Game-Theoretic Analysis Of Effort Allocation Of Contributors To Public Projects, Jared Soundy, Chenhao Wang, Clay Stevens, Hau Chan

School of Computing: Conference and Workshop Papers

Public projects can succeed or fail for many reasons such as the feasibility of the original goal and coordination among contributors. One major reason for failure is that insufficient work leaves the project partially completed. For certain types of projects anything short of full completion is a failure (e.g., feature request on software projects in GitHub). Therefore, project success relies heavily on individuals allocating sufficient effort. When there are multiple public projects, each contributor needs to make decisions to best allocate his/her limited effort (e.g., time) to projects while considering the effort allocation decisions of other strategic contributors and his/her …

Nlp Is Not Enough - Contextualization Of User Input In Chatbots, Nathan Dolbir, Triyasha Dastidar, Kaushik Roy

Publications

AI chatbots have made vast strides in technology improvement in recent years and are already operational in many industries. Advanced Natural Language Processing techniques, based on deep networks, efficiently process user requests to carry out their functions. As chatbots gain traction, their applicability in healthcare is an attractive proposition due to the reduced economic and people costs of an overburdened system. However, healthcare bots require safe and medically accurate information capture, which deep networks aren’t yet capable of due to user text and speech variations. Knowledge in symbolic structures is more suited for accurate reasoning but cannot handle natural language …

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 …

Semantics Of The Black-Box: Can Knowledge Graphs Help Make Deep Learning Systems More Interpretable And Explainable?, Manas Gaur, Keyur Faldu, Amit Sheth

Publications

The recent series of innovations in deep learning (DL) have shown enormous potential to impact individuals and society, both positively and negatively. The DL models utilizing massive computing power and enormous datasets have significantly outperformed prior historical benchmarks on increasingly difficult, well-defined research tasks across technology domains such as computer vision, natural language processing, signal processing, and human-computer interactions. However, the Black-Box nature of DL models and their over-reliance on massive amounts of data condensed into labels and dense representations poses challenges for interpretability and explainability of the system. Furthermore, DLs have not yet been proven in their ability to …

Simulation For Cybersecurity: State Of The Art And Future Directions, Hamdi Kavak, Jose J. Padilla, Daniele Vernon-Bido, Saikou Y. Diallo, Ross Gore, Sachin Shetty

VMASC Publications

In this article, we provide an introduction to simulation for cybersecurity and focus on three themes: (1) an overview of the cybersecurity domain; (2) a summary of notable simulation research efforts for cybersecurity; and (3) a proposed way forward on how simulations could broaden cybersecurity efforts. The overview of cybersecurity provides readers with a foundational perspective of cybersecurity in the light of targets, threats, and preventive measures. The simulation research section details the current role that simulation plays in cybersecurity, which mainly falls on representative environment building; test, evaluate, and explore; training and exercises; risk analysis and assessment; and humans …

Modeling The Effects Of Religious Belief And Affiliation On Prosociality, Luke Galen, Ross Gore, F. Leron Shults

VMASC Publications

To what extent do supernatural beliefs, group affiliation, and social interaction produce values and behaviors that benefit others, i.e., prosociality? Addressing this question involves multiple variables interacting within complex social networks that shape and constrain the beliefs and behaviors of individuals. We examine the relationships among some of these factors utilizing data from the World Values Survey to inform the construction of an Agent-Based Model. The latter was able to identify the conditions under which - and the mechanisms by which - the prosociality of simulated agents was increased or decreased within an "artificial society" designed to reflect real world …

Human Factors, Ergonomics And Industry 4.0 In The Oil & Gas Industry: A Bibliometric Analysis, Francesco Longo, Antonio Padovano, Lucia Gazzaneo, Jessica Frangella, Rafael Diaz

VMASC Publications

Over the last few years, the Human Factors and Ergonomics (HF/E) discipline has significantly benefited from new human-centric engineered digital solutions of the 4.0 industrial age. Technologies are creating new socio-technical interactions between human and machine that minimize the risk of design-induced human errors and have largely contributed to remarkable improvements in terms of process safety, productivity, quality, and workers’ well-being. However, despite the Oil&Gas (O&G) sector is one of the most hazardous environments where human error can have severe consequences, Industry 4.0 aspects are still scarcely integrated with HF/E. This paper calls for a holistic understanding of the changing …

Developing An Artificial Intelligence Framework To Assess Shipbuilding And Repair Sub-Tier Supply Chains Risk, Rafael Diaz, Katherine Smith, Beatriz Acero, Francesco Longo, Antonio Padovano

VMASC Publications

The defense shipbuilding and repair industry is a labor-intensive sector that can be characterized by low-product volumes and high investments in which a large number of shared resources, technology, suppliers, and processes asynchronously converge into large construction projects. It is mainly organized by the execution of a complex combination of sequential and overlapping stages. While entities engaged in this large-scale endeavor are often knowledgeable about their first-tier suppliers, they usually do not have insight into the lower tiers suppliers. A sizable part of any supply chain disruption is attributable to instabilities in sub-tier suppliers. This research note conceptually delineates a …

Scheduling Based Optimization In Software Defined Radio And Wireless Networks, Nathan Daniel Price

Doctoral Dissertations

"The objective of this work is to enable dynamic sharing of software-defined radio (SDR) transceivers through the concepts of hardware virtualization and real-time resource management. SDR is a way to build a digital radio that consists of a software back-end for digital signal processing (DSP) and an analog front-end transceiver for waveform generation and reception. This work proposes the use of a virtualization layer to decouple back-end SDR software from front-end transceivers. With this arrangement, front-ends are said to be virtualized, and it becomes possible to share a limited number of front-ends among many SDR back-ends through different multiplexing techniques. …

Energy Considerations In Blockchain-Enabled Applications, Cesar Enrique Castellon Escobar

UNF Graduate Theses and Dissertations

Blockchain-powered smart systems deployed in different industrial applications promise operational efficiencies and improved yields, while mitigating significant cybersecurity risks pertaining to the main application. Associated tradeoffs between availability and security arise at implementation, however, triggered by the additional resources (e.g., memory, computation) required by each blockchain-enabled host. This thesis applies an energy-reducing algorithmic engineering technique for Merkle Tree root and Proof of Work calculations, two principal elements of blockchain computations, as a means to preserve the promised security benefits but with less compromise to system availability. Using pyRAPL, a python library to measure computational energy, we experiment with both the …

Open Voting Client Architecture And Op-Ed Voting: A Novel Framework For Solving Requirement Conflicts In Secret Ballot Elections, Aaron M. Wilson

UNF Graduate Theses and Dissertations

Building voting systems for secret ballot elections has many challenges and is the subject of significant academic research efforts. These challenges come from conflicting requirements. In this paper, we introduce a novel architectural approach to voting system construction that may help satisfy conflicting requirements and increase voter satisfaction. Our design, called Open Voting Client Architecture, defines a voting system architectural approach that can harness the power of individualized voting clients. In this work, we contribute a voting system reference architecture to depict the current voting system construction and then use it to define Open Voting Client Architecture. We then detail …

An Sdn-Coordinated Multipath Transmission Steering Framework, Kiattikun Kawila

Chulalongkorn University Theses and Dissertations (Chula ETD)

Data transfer is a primary mechanism that can directly affect the overall performance of Big Data analytic systems. This is because most data are generated from several locations. It has been challenging to collect and transfer data among multiple storage regions. Using the traditional single-path transfer approaches is not efficient to serve several requirements of Big Data applications. In this dissertation, we propose an SDN-coordinated multipath transmission steering framework for Big Data transfer application. Multipath TCP protocol (MPTCP) and SDN architecture are mainly considered to design and develop our multipath transmission framework. To provide a practical routing solution, we propose …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

Strategies For Catalyzing Clinicians’ Support Of Telemedicine Programs In Rural Communities, Jonathan Liwag

Walden Dissertations and Doctoral Studies

Clinicians’ failure to accept contemporary technology has been a critical barrier to telemedicine program adoption. Staff technical challenges and resistance to change can affect technology return on investment, which concerns telemedicine program leaders. Grounded in Davis’s technology acceptance model, the purpose of this qualitative, descriptive single case study was to explore strategies used by program leaders in the Marianas Islands who successfully gained clinicians’ acceptance of contemporary technology. The participants were 5 program leaders recommended by their institution because of their leadership role and telemedicine technologies experience. Data were collected from 4 face-to-face and 1 audio teleconference interview with the …

Strategies For Catalyzing Clinicians’ Support Of Telemedicine Programs In Rural Communities, Jonathan Liwag

Walden Dissertations and Doctoral Studies

Clinicians’ failure to accept contemporary technology has been a critical barrier to telemedicine program adoption. Staff technical challenges and resistance to change can affect technology return on investment, which concerns telemedicine program leaders. Grounded in Davis’s technology acceptance model, the purpose of this qualitative, descriptive single case study was to explore strategies used by program leaders in the Marianas Islands who successfully gained clinicians’ acceptance of contemporary technology. The participants were 5 program leaders recommended by their institution because of their leadership role and telemedicine technologies experience. Data were collected from 4 face-to-face and 1 audio teleconference interview with the …

Human-Robot Interaction For Assistive Robotics, Jiawei Li

Dissertations

This dissertation presents an in-depth study of human-robot interaction (HRI) withapplication to assistive robotics. In various studies, dexterous in-hand manipulation is included, assistive robots for Sit-To-stand (STS) assistance along with the human intention estimation. In Chapter 1, the background and issues of HRI are explicitly discussed. In Chapter 2, the literature review introduces the recent state-of-the-art research on HRI, such as physical Human-Robot Interaction (HRI), robot STS assistance, dexterous in hand manipulation and human intention estimation. In Chapter 3, various models and control algorithms are described in detail. Chapter 4 introduces the research equipment. Chapter 5 presents innovative theories and …

Performance Optimization Of Big Data Computing Workflows For Batch And Stream Data Processing In Multi-Clouds, Huiyan Cao

Dissertations

Workflow techniques have been widely used as a major computing solution in many science domains. With the rapid deployment of cloud infrastructures around the globe and the economic benefits of cloud-based computing and storage services, an increasing number of scientific workflows have migrated or are in active transition to clouds. As the scale of scientific applications continues to grow, it is now common to deploy various data- and network-intensive computing workflows such as serial computing workflows, MapReduce/Spark-based workflows, and Storm-based stream data processing workflows in multi-cloud environments, where inter-cloud data transfer oftentimes plays a significant role in both workflow performance …

Semantic, Integrated Keyword Search Over Structured And Loosely Structured Databases, Xinge Lu

Dissertations

Keyword search has been seen in recent years as an attractive way for querying data with some form of structure. Indeed, it allows simple users to extract information from databases without mastering a complex structured query language and without having knowledge of the schema of the data. It also allows for integrated search of heterogeneous data sources. However, as keyword queries are ambiguous and not expressive enough, keyword search cannot scale satisfactorily on big datasets and the answers are, in general, of low accuracy. Therefore, flat keyword search alone cannot efficiently return high quality results on large data with structure. …