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Full-Text Articles in Other Computer Engineering

The Ftc And Ai Governance: A Regulatory Proposal, Michael Spiro Dec 2020

The Ftc And Ai Governance: A Regulatory Proposal, Michael Spiro

Seattle Journal of Technology, Environmental & Innovation Law

No abstract provided.


Empirical Analysis Of Cbow And Skip Gram Nlp Models, Tejas Menon Sep 2020

Empirical Analysis Of Cbow And Skip Gram Nlp Models, Tejas Menon

University Honors Theses

CBOW and Skip Gram are two NLP techniques to produce word embedding models that are accurate and performant. They were invented in the seminal paper by T. Mikolov et al. and have since observed optimizations such as negative sampling and subsampling. This paper implements a fully-optimized version of these models using Py-Torch and runs them through a toy sentiment/subject analysis. It is weakly observed that different corpus types affect the skew of work embeddings such that fictional corpus are better suited for sentiment analysis and non-fictional for subject analysis.


A New Approach For Homomorphic Encryption With Secure Function Evaluation On Genomic Data, Mounika Pratapa Aug 2020

A New Approach For Homomorphic Encryption With Secure Function Evaluation On Genomic Data, Mounika Pratapa

Electronic Thesis and Dissertation Repository

Additively homomorphic encryption is a public-key primitive allowing a sum to be computed on encrypted values. Although limited in functionality, additive schemes have been an essential tool in the private function evaluation toolbox for decades. They are typically faster and more straightforward to implement relative to their fully homomorphic counterparts, and more efficient than garbled circuits in certain applications. This thesis presents a novel method for extending the functionality of additively homomorphic encryption to allow the private evaluation of functions of restricted domain. Provided the encrypted sum falls within the restricted domain, the function can be homomorphically evaluated “for free ...


Ontology-Driven Semantic Data Integration In Open Environment, Islam M. Ali Aug 2020

Ontology-Driven Semantic Data Integration In Open Environment, Islam M. Ali

Electronic Thesis and Dissertation Repository

Collaborative intelligence in the context of information management can be defined as "A shared intelligence that results from the collaboration between various information systems". In open environments, these collaborating information systems can be heterogeneous, dynamic and loosely-coupled. Information systems in open environment can also possess a certain degree of autonomy. The integration of data residing in various heterogeneous information systems is essential in order to drive the intelligence efficiently and accurately. Because of the heterogeneous, loosely-coupled, and dynamic nature of open environment, the integration between these information systems in the data level is not efficient. Several approaches and models have ...


Terramechanics And Machine Learning For The Characterization Of Terrain, Bryan W. Southwell Aug 2020

Terramechanics And Machine Learning For The Characterization Of Terrain, Bryan W. Southwell

Electronic Thesis and Dissertation Repository

An instrumented rover wheel can collect vast amounts of data about a planetary surface. Planetary surfaces are changed by complex geological processes which can be better understood with an abundance of surface data and the use of terramechanics. Identifying terrain parameters such as cohesion and angle of friction hold importance for both the rover driver and the planetary scientist. Knowledge of terrain characteristics can warn of unsafe terrain and flag potential interesting scientific sites. The instrumented wheel in this research utilizes a pressure pad to sense load and sinkage, a string potentiometer to measure slip, and records motor current draw ...


Artificial Intelligence And Game Theory Controlled Autonomous Uav Swarms, Janusz Kusyk, M. Umit Uyar, Kelvin Ma, Eltan Samoylov, Ricardo Valdez, Joseph Plishka, Sagor E. Hoque, Giorgio Bertoli, Jefrey Boksiner Jul 2020

Artificial Intelligence And Game Theory Controlled Autonomous Uav Swarms, Janusz Kusyk, M. Umit Uyar, Kelvin Ma, Eltan Samoylov, Ricardo Valdez, Joseph Plishka, Sagor E. Hoque, Giorgio Bertoli, Jefrey Boksiner

Publications and Research

Autonomous unmanned aerial vehicles (UAVs) operating as a swarm can be deployed in austere environments, where cyber electromagnetic activities often require speedy and dynamic adjustments to swarm operations. Use of central controllers, UAV synchronization mechanisms or pre-planned set of actions to control a swarm in such deployments would hinder its ability to deliver expected services. We introduce artificial intelligence and game theory based flight control algorithms to be run by each autonomous UAV to determine its actions in near real-time, while relying only on local spatial, temporal and electromagnetic (EM) information. Each UAV using our flight control algorithms positions itself ...


Analysis Of Information Security Methods In Biosystems And Application Of Intelligent Tools In Information Security Systems, Sherzod Sayfullaev Jul 2020

Analysis Of Information Security Methods In Biosystems And Application Of Intelligent Tools In Information Security Systems, Sherzod Sayfullaev

Chemical Technology, Control and Management

In this paper, the methods of information protection in bio systems are studied. The paper considers the use of intelligent tools in information security systems and the use of adaptive information security systems. Several articles on the field of information protection in bio systems are analyzed. Disadvantages and advantages of neural network technologies in modern information security systems are described. The characteristics of bio systems and the specificity of DNA, the main features of the DNA code that provide information security and functional stability of bio systems data protection structure. Application of intelligent tools to create a comprehensive adaptive protection ...


User Interface Design For Mobile Financial Services: Users Perspective, Belachew U. Regane Jul 2020

User Interface Design For Mobile Financial Services: Users Perspective, Belachew U. Regane

African Conference on Information Systems and Technology

Users belonging to different countries have different exposure and perception to trust the technology to adopt it. Users’ trust and adoption rates are challenging issues in mobile financial services. Thus, the purpose of the research is how to design a trustful user interface. Market research is conducted to collect data. Using the data, personas and use cases developed. The result of personas and use cases used to develop prototypes. Prototype A and B designed differently to give choice to users to investigate users' trust. Prototype A is designed to make it easy to use and clear workflow. Whereas prototype B ...


A Comprehensive Study For Modern Models: Linking Requirements With Software Architectures, Sisay Yemata Jul 2020

A Comprehensive Study For Modern Models: Linking Requirements With Software Architectures, Sisay Yemata

African Conference on Information Systems and Technology

Several models recently have been addressed in software engineering for requirements transformation. However, such transformation models have encountered many problems due to the nature of requirements. In the classical transformation modeling, some requirements are discovered to be missing or erroneous at later stages, in addition to major assumptions that may affect the quality of the software. This has created a crucial need for new approaches to requirements transformation. In this paper, a comprehensive study is presented in the main modern models of linking requirements to software architectures. An extensive evaluation is conducted to investigate the capabilities of such modern models ...


Efficient Data Mining Algorithm Network Intrusion Detection System For Masked Feature Intrusions, Kassahun Admkie, Kassahun Admkie Tekle Jul 2020

Efficient Data Mining Algorithm Network Intrusion Detection System For Masked Feature Intrusions, Kassahun Admkie, Kassahun Admkie Tekle

African Conference on Information Systems and Technology

Most researches have been conducted to develop models, algorithms and systems to detect intrusions. However, they are not plausible as intruders began to attack systems by masking their features. While researches continued to various techniques to overcome these challenges, little attention was given to use data mining techniques, for development of intrusion detection. Recently there has been much interest in applying data mining to computer network intrusion detection, specifically as intruders began to cheat by masking some detection features to attack systems. This work is an attempt to propose a model that works based on semi-supervised collective classification algorithm. For ...


Born-Digital Preservation: The Art Of Archiving Photos With Script And Batch Processing, Rachel S. Evans, Leslie Grove, Sharon Bradley Jul 2020

Born-Digital Preservation: The Art Of Archiving Photos With Script And Batch Processing, Rachel S. Evans, Leslie Grove, Sharon Bradley

Articles, Chapters and Online Publications

With our IT department preparing to upgrade the University of Georgia’s Alexander Campbell King Law Library (UGA Law Library) website from Drupal 7 to 8 this fall, a web developer, an archivist, and a librarian teamed up a year ago to make plans for preserving thousands of born-digital images. We wanted to harvest photographs housed only in web-based photo galleries on the law school website and import them into our repository’s collection. The problem? There were five types of online photo galleries, and our current repository did not include appropriate categories for all of the photographs. The solution ...


Machine Learning Applications In Power Systems, Xinan Wang Jul 2020

Machine Learning Applications In Power Systems, Xinan Wang

Electrical Engineering Theses and Dissertations

Machine learning (ML) applications have seen tremendous adoption in power system research and applications. For instance, supervised/unsupervised learning-based load forecasting and fault detection are classic ML topics that have been well studied. Recently, reinforcement learning-based voltage control, distribution analysis, etc., are also gaining popularity. Compared to conventional mathematical methods, ML methods have the following advantages: (i). better robustness against different system configurations due to its data-driven nature; (ii). better adaption to system uncertainties; (iii). less dependent on the modeling accuracy and validity of assumptions. However, due to the unique physics of the power grid, many problems cannot be directly ...


A Survey On Exploring Key Performance Indicators, Amira Idrees Jun 2020

A Survey On Exploring Key Performance Indicators, Amira Idrees

Future Computing and Informatics Journal

Key Performance Indicators (KPIs) allows gathering knowledge and exploring the best way to achieve organization goals. Many researchers have provided different ideas for determining KPI's either manually, and semi-automatic, or automatic which is applied in different fields. This work concentrates on providing a survey of different approaches for exploring and predicting key performance indicators (KPIs).


Creation Of Mobile Applications For The Shrines Of Al-Hakim Al-Termizi, Mavlyuda Xodjayeva, Turdali Jumayev, Alimjon Dadamuhamedov, Barno Saydakhmedova Jun 2020

Creation Of Mobile Applications For The Shrines Of Al-Hakim Al-Termizi, Mavlyuda Xodjayeva, Turdali Jumayev, Alimjon Dadamuhamedov, Barno Saydakhmedova

The Light of Islam

We recognize that the sustainable development of tourism has great potential for the development of cultural and humanitarian ties around the world. We emphasize the importance of information technology in tourism, especially in the areas of advertising, marketing, differentiation and specialization of tourism products. In addition, we reaffirm our commitment to pilgrimage tourism for the individual growth of people and the strengthening of basic social norms and national values. The program uses modern programming languages such as Php, Java, C ++. Al-Hakim at-Termizi is one of the most famous places of worship in Uzbekistan, which is also known for its historical ...


Conference Roundup: Smart Cataloging - Beginning The Move From Batch Processing To Automated Classification, Rachel S. Evans Jun 2020

Conference Roundup: Smart Cataloging - Beginning The Move From Batch Processing To Automated Classification, Rachel S. Evans

Articles, Chapters and Online Publications

This article reviewed the Amigos Online Conference titled “Work Smarter, Not Harder: Innovating Technical Services Workflows” keynote session delivered by Dr. Terry Reese on February 13, 2020. Excerpt:

"As the developer of MarcEdit, a popular metadata suite used widely across the library community, Reese’s current work is focused on the ways in which libraries might leverage semantic web techniques in order to transform legacy library metadata into something new. So many sessions related to using new technologies in libraries or academia, although exciting, are not practical enough to put into everyday use by most librarians. Reese’s keynote, titled ...


Bootstrapping Massively Multiplayer Online Role Playing Games, Mitchell Miller Jun 2020

Bootstrapping Massively Multiplayer Online Role Playing Games, Mitchell Miller

Master's Theses

Massively Multiplayer Online Role Playing Games (MMORPGs) are a prominent genre in today's video game industry with the most popular MMORPGs generating billions of dollars in revenue and attracting millions of players. As they have grown, they have become a major target for both technological research and sociological research. In such research, it is nearly impossible to reach the same player scale from any self-made technology or sociological experiments. This greatly limits the amount of control and topics that can be explored. In an effort to make up a lacking or non-existent player-base for custom-made MMORPG research scenarios A ...


Analysis Of Human Affect And Bug Patterns To Improve Software Quality And Security, Md Rakibul Islam May 2020

Analysis Of Human Affect And Bug Patterns To Improve Software Quality And Security, Md Rakibul Islam

University of New Orleans Theses and Dissertations

The impact of software is ever increasing as more and more systems are being software operated. Despite the usefulness of software, many instances software failures have been causing tremendous losses in lives and dollars. Software failures take place because of bugs (i.e., faults) in the software systems. These bugs cause the program to malfunction or crash and expose security vulnerabilities exploitable by malicious hackers.

Studies confirm that software defects and vulnerabilities appear in source code largely due to the human mistakes and errors of the developers. Human performance is impacted by the underlying development process and human affects, such ...


Security Camera Using Raspberry Pi, Tejendra Khatri May 2020

Security Camera Using Raspberry Pi, Tejendra Khatri

Student Academic Conference

No abstract provided.


Predictive Analysis Of Ethanol Prices With Machine Learning, Benjamin Schilling May 2020

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 May 2020

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 ...


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 May 2020

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 ...


Lexicon Based Approaches To Sentiment Analysis Of Spanish Tweets: A Comparative Study, Jean Roca May 2020

Lexicon Based Approaches To Sentiment Analysis Of Spanish Tweets: A Comparative Study, Jean Roca

Computer Science and Computer Engineering Undergraduate Honors Theses

Sentiment analysis is a natural language processing technique that aims to classify text based on the emotions expressed in them. It is a research area that has been around for almost 20 years and has seen a lot of development. The works presented in this paper attempts to target a less-developed area in sentiment analysis known as multilingual sentiment analysis. More specifically, multilingual sentiment analysis of micro-texts. Using the existing WordNet lexicon and a domain-specific lexicon for a corpus of Spanish tweets, we analyze the effectiveness of these techniques.


A Capacitive Sensing Gym Mat For Exercise Classification & Tracking, Adam Goertz May 2020

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.


Efficient Elevator Algorithm, Sean M. Toll, Owen Barbour, Carl Edwards, Daniel Nichols, Austin Day May 2020

Efficient Elevator Algorithm, Sean M. Toll, Owen Barbour, Carl Edwards, Daniel Nichols, Austin Day

Chancellor’s Honors Program Projects

No abstract provided.


Qlime-A Quadratic Local Interpretable Model-Agnostic Explanation Approach, Steven Bramhall, Hayley Horn, Michael Tieu, Nibhrat Lohia Apr 2020

Qlime-A Quadratic Local Interpretable Model-Agnostic Explanation Approach, Steven Bramhall, Hayley Horn, Michael Tieu, Nibhrat Lohia

SMU Data Science Review

In this paper, we introduce a proof of concept that addresses the assumption and limitation of linear local boundaries by Local Interpretable Model-Agnostic Explanations (LIME), a popular technique used to add interpretability and explainability to black box models. LIME is a versatile explainer capable of handling different types of data and models. At the local level, LIME creates a linear relationship for a given prediction through generated sample points to present feature importance. We redefine the linear relationships presented by LIME as quadratic relationships and expand its flexibility in non-linear cases and improve the accuracy of feature interpretations. We coin ...


Sunseeker Solar Car Display And Driver Unit, Conner Mccarthy Apr 2020

Sunseeker Solar Car Display And Driver Unit, Conner Mccarthy

Honors Theses

Digital dashboard displays with critical driver information are found in all modern vehicles. Examples of such information available to the driver include a speedometer, odometer, engine RPM, fuel gauge and more. The current 2016 Sunseeker solar car already has numerous displays that can show critical information to the driver, however, there are several problems that exist. Each display itself is less than two inches in size, the text on the screens is difficult to read, and the measurements have no units. Furthermore, these displays were made by a company that no longer exists, thus preventing the solar car team from ...


Vex U Robotics, Kyle Lutterman, Jeffrey Ryan, Sierra Wong, Elizabeth Geiger Apr 2020

Vex U Robotics, Kyle Lutterman, Jeffrey Ryan, Sierra Wong, Elizabeth Geiger

Discovery Day - Prescott

VEX U is a competition hosted by the REC Foundation for university students to get engaged in hands-on engineering. Each team produces two robots using the VEX provided parts to compete in the VEX U competition. The competition changes every year with the only constants being the size of the field, the tools and parts teams are able to use, and the size constraints of the robots. The teams compete in regional competitions in order to qualify for the World Championship Competition, which is the highest competition a team can compete in for VEX U. The VEX U teams at ...


Bracelet Reminder For Alzheimer’S, Jennifer Islam, Caroline Rodriguez, Farrukh Zia Apr 2020

Bracelet Reminder For Alzheimer’S, Jennifer Islam, Caroline Rodriguez, Farrukh Zia

Publications and Research

This project involves the design, construction and testing of a personal reminder device for elderly who suffer from Alzheimer’s using a clock system and LED wearable technology. The device consists of an RGB LED strip connected to a 7-segment display (which operates as a clock circuit) attached to a microcontroller board. The device uses visual output to alert the user at that certain time the color being emitted represents the reminder the user set for that time. The project involves two phases. In the first phase, an RGB LED strip will be used to make a wearable device and ...


Towards Optimized Traffic Provisioning And Adaptive Cache Management For Content Delivery, Aditya Sundarrajan Mar 2020

Towards Optimized Traffic Provisioning And Adaptive Cache Management For Content Delivery, Aditya Sundarrajan

Doctoral Dissertations

Content delivery networks (CDNs) deploy hundreds of thousands of servers around the world to cache and serve trillions of user requests every day for a diverse set of content such as web pages, videos, software downloads and images. In this dissertation, we propose algorithms to provision traffic across cache servers and manage the content they host to achieve performance objectives such as maximizing the cache hit rate, minimizing the bandwidth cost of the network and minimizing the energy consumption of the servers.

Traffic provisioning is the process of determining the set of content domains hosted on the servers. We propose ...


A Comparative Evaluation Of The Detection And Tracking Capability Between Novel Event-Based And Conventional Frame-Based Sensors, James P. Boettiger Mar 2020

A Comparative Evaluation Of The Detection And Tracking Capability Between Novel Event-Based And Conventional Frame-Based Sensors, James P. Boettiger

Theses and Dissertations

Traditional frame-based technology continues to suffer from motion blur, low dynamic range, speed limitations and high data storage requirements. Event-based sensors offer a potential solution to these challenges. This research centers around a comparative assessment of frame and event-based object detection and tracking. A basic frame-based algorithm is used to compare against two different event-based algorithms. First event-based pseudo-frames were parsed through standard frame-based algorithms and secondly, target tracks were constructed directly from filtered events. The findings show there is significant value in pursuing the technology further.