Computer Sciences Commons^™

Managing Cyber Risks & Business Exposure In The Surface Transportation Ecosystem, Jacques R. Francoeur

Mineta Transportation Institute

This report focuses on Surface Transportation (ST), both fixed and route-based, and the growing threats to their information technology (IT) infrastructures. As an industry, ST seeks to optimize the movement of people and goods, while ensuring safety and resiliency and minimizing environmental impact. Cyber threats are a powerful medium for those with the political, social, and economic motivations and wherewithal to disrupt and destroy existing ST systems. The ultimate objective is to develop a new paradigm to define, describe, design, and deploy the most effective protection, at the lowest cost, in the shortest time within the limits of available resources. …

Transfer Learning Approach To Multiclass Classification Of Child Facial Expressions, Megan A. Witherow, Manar D. Samad, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

The classification of facial expression has been extensively studied using adult facial images which are not appropriate ground truths for classifying facial expressions in children. The state-of-the-art deep learning approaches have been successful in the classification of facial expressions in adults. A deep learning model may be better able to learn the subtle but important features underlying child facial expressions and improve upon the performance of traditional machine learning and feature extraction methods. However, unlike adult data, only a limited number of ground truth images exist for training and validating models for child facial expression classification and there is a …

Quantifying Activity Levels Of Community-Dwelling Seniors Through Beacon Monitoring, Jin Qiang Goh, Hwee-Pink Tan, Hwee Xian Tan

Research Collection School Of Computing and Information Systems

The ageing population is rapidly increasing, both in Singapore and worldwide. Due to the shortage of healthcare professionals and institutionalized care, there is a pertinent need for seniors to age-in-place-safely and in the familiarity of their neighborhoods. In addition, changing family structures and rising divorce rates, coupled with the desire for more personal space and independence, have resulted in a significant proportion of seniors who live alone at home. In this paper, we describe a scalable and low-cost monitoring system that can help to identify community-dwelling seniors who are at risk of social isolation and/or frailty. This is achieved by …

Determining Political Inclination In Tweets Using Transfer Learning, Mehtab Iqbal

College of Graduate Studies: Theses & Dissertations

Last few years have seen tremendous development in neural language modeling for transfer learning and downstream applications. In this research, I used Howard and Ruder’s Universal Language Model Fine Tuning (ULMFiT) pipeline to develop a classifier that can determine whether a tweet is politically left leaning or right leaning by likening the content to tweets posted by @TheDemocrats or @GOP accounts on Twitter. We achieved 87.7% accuracy in predicting political ideological inclination.

Online Burst Events Detection Oriented Real-Time Microblog Message Stream, Guozhong Dong, Jun Gao, Liang Huang, Chunlei Shi

Research Collection School Of Computing and Information Systems

The rapid spread of microblog messages and sensitivity of unexpected events make microblog become the public opinion center of burst events. Online burst events detection oriented real-time microblog message stream has become an important research problem in the field of microblog public opinion. Because of the large amount of real-time microblog message stream and irregular language of microblog message, it is important to process real-time microblog message stream and detect burst events accurately. In this paper, an online burst events detection framework is proposed. In this framework, abnormal messages are detected based on sliding time window and two-level hash table. …

Russia Today, Cyberterrorists Tomorrow: U.S. Failure To Prepare Democracy For Cyberspace, Jonathan F. Lancelot

Journal of Digital Forensics, Security and Law

This paper is designed to expose vulnerabilities within the US electoral system, the use of cyberspace to exploit weaknesses within the information assurance strategies of the democratic and republican party organizations, and deficiencies within the social media communications and voting machine exploits. A brief history of discriminatory practices in voting rights and voting access will be set as the foundation for the argument that the system is vulnerable in the cyber age, and the need for reform at the local, state and national levels will be emphasized. The possibility of a foreign nation-state influencing the outcome of an election by …

A Snowball's Chance: Debt Snowball Vs. Debt Avalanche, Evan Mcallister

Senior Honors Projects, 2010-2019

Traditional mathematical analysis states that the most efficient way to pay off interest-bearing consumer debt is to pay the individual debts in order from largest to smallest interest rate. In doing this, the debtor will eliminate the largest sources of interest first, thus shortening the overall time-to-pay. This method is known as the “Debt Avalanche.” The “Debt Snowball” method, popularized in large part by investor-author David Ramsey, recommends that consumers pay debts in order from smallest to largest, regardless of interest rate. In this paper, I conduct an empirical analysis of the Federal Reserve’s Survey of Consumer Finance (SCF), calculating …

The Evolution Of Computational Propaganda: Trends, Threats, And Implications Now And In The Future, Holly Schnader

Senior Honors Projects, 2010-2019

Computational propaganda involves the use of selected narratives, social networks, and complex algorithms in order to develop and conduct influence operations (Woolley and Howard, 2017). In recent years the use of computational propaganda as an arm of cyberwarfare has increased in frequency. I aim to explore this topic to further understand the underlying forces behind the implementation of this tactic and then conduct a futures analysis to best determine how this topic will change over time. Additionally, I hope to gain insights on the implications of the current and potential future trends that computational propaganda has.

My preliminary assessment shows …

Open Source Foundations For Spatial Decision Support Systems, Jochen Albrecht

Publications and Research

Spatial Decision Support Systems (SDSS) were a hot topic in the 1990s, when researchers tried to imbue GIS with additional decision support features. Successful practical developments such as HAZUS or CommunityViz have since been built, based on commercial desktop software and without much heed for theory other than what underlies their process models. Others, like UrbanSim, have been completely overhauled twice but without much external scrutiny. Both the practical and the theoretical foundations of decision support systems have developed considerably over the past 20 years. This article presents an overview of these developments and then looks at what corresponding tools …

Historical Effects Of Electronic Interfaces, G James Mitchell

Publications and Research

Electronic interfaces are a primary tool for most professional and personal communication currently happening. Electronics, like the human mind, are limited by the understanding of executing will, or commands. This can be characterized as “interface limitations” of digital technology. Identifying this bottleneck in technological development has been critical in historical changes to both hardware and software technology. Recent medical research examines a novel user interface to reduce task load. I hypothesize, interface developments that take cues from nonverbal human communication enhance and sustain the significance of those technologies in society. By examining pivotal moments of historical technology we can identify …

Using Deep Learning To Forecast Spatiotemporal Crime Patterns, Shuzhan Fan

LSU Doctoral Dissertations

The distributional patterns of crime occurrences are closely related to their spatial, temporal, and environmental contexts. It has been a hot topic for researchers and crime analysts to discover such complex relationships in order to forecast crime, both spatially and temporally. Many factors play a role in the occurrences of crimes. Conventional crime forecasting research has primarily relied on historical crime records and socioeconomic data, while ignoring the rich social media and other environmental context data. The large volume of data requires a more appropriate forecasting framework with the ability to take in massive multimodal data and possibly achieve better …

Project Renew Worcester, Danni Yue, Amy Zhang, Jing Han, Omid Ashrafi, Yiming Xu

School of Professional Studies

n The client for this capstone project is RENEW Worcester which is a fledgling solar power project whose main goals are to bring renewable energy in the form of solar power into local, primarily low-income communities and are committed to the mission of making the transition off of fossil fuels to clean, renewable power. Based in Worcester, Massachusetts, they are a local chapter of Co-op Power which is a consumer-owned sustainable energy cooperative (co-op) made up of numerous different local chapters all over the New England area as well as the state of New York. The problem that we will …

Induced Hesitant 2-Tuple Linguistic Aggregation Operators With Application In Group Decision Making, Tabasam Rashid, Ismat Beg, Raja N. Jamil

Applications and Applied Mathematics: An International Journal (AAM)

In this article, hesitant 2-tuple linguistic arguments are used to evaluate the group decision making problems which have inter dependent or inter active attributes. Operational laws are developed for hesitant 2-tuple linguistic elements and based on these operational laws hesitant 2- tuple weighted averaging operator and generalized hesitant 2- tuple averaging operator are proposed. Combining Choquet integral with hesitant 2-tuple linguistic information, some new aggregation operators are defined, including the hesitant 2-tuple correlated averaging operator, the hesitant 2-tuple correlated geometric operator and the generalized hesitant 2-tuple correlated averaging operator. These proposed operators successfully manage the correlations among the elements. After …

Revolution In Crime: How Cryptocurrencies Have Changed The Criminal Landscape, Igor Groysman

Student Theses

This thesis will examine the ways in which various cryptocurrencies have impacted certain traditional crimes. While crime is always evolving with technology, cryptocurrencies are a game changer in that they provide anonymous and decentralized payment systems which, while they can be tracked in a reactive sense via the blockchain, are seen by criminals as having better uses for them than traditional fiat currencies, such as the ability to send money relatively fast to another party without going through an intermediary, or the ability to obscure the origin of the money for money laundering purposes. Every week there are new cryptocurrencies …

Social Software Development: Insights And Solutions, Abhishek Sharma

Dissertations and Theses Collection (Open Access)

Over last few decades, the way software is developed has changed drastically. From being an activity performed by developers working individually to develop standalone programs, it has transformed into a highly collaborative and cooperative activity. Software development today can be considered as a participatory culture, where developers coordinate and engage together to develop software while continuously learning from one another and creating knowledge.

In order to support their communication and collaboration needs, software developers often use a variety of social media channels. These channels help software developers to connect with like-minded developers and explore collaborations on software projects of interest. …

Review Of: The World Of Scary Video Games: A Study In Videoludic Horror, Approaches To Digital Game Studies, Matthew Murray

Library Faculty Research

No abstract provided.

Data Mining Approach To The Detection Of Suicide In Social Media: A Case Study Of Singapore, Jane H. K. Seah, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

In this research, we focus on the social phenomenon of suicide. Specifically, we perform social sensing on digital traces obtained from Reddit. We analyze the posts and comments in that are related to depression and suicide. We perform natural language processing to better understand different aspects of human life that relate to suicide.

Using Smart Card Data To Model Commuters’ Responses Upon Unexpected Train Delays, Xiancai Tian, Baihua Zheng

Research Collection School Of Computing and Information Systems

The mass rapid transit (MRT) network is playing an increasingly important role in Singapore's transit network, thanks to its advantages of higher capacity and faster speed. Unfortunately, due to aging infrastructure, increasing demand, and other reasons like adverse weather condition, commuters in Singapore recently have been facing increasing unexpected train delays (UTDs), which has become a source of frustration for both commuters and operators. Most, if not all, existing works on delay management do not consider commuters' behavior. We dedicate this paper to the study of commuters' behavior during UTDs. We adopt a data-driven approach to analyzing the six-month' real …

Integrated Reward Scheme And Surge Pricing In A Ride-Sourcing Market, Hai Yang, Chaoyi Shao, Hai Wang, Jieping Ye

Research Collection School Of Computing and Information Systems

Surge pricing is commonly used in on-demand ride-sourcing platforms (e.g., Uber, Lyft and Didi) to dynamically balance demand and supply. However, since the price for ride service cannot be unlimited, there is usually a reasonable or legitimate range of prices in practice. Such a constrained surge pricing strategy fails to balance demand and supply in certain cases, e.g., even adopting the maximum allowed price cannot reduce the demand to an affordable level during peak hours. In addition, the practice of surge pricing is controversial and has stimulated long debate regarding its pros and cons. To address the limitation of current …

Project Management Madness: 3 Key Programs For Communication, Personal Tasks And Large Projects, Rachel S. Evans

Presentations

No matter what member of a team you are, be it content editor, web designer, database manager or systems administrator, getting things done and meeting goals depends largely on how you communicate with one another, handle your time and effectively collaborate on small and big projects. This session will use our own team's preferred platforms to show specific examples of how we are managing our taskflow across three different programs to tackle business as usual, short and long term work, and major special projects.

The three programs that will be compared for pros, cons, and their integration with one another …

Recommending Who To Follow In The Software Engineering Twitter Space, Abhabhisheksh Sharma, Yuan Tian, Agus Sulistya, Dinusha Wijedasa, David Lo

Research Collection School Of Computing and Information Systems

With the advent of social media, developers are increasingly using it in their software development activities. Twitter is one of the popular social mediums used by developers. A recent study by Singer et al. found that software developers use Twitter to “keep up with the fast-paced development landscape.” Unfortunately, due to the general-purpose nature of Twitter, it’s challenging for developers to use Twitter for their development activities. Our survey with 36 developers who use Twitter in their development activities highlights that developers are interested in following specialized software gurus who share relevant technical tweets.To help developers perform this task, in …

Comparing Elm With Svm In The Field Of Sentiment Classification Of Social Media Text Data, Zhihuan Chen, Zhaoxia Wang, Zhiping Lin, Ting Yang

Research Collection School Of Computing and Information Systems

Machine learning has been used in various fields with thousands of applications. Extreme learning machine (ELM), which is the most recently developed machine learning algorithm, has become increasingly popular for its good generalization ability. However, it has been relatively less applied to the domain of social media. Support Vector Machine (SVM), another popular learning-based algorithm, has been applied for sentiment classification of social media text data and has obtained good results. This paper investigates and compares the capabilities of these two learning-based methods in the field of sentiment classification of social media. The results indicate that SVM can obtain good …

Improving Multi-Label Emotion Classification Via Sentiment Classification With Dual Attention Transfer Network, Jianfei Yu, Luis Marujo, Jing Jiang, Pradeep Karuturi, William Brendel

Research Collection School Of Computing and Information Systems

In this paper, we target at improving the performance of multi-label emotion classification with the help of sentiment classification. Specifically, we propose a new transfer learning architecture to divide the sentence representation into two different feature spaces, which are expected to respectively capture the general sentiment words and the other important emotion-specific words via a dual attention mechanism. Extensive experimental results demonstrate that our transfer learning approach can outperform several strong baselines and achieve the state-of-the-art performance on two benchmark datasets.

Centroid-Amenities: An Interactive Visual Analytical Tool For Exploring And Analyzing Amenities In Singapore, Xue Qian Jazreel Siew, Sean Jia Ming Koh

Research Collection School Of Computing and Information Systems

Planning for civic amenities in a fast-changing urban setting such as Singapore is never an easy task. And as urban planners look toward more data-driven approaches toward urban planning, so grows the demand for more flexible geospatial analytics tools to facilitate a more iterative and granular approach toward urban planning. Such specific tools however, are not always readily available as plugins for traditional desktop GIS software, as numerous customizations must be made to model specific temporal planning scenarios for quick analysis, which could prove both costly and time-consuming. Hence, to address this need, open-source tools such as R Shiny could …

Imaginary People Representing Real Numbers: Generating Personas From Online Social Media Data, Jisun An, Haewoon Kwak, Soongyo Jung, Joni Salminen, M. Admad, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

We develop a methodology to automate creating imaginary people, referred to as personas, by processing complex behavioral and demographic data of social media audiences. From a popular social media account containing more than 30 million interactions by viewers from 198 countries engaging with more than 4,200 online videos produced by a global media corporation, we demonstrate that our methodology has several novel accomplishments, including: (a) identifying distinct user behavioral segments based on the user content consumption patterns; (b) identifying impactful demographics groupings; and (c) creating rich persona descriptions by automatically adding pertinent attributes, such as names, photos, and personal characteristics. …

Linky: Visualizing User Identity Linkage Results For Multiple Online Social Networks (Demo), Roy Ka-Wei Lee, Ming Shan Hee, Philips Kokoh Prasetyo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

User identity linkage across online social networks is an emerging research topic that has attracted attention in recent years. Many user identity linkage methods have been proposed so far and most of them utilize user profile, content and network information to determine if two social media accounts belong to the same person. In most cases, user identity linkage methods are evaluated by performing some prediction tasks with the results presented using some overall accuracy measures. However, the methods are rarely compared at the individual user level where a predicted matched (or linked) pair of user identities from different online social …

Emotion Recognition Using Deep Convolutional Neural Network With Large Scale Physiological Data, Astha Sharma

USF Tampa Graduate Theses and Dissertations

Classification of emotions plays a very important role in affective computing and has real-world applications in fields as diverse as entertainment, medical, defense, retail, and education. These applications include video games, virtual reality, pain recognition, lie detection, classification of Autistic Spectrum Disorder (ASD), analysis of stress levels, and determining attention levels. This vast range of applications motivated us to study automatic emotion recognition which can be done by using facial expression, speech, and physiological data.

A person’s physiological signals such are heart rate, and blood pressure are deeply linked with their emotional states and can be used to identify a …

Information Privacy Concerns In The Age Of Internet Of Things, Madhav Sharma, David Biros

KSU Proceedings on Cybersecurity Education, Research and Practice

Internet of things (IoT) offer new opportunities for advancement in many domains including healthcare, home automation, manufacturing and transportation. In recent years, the number of IoT devices have exponentially risen and this meteoric rise is poised to continue according to the industry. Advances in the IoT integrated with ambient intelligence are intended to make our lives easier. Yet for all these advancements, IoT also has a dark side. Privacy and security were already priorities when personal computers, devices and work stations were the only point of vulnerability to personal information, however, with the ubiquitous nature of smart technologies has increased …

A Bit Like Cash: Understanding Cash-For-Bitcoin Transactions Through Individual Vendors, Stephanie J. Robberson, Mark R. Mccoy

Journal of Digital Forensics, Security and Law

As technology improves and economies become more globalized, the concept of currency has evolved. Bitcoin, a cryptographic digital currency, has been embraced as a secure and convenient type of money. Due to its security and privacy for the user, Bitcoin is a good tool for conducting criminal trades. The Financial Crimes Enforcement Network (FinCEN) has regulations in place to make identification information of Bitcoin purchasers accessible to law enforcement, but enforcing these rules with cash-for-Bitcoin traders is difficult. This study surveyed cash-for-Bitcoin vendors in Oklahoma, Texas, Arkansas, Missouri, Kansas, Colorado, and New Mexico to determine personal demographic information, knowledge of …

How We Done It Good: Research Through Design As A Legitimate Methodology For Librarianship, Rachel Ivy Clarke

School of Information Studies - Faculty Scholarship

“How we done it good” publications—a genre concerning project-based approaches that describe how (and sometimes why) something was done—are often rebuked in the library research community for lacking traditional scientific validity, reliability, and generalizability. While scientific methodologies may be a common approach to research and inquiry, they are not the only methodological paradigms. This research posits that the “how we done it good” paradigm in librarianship reflects a valid and legitimate approach to research. By drawing on the concept of research through design, this study shows how these “how we done it good” projects reflect design methodologies which draw …