Ryan Benton

Ryan Benton
University of South Alabama | USA · School of Computing

Ph.D. Computer Science

About

89
Publications
30,342
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
342
Citations
Citations since 2016
55 Research Items
274 Citations
2016201720182019202020212022020406080
2016201720182019202020212022020406080
2016201720182019202020212022020406080
2016201720182019202020212022020406080
Introduction
I am currently an Associate Professor within the Computer Science department in School of Computing at the University of South Alabama.
Additional affiliations
August 2015 - present
University of South Alabama
Position
  • Professor (Assistant)
Description
  • Conduct research, pursue funding opportunities and teach students as the undergraduate, master and doctoral levels.
July 2014 - July 2015
University of Louisiana at Lafayette
Position
  • Researcher
Description
  • Within IRI, I conducted research, managed projects, and pursued funding. Three centers comprise IRI: Center for Business & Information Technologies, National Incident Management Systems and Advanced Technologies Institute, and CVDI.
February 2012 - June 2014
University of Louisiana at Lafayette
Position
  • Researcher
Description
  • One of the founders of the center. Part of team that manages the center. Conduct research (within realm of visual and decision informatics), recruit new industry/government members, and seek funding for center activities.
Education
August 1997 - May 2001
University of Louisiana at Lafayette
Field of study
  • Computer Science
August 1995 - May 1997
University of Louisiana at Lafayette
Field of study
  • Computer Science
August 1991 - May 1995
Loyola University New Orleans
Field of study
  • Computer Information Systems

Publications

Publications (89)
Article
Full-text available
Background Persuasive technology is an umbrella term that encompasses software (eg, mobile apps) or hardware (eg, smartwatches) designed to influence users to perform preferable behavior once or on a long-term basis. Considering the ubiquitous nature of mobile devices across all socioeconomic groups, user behavior modification thrives under the per...
Conference Paper
Full-text available
Android devices continue to dominate the market for global smartphone users, thus making them an ideal target for malicious software developers. In the past, side-channel attacks have been used for malicious purposes where attackers monitor system data such as power consumption, electromagnetic emissions, and CPU timing to infer sensitive user info...
Article
Full-text available
Selfish mining is an attack against a blockchain where miners hide newly discovered blocks instead of publishing them to the rest of the network. The selfish miners continue to mine on their private chain while the honest miners waste resources mining on a shorter chain. According to the blockchain protocol, a longer chain takes precedent and short...
Preprint
We developed a computational method for constructing synthetic signal peptides from a base set of signal peptides (SPs) and non-SP sequences. A large number of structured "building blocks", represented as m-step ordered pairs of amino acids, are extracted from the base. Using a straightforward procedure, the building blocks enable the construction...
Article
Full-text available
Modern-day aircraft are flying computer networks, vulnerable to ground station flooding, ghost aircraft injection or flooding, aircraft disappearance, virtual trajectory modifications or false alarm attacks, and aircraft spoofing. This work lays out a data mining process, in the context of big data, to determine flight patterns, including patterns...
Article
Full-text available
Acute respiratory failure (ARF) requiring mechanical ventilation, a complicating factor in sepsis and other disorders, is associated with high morbidity and mortality. Despite its severity and prevalence, treatment options are limited. In light of accumulating evidence that mitochondrial abnormalities are common in ARF, here we applied broad spectr...
Article
Full-text available
Recently, the incidence of hypertension has significantly increased among young adults. While aerobic exercise intervention (AEI) has long been recognized as an effective treatment, individual differences in response to AEI can seriously influence clinicians' decisions. In particular, only a few studies have been conducted to predict the efficacy o...
Conference Paper
Full-text available
Developments in virtual containers, especially in the cloud infrastructure, have led to diversification of jobs that containers are used to support, particularly in the big data and machine learning spaces. The diversification has been powered by the adoption of orchestration systems that marshal fleets of containers to accomplish complex programmi...
Article
Full-text available
The concept of equipment maintenance is older than the industrial revolution. The mode, medium, and timing of maintenance during equipment life cycle have evolved from reactive maintenance to predictive maintenance to prescriptive maintenance. Prescriptive maintenance, which incorporates the Internet of Things, digitization, and artificial intellig...
Article
Full-text available
Background Medical image data, like most patient information, have a strong requirement for privacy and confidentiality. This makes transmitting medical image data, within an open network, problematic, due to the aforementioned issues, along with the dangers of data/information leakage. Possible solutions in the past have included the utilization o...
Article
Full-text available
Background The breathing disorder obstructive sleep apnea syndrome (OSAS) only occurs while asleep. While polysomnography (PSG) represents the premiere standard for diagnosing OSAS, it is quite costly, complicated to use, and carries a significant delay between testing and diagnosis. Methods This work describes a novel architecture and algorithm d...
Article
Full-text available
Conducting digital forensic investigations in a big data distributed file system environment presents significant challenges to an investigator given the high volume of physical data storage space. Presented is an approach from which the Hadoop Distributed File System logical file space is mapped to the physical data location. This approach uses me...
Article
Full-text available
Background: Internet of things is fast becoming the norm in everyday life, and integrating the Internet into medical treatment, which is increasing day by day, is of high utility to both clinical doctors and patients. While there are a number of different health-related problems encountered in daily life, muscle fatigue is a common problem encount...
Article
Full-text available
Background: The medical community uses a variety of data standards for both clinical and research reporting needs. ISO 11179 Common Data Elements (CDEs) represent one such standard that provides robust data point definitions. Another standard is the Biomedical Research Integrated Domain Group (BRIDG) model, which is a domain analysis model that pr...
Conference Paper
Full-text available
Action rule mining develops rules that describe which attributes should be changed in order to move an object from an undesired state to a desired state, with the understanding that some attributes cannot be changed. While such rules can be very useful for end-users, a limitation in prior work is the underlying assumption that the attributes of a d...
Conference Paper
Full-text available
Association mining is the process of discovering relationships between items in a data set, where a group of items forms an itemset. A problem with the typical association mining approach is a large number of the generated frequent itemsets typically do not contain any items of interest to the user. Targeted association mining solves this by only d...
Conference Paper
Full-text available
Many epileptic patients do not respond to medication or surgery. Recent technology has demonstrated that closed-loop responsive neurostimulation therapy is a realistic treatment for epileptic patients. However, ambulatory care of epileptic patients requires a highly accurate automated seizure detection algorithm. In this research, we implement a me...
Conference Paper
Full-text available
Neural networks perform well when they are built for a specific task and the set of inputs and the set of outputs are well defined. However, these results are very limited in scope, and communication between different neural networks to share knowledge that can lead to the performance of more general tasks is still inadequate. Communication between...
Conference Paper
Embedded Systems (ES) underlie society's critical cyberinfrastructure and comprise the vast majority of consumer electronics, making them a prized target for dangerous malware and hardware Trojans. Malicious intrusion into these systems present a threat to national security and economic stability as globalized supply chains and tight network integr...
Chapter
The U.S. Next Generation Air Transportation System (NextGen) is designed to increase the capacity, safety and efficiency of the air traffic control via the integration of past experiences and advances in technology. However, the system is expected to greatly increase the amount and types of data generated as well as the knowledge to be managed. Add...
Article
With the increased assimilation of technology into all aspects of everyday life, rootkits pose a credible threat to individuals, corporations, and governments. Using various techniques, rootkits can infect systems and remain undetected for extended periods of time. This threat necessitates the careful consideration of real-time detection solutions....
Article
With the increased assimilation of technology into all aspects of everyday life, rootkits pose a credible threat to individuals, corporations, and governments. Using various techniques, rootkits can infect systems and remain undetected for extended periods of time. This threat necessitates the careful consideration of real-time detection solutions....
Conference Paper
Action rules are rules that describe how to transition a decision attribute from an undesired state to a desired state, with the understanding that some attributes are stable and others are flexible. Stable attributes, such as “age”, may not be changed, whereas flexible attributes, such as “interest rate”, may be changed. Action rules have great po...
Conference Paper
When analyzing streaming data, the results can depreciate in value faster than the analysis can be completed and results deployed. This is certainly the case in the area of anomaly detection, where detecting a potential problem as it is occurring (or in the early stages) can permit corrective behavior. However, most anomaly detection methods focus...
Conference Paper
For the last decade, the automatic generation of hypothesis from the literature has been widely studied. One common approach is to model biomedical literature as a concept network; then a prediction model is applied to predict the future relationships (links) between pairs of concept. Typically, this link prediction task can be cast into in one of...
Chapter
In order to have faith in the analysis of data, a key factor is to have confidence that the data is reliable. In the case of microRNA, reliability includes understanding the collection methods, ensuring that the analysis is appropriate, and ensuring that the data itself is accurate. A key element in ensuring data accuracy is the removal of noise. W...
Chapter
In recent years, the role of miRNAs in post-transcriptional gene regulation has provided new insights into the understanding of several types of cancers and neurological disorders. Although miRNA research has gathered great momentum since its discovery, traditional biological methods for finding miRNA genes and targets continue to remain a huge cha...
Conference Paper
Full-text available
Information about events happening in the real world are generated online on social media in real-time. There is substantial research done to detect these events using information posted on websites like Twitter, Tumblr, and Instagram. The information posted depends on the type of platform the website relies upon, such as short messages, pictures,...
Conference Paper
Full-text available
Social Media generates information about news and events in real-time. Given the vast amount of data available and the rate of information propagation, reliably identifying events is a challenge. Most state-of-the-art techniques are post hoc techniques that detect an event after it happened. Our goal is to detect onset of an event as it is happenin...
Conference Paper
Adverse drug events (ADEs) are among the leading causes of death in the United States. Although many ADEs are detected during pharmaceutical drug development and the FDA approval process, all of the possible reactions cannot be identified during this period. Currently, post-consumer drug surveillance relies on voluntary reporting systems, such as t...
Conference Paper
This paper presents a flu monitoring system that utilizes prescriptions-based data. It provides evidence-base information that may be "useful" to many users, e.g., Medical professionals, public health administrators, patients, prescription drugs manufacturers, elementary/middle/high schools. The system consists of a real-time flu surveillance engin...
Chapter
This chapter describes a comprehensive granular model for decision making with complex data. This granular model first uses information decomposition to form a horizontal set of granules for each of the data instances. Each granule is a partial view of the corresponding data instance; and collectively all the partial views of that data instance pro...
Article
Analysing and classifying sequences based on similarities and differences is a mathematical problem of escalating relevance and importance in many scientific disciplines. One of the primary challenges in applying machine learning algorithms to sequential data, such as biological sequences, is the extraction and representation of significant feature...
Conference Paper
The task of learning action rules aims to provide recommendations to analysts seeking to achieve a specific change. An action rule is constructed as a series of changes, or actions, which can be made to the flexible characteristics of a given object that ultimately triggers the desired change. Existing action rule discovery methods utilize a genera...
Conference Paper
Recently, with companies and government agencies saving large repositories of time stream/temporal data, there is a large push for adapting association rule mining algorithms for dynamic, targeted querying. In addition, issues with data processing latency and results depreciating in value with the passage of time, create a need for swifter and more...
Conference Paper
Voxel-based analysis of neuroimagery provides a promising source of information for early diagnosis of Alzheimer’s disease. However, neuroimaging procedures usually generate high-dimensional data. This complicates statistical analysis and modeling, resulting in high computational complexity and typically more complicated models. This study uses the...
Conference Paper
Full-text available
Analyzing and classifying sequence data based on structural similarities and differences is a mathematical problem of escalating relevance. Indeed, a primary challenge in designing machine learning algorithms to analyzing sequence data is the extraction and representation of significant features. This paper introduces a generalized sequence feature...
Conference Paper
Clinical trials for interventions that seek to delay the onset of Alzheimer’s disease (AD) are hampered by inadequate methods for selecting study subjects who are at risk, and who may therefore benefit from the interventions being studied. Automated monitoring tools may facilitate clinical research and thereby reduce the impact of AD on individuals...
Conference Paper
Voxel-based analysis of neuroimagery provides a promising source of information for early diagnosis of Alzheimer’s disease. However, neuroimaging procedures usually generate high-dimensional data. This complicates statistical analysis and modeling, resulting in high computational complexity and typically more complicated models. This study uses the...
Article
Alzheimer's Disease (AD) is one major cause of dementia. Previous studies have indicated that the use of features derived from Positron Emission Tomography (PET) scans lead to more accurate and earlier diagnosis of AD, compared to the traditional approaches that use a combination of clinical assessments. In this study, we compare Naive Bayes (NB) w...
Article
Alzheimer's disease (AD) is one major cause of dementia. Previous studies have indicated that the use of features derived from Positron Emission Tomography (PET) scans lead to more accurate and earlier diagnosis of AD, compared to the traditional approaches that use a combination of clinical assessments. In this study, we compare Naive Bayes (NB) w...
Conference Paper
The itemset tree data structure is used in targeted association mining to �find rules within a user's sphere of interest. In our earlier work, we proposed two enhancements to unordered itemset trees. The first enhancement consisted of sorting all nodes in lexical order based upon the itemsets they contain. In the second enhancement, called the Min-...
Conference Paper
The goal of association mining is to find potentially interesting rules in large repositories of data. Unfortunately using a minimum support threshold, a standard practice to improve the association mining processing complexity, can allow some of these rules to remain hidden. This occurs because not all rules which have high confidence have a high...