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#49 - Creaton And Analysis Of 3-Dimensional Thermal Models, Bradley Andrew, Ryan S. Elliott 2019 University of North Georgia

#49 - Creaton And Analysis Of 3-Dimensional Thermal Models, Bradley Andrew, Ryan S. Elliott

Georgia Undergraduate Research Conference (GURC)

According to the European Commissions, the largest potential saving of energy lies within commercial and residential buildings. A considerable amount of energy loss from buildings is due to heat or infrared radiation. For this reason, we have been collecting infrared data and creating 3-dimensional models of various structures located on the University of North Georgia Dahlonega campus. Images and data were obtained using a drone and a FLIR Pro infrared camera. Using a specialized software, we were able to analyze infrared images. Through the combined use of Agisoft Metashape and many high-resolution infrared images, a 3D model with thermal data ...


Simphysics, Taylor Woods, Maidel Fletes, Mary Elizabeth Harrell, Paul Halford 2019 Columbus State University

Simphysics, Taylor Woods, Maidel Fletes, Mary Elizabeth Harrell, Paul Halford

Georgia Undergraduate Research Conference (GURC)

Understanding and interpreting relationships and functional trends with 2-D graphs are foundational skills in STEM fields, in other sciences and in all disciplines that utilize data analysis. Introductory physics courses regularly start with the topic of kinematics which heavily utilizes 2-D graphs that describe motion. This is why difficulties that students face in understanding 2-D graphs surface early on in physics. Yet, for this same reason kinematics can be used as a great opportunity to teach graphing skills in general. The primary goal of this project is to develop an interactive intelligent tutoring system (PhysicsSim) that makes use of kinematics ...


Cyber Metaphors And Cyber Goals: Lessons From “Flatland”, Pierre Trepagnier 2019 Cyber Systems and Operations MIT Lincoln Laboratory Lexington, Massachusetts 02420

Cyber Metaphors And Cyber Goals: Lessons From “Flatland”, Pierre Trepagnier

Military Cyber Affairs

Reasoning about complex and abstract ideas is greatly influenced by the choice of metaphors through which they are represented. In this paper we consider the framing effect in military doctrine of considering cyberspace as a domain of action, parallel to the traditional domains of land, sea, air, and space. By means of the well-known Victorian science-fiction novella Flatland, we offer a critique of this dominant cyber metaphor. In Flatland, the problems of lower-dimensional beings comprehending additional dimensions are explored at some length. Inspired by Flatland, our suggested alternate metaphor for cyber is an additional (fourth) dimension. We then propose three ...


Combining Virtual Reality And Machine Learning For Enhancing The Resiliency Of Transportation Infrastructure In Extreme Events, Supratik Mukhopadhyay, Yimin Zhu, Ravindra Gudishala 2019 Louisiana State University

Combining Virtual Reality And Machine Learning For Enhancing The Resiliency Of Transportation Infrastructure In Extreme Events, Supratik Mukhopadhyay, Yimin Zhu, Ravindra Gudishala

Data

Corresponding data set for Tran-SET Project No. 18ITSLSU09. Abstract of the final report is stated below for reference:

"Traffic management models that include route choice form the basis of traffic management systems. High-fidelity models that are based on rapidly evolving contextual conditions can have significant impact on smart and energy efficient transportation. Existing traffic/route choice models are generic and are calibrated on static contextual conditions. These models do not consider dynamic contextual conditions such as the location, failure of certain portions of the road network, the social network structure of population inhabiting the region, route choices made by other ...


Combining Virtual Reality And Machine Learning For Enhancing The Resiliency Of Transportation Infrastructure In Extreme Events, Supratik Mukhopadhyay, Yimin Zhu, Ravindra Gudishala 2019 Louisiana State University

Combining Virtual Reality And Machine Learning For Enhancing The Resiliency Of Transportation Infrastructure In Extreme Events, Supratik Mukhopadhyay, Yimin Zhu, Ravindra Gudishala

Publications

Traffic management models that include route choice form the basis of traffic management systems. High-fidelity models that are based on rapidly evolving contextual conditions can have significant impact on smart and energy efficient transportation. Existing traffic/route choice models are generic and are calibrated on static contextual conditions. These models do not consider dynamic contextual conditions such as the location, failure of certain portions of the road network, the social network structure of population inhabiting the region, route choices made by other drivers, extreme conditions, etc. As a result, the model’s predictions are made at an aggregate level and ...


Aws Ec2 Instance Spot Price Forecasting Using Lstm Networks, Jeffrey Lancon, Yejur Kunwar, David Stroud, Monnie McGee, Robert Slater 2019 Southern Methodist University

Aws Ec2 Instance Spot Price Forecasting Using Lstm Networks, Jeffrey Lancon, Yejur Kunwar, David Stroud, Monnie Mcgee, Robert Slater

SMU Data Science Review

Cloud computing is a network of remote computing resources hosted on the Internet that allow users to utilize cloud resources on demand. As such, it represents a paradigm shift in the way businesses and industries think about digital infrastructure. With the shift from IT resources being a capital expenditure to a managed service, companies must rethink how they approach utilizing and optimizing these resources in order to maximize productivity and minimize costs. With proper resource management, cloud resources can be instrumental in reducing computing expenses.

Cloud resources are perishable commodities; therefore, cloud service providers have developed strategies to maximize utilization ...


Designing Cloud Computing Architecture For Bank Industry The Case Of Dashen Bank, Melaku Yenew 2019 Ambo University

Designing Cloud Computing Architecture For Bank Industry The Case Of Dashen Bank, Melaku Yenew

African Conference on Information Systems and Technology

Technology makes life easy. People contact banks in their day to day life activity. And also the banks are committed to serve their customers with the help of currently advanced technology. The aim of a bank is to give consistent and satisfactory banking services for the customers. The use of advanced technology in banking requires sophisticated knowledge of the technology and expertise and a large number of employees are required for implementation and management of that system.

Cloud computing makes easy the management of IT infrastructure and the bank sector systems. Cloud service providers provide three basic types of services ...


Investigating Semantic Properties Of Images Generated From Natural Language Using Neural Networks, Samuel Ward Schrader 2019 Boise State University

Investigating Semantic Properties Of Images Generated From Natural Language Using Neural Networks, Samuel Ward Schrader

Boise State University Theses and Dissertations

This work explores the attributes, properties, and potential uses of generative neural networks within the realm of encoding semantics. It works toward answering the questions of: If one uses generative neural networks to create a picture based on natural language, does the resultant picture encode the text's semantics in a way a computer system can process? Could such a system be more precise than current solutions at detecting, measuring, or comparing semantic properties of generated images, and thus their source text, or their source semantics?

This work is undertaken in the hope that detecting previously unknown properties, or better ...


Formally Designing And Implementing Cyber Security Mechanisms In Industrial Control Networks., Mehdi Sabraoui 2019 University of Louisville

Formally Designing And Implementing Cyber Security Mechanisms In Industrial Control Networks., Mehdi Sabraoui

Electronic Theses and Dissertations

This dissertation describes progress in the state-of-the-art for developing and deploying formally verified cyber security devices in industrial control networks. It begins by detailing the unique struggles that are faced in industrial control networks and why concepts and technologies developed for securing traditional networks might not be appropriate. It uses these unique struggles and examples of contemporary cyber-attacks targeting control systems to argue that progress in securing control systems is best met with formal verification of systems, their specifications, and their security properties. This dissertation then presents a development process and identifies two technologies, TLA+ and seL4, that can be ...


An Explainable Recommender System Based On Semantically-Aware Matrix Factorization., Mohammed Sanad Alshammari 2019 University of Louisville

An Explainable Recommender System Based On Semantically-Aware Matrix Factorization., Mohammed Sanad Alshammari

Electronic Theses and Dissertations

Collaborative Filtering techniques provide the ability to handle big and sparse data to predict the ratings for unseen items with high accuracy. Matrix factorization is an accurate collaborative filtering method used to predict user preferences. However, it is a black box system that recommends items to users without being able to explain why. This is due to the type of information these systems use to build models. Although rich in information, user ratings do not adequately satisfy the need for explanation in certain domains. White box systems, in contrast, can, by nature, easily generate explanations. However, their predictions are less ...


Adaptation Of A Deep Learning Algorithm For Traffic Sign Detection, Jose Luis Masache Narvaez 2019 The University of Western Ontario

Adaptation Of A Deep Learning Algorithm For Traffic Sign Detection, Jose Luis Masache Narvaez

Electronic Thesis and Dissertation Repository

Traffic signs detection is becoming increasingly important as various approaches for automation using computer vision are becoming widely used in the industry. Typical applications include autonomous driving systems, mapping and cataloging traffic signs by municipalities. Convolutional neural networks (CNNs) have shown state of the art performances in classification tasks, and as a result, object detection algorithms based on CNNs have become popular in computer vision tasks. Two-stage detection algorithms like region proposal methods (R-CNN and Faster R-CNN) have better performance in terms of localization and recognition accuracy. However, these methods require high computational power for training and inference that make ...


Computer Vision Machine Learning And Future-Oriented Ethics, Abagayle Lee Blank 2019 Seattle Pacific University

Computer Vision Machine Learning And Future-Oriented Ethics, Abagayle Lee Blank

Honors Projects

Computer Vision Machine Learning (CVML) in the application of facial recognition is currently being researched, developed, and deployed across the world. It is of interest to governments, technology companies, and consumers. However, fundamental issues remain related to human rights, error rates, and bias. These issues have the potential to create societal backlash towards the technology which could limit its benefits as well as harm people in the process. To develop facial recognition technology that will be beneficial to society in and beyond the next decade, society must put ethics at the forefront. Drawing on AI4People’s adaption of bioethics for ...


Bpm: Blz Package Manager, Kenneth Huang 2019 California Polytechnic State University, San Luis Obispo

Bpm: Blz Package Manager, Kenneth Huang

Computer Engineering

bpm (BLZ Package Manager) is a package manager for the open-source programming language BLZ, built in Java. It allows users of the BLZ programming language to create and upload their own packages, as well as downloading necessary dependency packages for their packages. To do this, the program communicates with the “cardiovascular”, a web server designed for users to upload and download BLZ packages.

The program has three primary functions. The first one, “init”, initializes a package directory for use with the package manager. Part of this initialization is creating a “heartbeat” meta file, which holds information about the package’s ...


Grammar-Based Procedurally Generated Village Creation Tool, Kevin Matthew Graves 2019 California Polytechnic State University, San Luis Obispo

Grammar-Based Procedurally Generated Village Creation Tool, Kevin Matthew Graves

Computer Engineering

This project is a 3D village generator tool for Unity. It consists of three components: a building, mountain, and river generator. All of these generators use grammar-based procedural generation in order to create a unique and logical village and landscape each time the program is run.


Labeling Paths With Convolutional Neural Networks, Sean Wallace, Kyle Wuerch 2019 California Polytechnic State University, San Luis Obispo

Labeling Paths With Convolutional Neural Networks, Sean Wallace, Kyle Wuerch

Computer Engineering

With the increasing development of autonomous vehicles, being able to detect driveable paths in arbitrary environments has become a prevalent problem in multiple industries. This project explores a technique which utilizes a discretized output map that is used to color an image based on the confidence that each block is a driveable path. This was done using a generalized convolutional neural network that was trained on a set of 3000 images taken from the perspective of a robot along with matching masks marking which portion of the image was a driveable path. The techniques used allowed for a labeling accuracy ...


Digital Forensics Challenge, Zoe Lie, Sydney Marie Mendoza 2019 California Polytechnic State University, San Luis Obispo

Digital Forensics Challenge, Zoe Lie, Sydney Marie Mendoza

Computer Engineering

No abstract provided.


Reach - A Community Service Application, Samuel Noel Magana 2019 California Polytechnic State University, San Luis Obispo

Reach - A Community Service Application, Samuel Noel Magana

Computer Engineering

Communities are familiar threads that unite people through several shared attributes and interests. These commonalities are the core elements that link and bond us together. Many of us are part of multiple communities, moving in and out of them depending on our needs. These common threads allow us to support and advocate for each other when facing a common threat or difficult situation. Healthy and vibrant communities are fundamental to the operation of our society. These interactions within our communities define the way we as individuals interact with each other, and society at large. Being part of a community helps ...


Keylime, Joshua Michael Magera 2019 California Polytechnic State University, San Luis Obispo

Keylime, Joshua Michael Magera

Computer Engineering

New freshmen arrive at Cal Poly every year, experience Week of Welcome, and, if they haven’t been to Firestone Grill within the first week, they can consider themselves an anomaly. But how long until those freshmen find the amazing sandwiches and breakfast burritos served at Gus’s Grocery or hear about the free burger promo at Sylvester’s? The goal of this senior project was to create an app, KeyLime, that makes it easy for college students to find new eateries and fresh deals that are local, affordable, and tasty. KeyLime aims to target college students and create a ...


Quorum Blockchain Stress Evaluation In Different Environments, Daniel P. Mera 2019 CUNY John Jay College

Quorum Blockchain Stress Evaluation In Different Environments, Daniel P. Mera

Student Theses

In today’s world, the Blockchain technology is used for different purposes has brought an increment in the development of different Blockchain platforms, services, and utilities for storing data securely and efficiently. Quorum Blockchain, an Ethereum fork created by JPMorgan Chase, has placed itself in one of the widely used, efficient and trustful Blockchain platforms available today. Because of the importance which Quorum is contributing to the world, it is important to test and measure different aspects of the platform, not only to prove how efficient the software can be but as well as to have a clear view on ...


Identifying Hourly Traffic Patterns With Python Deep Learning, Christopher L. Leavitt 2019 California Polytechnic State University, San Luis Obispo

Identifying Hourly Traffic Patterns With Python Deep Learning, Christopher L. Leavitt

Computer Engineering

This project was designed to explore and analyze the potential abilities and usefulness of applying machine learning models to data collected by parking sensors at a major metro shopping mall. By examining patterns in rates at which customer enter and exit parking garages on the campus of the Bellevue Collection shopping mall in Bellevue, Washington, a recurrent neural network will use data points from the previous hours will be trained to forecast future trends.


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