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A Novel Parking Management In Smart City Vehicular Datacenters, Syed Rizvi, Susan Zehra, Steven Olariu 2023 Old Dominion University

A Novel Parking Management In Smart City Vehicular Datacenters, Syed Rizvi, Susan Zehra, Steven Olariu

College of Sciences Posters

Researchers have shown that most vehicles spend the majority of their time parked in parking garages, lots, or driveways. During this time, their computing resources are unused and untapped. This has led to substantial interest in Vehicular Cloud, an area of research in which each vehicle acts as a computation node. The main difference between traditional cloud computing and vehicular cloud computing is the availability of nodes. In traditional clouds, nodes are available 24/7, while in vehicular clouds, nodes (vehicles) are only available while parked in parking lots. This creates a dynamic environment as vehicles enter and exit parking garages …


Scalable Quantum Edge Detection Method For D-Nisq Imaging Simulations: Use Cases From Nuclear Physics And Medical Image Computing, Emmanuel Billias, Nikos Chrisochoides 2023 Old Dominion University

Scalable Quantum Edge Detection Method For D-Nisq Imaging Simulations: Use Cases From Nuclear Physics And Medical Image Computing, Emmanuel Billias, Nikos Chrisochoides

The Graduate School Posters

Edge Detection is one of the computationally intensive modules in image analysis. It is used to find important landmarks by identifying a significant change (or “edge”) between pixels and voxels. We present a hybrid Quantum Edge Detection method by improving three aspects of an existing widely referenced implementation, which for our use cases generates incomprehensible results for the type and size of images we are required to process. Our contributions are in the pre- and post-processing (i.e., classical phase) and a quantum edge detection circuit: (1) we use space- filling curves to eliminate image artifacts introduced by the image decomposition, …


Robots Still Outnumber Humans In Web Archives In 2019, But Less Than In 2012, Himarsha R. Jayanetti, Kritika Garg, Sawood Alam, Michael L. Nelson, Michele C. Weigle 2023 Old Dominion University

Robots Still Outnumber Humans In Web Archives In 2019, But Less Than In 2012, Himarsha R. Jayanetti, Kritika Garg, Sawood Alam, Michael L. Nelson, Michele C. Weigle

College of Sciences Posters

To identify robots and human users in web archives, we conducted a study using the access logs from the Internet Archive’s (IA) Wayback Machine in 2012 (IA2012), 2015 (IA2015), and 2019 (IA2019), and the Portuguese Web Archive (PT) in 2019 (PT2019). We identified user sessions in the access logs and classified them as human or robot based on their browsing behavior. In 2013, AlNoamany et al. [1] studied the user access patterns using IA access logs from 2012. They established four web archive user access patterns: single-page access (Dip), access to the same page at multiple archive times (Dive), access …


Metaenhance: Metadata Quality Improvement For Electronic Theses And Dissertations, Muntabir H. Choudhury, Lamia Salsabil, Himarsha R. Jayanetti, Jian Wu 2023 Old Dominion University

Metaenhance: Metadata Quality Improvement For Electronic Theses And Dissertations, Muntabir H. Choudhury, Lamia Salsabil, Himarsha R. Jayanetti, Jian Wu

College of Sciences Posters

Metadata quality is crucial for digital objects to be discovered through digital library interfaces. Although DL systems have adopted Dublin Core to standardize metadata formats (e.g., ETD-MS v1.11), the metadata of digital objects may contain incomplete, inconsistent, and incorrect values [1]. Most existing frameworks to improve metadata quality rely on crowdsourced correction approaches, e.g., [2]. Such methods are usually slow and biased toward documents that are more discoverable by users. Artificial intelligence (AI) based methods can be adopted to overcome this limit by automatically detecting, correcting, and canonicalizing the metadata, featuring quick and unbiased responses to document metadata. …


Adhd Prediction Through Analysis Of Eye Movements With Graph Convolution Network, Gavindya Jayawardena, Sampath Jayarathna, Yi He 2023 Old Dominion University

Adhd Prediction Through Analysis Of Eye Movements With Graph Convolution Network, Gavindya Jayawardena, Sampath Jayarathna, Yi He

College of Sciences Posters

Processing speech with background noise requires appropriate parsing of the distorted auditory signal, fundamental language abilities as well as higher signal-to-noise ratio. Adolescents with ADHD have difficulty processing speech with background noise due to reduced inhibitory control and working memory capacity. In this study we utilize Audiovisual Speech-In-Noise performance and eye-tracking measures of young adults with ADHD compared to age-matched controls, and generate graphs for ADHD evaluation using the eye-tracking data. We form graphs utilizing the eight eye-tracking features (fixation count, average, total, and standard deviation of fixation duration, max and min saccade peak velocity, min, average, and standard deviation …


Completeness Of Nominal Props, Samuel Balco, Alexander Kurz 2023 Runtime Verication Inc.

Completeness Of Nominal Props, Samuel Balco, Alexander Kurz

Engineering Faculty Articles and Research

We introduce nominal string diagrams as string diagrams internal in the category of nominal sets. This leads us to define nominal PROPs and nominal monoidal theories. We show that the categories of ordinary PROPs and nominal PROPs are equivalent. This equivalence is then extended to symmetric monoidal theories and nominal monoidal theories, which allows us to transfer completeness results between ordinary and nominal calculi for string diagrams.


Crosshair Optimizer, Jason Torrence 2023 Central Washington University

Crosshair Optimizer, Jason Torrence

All Master's Theses

Metaheuristic optimization algorithms are heuristics that are capable of creating a "good enough'' solution to a computationally complex problem. Algorithms in this area of study are focused on the process of exploration and exploitation: exploration of the solution space and exploitation of the results that have been found during that exploration, with most resources going toward the former half of the process. The novel Crosshair optimizer developed in this thesis seeks to take advantage of the latter, exploiting the best possible result as much as possible by directly searching the area around that best result with a stochastic approach. This …


X-Disetrac: Distributed Eye-Tracking With Extended Realities, Bhanuka Mahanama, Sampath Jayarathna 2023 Old Dominion University

X-Disetrac: Distributed Eye-Tracking With Extended Realities, Bhanuka Mahanama, Sampath Jayarathna

College of Sciences Posters

Humans use heterogeneous collaboration mediums such as in-person, online, and extended realities for day-to-day activities. Identifying patterns in viewpoints and pupillary responses (a.k.a eye-tracking data) provide informative cues on individual and collective behavior during collaborative tasks. Despite the increasing ubiquity of these different mediums, the aggregation and analysis of eye-tracking data in heterogeneous collaborative environments remain unexplored. Our study proposes X-DisETrac: Extended Distributed Eye Tracking, a versatile framework for eye tracking in heterogeneous environments. Our approach tackles the complexity by establishing a platform-agnostic communication protocol encompassing three data streams to simplify data aggregation and …


Famaid: A Tool For Aiding People With Disability, Mohamad Maad, Ahmad Owaydate, Mohammad Kojok, Firas Aboudaher, Layal Abu Daher, May Itani 2022 Department of Mathematics and Computer Science, Beirut Arab University

Famaid: A Tool For Aiding People With Disability, Mohamad Maad, Ahmad Owaydate, Mohammad Kojok, Firas Aboudaher, Layal Abu Daher, May Itani

BAU Journal - Science and Technology

People with disabilities suffer from discrimination and obstacles that restrict them from participating in society on an equal basis with others every day. They are deprived of their rights to be included in ordinary school systems and even in the work market. In the process of raising awareness, facilitating dailyroutines, and developing guidance, the idea of assisting such people with handy tools/software arose and was implemented in the FamAid tool. FamAid offers people with hearing disability the opportunity to be engaged in the society through many facilities. In this work, we implemented a web application that serves as a community …


Explainable Ai Helps Bridge The Ai Skills Gap: Evidence From A Large Bank, Selina Carter, Jonathan Hersh 2022 Carnegie Mellon University

Explainable Ai Helps Bridge The Ai Skills Gap: Evidence From A Large Bank, Selina Carter, Jonathan Hersh

Economics Faculty Articles and Research

Advances in machine learning have created an “AI skills gap” both across and within firms. As AI becomes embedded in firm processes, it is unknown how this will impact the digital divide between workers with and without AI skills. In this paper we ask whether managers trust AI to predict consequential events, what manager characteristics are associated with increasing trust in AI predictions, and whether explainable AI (XAI) affects users’ trust in AI predictions. Partnering with a large bank, we generated AI predictions for whether a loan will be late in its final disbursement. We embedded these predictions into a …


Analyzing Business-Focused Social Networks In Hiring: The Influence Of A Job Candidate's Network On A Recruiter's Hiring Recommendation, Hannah V. Kibby 2022 University of South Alabama

Analyzing Business-Focused Social Networks In Hiring: The Influence Of A Job Candidate's Network On A Recruiter's Hiring Recommendation, Hannah V. Kibby

Theses and Dissertations

Social media has altered the ways in which people interact. Business-focused social media profiles, such as those on LinkedIn, can act as a proxy for a traditional resume. However, these websites differ from a traditional resume in that information presented is sometimes informal, personal, and irrelevant to the member’s career. Furthermore, HR employees are able to view a job candidate’s social network. This research investigates the influence of a recruiter’s knowledge of an applicant’s professional network on the recruiter’s perception of the applicant’s trustworthiness and hence their willingness to take risk in the hiring relationship. A review of the literature …


Detecting Selfish Mining Attacks Against A Blockchain Using Machine Learing, Matthew A. Peterson 2022 University of South Alabama

Detecting Selfish Mining Attacks Against A Blockchain Using Machine Learing, Matthew A. Peterson

Theses and Dissertations

Selfish mining is an attack against a blockchain where miners hide newly discovered blocks instead of publishing them to the rest of the network. Selfish mining has been a potential issue for blockchains since it was first discovered by Eyal and Sirer. It can be used by malicious miners to earn a disproportionate share of the mining rewards or in conjunction with other attacks to steal money from network users. Several of these attacks were launched in 2018, 2019, and 2020 with the attackers stealing as much as $18 Million. Developers made several different attempts to fix this issue, but …


Computer Engineering Education, Marilyn Wolf 2022 University of Nebraska-Lincoln

Computer Engineering Education, Marilyn Wolf

CSE Conference and Workshop Papers

Computer engineering is a rapidly evolving discipline. How should we teach it to our students?

This virtual roundtable on computer engineering education was conducted in summer 2022 over a combination of email and virtual meetings. The panel considered what topics are of importance to the computer engineering curriculum, what distinguishes computer engineering from related disciplines, and how computer engineering concepts should be taught.


A Blockchain Based Policy Framework For The Management Of Electronic Health Record (Ehrs), Aysha Ali Mohammed Murad Qambar 2022 United Arab Emirates University

A Blockchain Based Policy Framework For The Management Of Electronic Health Record (Ehrs), Aysha Ali Mohammed Murad Qambar

Theses

The rapid development of information technology during the last decade has greatly influenced all aspects of society, including individuals and enterprise organizations. Adopting new technologies by individuals and organizations depends on several factors, such as usability, available resources, support needed for adoption benefits, and return on investment, to mention a few. When it comes to the adoption of new technologies, one of the main challenges faced by organizations is the ability to effectively incorporate such technologies into their enterprise solutions to maximize the expected benefits. For the last several years, Blockchain technology has become a popular trend in a variety …


Communicative Information Visualizations: How To Make Data More Understandable By The General Public, Alyxander Burns 2022 University of Massachusetts Amherst

Communicative Information Visualizations: How To Make Data More Understandable By The General Public, Alyxander Burns

Doctoral Dissertations

Although data visualizations have been around for centuries and are encountered frequently by the general public, existing evidence suggests that a significant portion of people have difficulty understanding and interpreting them. It might not seem like a big problem when a reader misreads a weather map and finds themselves without an umbrella in a rainstorm, but for those who lack the means, experience, or ability to make sense of data, misreading a data visualization concerning public health and safety could be a matter of life and death. However, figuring out how to make visualizations truly usable for a diverse audience …


Computing Concept: Genealogy Potential, Power, Arithmetic, Algorithm And Ritual Of Computation, Yuhang LIU, Fei ZHANG 2022 Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China

Computing Concept: Genealogy Potential, Power, Arithmetic, Algorithm And Ritual Of Computation, Yuhang Liu, Fei Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

In the new era, China needs more rational, firm, dialectical, and practical cultural confidence in the field of computational technology. The study conducted rigorous literature research, and established the correspondence between the ancient Chinese ideologies and different focuses of computation. The study proposes the computation concept genealogy (i.e., potential, power, arithmetic, algorithm, and ritual of computation) to deepen the multi-dimensional understanding of the concept of computation, and gives some suggestions for cultivating the computational culture that is facing the world and is of Chinese characteristics.


An Investigation Into Time Gazed At Traffic Objects By Drivers, Kolby R. Sarson 2022 The University of Western Ontario

An Investigation Into Time Gazed At Traffic Objects By Drivers, Kolby R. Sarson

Electronic Thesis and Dissertation Repository

Several studies have considered driver’s attention for a multitude of distinct purposes, ranging from the analysis of a driver’s gaze and perception, to possible use in Advanced Driving Assistance Systems (ADAS). These works typically rely on simple definitions of what it means to “see,” considering a driver gazing upon an object for a single frame as being seen. In this work, we bolster this definition by introducing the concept of time. We consider a definition of ”seen” which requires an object to be gazed upon for a set length of time, or frames, before it can be considered as seen …


Agglomerative Hierarchical Clustering With Dynamic Time Warping For Household Load Curve Clustering, Fadi AlMahamid, Katarina Grolinger 2022 Western University

Agglomerative Hierarchical Clustering With Dynamic Time Warping For Household Load Curve Clustering, Fadi Almahamid, Katarina Grolinger

Electrical and Computer Engineering Publications

Energy companies often implement various demand response (DR) programs to better match electricity demand and supply by offering the consumers incentives to reduce their demand during critical periods. Classifying clients according to their consumption patterns enables targeting specific groups of consumers for DR. Traditional clustering algorithms use standard distance measurement to find the distance between two points. The results produced by clustering algorithms such as K-means, K-medoids, and Gaussian Mixture Models depend on the clustering parameters or initial clusters. In contrast, our methodology uses a shape-based approach that combines Agglomerative Hierarchical Clustering (AHC) with Dynamic Time Warping (DTW) to classify …


Virtual Sensor Middleware: Managing Iot Data For The Fog-Cloud Platform, Fadi AlMahamid, Hanan Lutfiyya, Katarina Grolinger 2022 Western University

Virtual Sensor Middleware: Managing Iot Data For The Fog-Cloud Platform, Fadi Almahamid, Hanan Lutfiyya, Katarina Grolinger

Electrical and Computer Engineering Publications

This paper introduces the Virtual Sensor Middleware (VSM), which facilitates distributed sensor data processing on multiple fog nodes. VSM uses a Virtual Sensor as the core component of the middleware. The virtual sensor concept is redesigned to support functionality beyond sensor/device virtualization, such as deploying a set of virtual sensors to represent an IoT application and distributed sensor data processing across multiple fog nodes. Furthermore, the virtual sensor deals with the heterogeneous nature of IoT devices and the various communication protocols using different adapters to communicate with the IoT devices and the underlying protocol. VSM uses the publish-subscribe design pattern …


Towards Qos-Based Embedded Machine Learning, Tom Springer, Erik Linstead, Peiyi Zhao, Chelsea Parlett-Pelleriti 2022 Chapman University

Towards Qos-Based Embedded Machine Learning, Tom Springer, Erik Linstead, Peiyi Zhao, Chelsea Parlett-Pelleriti

Engineering Faculty Articles and Research

Due to various breakthroughs and advancements in machine learning and computer architectures, machine learning models are beginning to proliferate through embedded platforms. Some of these machine learning models cover a range of applications including computer vision, speech recognition, healthcare efficiency, industrial IoT, robotics and many more. However, there is a critical limitation in implementing ML algorithms efficiently on embedded platforms: the computational and memory expense of many machine learning models can make them unsuitable in resource-constrained environments. Therefore, to efficiently implement these memory-intensive and computationally expensive algorithms in an embedded computing environment, innovative resource management techniques are required at the …


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