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Articles 451 - 480 of 1394
Full-Text Articles in Engineering
Circus In Motion: A Multimodal Exergame Supporting Vestibular Therapy For Children With Autism, Oscar Peña, Franceli L. Cibrian, Monica Tentori
Circus In Motion: A Multimodal Exergame Supporting Vestibular Therapy For Children With Autism, Oscar Peña, Franceli L. Cibrian, Monica Tentori
Engineering Faculty Articles and Research
Exergames are serious games that involve physical exertion and are thought of as a form of exercise by using novel input models. Exergames are promising in improving the vestibular differences of children with autism but often lack of adaptation mechanisms that adjust the difficulty level of the exergame. In this paper, we present the design and development of Circus in Motion, a multimodal exergame supporting children with autism with the practice of non-locomotor movements. We describe how the data from a 3D depth camera enables the tracking of non-locomotor movements allowing children to naturally interact with the exergame . A …
Terramechanics And Machine Learning For The Characterization Of Terrain, Bryan W. Southwell
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. …
Exploring The Efficacy Of Transfer Learning In Mining Image‑Based Software Artifacts, Natalie Best, Jordan Ott, Erik J. Linstead
Exploring The Efficacy Of Transfer Learning In Mining Image‑Based Software Artifacts, Natalie Best, Jordan Ott, Erik J. Linstead
Engineering Faculty Articles and Research
Background
Transfer learning allows us to train deep architectures requiring a large number of learned parameters, even if the amount of available data is limited, by leveraging existing models previously trained for another task. In previous attempts to classify image-based software artifacts in the absence of big data, it was noted that standard off-the-shelf deep architectures such as VGG could not be utilized due to their large parameter space and therefore had to be replaced by customized architectures with fewer layers. This proves to be challenging to empirical software engineers who would like to make use of existing architectures without …
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
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 …
Optimized Machine Learning Models Towards Intelligent Systems, Mohammadnoor Ahmad Mohammad Injadat
Optimized Machine Learning Models Towards Intelligent Systems, Mohammadnoor Ahmad Mohammad Injadat
Electronic Thesis and Dissertation Repository
The rapid growth of the Internet and related technologies has led to the collection of large amounts of data by individuals, organizations, and society in general [1]. However, this often leads to information overload which occurs when the amount of input (e.g. data) a human is trying to process exceeds their cognitive capacities [2]. Machine learning (ML) has been proposed as one potential methodology capable of extracting useful information from large sets of data [1]. This thesis focuses on two applications. The first is education, namely e-Learning environments. Within this field, this thesis proposes different optimized ML ensemble models to …
Two Techniques For Automated Logging Statement Evolution, Allan R. Spektor
Two Techniques For Automated Logging Statement Evolution, Allan R. Spektor
Theses and Dissertations
This thesis presents and explores two techniques for automated logging statement evolution. The first technique reinvigorates logging statement levels to reduce information overload using degree of interest obtained via software repository mining. The second technique converts legacy method calls to deferred execution to achieve performance gains, eliminating unnecessary evaluation overhead.
Analysis Of Information Security Methods In Biosystems And Application Of Intelligent Tools In Information Security Systems, Sherzod Sayfullaev
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
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
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
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 …
A Deep-Learning Based Robust Framework Against Adversarial P.E. And Cryptojacking Malware, Faraz Amjad Naseem
A Deep-Learning Based Robust Framework Against Adversarial P.E. And Cryptojacking Malware, Faraz Amjad Naseem
FIU Electronic Theses and Dissertations
This graduate thesis introduces novel, deep-learning based frameworks that are resilient to adversarial P.E. and cryptojacking malware. We propose a method that uses a convolutional neural network (CNN) to classify image representations of malware, that provides robustness against numerous adversarial attacks. Our evaluation concludes that the image-based malware classifier is significantly more robust to adversarial attacks than a state-of-the-art ML-based malware classifier, and remarkably drops the evasion rate of adversarial samples to 0% in certain attacks. Further, we develop MINOS, a novel, lightweight cryptojacking detection system that accurately detects the presence of unwarranted mining activity in real-time. MINOS can detect …
Born-Digital Preservation: The Art Of Archiving Photos With Script And Batch Processing, Rachel S. Evans, Leslie Grove, Sharon Bradley
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? Expand our …
Machine Learning Applications In Power Systems, Xinan Wang
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 solved …
A Private Bitcoin Payment Network With Reduced Transaction Fees And Confirmation Times, Enes Erdin
A Private Bitcoin Payment Network With Reduced Transaction Fees And Confirmation Times, Enes Erdin
FIU Electronic Theses and Dissertations
Since its introduction, Bitcoin cryptocurrency has revolutionized the way payment systems can be designed in a purely distributed manner through its novel Blockchain data structure. While Bitcoin has opened new opportunities, it has been long criticized for its slow transaction confirmation times and high transaction fees. To address this issue, one of the recently emerging solutions is to build a payment channel network (PCN) on top of Bitcoin where the transactions can be made without writing to blockchain. Specifically, a PCN is a network where the users connect either directly or indirectly to send payments to each other in a …
A Survey On Exploring Key Performance Indicators, Amira Idrees
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
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 …
Reading Robot, Gillian Watts, Andrew Myers, Sabrinna Tan, Taylor Klein, Omeed Djassemi
Reading Robot, Gillian Watts, Andrew Myers, Sabrinna Tan, Taylor Klein, Omeed Djassemi
General Engineering
Presently, there is an insufficient availability of human experts to assist students in reading competency and comprehension. Our team’s goal was to create an improved socially assistive robot for use by therapists, teachers, and parents to help children and adults develop reading skills while they do not have access to specialists. HAPI is a socially assistive robot that we created with the goal of helping students practice their reading comprehension skills. HAPI enables a student to improve their reading skills without an educator present, while enabling educators to review the student's performance remotely. Design constraints included: physical size, weight, duration …
Conference Roundup: Smart Cataloging - Beginning The Move From Batch Processing To Automated Classification, Rachel S. Evans
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 Smart Cataloging: …
Human Facial Emotion Recognition System In A Real-Time, Mobile Setting, Claire Williamson
Human Facial Emotion Recognition System In A Real-Time, Mobile Setting, Claire Williamson
Honors Theses
The purpose of this project was to implement a human facial emotion recognition system in a real-time, mobile setting. There are many aspects of daily life that can be improved with a system like this, like security, technology and safety.
There were three main design requirements for this project. The first was to get an accuracy rate of 70%, which must remain consistent for people with various distinguishing facial features. The second goal was to have one execution of the system take no longer than half of a second to keep it as close to real time as possible. Lastly, …
Bootstrapping Massively Multiplayer Online Role Playing Games, Mitchell Miller
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.I. agents, …
Analysis Of Human Affect And Bug Patterns To Improve Software Quality And Security, Md Rakibul Islam
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 as …
Alexa, Ask My Library: How Do I Build A Custom Skill To Extend Reference Services?, Christopher M. Jimenez
Alexa, Ask My Library: How Do I Build A Custom Skill To Extend Reference Services?, Christopher M. Jimenez
Works of the FIU Libraries
The Reference Technology team at Florida International University recently published an Alexa Skill that incorporates the LibAnswers API into the device’s answer bank. We have several Echo Show devices at our public service desks to meet the demands of extended hours while also enhancing public service presence beyond the reference desk.
The Green Library at FIU’s Modesto Maidique Campus now operates on a 24/5 schedule, allowing students to access library facilities at any time during the week. In addition, both the Hubert Library and the Engineering Library Service Center stay open past times when personal reference assistance is available. This …
Security Camera Using Raspberry Pi, Tejendra Khatri
Security Camera Using Raspberry Pi, Tejendra Khatri
Student Academic Conference
No abstract provided.
Predictive Analysis Of Ethanol Prices With Machine Learning, Benjamin Schilling
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
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 …
Less-Java, More Type Safety: Type Inference And Static Analysis In Less-Java, Charles D. Hines
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.
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
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 …
Campuspartner: An Assistive Technology For Pedestrians With Mobility Impairments, Cynthia R. Zastudil
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 …
Lexicon Based Approaches To Sentiment Analysis Of Spanish Tweets: A Comparative Study, Jean Roca
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.
Computational Techniques In Medical Image Analysis Application For White Blood Cells Classification., Omar Dekhil
Computational Techniques In Medical Image Analysis Application For White Blood Cells Classification., Omar Dekhil
Electronic Theses and Dissertations
White blood cells play important rule in the human body immunity and any change in their count may cause serious diseases. In this study, a system is introduced for white blood cells localization and classification. The dataset used in this study is formed by two components, the first is the annotation dataset that will be used in the localization (364 images), and the second is labeled classes that will be used in the classification (12,444 images). For the localization, two approaches will be discussed, a classical approach and a deep learning based approach. For the classification, 5 different deep learning …