Physical Sciences and Mathematics Commons^™

On The Effects Of Information Asymmetry In Digital Currency Trading, Kwansoo Kim, Robert John Kauffman

Research Collection School Of Computing and Information Systems

We report on two studies that examine how social sentiment influences information asymmetry in digital currency markets. We also assess whether cryptocurrency can be an investment vehicle, as opposed to only an instrument for asset speculation. Using a dataset on transactions from an exchange in South Korea and sentiment from Korean social media in 2018, we conducted a study of different trading behavior under two cryptocurrency trading market microstructures: a bid-ask spread dealer's market and a continuous trading buy-sell, immediate trade execution market. Our results highlight the impacts of positive and negative trader social sentiment valences on the effects of …

Pdf Malware Detection: Toward Machine Learning Modeling With Explainability Analysis, G. M.Sakhawat Hossain, Kaushik Deb, Helge Janicke, Iqbal H. Sarker

Research outputs 2022 to 2026

The Portable Document Format (PDF) is one of the most widely used file types, thus fraudsters insert harmful code into victims' PDF documents to compromise their equipment. Conventional solutions and identification techniques are often insufficient and may only partially prevent PDF malware because of their versatile character and excessive dependence on a certain typical feature set. The primary goal of this work is to detect PDF malware efficiently in order to alleviate the current difficulties. To accomplish the goal, we first develop a comprehensive dataset of 15958 PDF samples taking into account the non-malevolent, malicious, and evasive behaviors of the …

Teaching Analytics Online: A Self-Study Of Professional Practice, Andrew J. Collins, Brandon Butler, James F. Leathrum Jr., Christopher J. Lynch

Engineering Management & Systems Engineering Faculty Publications

As the COVID-19 pandemic caused severe disruption to education enterprises throughout the world, the main response by educational institutions was to move to online learning environments. The purpose of this study was to understand better how instructors could improve online learning for a professional-level week-long short course in a highly technical area (data analytics), which had, pre-COVID, been a hands-on computer, laboratory-based learning experience. The authors used self-study of professional practice to elicit and understand the major issues and concerns of the transition to an online learning environment. Under the guidance of a colleague in teacher education, three course instructors …

Sports Data Science Job Requirements, Cam E. Morse

Student Publications

Data science is an extremely fast growing field in which job opportunities are opening in every industry related to data science. Within the data science field is the sports data science industry which has it's own requirements and specificities that may not be present in other industries. In this paper, research is done using multiple job posting websites such as LinkedIn, Indeed, Sportstek jobs, and TeamworkOnline to explore the job descriptions of many different sports data science jobs. These job descriptions are then examined using Python coding to find the frequencies of specific data science skills in the various job …

Green Data Analytics Of Supercomputing From Massive Sensor Networks: Does Workload Distribution Matter?, Zhiling Guo, Jin Li, Ram Ramesh

Research Collection School Of Computing and Information Systems

Energy costs represent a significant share of the total cost of ownership in high performance computing (HPC) systems. Using a unique data set collected by massive sensor networks in a peta scale national supercomputing center, we first present an explanatory model to identify key factors that affect energy consumption in supercomputing. Our analytic results show that, not only does computing node utilization significantly affect energy consumption, workload distribution among the nodes also has significant effects and could effectively be leveraged to improve energy efficiency. Next, we establish the high model performance using in-sample and out-of-sample analyses. We then develop prescriptive …

Governing Smart Cities As Knowledge Commons - Introduction, Chapter 1 & Conclusion, Brett M. Frischmann, Michael J. Madison, Madelyn Sanfilippo

Book Chapters

Smart city technology has its value and its place; it isn’t automatically or universally harmful. Urban challenges and opportunities addressed via smart technology demand systematic study, examining general patterns and local variations as smart city practices unfold around the world. Smart cities are complex blends of community governance institutions, social dilemmas that cities face, and dynamic relationships among information and data, technology, and human lives. Some of those blends are more typical and common. Some are more nuanced in specific contexts. This volume uses the Governing Knowledge Commons (GKC) framework to sort out relevant and important distinctions. The framework grounds …

It’S Your Turn, Are You Ready To Get Vaccinated? Towards An Exploration Of Vaccine Hesitancy Using Sentiment Analysis Of Instagram Posts, Mohammed Talha Alam, Shahab Saquib Sohail, Syed Ubaid, Shakil, Zafar Ali, Mohammad Hijji, Abdul Khader Jilani Saudagar, Khan Muhammad

Computer Vision Faculty Publications

The deadly threat caused by the rapid spread of COVID-19 has been restricted by virtue of vaccines. However, there is misinformation regarding the certainty and positives outcome of getting vaccinated; hence, many people are reluctant to opt for it. Therefore, in this paper, we identified public sentiments and hesitancy toward the COVID-19 vaccines based on Instagram posts as part of intelligent surveillance. We first retrieved more than 10k publicly available comments and captions posted under different vaccine hashtags (namely, covaxin, covishield, and sputnik). Next, we translated the extracted comments into a common language (English), followed by the calculation of the …

Prospects For Legal Analytics: Some Approaches To Extracting More Meaning From Legal Texts, Kevin D. Ashley

University of Cincinnati Law Review

No abstract provided.

Industrial Digital Twins At The Nexus Of Nextg Wireless Networks And Computational Intelligence: A Survey, Shah Zeb, Aamir Mahmood, Syed Ali Hassan, Md. Jalil Piran, Mikael Gidlund, Mohsen Guizani

Machine Learning Faculty Publications

By amalgamating recent communication and control technologies, computing and data analytics techniques, and modular manufacturing, Industry 4.0 promotes integrating cyber–physical worlds through cyber–physical systems (CPS) and digital twin (DT) for monitoring, optimization, and prognostics of industrial processes. A DT enables interaction with the digital image of the industrial physical objects/processes to simulate, analyze, and control their real-time operation. DT is rapidly diffusing in numerous industries with the interdisciplinary advances in the industrial Internet of things (IIoT), edge and cloud computing, machine learning, artificial intelligence, and advanced data analytics. However, the existing literature lacks in identifying and discussing the role and …

An Exploration In Health Analytics: Pediatric Burns, Care Policy Assessment And Interrupted Time Series, Chao Wang

2022

Healthcare systems globally face multiple challenges in the face of population growth and changes in disease pathology. With regard to the rising demand of the healthcare and the global threats of the pandemic, the medical datasets can be trained further to develop preventive methods. Meanwhile, policy reforms of health systems could be a critical aspect to deal with the public crisis and concerns. However, two basic problems must be addressed first: identification of key factors on a priority basis and evaluation of changes.

Thus, the paper presents a series of trials on the application of data analytics to health-related problems, …

Antitrust By Algorithm, Cary Coglianese, Alicia Lai

All Faculty Scholarship

Technological innovation is changing private markets around the world. New advances in digital technology have created new opportunities for subtle and evasive forms of anticompetitive behavior by private firms. But some of these same technological advances could also help antitrust regulators improve their performance in detecting and responding to unlawful private conduct. We foresee that the growing digital complexity of the marketplace will necessitate that antitrust authorities increasingly rely on machine-learning algorithms to oversee market behavior. In making this transition, authorities will need to meet several key institutional challenges—building organizational capacity, avoiding legal pitfalls, and establishing public trust—to ensure successful …

Data Analytics For Sustainable Food And Agriculture Systems, Megan Lord Reavis

Graduate Theses and Dissertations

The increasing concentration of anthropogenic greenhouse gases in the atmosphere is altering the climate, posing a serious threat to global agriculture and food security. Agriculture and food production contribute a quarter of all GHG emissions produced, so there is a critical need to limit emissions in this area while increasing food production to feed the anticipated 10 billion people by 2050. To address the needs of the future, data-driven solutions are needed to guide decision-making and provide support for actionable climate mitigation and survival strategies. Research efforts must be focused on analyzing problems on multiple scales, identifying new ways to …

Data Analytics In Hotel And Integrated Resort Brands: An Evaluation Of Past Literature And Proposed Research For The Future, Luke Andrew Walocko

UNLV Theses, Dissertations, Professional Papers, and Capstones

Data analytics in hotel and integrated resort brands is a growing strategy implemented to support business decisions designed to generate revenue or save costs. This study utilizes a literature review of data analytics related publications to provide recommendations on future research topics to improve the quality of literature related to data analytics in hotel and integrated resort brands. The study is not limited to hospitality specific research and uses research from all industries to identify gaps in publications for hospitality scholars to explore. Three proposed research questions for future exploration were composed based on the comparison of literature written for …

Transforming Businesses With E-Commerce Intelligence, Yuanto Kusnadi, Gary Pan

Research Collection School Of Accountancy

2020 had been an extraordinary year as the Covid-19 pandemic struck almost all countries in the world and created an extraordinary impact on businesses worldwide. Singapore and many other Southeast Asian countries were not spared and had to implement lockdowns swiftly. To cope with physical store closures and the increased volume of online transactions, most businesses tried to revamp their business models and set up online stores to capitalise on the rise of the e-commerce wave. With the growing trend of online transactions, it has become imperative for companies operating in the Fast Moving Consumer Goods (FMCG) industry to track …

A Web Application To Disseminate Repatriation And Travel Information About African Countries, Daniel Otuo-Acheampong

Theses, Dissertations and Culminating Projects

Africa is a continent with incredibly diversified cultures, landscapes, and people. Due its vastness, it can be difficult to assess accurate travel related information about African countries. The purpose of this project is to build a website that will serve as an African destination information insider. African countries are drawing people from all around the world, and this is evident in the formulation of initiatives to attract people to the continent during the past decade. Prime examples of these initiatives include Ghana’s Year of Return initiative and Nigeria’s door of return. This project, that entails the design and development of …

Enhancing Healthcare Professional And Caregiving Staff Informedness With Data Analytics For Chronic Disease Management, Na Liu, Robert John Kauffman

Research Collection School Of Computing and Information Systems

An important area in healthcare to which data analytics can be applied is chronic disease management. The chronic care model is mostly patient-centric, so patients have been considered as the end users of data analytics. The information needs of healthcare providers have been overlooked. Drawing upon the theory of informedness and the transtheoretical model of health behavior change, we use a multicase study approach to investigate the information needs of different caregiving stakeholders in the spectrum of chronic diseases, and how data analytics can be designed to meet the varying needs of professionals and staff to support their informedness.

Fourth Down Decision Making: Challenging The Conservative Nature Of Nfl Coaches, Will Palmquist, Ryan Elmore, Benjamin Williams

DU Undergraduate Research Journal Archive

This thesis analyzes the hypothesis that coaches in the National Football League are often too conservative in their decision making on fourth downs. I used R Studio and NFL play-by-play data to simulate actual football plays and drives according to different fourth down strategies. By measuring expected points per drive over thousands of simulated drives, we are able to evaluate the effectiveness of different fourth down strategies. This research points to a number of conclusions regarding the nature of NFL coaches on fourth downs as well as the complexity of modeling and simulating decision making in a complex sport such …

Analyzing Tweets On New Norm: Work From Home During Covid-19 Outbreak, Swapna Gottipati, Kyong Jin Shim, Hui Hian Teo, Karthik Nityanand, Shreyansh Shivam

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic triggered a large-scale work-from-home trend globally in recent months. In this paper, we study the phenomenon of “work-from-home” (WFH) by performing social listening. We propose an analytics pipeline designed to crawl social media data and perform text mining analyzes on textual data from tweets scrapped based on hashtags related to WFH in COVID-19 situation. We apply text mining and NLP techniques to analyze the tweets for extracting the WFH themes and sentiments (positive and negative). Our Twitter theme analysis adds further value by summarizing the common key topics, allowing employers to gain more insights on areas of …

Vision-Based Analytics For Improved Ai-Driven Iot Applications, Amit Sharma

Dissertations and Theses Collection (Open Access)

Proliferation of Internet of Things (IoT) sensor systems, primarily driven by cheaper embedded hardware platforms and wide availability of light-weight software platforms, has opened up doors for large-scale data collection opportunities. The availability of massive amount of data has in-turn given way to rapidly growing machine learning models e.g. You Only Look Once (YOLO), Single-Shot-Detectors (SSD) and so on. There has been a growing trend of applying machine learning techniques, e.g., object detection, image classification, face detection etc., on data collected from camera sensors and therefore enabling plethora of vision-sensing applications namely self-driving cars, automatic crowd monitoring, traffic-flow analysis, occupancy …

Toward A Sustainable Cybersecurity Ecosystem, Shahrin Sadik, Mohiuddin Ahmed, Leslie F. Sikos, A.K.M. Najmul Islam

Research outputs 2014 to 2021

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Cybersecurity issues constitute a key concern of today’s technology-based economies. Cybersecurity has become a core need for providing a sustainable and safe society to online users in cyberspace. Considering the rapid increase of technological implementations, it has turned into a global necessity in the attempt to adapt security countermeasures, whether direct or indirect, and prevent systems from cyberthreats. Identifying, characterizing, and classifying such threats and their sources is required for a sustainable cyber-ecosystem. This paper focuses on the cybersecurity of smart grids and the emerging trends such as using blockchain in …

Changing The Focus: Worker-Centric Optimization In Human-In-The-Loop Computations, Mohammadreza Esfandiari

Dissertations

A myriad of emerging applications from simple to complex ones involve human cognizance in the computation loop. Using the wisdom of human workers, researchers have solved a variety of problems, termed as “micro-tasks” such as, captcha recognition, sentiment analysis, image categorization, query processing, as well as “complex tasks” that are often collaborative, such as, classifying craters on planetary surfaces, discovering new galaxies (Galaxyzoo), performing text translation. The current view of “humans-in-the-loop” tends to see humans as machines, robots, or low-level agents used or exploited in the service of broader computation goals. This dissertation is developed to shift the focus back …

Social Participation Performance Of Wheelchair Users Using Clustering And Geolocational Sensor's Data, Yukun Yin, Kar Way Tan

Research Collection School Of Computing and Information Systems

For wheelchair users, social participation and physical mobility play a significant part in determining their mental health and quality of life outcomes. However, little is known about how wheelchair users move about and engage in social interactions within their life-spaces. In this project, we investigate the social participation performance of the wheelchair users based on a combination of geolocational and lifestyle survey data collected over a period of three months. This paper adopts a multi-variate approach combining geolocational travel patterns and various factors such as independence, willingness and self-perception to provide multi-faceted analysis to their lifestyles. We provide profiles of …

Real-Time Tracking And Mining Of Users’ Actions Over Social Media, Ejub Kajan, Noura Faci, Zakaria Maamar, Mohamed Sellami, Emir Ugljanin, Hamamache Kheddouci, Dragan H. Stojanović, Djamal Benslimane

All Works

© 2020, ComSIS Consortium. All rights reserved. With the advent of Web 2.0 technologies and social media, companies are actively looking for ways to know and understand what users think and say about their products and services. Indeed, it has become the practice that users go online using social media like Facebook to raise concerns, make comments, and share recommendations. All these actions can be tracked in real-time and then mined using advanced techniques like data analytics and sentiment analysis. This paper discusses such tracking and mining through a system called Social Miner that allows companies to make decisions about …

Detecting Credit Card Fraud: An Analysis Of Fraud Detection Techniques, William Lovo

Senior Honors Projects, 2020-current

Advancements in the modern age have brought many conveniences, one of those being credit cards. Providing an individual the ability to hold their entire purchasing power in the form of pocket-sized plastic cards have made credit cards the preferred method to complete financial transactions. However, these systems are not infallible and may provide criminals and other bad actors the opportunity to abuse them. Financial institutions and their customers lose billions of dollars every year to credit card fraud. To combat this issue, fraud detection systems are deployed to discover fraudulent activity after they have occurred. Such systems rely on advanced …

Exploring Strategies To Transition To Big Data Technologies From Dw Technologies, Mbah Johnas Fortem

Walden Dissertations and Doctoral Studies

As a result of innovation and technological improvements, organizations are now capable of capturing and storing massive amounts of data from various sources and domains. This increase in the volume of data resulted in traditional tools used for processing, storing, and analyzing large amounts of data becoming increasingly inefficient. Grounded in the extended technology acceptance model, the purpose of this qualitative multiple case study was to explore the strategies data managers use to transition from traditional data warehousing technologies to big data technologies. The participants included data managers from 6 organizations (medium and large size) based in Munich, Germany, who …

Effective Data Analytics And Security Strategies In Internal Audit Organizations, Desiree Auchey

Walden Dissertations and Doctoral Studies

The digitization of the corporate and regulatory environment presents an opportunity for internal audit organizations to change their audit techniques and increase their value to corporations. Audit functions have not kept pace with these advancements, as evidenced by the massive frauds in recent years, and current audit methodology does not robustly incorporate analytics and security of data. Grounded in agency theory, the purpose of this qualitative case study was to explore successful strategies business leaders use to implement data analytics and security for internal auditing and fraudulent activity. The participants comprised 3 audit leaders in Pennsylvania, who effectively used data …

Reliability Comparisons Of Mobile Network Operators: An Experimental Case Study From A Crowdsourced Dataset, Engi̇n Zeydan, Ahmet Yildirim

Turkish Journal of Electrical Engineering and Computer Sciences

It is of great interest for Mobile Network Operators (MNOs) to know how well their network infrastructure performance behaves in different geographical regions of their operating country compared to their horizontal competitors. However, traditional network monitoring and measurement methods of network infrastructure use limited numbers of measurement points that are insufficient for detailed analysis and expensive to scale using an internal workforce. On the other hand, the abundance of crowdsourced content can engender various unforeseen opportunities for MNOs to cope with this scaling problem. This paper investigates end-to-end reliability and packet loss (PL) performance comparisons of MNOs using a previously …

Rcrab: An R Analytics Tool To Visualize And Analyze The Movement Of Horseshoe Crabs In Long Island Sound, Ismael Youssef, Samah Senbel, Jo-Marie Kasinak, Jennifer Mattei

School of Computer Science & Engineering Faculty Publications

Mark-recapture programs are important for studying the ecology and population dynamics of wildlife. An R shiny analytics tool was developed to track the movement of horseshoe crabs in Long Island Sound based on tag and resight data. The crabs were tagged and recaptured by volunteers of Project Limulus, a community-based research program. The dataset contains tag and recapture location information for 14,065 horseshoe crabs over 18 years. The dataset was initially cleaned by removing records with missing, duplicate or incorrect data. A new data structure was developed to save the data and simplify processing: Three dimensions were used, one for …

Field Drilling Data Cleaning And Preparation For Data Analytics Applications, Daniel Cardoso Braga

LSU Master's Theses

Throughout the history of oil well drilling, service providers have been continuously striving to improve performance and reduce total drilling costs to operating companies. Despite constant improvement in tools, products, and processes, data science has not played a large part in oil well drilling. With the implementation of data science in the energy sector, companies have come to see significant value in efficiently processing the massive amounts of data produced by the multitude of internet of thing (IOT) sensors at the rig. The scope of this project is to combine academia and industry experience to analyze data from 13 different …

How To Derive Causal Insights For Digital Commerce In China? A Research Commentary On Computational Social Science Methods, David C.W. Phang, Kanliang Wang, Qiu-Hong Wang, Robert John Kauffman, Maurizio Naldi

Research Collection School Of Computing and Information Systems

The transformation of empirical research due to the arrival of big data analytics and data science, as well as the new availability of methods that emphasize causal inference, are moving forward at full speed. In this Research Commentary, we examine the extent to which this has the potential to influence how e-commerce research is conducted. China offers the ultimate in data-at-scale settings, and the construction of real-world natural experiments. Chinese e-commerce includes some of the largest firms involved in e-commerce, mobile commerce, social media and social networks. This article was written to encourage young faculty and doctoral students to engage …