Case Study: Transition To A Vegan Diet In An Elite Male Gaelic Football Player, Daniel Davey, Shane Malone, Brendan Egan

Articles

Vegan diets are increasingly of interest to athletes, but require a well-planned approach in order to mitigate the risk of potential adverse effects on nutrient intakes, and consequently performance. This case study reports the process of an elite male Gaelic football player (age 25 years; height, 1.88 m; body mass, 87.8 kg; lean body mass, 73.26 kg; body fat, 11.3%) transitioning from an omnivorous diet to a vegan diet at the beginning of a competitive season. The report encompasses key considerations in the planning and provision of nutrition support in this context, in addition to iterations needed based on challenges …

Are Entrepreneurial Capabilities And Prior Knowledge The Silver Bullet For The Generation Of New Digital Venture Ideas In A Digital Context?, Meifang Yao, Dan Ye, Gao Yang, Hui Shi, Xianrong Zheng

Information Technology & Decision Sciences Faculty Publications

Digital technology has had an important impact on entrepreneurship. It has changed the uncertain nature of the process of new venture idea generation, and it has also brought unprecedented opportunities for the generation of new digital venture ideas. In order to explore how startups can deal with major challenges brought by digital technology and create new digital venture ideas, this paper focuses on micro level entrepreneurial actions and constructs a theoretical model of the relationship among networking capabilities, IT capabilities, prior knowledge, and new digital venture ideas. Furthermore, through the hierarchical linear regression analysis of 278 sample data, the paper …

A Systematic Review Of Convolutional Neural Network-Based Structural Condition Assessment Techniques, Sandeep Sony, Kyle Dunphy, Ayan Sadhu, Miriam A M Capretz

Electrical and Computer Engineering Publications

With recent advances in non-contact sensing technology such as cameras, unmanned aerial and ground vehicles, the structural health monitoring (SHM) community has witnessed a prominent growth in deep learning-based condition assessment techniques of structural systems. These deep learning methods rely primarily on convolutional neural networks (CNNs). The CNN networks are trained using a large number of datasets for various types of damage and anomaly detection and post-disaster reconnaissance. The trained networks are then utilized to analyze newer data to detect the type and severity of the damage, enhancing the capabilities of non-contact sensors in developing autonomous SHM systems. In recent …

Video Analysis And Verification Of Direct Head Impacts Recorded By Wearable Sensors In Junior Rugby League Players, Lauchlan Carey, Douglas P. Terry, Andrew S. Mcintosh, Peter Stanwell, Grant L. Iverson, Andrew J. Gardner

Research outputs 2014 to 2021

Background: Rugby league is a high-intensity collision sport that carries a risk of concussion. Youth athletes are considered to be more vulnerable and take longer to recover from concussion than adult athletes. Purpose: To review head impact events in elite-level junior representative rugby league and to verify and describe characteristics of X-patchTM-recorded impacts via video analysis. Study Design: Observational case series. Methods: The X-patchTM was used on twenty-one adolescent players (thirteen forwards and eight backs) during a 2017 junior representative rugby league competition. Game-day footage, recorded by a trained videographer from a single camera, was synchronised with X-patchTM-recorded timestamped events. …

Save-T: Safety Analysis Visualization And Evaluation Tool, Yuan Zhu, Sami Demiroluk, Kaan Ozbay, Kun Xie, Hong Yang, Di Sha

Civil & Environmental Engineering Faculty Publications

Traffic crashes are one of the biggest issues which constitute a threat to lives of the motorists and disrupt operations of the transportation system. To reduce the number of crashes and alleviate their impacts, it is necessary to scrutinize the factors contributing to the risk of traffic crashes. Lately, visual analytics tools become very popular for data exploration and obtaining insights from the data. In this paper, a new web-based data visualization tool called Safety Analysis Visualization and Evaluation Tool (SAVE-T) was introduced. This tool enables users to interactively create queries and visually explore the results. By utilizing an online …

Green Underwater Wireless Communications Using Hybrid Optical-Acoustic Technologies, Kazi Y. Islam, Iftekhar Ahmad, Daryoush Habibi, M. Ishtiaque A. Zahed, Joarder Kamruzzaman

Research outputs 2014 to 2021

Underwater wireless communication is a rapidly growing field, especially with the recent emergence of technologies such as autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs). To support the high-bandwidth applications using these technologies, underwater optics has attracted significant attention, alongside its complementary technology – underwater acoustics. In this paper, we propose a hybrid opto-acoustic underwater wireless communication model that reduces network power consumption and supports high-data rate underwater applications by selecting appropriate communication links in response to varying traffic loads and dynamic weather conditions. Underwater optics offers high data rates and consumes less power. However, due to the severe …

Class Distribution-Aware Adaptive Margins And Cluster Embedding For Classification Of Fruit And Vegetables At Supermarket Self-Checkouts, Khurram Hameed, Douglas Chai, Alexander Rassau

Research outputs 2014 to 2021

The complex task of vision based fruit and vegetables classification at a supermarket self-checkout poses significant challenges. These challenges include the highly variable physical features of fruit and vegetables i.e. colour, texture shape and size which are dependent upon ripeness and storage conditions in a supermarket as well as general product variation. Supermarket environments are also significantly variable with respect to lighting conditions. Attempting to build an exhaustive dataset to capture all these variations, for example a dataset of a fruit consisting of all possible colour variations, is nearly impossible. Moreover, some fruit and vegetable classes have significant similar physical …

Enabling Machine Learning On The Edge Using Sram Conserving Efficient Neural Networks Execution Approach, Bharath Sudharsan, Pankesh Patel, John G. Breslin, Muhammad Intizar Ali

Publications

Edge analytics refers to the application of data analytics and Machine Learning (ML) algorithms on IoT devices. The concept of edge analytics is gaining popularity due to its ability to perform AI-based analytics at the device level, enabling autonomous decision-making, without depending on the cloud. However, the majority of Internet of Things (IoT) devices are embedded systems with a low-cost microcontroller unit (MCU) or a small CPU as its brain, which often are incapable of handling complex ML algorithms.

In this paper, we propose an approach for the ecient execution of already deeply compressed, large neural networks (NNs) on tiny …

Distributed Cross-Community Collaboration For The Cloud-Based Energy Management Service, Yu-Wen Chen, J. Morris Chang

Publications and Research

Customers’ participation is a critical factor for inte-grating the distributed energy resources via demand response and demand-side management programs, especially when customers become prosumers. Incentives need to be delivered by the energy management service to attract prosumers to operate their distributed energy resources and electricity loads grid-friendly actively. The cloud-based energy management service enables virtual trading for customers within the same community to minimize cost and smooth the fluctuation. With the potential fast-growing number of service providers and customers, the needs exist for efficiently collaborating across multiple service providers and customers. This paper proposes the distributed cross-community collaboration (XCC) for …

Cooperative Target Tracking In Concentric Formations, Lili Ma

Publications and Research

This paper considers the problem of coordinating multiple unmanned aerial vehicles (UAVs) in a circular formation around a moving target. The main contribution is allowing for versatile formation patterns on the basis of the following components. Firstly, new uniform spacing control laws are proposed that spread the agents not necessarily over a full circle, but over a circular arc. Uniform spacing formation controllers are proposed, regulating either the separation distances or the separation angles between agents. Secondly, the use of virtual agents is proposed to allow for different radii in agents’ orbits. Thirdly, a hierarchical combination of formation patterns is …

Detecting Interlocutor Confusion In Situated Human-Avatar Dialogue: A Pilot Study, Na Li, John D. Kelleher, Robert J. Ross

Conference papers

In order to enhance levels of engagement with conversational systems, our long term research goal seeks to monitor the confusion state of a user and adapt dialogue policies in response to such user confusion states. To this end, in this paper, we present our initial research centred on a user-avatar dialogue scenario that we have developed to study the manifestation of confusion and in the long term its mitigation. We present a new definition of confusion that is particularly tailored to the requirements of intelligent conversational system development for task-oriented dialogue. We also present the details of our Wizard-of-Oz based …

Ieee Access Special Section Editorial: Trends And Advances In Bio-Inspired Image-Based Deep Learning Methodologies And Applications, Peter Peer, Carlos M. Travieso-Gonzalez, Vijayan K. Asari, Malay Kishore Dutta

Electrical and Computer Engineering Faculty Publications

Many of the technological advances we enjoy today have been inspired by biological systems due to their ease of operation and outstanding efficiency. Designing technological solutions based on biological inspiration has become a cornerstone of research in a variety of areas ranging from control theory and optimization to computer vision, machine learning, and artificial intelligence. Especially in the latter few areas, biologically relevant solutions are becoming increasingly important as we look for new ways to make artificial systems more efficient, intelligent, and overall effective.

Dales Objects: A Large Scale Benchmark Dataset For Instance Segmentation In Aerial Lidar, Nina M. Singer, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

We present DALES Objects, a large-scale instance segmentation benchmark dataset for aerial lidar. DALES Objects contains close to half a billion hand-labeled points, including semantic and instance segmentation labels. DALES Objects is an extension of the DALES (Varney et al., 2020) dataset, adding additional intensity and instance segmentation annotation. This paper provides an overview of the data collection, preprocessing, hand-labeling strategy, and final data format. We propose relevant evaluation metrics and provide insights into potential challenges when evaluating this benchmark dataset. Finally, we provide information about how researchers can access the dataset for their use at go.udayton.edu/dales3d.

Quantum Clustering Drives Innovations: A Bibliometric And Patentometric Analysis, Shradha Deshmukh, Preeti Mulay

Library Philosophy and Practice (e-journal)

The paper presents a bibliometric analysis from 2014 to 2020 of the emerging and engaging field of quantum computing called Quantum Machine Learning (QML). The study discusses the analysis results from the comprehensive high indexed databases worldwide such as Institute of Electrical and Electronics Engineers (IEEE), Scopus, Web of Science (WOS), Google Scholar and the Association for Computing Machinery (ACM). Tools like iMapbuilder, IBM and SPSS Statistics are used to provide meaningful insights and flawless representations of the extracted data. There has been little research to provide a macroscopic overview of renowned authors, subject areas, funding agencies and patent applications …

Demystifying Artificial Intelligence Based Behavior Prediction Of Traffic Actors For Autonomous Vehicle- A Bibliometric Analysis Of Trends And Techniques, Suresh Sudam Kolekar, Shilpa Shailesh Gite, Biswajeet Pradhan

Library Philosophy and Practice (e-journal)

Background: The purpose of this study is to examine, using bibliometric methods, the work done on behavior prediction of traffic actors for autonomous vehicles using various artificial intelligence algorithms from 2011 to 2020.

Methods: Using one of the most common databases, Scopus, numerous papers on behavior prediction of traffic actors for autonomous vehicles were retrieved. The research papers are being considered for the period from 2011 to 2020. The Scopus analyzer is used to obtain some results of the study, such as documents by year, source, and country and so on. VOSviewer Version 1.6.16 is used for the analysis of …

Converting Optical Videos To Infrared Videos Using Attention Gan And Its Impact On Target Detection And Classification Performance, Mohammad Shahab Uddin, Reshad Hoque, Kazi Aminul Islam, Chiman Kwan, David Gribben, Jiang Li

Electrical & Computer Engineering Faculty Publications

To apply powerful deep-learning-based algorithms for object detection and classification in infrared videos, it is necessary to have more training data in order to build high-performance models. However, in many surveillance applications, one can have a lot more optical videos than infrared videos. This lack of IR video datasets can be mitigated if optical-to-infrared video conversion is possible. In this paper, we present a new approach for converting optical videos to infrared videos using deep learning. The basic idea is to focus on target areas using attention generative adversarial network (attention GAN), which will preserve the fidelity of target areas. …

Covid-19 And Biocybersecurity's Increasing Role On Defending Forward, Xavier Palmer, Lucas N. Potter, Saltuk Karahan

Electrical & Computer Engineering Faculty Publications

The evolving nature of warfare has been changing with cybersecurity and the use of advanced biotechnology in each aspect of the society is expanding and overlapping with the cyberworld. This intersection, which has been described as “biocybersecurity” (BCS), can become a major front of the 21st-century conflicts. There are three lines of BCS which make it a critical component of overall cybersecurity: (1) cyber operations within the area of BCS have life threatening consequences to a greater extent than other cyber operations, (2) the breach in health-related personal data is a significant tool for fatal attacks, and (3) health-related misinformation …

Hr Process Automation: A Bibliometric Analysis, Shubham Mishra, Monica Kunte, Netra Neelam, Sanjay Bhattacharya, Preeti Mulay

Library Philosophy and Practice (e-journal)

Automation is interpreted as the replacement of manual operations by electronics and computer-controlled systems. Human resource management is an indispensable part of every firm be it the space of retail, healthcare, education or any other sector. Activities such as hiring new workers, training, or making sure that local labour laws are obeyed with HR processes and are a crucial part of every organisation. HR has typically been believed of as an extremely manual department procedure. Employees are accustomed to doing this manually and getting the job done themselves. But everything around the HR processes are changing rapidly. HR Automation is …

The First Amendment, Common Carriers, And Public Accommodations: Net Neutrality, Digital Platforms, And Privacy, Christopher S. Yoo

All Faculty Scholarship

Recent prominent judicial opinions have assumed that common carriers have few to no First Amendment rights and that calling an actor a common carrier or public accommodation could justify limiting its right to exclude and mandating that it provide nondiscriminatory access. A review of the history reveals that the underlying law is richer than these simple statements would suggest. The principles for determining what constitutes a common carrier or a public accommodation and the level of First Amendment protection both turn on whether the actor holds itself out as serving all members of the public or whether it asserts editorial …

On The (Im)Practicality Of Adversarial Perturbation For Image Privacy, Arezoo Rajabi, Rakesh B. Bobba, Mike Rosulek, Charles Wright, Wu-Chi Feng

Computer Science Faculty Publications and Presentations

Image hosting platforms are a popular way to store and share images with family members and friends. However, such platforms typically have full access to images raising privacy concerns. These concerns are further exacerbated with the advent of Convolutional Neural Networks (CNNs) that can be trained on available images to automatically detect and recognize faces with high accuracy.

Recently, adversarial perturbations have been proposed as a potential defense against automated recognition and classification of images by CNNs. In this paper, we explore the practicality of adversarial perturbation based approaches as a privacy defense against automated face recognition. Specifically, we first …

Human Characteristics Impact On Strategic Decisions In A Human-In-The-Loop Simulation, Andrew J. Collins, Shieda Etemadidavan

Engineering Management & Systems Engineering Faculty Publications

In this paper, a hybrid simulation model of the agent-based model and cooperative game theory is used in a human-in-the-loop experiment to study the effect of human demographic characteristics in situations where they make strategic coalition decisions. Agent-based modeling (ABM) is a computational method that can reveal emergent phenomenon from interactions between agents in an environment. It has been suggested in organizational psychology that ABM could model human behavior more holistically than other modeling methods. Cooperative game theory is a method that models strategic coalitions formation. Three characteristics (age, education, and gender) were considered in the experiment to see if …

Blockchain For A Resilient, Efficient, And Effective Supply Chain, Evidence From Cases, Adrian Gheorghe, Farinaz Sabz Ali Pour, Unal Tatar, Omer Faruk Keskin

Engineering Management & Systems Engineering Faculty Publications

In the modern acquisition, it is unrealistic to consider single entities as producing and delivering a product independently. Acquisitions usually take place through supply networks. Resiliency, efficiency, and effectiveness of supply networks directly contribute to the acquisition system's resiliency, efficiency, and effectiveness. All the involved firms form a part of a supply network essential to producing the product or service. The decision-makers have to look for new methodologies for supply chain management. Blockchain technology introduces new methods of decentralization and delegation of services, which can transform supply chains and result in a more resilient, efficient, and effective supply chain. This …

Ship Deck Segmentation In Engineering Document Using Generative Adversarial Networks, Mohammad Shahab Uddin, Raphael Pamie-George, Daron Wilkins, Andres Sousa Poza, Mustafa Canan, Samuel Kovacic, Jiang Li

Engineering Management & Systems Engineering Faculty Publications

Generative adversarial networks (GANs) have become very popular in recent years. GANs have proved to be successful in different computer vision tasks including image-translation, image super-resolution etc. In this paper, we have used GAN models for ship deck segmentation. We have used 2D scanned raster images of ship decks provided by US Navy Military Sealift Command (MSC) to extract necessary information including ship walls, objects etc. Our segmentation results will be helpful to get vector and 3D image of a ship that can be later used for maintenance of the ship. We applied the trained models to engineering documents provided …

Administrative Law In The Automated State, Cary Coglianese

All Faculty Scholarship

In the future, administrative agencies will rely increasingly on digital automation powered by machine learning algorithms. Can U.S. administrative law accommodate such a future? Not only might a highly automated state readily meet longstanding administrative law principles, but the responsible use of machine learning algorithms might perform even better than the status quo in terms of fulfilling administrative law’s core values of expert decision-making and democratic accountability. Algorithmic governance clearly promises more accurate, data-driven decisions. Moreover, due to their mathematical properties, algorithms might well prove to be more faithful agents of democratic institutions. Yet even if an automated state were …

Development Of A Real Time Human Face Recognition Software System, Askar Boranbayev, Seilkhan Boranbayev, Mukhamedzhan Amirtaev, Malik Baimukhamedov, Askar Nurbekov

Physics and Astronomy Faculty Publications and Presentations

In this study, a system for real-time face recognition was built using the Open Face tools of the Open CV library. The article describes the methodology for creating the system and the results of its testing. The Open CV library has various modules that perform many tasks. In this paper, Open CV modules were used for face recognition in images and face identification in real time. In addition, the HOG method was used to detect a person by the front of his face. After performing the HOG method, 128 face measurements were obtained using the image encoding method. A convolutional …

A Bibliometric Analysis On Optimization Of Application Layer Protocols In The Internet Of Things, Sagar Jaikar

Library Philosophy and Practice (e-journal)

Internet of Things (IoT), getting popular day by day, thanks to the every object that has been made intelligent and started communicated among themselves with ease. These objects are equipped with sensors and capable of connecting and exchanging the application data over the Internet. While the application data is getting exchanged among these intelligent objects smoothly, there are various concerns with these intelligent objects like they are constrained when it comes to resources like memory, processing capability, power consumption etc. In this regard many attempts are made to enhance or to optimize existing messaging protocols so that we can get …

Bibliometric Review On Image Based Plant Phenotyping, Shrikrishna Ulhas Kolhar, Jayant Jagtap

Library Philosophy and Practice (e-journal)

Plant phenotyping is a quantitative description of structural, physiological and temporal traits of plants resulting from interaction of plant genotypes with the environment. A rapid development is in progress in the field of image-based plant phenotyping. Plant phenotyping has wide range of applications in plant breeding research, plant growth prediction, biotic and abiotic stress analysis, crop management and early disease detection. The main motive is to provide detailed bibliometric review in order to know the available literature and current research trends in the area of plant phenotyping using plant images. The bibliometric analysis is primarily based on Scopus, web of …

Predictive Maintenance Of Bearing Machinery Using Simulation- A Bibliometric Study, Karan Gulati Mr., Keshav Basandrai Mr., Shubham Tiwari Mr., Pooja Kamat Prof., Satish Kumar Dr.

Library Philosophy and Practice (e-journal)

Modelling is a way of constructing a virtual representation of software and hardware that involves a real-world device. We will discover the behaviour of the system if the software elements of this model are guided by mathematical relationships. For testing conditions that may be difficult to replicate with hardware prototypes alone, modelling and simulation are particularly useful, especially in the early phase of the design process when hardware might not be available. Model-based approach in MATLAB-Simulink can be useful for predictive maintenance of machines as it can reduce unplanned downtimes and maintenance costs when industrial equipment breaks. Through this bibliometric …

Clustering School Libraries In Indonesia Using C4.5 And K-Means Algorithm, Dian Wardiana Sjuchro, Rulinawaty Rulinawaty, Fathurrahim Fathurrahim, Danu Eko Agustinova, Rima Herlina S Siburian, Pandu Adi Cakranegara, Ardianto Ardianto, Robbi Rahim

Library Philosophy and Practice (e-journal)

This research is to analyze the data mining by analyzing clusters formed. This study was about determining the number of libraries available at the primary and junior high school levels in Indonesia. The main role of libraries is in the current implementation of quality education. The data are from the central statistics agency which contains 34 records indicating the number of libraries at the primary and junior high school levels. The proposed method is a combination of the C4.5 and k-means methods. clustering is performed based on the number of clusters (k). Thus, the results will be classified according to …

Assessment Of The Privacy And Security Practices Of The Indian Academic Websites, Chanlang Ki Bareh

Library Philosophy and Practice (e-journal)

The study presents the comprehensive assessment of the Indian Institutions of National Importance (IoNI) website’s privacy and security practices. These 130 IoNI websites were selected because of the status conferred to premier institutions by the Government of India. This empirical study was based on webometric methods that assessed the quantitative aspects of information technologies structures on the web. The study also employed content analysis for analyzing the sites privacy policies. The assessment reveals numerous security vulnerabilities like the adoption of HTTPS may not always provide better protection to their users because 39 websites do not have TLS encrypted connection; still …