Health informaticians have developed a sophisticated two-level systems design approach for electronic health documentation over many years, and with the use of archetypes, have shown how knowledge interoperability among heterogeneous systems can be achieved. Translating two-level modelling techniques to a new domain is a complex task. A proof-of-concept archetype enabled data buoy eco-system is presented. The concept of operational templates-as-a service is proposed. Design recommendations and implementation experiences of re-working the proposed architecture to run …
Farmbot Rfid Integration,
2017
California Polytechnic State University, San Luis Obispo
Farmbot Rfid Integration, Laura R. Swart
Computer Engineering
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.
Daily Dose,
2017
California Polytechnic State University, San Luis Obispo
Daily Dose, Ken H. Yasui, Joey M. Angeja
Computer Engineering
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 …
Micro-Spi Sediment Profile Imaging Micro-Inspector,
2017
California Polytechnic State University, San Luis Obispo
Micro-Spi Sediment Profile Imaging Micro-Inspector, Andrew P. Corvin, Caleb T. Davies, Matt R. Ferrari
Mechanical Engineering
This project was proposed by Dr. Brian Paavo through a desire to more easily study the benthic sediment layers of the ocean. To do so, he asked us to build a simple and compact machine for use in sediment profile imagery (SPI). Although devices like this already exist, they are all large scale devices that require a ship with a crane to deploy, which is expensive and time consuming. Instead, he desired a “micro” SPI, which is capable of being deployed from a small vessel that can easily navigate shallow waters. Our interpretation of these requirements was as follows: a …
Cpu Db Data Visualization,
2017
California Polytechnic State University, San Luis Obispo
Cpu Db Data Visualization, Ruchita Patel, Marek Moreno
Computer Engineering
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.
Improving A Particle Swarm Optimization-Based Clustering Method,
2017
University of New Orleans
Improving A Particle Swarm Optimization-Based Clustering Method, Sharif Shahadat
LSU New Orleans Theses and Dissertations
This thesis discusses clustering related works with emphasis on Particle Swarm Optimization (PSO) principles. Specifically, we review in detail the PSO clustering algorithm proposed by Van Der Merwe & Engelbrecht, the particle swarm clustering (PSC) algorithm proposed by Cohen & de Castro, Szabo’s modified PSC (mPSC), and Georgieva & Engelbrecht’s Cooperative-Multi-Population PSO (CMPSO). In this thesis, an improvement over Van Der Merwe & Engelbrecht’s PSO clustering has been proposed and tested for standard datasets. The improvements observed in those experiments vary from slight to moderate, both in terms of minimizing the cost function, and in terms of run time.
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
MODVIS Workshop
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 …
Source Anonymization Of Digital Images: A Counter–Forensic Attack On Prnu Based Source Identification Techniques,
2017
National Institute of Technology, Rourkela
Source Anonymization Of Digital Images: A Counter–Forensic Attack On Prnu Based Source Identification Techniques, Prithviraj Sengupta, Venkata Udaya Sameer, Ruchira Naskar, Ezhil Kalaimannan
Annual ADFSL Conference on Digital Forensics, Security and Law
A lot of photographers and human rights advocates need to hide their identity while sharing their images on the internet. Hence, source–anonymization of digital images has become a critical issue in the present digital age. The current literature contains a number of digital forensic techniques for “source–identification” of digital images, one of the most efficient of them being Photo–Response Non–Uniformity (PRNU) sensor noise pattern based source detection. PRNU noise pattern being unique to every digital camera, such techniques prove to be highly robust way of source–identification. In this paper, we propose a counter–forensic technique to mislead this PRNU sensor noise …
An Accidental Discovery Of Iot Botnets And A Method For Investigating Them With A Custom Lua Dissector,
2017
University of Alabama, Birmingham
An Accidental Discovery Of Iot Botnets And A Method For Investigating Them With A Custom Lua Dissector, Max Gannon, Gary Warner, Arsh Arora
Annual ADFSL Conference on Digital Forensics, Security and Law
This paper presents a case study that occurred while observing peer-to-peer network communications on a botnet monitoring station and shares how tools were developed to discover what ultimately was identified as Mirai and many related IoT DDOS Botnets. The paper explains how researchers developed a customized protocol dissector in Wireshark using the Lua coding language, and how this enabled them to quickly identify new DDOS variants over a five month period of study.
Classification Of Images Based On Pixels That Represent A Small Part Of The Scene. A Case Applied To Microaneurysms In Fundus Retina Images,
2017
Kennesaw State University
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 …
