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A Survey On Various Image Inpainting Techniques, Nermin Mohamed Fawzy Salem PhD 2021 Electrical Engineering Department - Future University in Egypt

A Survey On Various Image Inpainting Techniques, Nermin Mohamed Fawzy Salem Phd

Future Engineering Journal

Over the decades' researchers have studied the image inpainting problem intensively due to its high significance and effectiveness in various image processing applications such as people and object security, object removal, face editing applications. Image inpainting is defined as the process of completing or removing a missing region in images. It is considered one of the most challenging topics in the image processing field, although, it requires a deep understanding of the image details in terms of texture and structure. In this paper, a survey of most image inpainting techniques is presented and summarized with comparisons including the merits and …


Translating Video Recordings Of Mobile App Ui Gestures Into Replayable Scenarios For Native And Hybrid Apps, Madeleine Havranek 2021 William & Mary

Translating Video Recordings Of Mobile App Ui Gestures Into Replayable Scenarios For Native And Hybrid Apps, Madeleine Havranek

Undergraduate Honors Theses

Screen recordings of mobile applications are easy to obtain and capture a wealth of information pertinent to software developers (e.g., bugs or feature requests), making them a popular mechanism for crowdsourced app feedback. Thus, these videos are becoming a common artifact that developers must manage. In light of unique mobile development constraints, including swift release cycles and rapidly evolving platforms, automated techniques for analyzing all types of rich software artifacts provide benefit to mobile developers. Unfortunately, automatically analyzing screen recordings presents serious challenges, due to their graphical nature, compared to other types of (textual) artifacts. To address these challenges, this …


Exploring Neural Networks For Predicting Sentinel-C Backscatter Between Image Acquisitions, Zhongdi Wu 2021 Southern Methodist University

Exploring Neural Networks For Predicting Sentinel-C Backscatter Between Image Acquisitions, Zhongdi Wu

Computer Science and Engineering Theses and Dissertations

Measuring moisture dynamics in soil and overlying vegetation is key to understanding ecosystem and agricultural dynamics in many contexts. For many applications, moisture information is demanded at high temporal frequency over large areas. Sentinel-1 C-band radar backscatter satellite images provide a repeating sequence of fine-resolution (10-m) observations that can be used to infer soil and vegetation moisture, but the 12-day interval between satellite observations is infrequent relative to the sensed moisture dynamics. Machine learning approaches have been used to predict soil moisture at higher spatial resolutions than the original satellite images, but little effort has been made to increase the …


Incorporating Virtual Reality Training In An Introductory Public Speaking Course, Kevin Kryston, Henry Goble, Allison Eden 2021 Michigan State University

Incorporating Virtual Reality Training In An Introductory Public Speaking Course, Kevin Kryston, Henry Goble, Allison Eden

Journal of Communication Pedagogy

This study presents the results of two studies using a virtual reality (VR) public-speaking training simulation as an instructional aid in a basic communication course. Results from the first study suggest that VR practice was associated with higher subsequent speech delivery grades in the course compared to no practice. However, VR practice did not reduce public speaking anxiety (PSA). In a follow-up study, VR practice was compared with other forms of lab-based practice including in front of a mirror and a recorded video session. All forms of lab practice (VR, mirror, or video) were associated with higher speech grades than …


A New Era Of Education: Incorporating Machine Teachers Into Education, Jihyun Kim 2021 University of Central Florida

A New Era Of Education: Incorporating Machine Teachers Into Education, Jihyun Kim

Journal of Communication Pedagogy

This editorial briefly discusses the potential of machine agents in education that can assist in creating more positive and meaningful teaching and learning environments. Then, it introduces three articles, two empirical research studies and one research-based instructional activity, compromising a special section on “Machine Teachers in Education” of Journal of Communication Pedagogy. Collectively, these articles help us better understand the role of machines in education and facilitate intellectual dialogues.


Human-Machine Communication: Complete Volume. Volume 3. Diffusion Of Human-Machine Communication During And After The Covid-19 Pandemic, 2021 University of Central Florida

Human-Machine Communication: Complete Volume. Volume 3. Diffusion Of Human-Machine Communication During And After The Covid-19 Pandemic

Human-Machine Communication

This is the complete volume of HMC Volume 3. Diffusion of Human-Machine Communication During and After the COVID-19 Pandemic


What Will Affect The Diffusion Of Ai Agents?, James W. Dearing 2021 Michigan State University

What Will Affect The Diffusion Of Ai Agents?, James W. Dearing

Human-Machine Communication

For billions of people, the threat of the Novel Coronavirus SARS-CoV-2 and its variants has precipitated the adoption of new behaviors. Pandemics are radical events that disrupt the gradual course of societal change, offering the possibility that some rapidly adopted innovations will persist in use past the time period of the event and, thus, diffuse more rapidly than in the absence of such an event. Human-machine communication includes a range of technologies with which many of us have quickly become more familiar due to stay-athome orders, distancing, workplace closures, remote instruction, home-bound entertainment, fear of contracting COVID-19, and boredom. In …


The Role Of Vidura Chatbot In The Diffusion Of Knowcovid-19 Gateway, Kerk F. Kee, Prasad P. Calyam, Hariharan Regunath 2021 Texas Tech University

The Role Of Vidura Chatbot In The Diffusion Of Knowcovid-19 Gateway, Kerk F. Kee, Prasad P. Calyam, Hariharan Regunath

Human-Machine Communication

The COVID-19 pandemic is an unprecedented global emergency. Clinicians and medical researchers are suddenly thrown into a situation where they need to keep up with the latest and best evidence for decision-making at work in order to save lives and develop solutions for COVID-19 treatments and preventions. However, a challenge is the overwhelming numbers of online publications with a wide range of quality. We explain a science gateway platform designed to help users to filter the overwhelming amount of literature efficiently (with speed) and effectively (with quality), to find answers to their scientific questions. It is equipped with a chatbot …


Communicative Development And Diffusion Of Humanoid Ai Robots For The Post-Pandemic Health Care System, Do Kyun David Kim, Gary Kreps, Rukhsana Ahmed 2021 University of Louisiana at Lafayette

Communicative Development And Diffusion Of Humanoid Ai Robots For The Post-Pandemic Health Care System, Do Kyun David Kim, Gary Kreps, Rukhsana Ahmed

Human-Machine Communication

As humanoid robot technology, anthropomorphized by artificial intelligence (AI), has rapidly advanced to introduce more human-resembling automated robots that can communicate, interact, and work like humans, we have begun to expect active interactions with Humanoid AI Robots (HAIRs) in the near future. Coupled with the HAIR technology development, the COVID-19 pandemic triggered our interest in using health care robots with many substantial advantages that overcome critical human vulnerabilities against the strong infectious COVID-19 virus. Recognizing the tremendous potential for the active application of HAIRs, this article explores feasible ways to implement HAIRs in health care and patient services and suggests …


The Impact Of Cloud Computing On Academic Libraries, Sivankalai S 2021 PSN College of Engineering & Technology

The Impact Of Cloud Computing On Academic Libraries, Sivankalai S

Library Philosophy and Practice (e-journal)

With the introduction of computers and other forms of communication technology, library services have undergone a significant transformation. Libraries have been automated, networked, and are currently being converted into virtual or paperless libraries. This article is dedicated to many aspects of cloud computing, including different kinds and applications. There is a discussion about the advantages and drawbacks of cloud computing in academic libraries. The article also includes recommendations for professional librarians and academic libraries across the globe on how to take advantage of cloud computing resources. This article may be of use in the development of cloud-based services for university …


Detecting Driver Drowsiness With Multi-Sensor Data Fusion Combined With Machine Learning, Hovannes Kulhandjian 2021 California State University, Fresno

Detecting Driver Drowsiness With Multi-Sensor Data Fusion Combined With Machine Learning, Hovannes Kulhandjian

Mineta Transportation Institute Publications

According to the National Highway Traffic Safety Administration, in 2017 drowsy driving resulted in 50,000 injuries across 91,000 police-reported accidents, as well as almost 800 deaths. Through the application of visual and radar sensors combined with machine learning, this research developed a drowsy driver detection system aimed to prevent potentially fatal accidents. The working prototype of Advanced Driver Assistance Systems can be installed in present-day vehicles to detect drowsy drivers with over 95% accuracy. It integrates two types of visual surveillance to examine the driver for signs of drowsiness. A camera is used to monitor the driver’s eyes, mouth and …


Evaluating Algorithms Used For Fetal Brain Scan Segmentation, Connor Stewart Burgess 2021 Western University

Evaluating Algorithms Used For Fetal Brain Scan Segmentation, Connor Stewart Burgess

Undergraduate Student Research Internships Conference

The goal for this project was to successfully segment a fetal brain scan (fetal scan) using the algorithms provided by the program Slicer3D. To better understand the hurdles that arose when segmenting a fetal scan, we first look at the segmentation of an adult brain scan. This will allow us to see the straightforward nature of a brain segmentation when a high quality, high resolution volume with distinct structures is available. After examining the adult brain scan, attention will be moved to the segmentation of the fetal scan, where we’ll first look at the algorithms used and methods followed. Finally …


Distributed Parallel Processing, Adrian Wu 2021 Western University

Distributed Parallel Processing, Adrian Wu

Undergraduate Student Research Internships Conference

This report summarizes the development of testing new microcontrollers in performing image processing and parallel processing to solve the problem of testing and deploying expensive computer hardware technology in space. The project determined that the I2C communication protocol should be converted to an alternative protocol to maximize data transfer in parallel processing. This report also analyzes the software components and hardware components of the Distributed Parallel Processing project.

This project was to research the alternative protocols for the recently developed project Distributed Parallel Processing with CubeSats. There project was to develop a suitable microcontroller to perform image processing techniques with …


Multi-Agent Radiation Localization, Teresa Nguyen 2021 Portland State University

Multi-Agent Radiation Localization, Teresa Nguyen

REU Final Reports

Advancement of radiation detection technology is an ongoing process, and adjustments are made based on pre-existing conditions of radiation presence--both natural and man made. Tools that are currently used for safely detecting radiation in urban environments exist in several forms: drones, robots, or handheld radiation detection devices. This is a harm reductive way to explore radiation-infected environments while preserving human health as best as possible. In order for these autonomous platforms to successfully detect radiation sources, an algorithm needs to be created that is capable of gathering crucial data on its own with little to no human interference. Machine learning …


Deep Learning For High-Impedance Fault Detection And Classification, Khushwant Rai 2021 The University of Western Ontario

Deep Learning For High-Impedance Fault Detection And Classification, Khushwant Rai

Electronic Thesis and Dissertation Repository

High-Impedance Faults (HIFs) are a hazard to public safety but are difficult to detect because of their low current amplitude and diverse characteristics. Supervised machine learning techniques have shown great success in HIF detection; however, these approaches rely on resource-intensive signal processing techniques and fail in presence of non-HIF disturbances and even for scenarios not included in training data. This thesis leverages unsupervised learning and proposes a Convolutional Autoencoder framework for HIF Detection (CAE-HIFD). In CAE-HIFD, Convolutional Autoencoder learns only from HIF signals by employing cross-correlation; consequently, eliminating the need for diverse non-HIF scenarios in training. Furthermore, this thesis proposes …


Deep Learning Based Music Source Separation, Ryan Henning, Abdullah Choudhry, Ming Ma 2021 Winona State University

Deep Learning Based Music Source Separation, Ryan Henning, Abdullah Choudhry, Ming Ma

SCSU Journal of Student Scholarship

Decades of music exists in the world with no way to find the original multitrack recordings that they are composed of, whether it be a lack of access or just being lost to time. Music source separation is the process of using technology to isolate the individual components of a song after they have been fully arranged and mixed together. These components, or stems, can be the vocals, drums, bass, or any other instrument found in the song. By doing complex analysis on the structure of songs to determine which frequencies or waveform patterns belong to particular sources, a convolutional …


Flight Trajectory Prediction For Aeronautical Communications., Nathan T Schimpf 2021 University of Louisville

Flight Trajectory Prediction For Aeronautical Communications., Nathan T Schimpf

Electronic Theses and Dissertations

The development of future technologies for the National Airspace System (NAS) will be reliant on a new communications infrastructure capable of managing a limited spectrum among aircraft and ground systems. Emerging approaches to this spectrum allocation task mostly consider machine learning techniques reliant on aircraft and Air Traffic Control (ATC) sector data. Much of this data, however, is not directly available. This thesis considers the development of two such data products: the 4D trajectory (latitude, longitude, altitude, and time) of aircraft, and the anticipated airspace utilization and communication demand within an ATC sector. Data predictions are treated as a time …


Cosine-Based Explainable Matrix Factorization For Collaborative Filtering Recommendation., Pegah Sagheb Haghighi 2021 University of Louisville

Cosine-Based Explainable Matrix Factorization For Collaborative Filtering Recommendation., Pegah Sagheb Haghighi

Electronic Theses and Dissertations

Recent years saw an explosive growth in the amount of digital information and the number of users who interact with this information through various platforms, ranging from web services to mobile applications and smart devices. This increase in information and users has naturally led to information overload which inherently limits the capacity of users to discover and find their needs among the staggering array of options available at any given time, the majority of which they may never become aware of. Online services have handled this information overload by using algorithmic filtering tools that can suggest relevant and personalized information …


Projection-Based Ar For Hearing Parent-Deaf Child Communication, Victor N. Antony, Adira Blumenthal, Ziyue Qiu, Ashely Tenesaca, Wanyin Hu, Zhen Bai 2021 University of Rochester

Projection-Based Ar For Hearing Parent-Deaf Child Communication, Victor N. Antony, Adira Blumenthal, Ziyue Qiu, Ashely Tenesaca, Wanyin Hu, Zhen Bai

Frameless

Deaf infants born to hearing parents are at risk of language deprivation due to lack of sign language fluency and subpar parent-child communication. We present a projection-based Augmented Reality (AR) prototype designed to improve parent-child communication and American Sign Language (ASL) acquisition. Our system aims to non-intrusively augment play episodes by projecting just-in-time and context-aware ASL equivalents extracted from nursery rhymes being sung by parents. This paper presents the initial implementation of the prototype .


Designing Blended Experiences: Laugh Traders Design Fiction, BRIAN J. OKEEFE 2021 Farmingdale State College

Designing Blended Experiences: Laugh Traders Design Fiction, Brian J. Okeefe

Frameless

The increasing ubiquity of interactions that involve complementary digital content, physical objects, and spaces, brings about new challenges for designers. There is a need to embed designs in legacy systems, whether those are existing physical structures or existing digital platforms. Traditional approaches to product design, interaction design, and user experience design often do not take this new context into account. Many systems do not consider how designers produce new digital and physical experiences that work harmoniously, while supporting new interactions and relationships with people (Imaz and Benyon 2007; Jetter, Geyer, Schwarz & Reiterer 2012). To address this, we propose the …


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