Digital Commons Network^™

Preparing Uk Students For The Workplace: The Acceptability Of A Gamified Cybersecurity Training, Oliver J. Mason, Siobhan Collman, Stella Kazamia, Ioana Boureanu

Journal of Cybersecurity Education, Research and Practice

This pilot study aims to assess the acceptability of Open University’s training platform called Gamified Intelligent Cyber Aptitude and Skills Training course (GICAST), as a means of improving cybersecurity knowledge, attitudes, and behaviours in undergraduate students using both quantitative and qualitative methods. A mixed-methods, pre-post experimental design was employed. 43 self-selected participants were recruited via an online register and posters at the university (excluding IT related courses). Participants completed the Human Aspects of Information Security Questionnaire (HAIS-Q) and Fear of Missing Out (FoMO) Scale. They then completed all games and quizzes in the GICAST course before repeating the HAIS-Q and …

Unmc Ai Task Force Report, Emily Glenn, Rachel Lookadoo, Unmc Ai Task Force

Reports: University of Nebraska Medical Center

In July 2023, University of Nebraska Medical Center and Nebraska Medicine leadership charged a task force with investigating facets of artificial intelligence (AI) in an academic health center setting. What must we know, do and plan for regarding generative artificial intelligence in the domains of enhancing education, research, clinical care, business functions and in combating misinformation/disinformation? Task force members were allocated into five subcommittees to investigate key points to inform strategic planning—Enhance Learning, Enhance Research, Enhance Clinical Care, Enhance Business Function and Combat Dis-/Mis-Information and Bias. This work was aligned with the UNMC Strategic Planning process as a “big rock” …

Offenseval 2023: Offensive Language Identification In The Age Of Large Language Models, Marcos Zampieri, Sara Rosenthal, Preslav Nakov, Alphaeus Dmonte, Tharindu Ranasinghe

Natural Language Processing Faculty Publications

The OffensEval shared tasks organized as part of SemEval-2019-2020 were very popular, attracting over 1300 participating teams. The two editions of the shared task helped advance the state of the art in offensive language identification by providing the community with benchmark datasets in Arabic, Danish, English, Greek, and Turkish. The datasets were annotated using the OLID hierarchical taxonomy, which since then has become the de facto standard in general offensive language identification research and was widely used beyond OffensEval. We present a survey of OffensEval and related competitions, and we discuss the main lessons learned. We further evaluate the performance …

Recognition Of Arabic Air-Written Letters: Machine Learning, Convolutional Neural Networks, And Optical Character Recognition (Ocr) Techniques, Khalid Nahar, Izzat Alsmadi, Rabia Emhamed Al Mamlook, Ahmad Nasayreh, Hasan Gharaibeh, Ali Saeed Almuflih, Fahad Alasim

All Faculty Scholarship (Archived)

Air writing is one of the essential fields that the world is turning to, which can benefit from the world of the metaverse, as well as the ease of communication between humans and machines. The research literature on air writing and its applications shows significant work in English and Chinese, while little research is conducted in other languages, such as Arabic. To fill this gap, we propose a hybrid model that combines feature extraction with deep learning models and then uses machine learning (ML) and optical character recognition (OCR) methods and applies grid and random search optimization algorithms to obtain …

Intelligent Biomedical Image Classification In A Big Data Architecture Using Metaheuristic Optimization And Gradient Approximation, Laila Almutairi, Ahed Abugabah, Hesham Alhumyani, Ahmed A. Mohamed

All Works

Medical imaging has experienced significant development in contemporary medicine and can now record a variety of biomedical pictures from patients to test and analyze the illness and its severity. Computer vision and artificial intelligence may outperform human diagnostic ability and uncover hidden information in biomedical images. In healthcare applications, fast prediction and reliability are of the utmost importance parameters to assure the timely detection of disease. The existing systems have poor classification accuracy, and higher computation time and the system complexity is higher. Low-quality images might impact the processing method, leading to subpar results. Furthermore, extensive preprocessing techniques are necessary …

Emerging Sensing, Imaging, And Computational Technologies To Scale Nano-To Macroscale Rhizosphere Dynamics – Review And Research Perspectives, Amir H. Ahkami, Odeta Qafoku, Tiina Roose, Quanbing Mou, Yi Lu, Zoe G. Cardon, Yuxin Wu, Chunwei Chou, Joshua B. Fisher, Tamas Varga, Pubudu Handakumbura, Jayde A. Aufrecht, Arunima Bhattacharjee, James J. Moran

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The soil region influenced by plant roots, i.e., the rhizosphere, is one of the most complex biological habitats on Earth and significantly impacts global carbon flow and transformation. Understanding the structure and function of the rhizosphere is critically important for maintaining sustainable plant ecosystem services, designing engineered ecosystems for long-term soil carbon storage, and mitigating the effects of climate change. However, studying the biological and ecological processes and interactions in the rhizosphere requires advanced integrated technologies capable of decoding such a complex system at different scales. Here, we review how emerging approaches in sensing, imaging, and computational modeling …

Evaluating The Efficacy Of Chatgpt In Navigating The Spanish Medical Residency Entrance Examination (Mir): Promising Horizons For Ai In Clinical Medicine., Francisco Guillen-Grima, Sara Guillen-Aguinaga, Laura Guillen-Aguinaga, Rosa Alas-Brun, Luc Onambele, Wilfrido Ortega, Rocio Montejo, Enrique Aguinaga-Ontoso, Paul Barach, Ines Aguinaga-Ontoso

Department of Medicine Faculty Papers

UNLABELLED: The rapid progress in artificial intelligence, machine learning, and natural language processing has led to increasingly sophisticated large language models (LLMs) for use in healthcare. This study assesses the performance of two LLMs, the GPT-3.5 and GPT-4 models, in passing the MIR medical examination for access to medical specialist training in Spain. Our objectives included gauging the model's overall performance, analyzing discrepancies across different medical specialties, discerning between theoretical and practical questions, estimating error proportions, and assessing the hypothetical severity of errors committed by a physician.

MATERIAL AND METHODS: We studied the 2022 Spanish MIR examination results after excluding …

“...I Have My Dad, Sister, Brother, And Mom’S Password”: Unveiling Users’ Mental Models Of Security And Privacy-Preserving Tools, Prakriti Dumaru, Ankit Shrestha, Rizu Paudel, Cassity Haverkamp, Maryellen Mcclain Verdoes, Mahdi Nasrullah Al-Ameen

Computer Science Student Research

Purpose: Security and privacy-preserving tools (for brevity, we term them as ‘security tools’ in this paper, unless otherwise specified) are designed to protect the security and privacy of people in the digital environment. However, inappropriate use of these tools can lead to unexpected consequences that are preventable. Hence, it is significant to examine why users do not understand the security tools.

Methodology: We conducted a qualitative study with 40 participants in the USA to investigate the prevalent misconceptions of people regarding security tools, their perceptions of data access, and the corresponding impact on their usage behavior and data protection strategies. …

Hybrid Flexible (Hyflex) Learning Space Design And Implementation At Graduate Level: An Iterative Process, David Santandreu Calonge, Mark Thompson, Leisa Hassock, Mohammad Yaqub

Computer Vision Faculty Publications

This paper investigates the process of designing HyFlex classrooms at Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), a graduate-level research university located in Abu Dhabi, United Arab Emirates, underpinned by the application of the EDUCAUSE Learning Space Rating System (LSRS). This investigation takes the form of a case-study and specifically focuses on the rationale, planning, design, and technology behind the implementation of the flexible HyFlex spaces as deployed in several classroom environments at MBZUAI. Iterations’ performance was assessed with the LSRS—V3. The findings should make an important contribution to the field of HyFlex learning spaces and technology-enhanced classroom design …

Towards Designing A Knowledge Sharing System For Higher Learning Institutions In The Uae Based On The Social Feature Framework, S. M. F. D. Syed Mustapha, Edmund Evangelista, Farhi Marir

All Works

Numerous ICT instruments, such as communication tools, social media platforms, and collaborative software, bolster and facilitate knowledge sharing activities. Determining the vital success factors for knowledge sharing within its unique context is argued to be essential before implementing it. Therefore, it is imperative to define domain-specific critical success factors when envisioning the design of a knowledge sharing system. This research paper introduces the blueprint for an Academic Knowledge Sharing System (AKSS), rooted in an essential success framework tailored to knowledge sharing to deploy within an academic institution. In this regard, an extensive exploration of the relevant literature led to the …

Domain Specific Feature Representation Learning For Diverse Temporal Data, Farhan Asif Chowdhury

Computer Science ETDs

Humans can leverage domain context to recognize novel patterns and categories based on limited known examples. In contrast, computational learning methods are not adept at exploiting context and require sufficient labeled examples to achieve similar accuracy. Many temporal data domain, for example, seismic signals and oil mining sensor data, requires domain expert annotation, which is both costly and time-consuming. The dependency on training data limits the applicability of machine learning algorithms for domains with limited labeled data. This dissertation aims to address this gap by developing temporal mining algorithms that exploit domain context to learn discriminative feature representation from limited …

Building A Diverse Cybersecurity Workforce: A Study On Attracting Learners With Varied Educational Backgrounds, Mubashrah Saddiqa, Kristian Helmer Kjær Larsen1 Helmer Kjær Larsen, Robert Nedergaard Nielsen, Jens Myrup Pedersen

Journal of Cybersecurity Education, Research and Practice

Cybersecurity has traditionally been perceived as a highly technical field, centered around hacking, programming, and network defense. However, this article contends that the scope of cybersecurity must transcend its technical confines to embrace a more inclusive approach. By incorporating various concepts such as privacy, data sharing, and ethics, cybersecurity can foster diversity among audiences with varying educational backgrounds, thereby cultivating a richer and more resilient security landscape. A more diverse cybersecurity workforce can provide a broader range of perspectives, experiences, and skills to address the complex and ever-evolving threats of the digital age. The research focuses on enhancing cybersecurity education …

A Parallel Algorithm For Updating A Multi-Objective Shortest Path In Large Dynamic Networks, Arindam Khanda, S. M. Shovan, Sajal K. Das

Computer Science Faculty Research & Creative Works

In dynamic networks, where continuous topological changes are prevalent, it becomes paramount to find and update different graph properties without the computational burden of recalculating from the ground up. However finding or updating a multi-objective shortest path (MOSP) in such a network is challenging, as it involves simultaneously optimizing multiple (conflicting) objectives. In light of this, our paper focuses on shortest path search and proposes parallel algorithms tailored specifically for large incremental graphs. We first present an efficient algorithm that updates the single-objective shortest path (SOSP) whenever a new set of edges are introduced. Leveraging this SOSP update algorithm, we …

The Process Of Adapting Innovations In Banking Services By Businesses In Kosovo, Burim Isa Berisha Dr.Sc, Burim Berisha B.B

International Journal of Business and Technology

This dissertation addresses the importance of a business model from businesses in Kosovo, which is able to adapt innovations from the banking sector such as digital services, and through which become part of a global market where such developments occur step by step. very fast At the beginning of this paper will be given definitions related to the main concepts that are addressed such as business model, innovations in banking services - digitalization of services and the role and importance of linking a business model with banking services of the time. After the theoretical part, from which the main concepts …

Agency Theory And Audit Quality, Burim Isa Berisha Bb

International Journal of Business and Technology

Auditing plays a vital role in reducing both: information asymmetry by empirically confi rming the validity of fi nancial statements and agency problems. The principal- agent confl ict illustrated in agency theory, where principal (owner) lack reasons to believe their agents (managers) because of information asymmetries and contradictory motives. Information asymmetry deals with the study of decisions in transactions where one party has more or superior information than other. Agents (either directors or auditors) may be trustworthy without further incentives to align interest or monitoring strategies such as audit or increased regulation. However, the simple agency model would recommend that …

The Process Of Adapting Innovations In Banking Services By Businesses In Kosovo, Burim Isa Berisha Dr.Sc, Burim Berisha B.B

International Journal of Business and Technology

This dissertation addresses the importance of a business model from businesses in Kosovo, which is able to adapt innovations from the banking sector such as digital services, and through which become part of a global market where such developments occur step by step. very fast At the beginning of this paper will be given definitions related to the main concepts that are addressed such as business model, innovations in banking services - digitalization of services and the role and importance of linking a business model with banking services of the time. After the theoretical part, from which the main concepts …

All Quiet On The Digital Front: The Unseen Psychological Impacts On Cybersecurity First Responders, Tammie R. Hollis

USF Tampa Graduate Theses and Dissertations

Driven by the increasing frequency of cyberattacks and the existing talent gap between industry needs and skilled professionals, this research study focused on the crucial human element in the domain of cybersecurity incident response. The objective of this dissertation was to offer a meaningful exploration of the lived experiences encountered by cybersecurity incident responders and an assessment of the subsequent impacts on their well-being. Additionally, this study sought to draw comparisons between the experiences of cybersecurity incident responders and their counterparts in traditional emergency response roles. Semi-structured interviews were conducted with a cohort of 22 individuals with first-hand experience working …

The Fast And The Curious: Accelerating Literature Reviews With Ai, Jennifer Freer, Natalia Tingle Dolan, Gabrielle Wiersma

Presentations and other scholarship

As the world of academic research shifts gears into the digital age, AI-powered tools are beginning to shape the scholarly landscape. Just as high-performance vehicles transformed the world of car racing, AI-powered tools like scite, Elicit, and Research Rabbit have the potential to revolutionize the traditional literature review process. This presentation will accelerate your understanding of AI literature review tools and how these technologies can turbocharge the research process. Navigating between traditional library tools and AI-powered systems can be like choosing the right vehicle for the race. AI tools can enhance the speed, depth, and breadth of literature reviews, allowing …

Big Data Analytics For Healthcare Social Media: New Algorithms And Insights, Negar Maleki

USF Tampa Graduate Theses and Dissertations

Over the last two decades, there has been a rapid evolution in information and communication technology, including the emergence of social media. Social media has a significant impact on various fields such as politics, business, culture, education, careers, innovation, and especially healthcare. This influence is not a new phenomenon since a survey from ten years ago showed that up to 78\% of American adults used the internet to look for health-related information for themselves or someone else. With the shift towards on-demand services in society, healthcare is also affected by this trend. Instead of waiting for weeks or months to …

Human Vs Machine: Hyper-Realistic Avatars And Their Efficacy As A Communication Channel, Jill S. Schiefelbein

USF Tampa Graduate Theses and Dissertations

Hyper-realistic avatars (HRAs), a form of synthetic media, are custom-created digital embodiments of a human, created by capturing and combining that person’s video and vocal likeness. This is the first known study of the efficacy of videos delivered by hyper-realistic avatars as a communication channel in comparison to videos delivered by their human counterparts. An experiment testing how information retention, engagement, and trust vary between viewers of videos delivered by a real human, videos delivered by the HRA representing that same human, and videos delivered by the HRA that discloses to viewers that it is a hyper-realistic avatar is presented. …

Preface: Special Issue On Nlp Approaches To Offensive Content Online, Marcos Zampieri, Isabelle Augenstein, Siddharth Krishnan, Joshua Melton, Preslav Nakov

Natural Language Processing Faculty Publications

No abstract provided.

The Age Of Synthetic Realities: Challenges And Opportunities, João Phillipe Cardenuto, Jing Yang, Rafael Padilha, Renjie Wan, Daniel Moreira, Haoliang Li, Shiqi Wang, Fernanda Andaló, Sébastien Marcel, Anderson Rocha

Computer Science: Faculty Publications and Other Works

Synthetic realities are digital creations or augmentations that are contextually generated through the use of Artificial Intelligence (AI) methods, leveraging extensive amounts of data to construct new narratives or realities, regardless of the intent to deceive. In this paper, we delve into the concept of synthetic realities and their implications for Digital Forensics and society at large within the rapidly advancing field of AI. We highlight the crucial need for the development of forensic techniques capable of identifying harmful synthetic creations and distinguishing them from reality. This is especially important in scenarios involving the creation and dissemination of fake news, …

Bridging Domain Gaps For Cross-Spectrum And Long-Range Face Recognition Using Domain Adaptive Machine Learning, Cedric Armel Nimpa Fondje

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Face recognition technology has witnessed significant advancements in recent decades, enabling its widespread adoption in various applications such as security, surveillance, and biometrics applications. However, one of the primary challenges faced by existing face recognition systems is their limited performance when presented with images from different modalities or domains( such as infrared to visible, long range to close range, nighttime to daytime, profile to f rontal, etc.) Additionally, advancements in camera sensors, analytics beyond the visible spectrum, and the increasing size of cross-modal datasets have led to a particular interest in cross-modal learning for face recognition in the biometrics and …

Deciphering Trends And Tactics: Data-Driven Techniques For Forecasting Information Spread And Detecting Coordinated Campaigns In Social Media, Kin Wai Ng Lugo

USF Tampa Graduate Theses and Dissertations

The main objective of this dissertation is to develop models that predict and investigate the spread of information in social media over time. In this context, we consider topics of discussions as the information that spreads. Thus, we are interested in forecasting the number of messages per day in a future interval of time. We take a data-driven approach, in which we compare our results with real datasets from a multitude of socio-political contexts and from multiple social media platforms, specifically, Twitter and YouTube.

We identified a number of challenges related to forecasting social media time series per topic. First, …

Green Synthesized Silver Nanoparticles-Based Sensing For Monitoring Water Pollution: An Updated Review, Muhamad Allan Serunting, Muhammad Ali Zulfikar, Henry Setiyanto, Dian Ayu Setyorini, Vienna Saraswaty

Karbala International Journal of Modern Science

Water is a basic human need and has been heavily contaminated. Therefore, it becomes a concern to remove the pollutant and monitor its quality. The removal methods include precipitation, filtration, adsorption, and photodegradation. Meanwhile, the monitoring can be done by measuring and analyzing the contaminant using spectrophotometry and chromatography. Nevertheless, those methods usually need a complicated preparation, and are expensive. Thus, a simple method is necessary to overcome these drawbacks by developing a sensor. In recent years, the sensor performance has been enhanced by using nanomaterials, such as silver nanoparticles (AgNPs). AgNPs can be synthesized using plant extracts through a …

Synthesis And Characterization Of Zirconium Oxide Nanoparticles Using Z. Officinale And S. Aromaticum Plant Extracts For Antibacterial Application, M. J. Tuama, M. F. A. Alias

Karbala International Journal of Modern Science

Abstract The dramatic rise in bacterial infections and increased resistance to conventional antibiotics has led to the exploration of biologically derived nanomaterials to counteract bacterial activity. Nanotechnology, which deals with materials at the atomic or molecular level, is a promising way to achieve this goal. Zirconium oxide nanoparticles (ZrO2NPs) have shown strong antibacterial effects due to the increased surface-to-volume ratio at the nanoscale. This study focused on the production of ZrO2NPs in an environmentally friendly manner, which included extracts from Zingiber officinale (ginger), where G-ZrO2NPs were produced, and Syzygium aromaticum (clove), which produced S-ZrO2NPs. Various techniques were used, such as …

Enhancing Search Engine Results: A Comparative Study Of Graph And Timeline Visualizations For Semantic And Temporal Relationship Discovery, Muhammad Shahiq Qureshi

Electronic Theses and Dissertations

In today’s digital age, search engines have become indispensable tools for finding information among the corpus of billions of webpages. The standard that most search engines follow is to display search results in a list-based format arranged according to a ranking algorithm. Although this format is good for presenting the most relevant results to users, it fails to represent the underlying relations between different results. These relations, among others, can generally be of either a temporal or semantic nature. A user who wants to explore the results that are connected by those relations would have to make a manual effort …

Limitations And Possibilities Of Digital Restoration Techniques Using Generative Ai Tools: Reconstituting Antoine François Callet’S Achilles Dragging Hector’S Body Past The Walls Of Troy, Charles O'Brien, James Hutson, Trent Olsen, Jay Ratican

Faculty Scholarship

Digital restoration offers new avenues for conserving historical artworks, yet presents unique challenges. This research delves into the balance between traditional restoration methods and the use of generative artificial intelligence (AI) tools, using Antoine François Callet’s portrayal of Achilles Dragging Hector’s Body Past the Walls of Troy as a case study. The application of Easy Diffusion and Stable Diffusion 2.1 technologies provides insights into AI-driven restoration methods such as inpainting and colorization. Results indicate that while AI can streamline the restoration process, repeated inpainting can compromise the painting’s color quality and detailed features. Furthermore, the AI approach occasionally introduces unintended …

Healthaichain: Improving Security And Safety Using Blockchain Technology Applications In Ai-Based Healthcare Systems, Naresh Kshetri, James Hutson, Revathy G

Faculty Scholarship

Blockchain as a digital ledger for keeping records of digital transactions and other information, it is secure and decentralized technology. The globally growing number of digital population every day possesses a significant threat to online data including the medical and patients’ data. After bitcoin, blockchain technology has emerged into a general-purpose technology with applications in medical industries and healthcare. Blockchain can promote highly configurable openness while retaining the highest security standards for critical data of medical patients. Referred to as distributed record keeping for healthcare systems which makes digital assets unalterable and transparent via a cryptographic hash and decentralized network. …

Designing Secure Mental Healthcare Chatbots For Older Adults, Aishwarya Surani

Electronic Theses and Dissertations

The landscape of mental health support has evolved as a result of the rising demand for digital mental healthcare services. Users now have an opportunity to seek mental health support online due to the growth of digital platforms. For those looking for mental health treatments, chatbots have evolved as user-friendly, accessible platforms that provide remote access and convenience. However, for chatbots to be effective, users must divulge personal and sensitive information, such as demographics, insurance information, and a history of mental illness. While chatbots offer services to a variety of demographic users, older adults face unique challenges related to usability, …