Hayden Wimmer

Georgia Southern University | GSU · Department of Information Technology

As the amount of data available in the health sector continues to grow in the era of information overload, it becomes increasingly crucial than ever to communicate essential information concisely. The vast amount of textual data from electronic health records can overwhelm healthcare professionals, reducing the time they can dedicate to patient car...

Generative Artificial Intelligence (AI) model is a revolutionary type of AI capable of producing high quality images based on textual inputs. These models utilize natural language processing (NLP) techniques and computer vision to understand and interpret the textual descriptions and then generate images that align with the given descriptions. This...

Phishing and spam have been a cybersecurity threat with the majority of breaches resulting from these types of social engineering attacks. Therefore, detection has been a long‐standing challenge for both academic and industry researcher. New and innovative approaches are required to keep up with the growing sophistication of threat actors. One such...

Virtual reality (VR) in education has gained momentum in recent years, presenting both promises and challenges. This technology can be found in many areas of learning, but its use is deficient in marketing education. VR technology has improved to offer many choices and is within reach regarding cost and implementation. This study presents and revie...

In the modern world, emerging hazards not only attack computers but also steal personal information and financial resources. The most widely used means of interaction lately are emails and text messages, and as the percentage of emails increases, so does the amount of spam and phishing. Spam is any type of unwanted, unauthorized electronic communic...

Phishing and spam detection is a long standing challenge that has been the subject of much academic research. Large Language Models (LLM) have vast potential to transform society and provide new and innovative approaches to solve well-established challenges. Phishing and spam have caused financial hardships and lost time and resources to email user...

The significance of adopting cloud technology in enterprises is accelerating and becoming ubiquitous in business and industry. Due to migrating the on-premises servers and services into cloud, companies can leverage several advantages such as cost optimization, high performance, and flexible system maintenance, to name a few. As the data volume, va...

Botnets have become a vital security problem on the Internet as such attacks lead to fraud, spam, identity theft, and information leakage. No intelligent classification knowledge graph of Botnets has been created for integration into AI applications. We address this by integrating concepts from cybersecurity into AI. Using an ontology model, we des...

Websites are growing in number and size at an explosive rate. This has created an enormous field of service competitors, which can cause a real challenge for information seekers and inexperienced users. As a result, these users require public information to help their decision about service selection. This aid comes in the form of clear and accessi...

Due to the speedy rate, constant increase in the size, and type of data generated per second globally, industries up to the organizational level are experiencing multiple difficulties of not being able to analyze, understand and interpret data after data generation to aid in making effective decisions or forecasts, owing to the raw form in which th...

This study uses a novel theoretical approach that combines two multidimensional service quality models that focus on customer satisfaction, perceived value, and customer loyalty as outcomes of service quality in the context of mobile banking. Additionally, the study assesses the potential moderating effects of switching costs between mobile banking...

The escalating rate and sheer volume of global data generation pose challenges for industries in comprehending and leveraging this data for decision-making. To address this, machine learning, a branch of artificial intelligence, is employed to process and analyze large datasets. This research project focuses on utilizing supervised learning algorit...

With the law enforcement closure of Silk Road, an increasing number of crypto-markets surfaced at a rapid rate. Taking an interest in this kind of market, multiple studies were conducted using different techniques and tools to collect the data. This data ranged from the kind of drugs being traded, how long the seller was active and the number of tr...

Knowledge portals are a method to provide integrated access to users of multiple systems through a single-entry point. A large body of literature exists on knowledge portals; however, the only published literature reviews are outdated, as they only cover material prior to the 21st century. The purpose of this article is to present review on some ma...

Artificial intelligence techniques have long been applied to financial investing scenarios to determine market inefficiencies, criteria for credit scoring, and bankruptcy prediction, to name a few. While there are many subfields to artificial intelligence, this work seeks to identify the most commonly applied AI techniques to financial investing as...

A review of the literature highlights the ways in which information technology offers opportunities in long-term care, an area of research and application that might be called gerotechnology. The authors reviewed eight books about long-term care to find evidence of the possibilities for information technology. That led to the hypothesis that qualit...

The practice of including online discussion posts to traditional courses is increasing. Online discussions allow for active learning to occur as students express their ideas and respond to others. The time and thought provided by online discussion posts allows students to utilize higher level cognitive skills. Web-based assessments are another tech...

In IS research, there is a dichotomy where design science and behavioral science are distinct research paradigms. IS researchers should view these paradigms as complementary with research drawing upon the strengths of both, yet few have done so. This work demonstrates how design science and behavioral science can be united in IS research via counte...

Data science is a relatively new and emerging field with strong job growth projections. In this work, we develop a new theoretical model based on the theory of planned behavior and the IS Success Model in order to understand public perceptions about data science. Specifically, we aim to determine the potential impact and if the public views data sc...

Higher education increasingly relies on course assessment; however, it is challenging to cover all course and assessed content. Homework has been linked to increased student performance and may be a solution to covering or reinforcing key course and assessed concepts. Instructor time and resources are limited, making additional grading challenging....

The Semantic Web is inherently multi-disciplinary and many domains have taken advantage of semantic technologies. Yet, the geosciences are one of the fields leading the way in Semantic Web adoption and validation. Astronomy, Earth science, hydrology, and solar-terrestrial physics have seen a noteworthy amount of semantic integration. The geoscience...

In today's digital and technical environment, employers are looking for personnel that can contribute to the organization not only with the use of technical skills but can also express their expertise with the use of positive emotional intelligence and communication effectiveness. As research is lacking in the investigation of soft skills used by i...

A decision tree program for forecasting stock performance is applied to Compustat's Global financial statement data augmented with International Monetary Fund data. The hypothesis is that certain Compustat variables will be most used by the decision tree program and will provide insight as to how to make investing decisions. Surprisingly, the autho...

Evidence based medicine is the modern standard for clinical decision making where the use of medical evidence combined with clinical expertise and research are leveraged for clinical decisions. Supporting evidence based medicine (EBM) and clinical decision making (CDM) requires access to accurate predictive models and a multi-dimensional patient vi...

The authors are currently developing integrated ERP and CRM courses based on the Microsoft Dynamics platform (chosen in part because the authors’ institution has a pre-existing membership in the Dynamics Academic Alliance). Students will co-register in both ERP and CRM with projects, assessments, and instructors flowing between courses to provide t...

The Hour of Code is a one-hour introduction to computer science organized by Code.org, a non-profit dedicated to expanding participation in computer science. This study investigated the im-pact of the Hour of Code on students' attitudes towards computer programming and their knowledge of programming. A sample of undergraduate students from two univ...

In today’s global economy, understanding the leadership behavior of employees in cross-cultural context is strategically important as the workforce has become highly culturally diverse. This paper investigates the leadership orientations of people in the culture of Germany and Oman. Using univariate analysis of variance (two-way ANOVA) to analyze 4...

Distribution of deceptive counterfeit goods via online marketplaces such as Amazon and eBay has introduced a particularly burdensome decision making process for the consumers. The consumers need to spend additional time in the information search step, reading product and seller reviews to assist with counterfeit detection. Automated counterfeit det...

Good knowledge would be expected to help a knowledge-based algorithm more than bad knowledge. In this research, the precise effect of good versus bad knowledge on evolutionary algorithms is explored. The testable hypothesis of this paper is that good knowledge will have a significant effect on the evolutionary mutation process, whereas bad knowledg...

While research has been conducted in machine learning algorithms and in privacy preserving in data mining (PPDM), a gap in the literature exists which combines the aforementioned areas to determine how PPDM affects common machine learning algorithms. The aim of this research is to narrow this literature gap by investigating how a common PPDM algori...

As uncertainty plagues the economic landscape, many individuals have posed the question “How can I be my own boss?” or “How can I be successful and self-reliant?” Many have considered creating products only to be discouraged by the labyrinth of legal regulations or to be discouraged by friends, colleagues, and family. Patricia Nola-Brown’s book Ide...

There is no single data source for financial data. Integrating financial data sources reveals multiple challenges such as lack of a common terminology as well as trust and quality concerns resulting from a lack of knowledge concerning the origins of data. This research proposes a conceptual methodology to integrate data from multiple sources such a...

Research has been conducted on distributed data mining, privacy preserving data mining, and multiagent systems; however, integrating the aforementioned research areas require further investigation. Sensitive data sources, such as healthcare organizations, may be reluctant to permit sensitive data to leave the source or permit mining of the sensitiv...

The concept of ontologies has been around for millennia and spans many domains and disciplines. Ontologies are a powerful concept when applied to intelligent computing. Ontologies are the backbone of intelligent computing on the World Wide Web and crucial in many decision-support situations. Many sophisticated tools have been developed to support w...

Determining which attributes may be employed for predicting the market capitalization of a business firm is a challenging task which may benefit from research intersecting principles of accounting and finance with information technology. In our approach, information technology in the form of decision trees and genetic algorithms is applied to funda...

Ontology learning aims to automatically extract ontological concepts and relationships from related text repositories and is expected to be more efficient and scalable than manual ontology development. One of the challenging issues associated with ontology learning is word sense disambiguation (WSD). Most WSD research employs resources such as Word...

There has been a plethora of research in the area of knowledge portals, knowledge warehouses, ontologies, ontology creation and mapping, as well as the automatic creation and mapping of ontologies. While research exists in each respective area there is a lack of conceptual models that will integrate ontologies as a tool for disparate data source in...

This paper provides an integrated and comprehensive conceptual framework for knowledge based decision making support systems. Previous research has focused primarily on general decision support systems. The paper extends the previous work by presenting a framework to support specific decisions using knowledge marts that contain decision pertinent k...

Ontologies are the backbone of intelligent computing on the World Wide Web but also crucial in many decision support situations. Many sophisticated tools have been developed to support working with ontologies, including prominently exploiting the vast array of existing ontologies. A system called ALIGN is developed that demonstrates how to use free...