Computer Sciences Commons^™

Ai-Enhanced Detection Of Clinically Relevant Structural And Functional Anomalies In Mri: Traversing The Landscape Of Conventional To Explainable Approaches, Pegah Khosravi, Saber Mohammadi, Fatemeh Zahiri, Masoud Khodarahmi, Javad Zahiri

Publications and Research

Anomaly detection in medical imaging, particularly within the realm of magnetic resonance imaging (MRI), stands as a vital area of research with far-reaching implications across various medical fields. This review meticulously examines the integration of artificial intelligence (AI) in anomaly detection for MR images, spotlighting its transformative impact on medical diagnostics. We delve into the forefront of AI applications in MRI, exploring advanced machine learning (ML) and deep learning (DL) methodologies that are pivotal in enhancing the precision of diagnostic processes. The review provides a detailed analysis of preprocessing, feature extraction, classification, and segmentation techniques, alongside a comprehensive evaluation of …

Determining Critical Nodes In Optimal Cost Attacks On Networked Infrastructures, Ishfaq Ahmad, Addison Clark, Muhammad Ali, Hansheng Lei, David Ferris, Alex Aved

Informatics and Engineering Systems Faculty Publications

A wide range of critical infrastructures are connected via wide area networks as well as the Internet-of-Thing (IoT). Apart from natural disasters, these infrastructures, providing services such as electricity, water, gas, and Internet, are vulnerable to terrorist attacks. Clearly, damages to these infrastructures can have dire consequences on economics, health services, security and safety, and various business sectors. An infrastructure network can be represented as a directed graph in which nodes and edges denote operation entities and dependencies between entities, respectively. A knowledgeable attacker who plans to harm the system would aim to use the minimum amount of effort, cost, …

Enabling The Clinical Application Of Artificial Intelligence In Genomics: A Perspective Of The Amia Genomics And Translational Bioinformatics Workgroup, Nephi A Walton, Radha Nagarajan, Chen Wang, Murat Sincan, Robert R Freimuth, David B Everman, Derek C Walton, Scott P Mcgrath, Dominick J Lemas, Panayiotis V Benos, Alexander V Alekseyenko, Qianqian Song, Ece Gamsiz Uzun, Casey Overby Taylor, Alper Uzun, Thomas Nate Person, Nadav Rappoport, Zhongming Zhao, Marc S Williams

Faculty, Staff and Student Publications

OBJECTIVE: Given the importance AI in genomics and its potential impact on human health, the American Medical Informatics Association-Genomics and Translational Biomedical Informatics (GenTBI) Workgroup developed this assessment of factors that can further enable the clinical application of AI in this space.

PROCESS: A list of relevant factors was developed through GenTBI workgroup discussions in multiple in-person and online meetings, along with review of pertinent publications. This list was then summarized and reviewed to achieve consensus among the group members.

CONCLUSIONS: Substantial informatics research and development are needed to fully realize the clinical potential of such technologies. The development of …

Neutrosophic Statistical Analysis Of Temperatures Of Cities In The Southeastern Anatolia Region Of Turkey, Hacer Şengül Kandemir, Nazlım Deniz Aral, Murat Karakaş, Mikail Et

Neutrosophic Systems with Applications

In the paper, neutrosophic statistical analysis of temperature data of different cities in the southeastern Anatolia region of Turkey is given. The neutrosophic mean and neutrosophic coefficient of variation are computed using the temperature data. From the analysis, it is concluded that the temperatures of Mardin and Şanlıurfa cities are more consistent than the other cities in Turkey. In addition, the neutrosophic results are compared with results under classical statistics. Based on the comparative study, it can be concluded that neutrosophic statistical results are more adequate, flexible, and more informative than classical statistics.

Neutrosophic Statistical Analysis Of Temperatures Of Cities In The Southeastern Anatolia Region Of Turkey, Hacer Şengül Kandemir, Nazlım Deniz Aral, Murat Karakaş, Mikail Et

Neutrosophic Systems with Applications

In the paper, neutrosophic statistical analysis of temperature data of different cities in the southeastern Anatolia region of Turkey is given. The neutrosophic mean and neutrosophic coefficient of variation are computed using the temperature data. From the analysis, it is concluded that the temperatures of Mardin and Şanlıurfa cities are more consistent than the other cities in Turkey. In addition, the neutrosophic results are compared with results under classical statistics. Based on the comparative study, it can be concluded that neutrosophic statistical results are more adequate, flexible, and more informative than classical statistics.

Towards Assessing Cybersecurity Posture Of Manufacturing Companies: Review And Recommendations, John Del Vecchio, Yair Levy, Ling Wang, Ajoy Kumar

KSU Proceedings on Cybersecurity Education, Research and Practice

With the continued changes in the way businesses work, cyber-attack targets are in a constant state of flux between organizations, individuals, as well as various aspects of the supply chain of interconnected goods and services. As one of the 16 critical infrastructure sectors, the manufacturing sector is known for complex integrated Information Systems (ISs) that are incorporated heavily into production operations. Many of these ISs are procured and supported by third parties, also referred to as interconnected entities in the supply chain. Disruptions to manufacturing companies would not only have significant financial losses but would also have economic and safety …

Quantum Computing: Computing Of The Future Made Reality, Janelle Mathis

KSU Proceedings on Cybersecurity Education, Research and Practice

Abstract—Quantum computing is an emerging new area focused on technology consisting of quantum theory aspects such as electrons, sub-atomic particles, and other materials engineered using quantum mechanics. Through quantum mechanics, these computers can solve problems that classical computers deem too complex. Today the closest computing technology compared to quantum computers are supercomputers, but similarly to classical computers, supercomputers also have faults. With supercomputers, when a problem is deemed too complex, it is due to the classical machinery components within the computer, thus causing a halt in solving the task or problem. In contrast, these problems could be solved with a …

Rfid Key Fobs In Vehicles: Unmasking Vulnerabilities & Strengthening Security, Devon Magda, Bryson R. Payne

KSU Proceedings on Cybersecurity Education, Research and Practice

No abstract provided.

The Impact Of Individual Techno-Characteristics On Information Privacy Concerns In The Diffusion Of Mobile Contact Tracing, Jiesen Lin, Dapeng Liu, Lemuria Carter

KSU Proceedings on Cybersecurity Education, Research and Practice

In the wake of the global health crisis, mobile contact tracing applications have emerged as important tools in managing disease spread. However, their effectiveness heavily relies on mass adoption, significantly influenced by the public's information privacy concerns. To date, systematic examination of how these privacy concerns relate to the innovation adopter categories in mobile contact tracing remains sparse. Furthermore, the influence of individual techno-characteristics on these concerns is to be explored. This research seeks to fill these gaps. Drawing on the diffusion of innovation theory, we examine the impact of the key techno-characteristics—adopter category, propensity for identification misrepresentation, and exposure …

Exploring Information Privacy Concerns During The Covid-19 Pandemic: A Juxtaposition Of Three Models, Dapeng Liu, Lemuria Carter, Jiesen Lin

KSU Proceedings on Cybersecurity Education, Research and Practice

Government agencies across the globe utilize mobile applications to interact with constituents. In response to the global pandemic, several nations have employed contact tracing services to manage the spread of COVID-19. Extent literature includes various models that explore information privacy. Several researchers have highlighted the need to compare the effectiveness of diverse information privacy models. To fill this gap, we explore the impact of information privacy concerns on citizens’ willingness to download a federal contact tracing app. In particular, we compare three types of prevalent information privacy concerns: global information privacy concerns (GIPC), concern for information privacy (CFIP), and internet …

Understanding Trust Drivers Of S-Commerce, Mousa Al-Kfairy, Ahmed Shuhaiber, Ayman Wael Al-Khatib, Saed Alrabaee, Souheil Khaddaj

All Works

Trust has emerged as a pillar in the acceptance and use of new technologies in the ever-changing digital landscape, notably in the booming field of social commerce. The importance of this study lies in the fact that it explores in-depth the aspects of customer trust in Instashopping using new constructs that have yet to be explored in s-commerce literature. Focusing on Instashopping, the research proposed a multi-dimensional model of trust to examine the dynamics of user trust in social commerce platforms and analyses the effects of various factors, including institution-based trust, disposition to trust, personal inventiveness, perceived page quality, and …

Future Frame Prediction Using Generative Adversarial Networks, Nishtha Jatana, Deekshant Wadhwa, Nitesh Kumar Singh, Oday Ali Hassen, Charu Gupta, Saad Mohammed Darwish, Sundws Mustafa Mohammed, Dhyeauldeen Ahmed Farhan, Ansam Ali Abdulhussein

Karbala International Journal of Modern Science

The ability of a human to anticipate what is going to happen in the near future given the current situation helps in making intelligent decisions about how to react in that situation. In this paper, we have developed multiple Deep Neural Network models, intending to generate the next frame in a sequence given previous frames. In recent years, Generative Adversarial Networks (GAN) have shown promising results in the field of image generation. Hence, in this paper, we aim to create and compare two Generative Adversarial Models created for Future Frame Prediction by combining GANs with convolutional neural networks, Long Short-Term …

Extended Event Calculus Using Neutrosophic Logic: Method, Implementation, Analysis, Recent Progress And Future Directions, Antonios Paraskevas

Neutrosophic Systems with Applications

Brains do not reason as digital computers do. Computers reason in clear steps with statements that are either true or false, while humans reason with vague terms of common sense. Neutrosophy is a new branch of philosophy and machine intelligence that deals with neutralities, specifically the idea of indeterminacy that is evident and experienced in our everyday lives. Indeterminacy is interpreted as everything that falls between a concept, idea, statement, declaration, etc. and its opposite. The fundamental thesis of neutrosophy is to employ neutrosophic logic, an extension of fuzzy logic, to incorporate fuzzy truth into complex schemes of formal reasoning. …

Extended Event Calculus Using Neutrosophic Logic: Method, Implementation, Analysis, Recent Progress And Future Directions, Antonios Paraskevas

Neutrosophic Systems with Applications

Brains do not reason as digital computers do. Computers reason in clear steps with statements that are either true or false, while humans reason with vague terms of common sense. Neutrosophy is a new branch of philosophy and machine intelligence that deals with neutralities, specifically the idea of indeterminacy that is evident and experienced in our everyday lives. Indeterminacy is interpreted as everything that falls between a concept, idea, statement, declaration, etc. and its opposite. The fundamental thesis of neutrosophy is to employ neutrosophic logic, an extension of fuzzy logic, to incorporate fuzzy truth into complex schemes of formal reasoning. …

Detection And Classification Of Sporadic E Using Convolutional Neural Networks, J. A. Ellis, Daniel J. Emmons, M. B. Cohen

Faculty Publications

In this work, convolutional neural networks (CNN) are developed to detect and characterize sporadic E (E_s), demonstrating an improvement over current methods. This includes a binary classification model to determine if Es is present, followed by a regression model to estimate the Es ordinary mode critical frequency (foEs), a proxy for the intensity, along with the height at which the Es layer occurs (hEs). Signal-to-noise ratio (SNR) and excess phase profiles from six Global Navigation Satellite System (GNSS) radio occultation (RO) missions during the years 2008–2022 are used as the inputs of the model. Intensity (foEs) and the …

Meet Scite, “Chatgpt For Research”, A New Artificial Intelligence (Ai) Tool Available Via Clemson Libraries, Jennifer Groff, Shelby Carroll

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Hiccups And Hallucinations: Critically Engaging Ai In The Design Classroom, Drew Sisk

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

The Use And Misuse Of Generative Ai For Photos And Imagery, Erica B. Walker

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Academic Ethics In Ai-Assisted Writing: A Writing Center-Informed Approach, John Falter

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Navigating Anxiety And Activity: Generative Ai And Writing Support, Chelsea J. Murdock

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Using Generative Artificial Intelligence For Engaged Student Learning, Janice G. Lanham, Charlotte Branyon

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Ghostwriter To Co-Author: Helping Students Leverage Ai In The Classroom, Ishani Banerji

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Optimizing Ideation And Digital Prepress Workflows With Ai Integration, Carl N. Blue

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Requiring Students To Integrate Chatgptinto Course Assignments, Mark Small, Venera Balidemaj

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Using Ai In The Teacher Preparation Programs And Social Studies Classrooms, Brandon Beck

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Language Portraits: A Space To Explore Identities In A Graduate Course, Hazel Vega

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Ai-Enhanced Education: Fostering Creativity, Efficiency, And Future-Ready Skills, Rodger Eugene Bishop

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Critical Ai Engagement: Crafting Assignments That Encourage Productive Engagement With Ai, Carl Ehrett

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Challenging Others When Posting Misinformation: A Uk Vs. Arab Cross-Cultural Comparison On The Perception Of Negative Consequences And Injunctive Norms, Muaadh Noman, Selin Gurgun, Keith Phalp, Preslav Nakov, Raian Ali

Natural Language Processing Faculty Publications

This study investigates the factors influencing the willingness to challenge misinformation on social media across two cultural contexts, the United Kingdom (UK) and Arab countries. A total of 462 participants completed an online survey (250 UK, 212 Arabs). The analysis revealed that three types of negative consequences (relationship cost, negative impact on the person being challenged, futility) and also injunctive norms influence the willingness to challenge misinformation. Cross-cultural comparisons using t-tests showed significant differences between the UK and the Arab countries in all factors except the injunctive norms. Multiple regression analyses identified differences between the UK and Arab participants concerning …

Texcot22, Md Ahmed Al Muzaddid, William J. Beksi

Computer Science and Engineering Datasets - Archive

The TexCot22 dataset is a set of cotton crop video sequences for training and testing multi-object tracking methods. Each tracking sequence is 10 to 20 seconds in length. The dataset contains of a total of 30 sequences of which 17 are for training and the remaining 13 are for testing. Among the training sequences, 2 of them consist of roughly 5,000 annotated images, which can be used to train a cotton boll detection model. The video sequences were captured at 4K resolution and at distinct frame rates (e.g., 10, 15, 30). There are typically 2 to 10 cotton bolls per …