Computer Engineering Commons^™

Recent Advances And Trends Of Predictive Maintenance From Data-Driven Machine Prognostics Perspective, Yuxin Wen, Md. Fashiar Rahman, Honglun Xu, Tzu-Liang Bill Tseng

Engineering Faculty Articles and Research

In the Engineering discipline, prognostics play an essential role in improving system safety, reliability and enabling predictive maintenance decision-making. Due to the adoption of emerging sensing techniques and big data analytics tools, data-driven prognostic approaches are gaining popularity. This paper aims to deliver an extensive review of recent advances and trends of data-driven machine prognostics, with a focus on their applications in practice. The primary purpose of this review is to categorize existing literature and report the latest research progress and directions to support researchers and practitioners in acquiring a clear comprehension of the subject area. This paper first summarizes …

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

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

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

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

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

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

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

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

Mineta Transportation Institute

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 …

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 …

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 …

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 …

Towards Verifying Smartphone Users Via Gripping Hand Image Classification, Kaitlyn M. Madden

LSU Master's Theses

Smartphones continue to proliferate throughout our daily lives, not only in sheer quantity but also their ever-growing list of uses. They are no longer just for communication and the occasional phone game. Smartphones can be used to open garage doors, transfer money, see who is at your front door, and much, much more. With this increased dependence and use, smartphone security is critical. In this paper we propose a system to verify a user’s identity by applying a convolutional neural network (CNN) model to an image of the user’s hand while holding their device. This model aims to address situations …

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

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 …

Review Of Data Mining Techniques For Detecting Churners In The Telecommunication Industry, Mahmoud Ewieda, Mohamed Ismail Roushdy, Essam Shaaban

Future Computing and Informatics Journal

The telecommunication sector has been developed rapidly and with large amounts of data obtained as a result of increasing in the number of subscribers, modern techniques, data-based applications, and services. As well as better awareness of customer requirements and excellent quality that meets their satisfaction. This satisfaction raises rivalry between firms to maintain the quality of their services and upgrade them. These data can be helpfully extracted for analysis and used for predicting churners. Researchers around the world have conducted important research to understand the uses of Data mining (DM) that can be used to predict customers' churn. This …

Web Services In Cloud Computing Research: Insights From Scientometric, Sivankalai S, Virumandi A

Library Philosophy and Practice (e-journal)

The research is the outcome of the investigation of 4035 papers on web services and cloud study, as covered in the Web of Knowledge core collection database during 2010 - 2019, going through an overall group author contribution of 29.00% during the period, Iosup, Alexandru, et al with a citation impact per paper of 44.10% and a journal impact per paper of 5.768 by Future generation computer systems-the international journal of science. The world's web services and cloud research output is diverse, with the top three open access research journals accounting for 66.59% (All Open Access 44.03%, DOAJ Gold 17.41%, …

A Quantitative Validation Of Multi-Modal Image Fusion And Segmentation For Object Detection And Tracking, Nicholas Lahaye, Michael J. Garay, Brian D. Bue, Hesham El-Askary, Erik Linstead

Mathematics, Physics, and Computer Science Faculty Articles and Research

In previous works, we have shown the efficacy of using Deep Belief Networks, paired with clustering, to identify distinct classes of objects within remotely sensed data via cluster analysis and qualitative analysis of the output data in comparison with reference data. In this paper, we quantitatively validate the methodology against datasets currently being generated and used within the remote sensing community, as well as show the capabilities and benefits of the data fusion methodologies used. The experiments run take the output of our unsupervised fusion and segmentation methodology and map them to various labeled datasets at different levels of global …

Physically Based Rendering Techniques To Visualize Thin-Film Smoothed Particle Hydrodynamics Fluid Simulations, Aditya H. Prasad

Dartmouth College Undergraduate Theses

This thesis introduces a methodology and workflow I developed to visualize smoothed hydrodynamic particle based simulations for the research paper ’Thin-Film Smoothed Particle Hydrodynamics Fluid’ (2021), that I co-authored. I introduce a physically based rendering model which allows point cloud simulation data representing thin film fluids and bubbles to be rendered in a photorealistic manner. This includes simulating the optic phenomenon of thin-film interference and rendering the resulting iridescent patterns. The key to the model lies in the implementation of a physically based surface shader that accounts for the interference of infinitely many internally reflected rays in its bidirectional surface …

Pier Ocean Pier, Brandon J. Nowak

Computer Engineering

Pier Ocean Peer is a weatherproof box containing a Jetson Nano, connected to a cell modem and camera, and powered by a Lithium Iron Phosphate battery charged by a 50W solar panel. This system can currently provide photos to monitor the harbor seal population that likes to haul out at the base of the Cal Poly Pier, but more importantly it provides a platform for future expansion by other students either though adding new sensors directly to the Jetson Nano or by connecting to the jetson nano remotely through a wireless protocol of their choice.

Observation Of The Evolution Of Hide And Seek Ai, Anthony J. Catelani

Computer Science and Software Engineering

The purpose of this project is to observe the evolution of two artificial agents, a ‘Seeker’ and a ‘Hider’, as they play a simplified version of the game Hide and Seek. These agents will improve through machine learning, and will only be given an understanding of the rules of the game and the ability to navigate through the grid-like space where the game shall be played; they will not be taught or given any strategies, and will be made to learn from a clean slate. Of particular interest is observing the particular playstyle of hider and seeker intelligences as new …

Automating Deep-Sea Video Annotation, Hanson Egbert

Master's Theses

As the world explores opportunities to develop offshore renewable energy capacity, there will be a growing need for pre-construction biological surveys and post-construction monitoring in the challenging marine environment. Underwater video is a powerful tool to facilitate such surveys, but the interpretation of the imagery is costly and time-consuming. Emerging technologies have improved automated analysis of underwater video, but these technologies are not yet accurate or accessible enough for widespread adoption in the scientific community or industries that might benefit from these tools.

To address these challenges, prior research developed a website that allows to: (1) Quickly play and annotate …

Efficient Protocols For Multi-Party Computation, Tahereh Jafarikhah

Dissertations, Theses, and Capstone Projects

Secure Multi-Party Computation (MPC) allows a group of parties to compute a join function on their inputs without revealing any information beyond the result of the computation. We demonstrate secure function evaluation protocols for branching programs, where the communication complexity is linear in the size of the inputs, and polynomial in the security parameter. Our result is based on the circular security of the Paillier's encryption scheme. Our work followed the breakthrough results by Boyle et al. [9; 11]. They presented a Homomorphic Secret Sharing scheme which allows the non-interactive computation of Branching Programs over shares of the secret inputs. …

Hierarchical Scheduling For Real-Time Periodic Tasks In Symmetric Multiprocessing, Tom Springer, Peiyi Zhao

Engineering Faculty Articles and Research

In this paper, we present a new hierarchical scheduling framework for periodic tasks in symmetric multiprocessor (SMP) platforms. Partitioned and global scheduling are the two main approaches used by SMP based systems where global scheduling is recommended for overall performance and partitioned scheduling is recommended for hard real-time performance. Our approach combines both the global and partitioned approaches of traditional SMP-based schedulers to provide hard real-time performance guarantees for critical tasks and improved response times for soft real-time tasks. Implemented as part of VxWorks, the results are confirmed using a real-time benchmark application, where response times were improved for soft …

Online Laboratory Course Using Low Tech Supplies To Introduce Digital Logic Design Concepts, Dhanya Nair

Engineering Faculty Articles and Research

This paper describes a Digital Logic Design Laboratory Course developed to engage students with hardware systems within an online setting. This is a junior level core course for students from Computer Science (CS), Computer Engineering (CE) and Electrical Engineering (EE). Hence, the laboratories are designed to provide the hands-on experience of breadboarding, testing and debugging essential to CE and EE while accommodating CS students with no prior hardware experience. Commercially available low-cost electronic trainers (portable workstations) are loaned to the students in addition to basic electronic components. To ensure a strong foundation in debugging, prior to utilizing these workstations, students …

Using Pitch Tipping For Baseball Pitch Prediction, Brian Ishii

Master's Theses

Data Analytics and technology have changed baseball as we know it. From the increase in defensive shifts to teams using cameras in the outfield to steal signs, teams will try anything to win. One way to gain an edge in baseball is to figure out what pitches a pitcher will pitch. Pitch prediction is a popular task to try to accomplish with all the data that baseball provides. Most methods involve using situational data like the ball and strike count. In this paper, we try a different method of predicting pitch type by only looking at the pitcher's pose in …

Dependencyvis: Helping Developers Visualize Software Dependency Information, Nathan Lui

Master's Theses

The use of dependencies have been increasing in popularity over the past decade, especially as package managers such as JavaScript's npm has made getting these packages a simple command to run. However, while incidents such as the left-pad incident has increased awareness of how vulnerable relying on these packages are, there is still some work to be done when it comes to getting developers to take the extra research step to determine if a package is up to standards. Finding metrics of different packages and comparing them is always a difficult and time consuming task, especially since potential vulnerabilities are …

Convolutional Neural Networks For Deflate Data Encoding Classification Of High Entropy File Fragments, Nehal Ameen

LSU New Orleans Theses and Dissertations

Data reconstruction is significantly improved in terms of speed and accuracy by reliable data encoding fragment classification. To date, work on this problem has been successful with file structures of low entropy that contain sparse data, such as large tables or logs. Classifying compressed, encrypted, and random data that exhibit high entropy is an inherently difficult problem that requires more advanced classification approaches. We explore the ability of convolutional neural networks and word embeddings to classify deflate data encoding of high entropy file fragments after establishing ground truth using controlled datasets. Our model is designed to either successfully classify file …

A Probabilistic Broadcasting Protocols In Mobile Ad Hoc Networks: A Bibliometric Survey, Sumit Kumar, Ayushi Kamboj

Library Philosophy and Practice (e-journal)

Broadcasting in Mobile ad hoc network is very crucial process and if not taken care led to Broadcast storm problem. Several Broadcasting techniques are proposed in the literature, but probabilistic broadcasting is the one the major technique which can really avoid the broadcasting storm problem. The protocols employing probabilistic broadcasting is surveyed in this bibliometric paper. The bibliometric survey aims to throw light on several types of protocols employed in Mobile ad hoc Network. The primary aim of this paper is to assess the amount of work done in the field of Probabilistic Broadcasting in Mobile ad hoc Network, as …