Social and Behavioral Sciences Commons^™

A Framework For Inland Cities To Prevent Marine Debris: A Case Study From Durham, North Carolina, Nancy Lauer, Michelle B. Nowlin

Faculty Scholarship

Land-based sources of litter are increasingly recognized as significant contributors to marine debris, and rivers can carry debris to the coast from far-inland sources. In this paper, we demonstrate the important role inland cities can play in the marine debris crisis by reducing their own marine debris contributions. Given this role, we provide a framework for inland cities to prevent plastic pollution along with the lessons learned from introducing these strategies in Durham, North Carolina, a mid-sized, inland city that drains to the ocean through the Cape Fear and Neuse River watersheds. This framework guides city officials, resource managers, and …

Leveraging Natural Language Processing To Analyse The Temporal Behavior Of Extremists On Social Media, May El Barachi, Sujith Samuel Mathew, Farhad Oroumchian, Imene Ajala, Saad Lutfi, Rand Yasin

All Works

Aiming at achieving sustainability and quality of life for citizens, future smart cities adopt a data-centric approach to decision making in which assets, people, and events are constantly monitored to inform decisions. Public opinion monitoring is of particular importance to governments and intelligence agencies, who seek to monitor extreme views and attempts of radicalizing individuals in society. While social media platforms provide increased visibility and a platform to express public views freely, such platforms can also be used to manipulate public opinion, spread hate speech, and radicalize others. Natural language processing and data mining techniques have gained popularity for the …

Development And Initial Validation Of An Acculturation Measure For Arab Expatriates In Qatar Using Mixed Methods, Sara Ali Ahmed Zikri

Electronic Theses and Dissertations

Prior research on acculturation has predominantly focused on specific immigrant and ethnic groups in the United States, Europe, and Asia, and there is a lack of publicly available scales that measure acculturation among expatriates in countries of the Gulf Cooperation Council. The purpose of this study was to use a mixed methods research design to develop a theoretical framework of acculturation for white-collar Arab expatriates in Qatar as well as a culturally appropriate self-report acculturation measure. The acculturation stories and experiences of white-collar Arab expatriates in Qatar were qualitatively explored and analyzed, and their findings were used to construct an …

New Political Ecologies Of Renewable Energy, Sarah Knuth, Ingrid Behrsin, Anthony Levenda, James Mccarthy

Geography

The critique of fossil fuel regimes has been a foundational concern for the field of political ecology, in its drives to expose the injustices and harms of energy extractivism and its early warnings of the climate crisis. However, it is increasingly evident that renewable energy sources and their infrastructures will carry their own costs and trade-offs, and that critique, resistance and alternative movement-building are needed to forge a truly just renewable energy transition. This theme issue underlines the many ways in which political ecology is well-positioned to lead critical and engaged scholarship in support of energy/climate justice. In this introduction …

Drivers’ Response To Scenarios When Driving Connected And Automated Vehicles Compared To Vehicles With And Without Driver Assist Technology, Srinivas S. Pulugurtha, Raghuveer Gouribhatla

Mineta Transportation Institute

Traffic related crashes cause more than 38,000 fatalities every year in the United States. They are the leading cause of death among drivers up to 54 years in age and incur $871 million in losses each year. Driver errors contribute to about 94% of these crashes. In response, automotive companies have been developing vehicles with advanced driver assistance systems (ADAS) that aid in various driving tasks. These features are aimed at enhancing safety by either warning drivers of a potential hazard or picking up certain driving maneuvers like maintaining the lane. These features are already part of vehicles with Driver …

Taming The Data In The Internet Of Vehicles, Shahab Tayeb

Mineta Transportation Institute

As an emerging field, the Internet of Vehicles (IoV) has a myriad of security vulnerabilities that must be addressed to protect system integrity. To stay ahead of novel attacks, cybersecurity professionals are developing new software and systems using machine learning techniques. Neural network architectures improve such systems, including Intrusion Detection System (IDSs), by implementing anomaly detection, which differentiates benign data packets from malicious ones. For an IDS to best predict anomalies, the model is trained on data that is typically pre-processed through normalization and feature selection/reduction. These pre-processing techniques play an important role in training a neural network to optimize …

Exploring Cyberterrorism, Topic Models And Social Networks Of Jihadists Dark Web Forums: A Computational Social Science Approach, Vivian Fiona Guetler

Graduate Theses, Dissertations, and Problem Reports (ETD)

This three-article dissertation focuses on cyber-related topics on terrorist groups, specifically Jihadists’ use of technology, the application of natural language processing, and social networks in analyzing text data derived from terrorists' Dark Web forums. The first article explores cybercrime and cyberterrorism. As technology progresses, it facilitates new forms of behavior, including tech-related crimes known as cybercrime and cyberterrorism. In this article, I provide an analysis of the problems of cybercrime and cyberterrorism within the field of criminology by reviewing existing literature focusing on (a) the issues in defining terrorism, cybercrime, and cyberterrorism, (b) ways that cybercriminals commit a crime in …

Analysis Of Forensically Relevant Evidence Using Electrochemistry, Spectroscopy, And Mass Spectrometry Tools, Colby Edward Ott

Graduate Theses, Dissertations, and Problem Reports (ETD)

Forensic science relies on the use of multiple techniques in the assessment of evidence to increase the accuracy and reliability of the results. However, with the rapidly changing drug landscape due to the introduction of novel psychoactive substances, many traditional screening methods are no longer sensitive or selective enough for use. Additionally, many screening methods such as chemical color tests are prone to false positive and negative results and are subjective. Therefore, the goal of this dissertation was to develop a novel analytical scheme that can provide a more efficient, rapid, and sensitive method that will facilitate adoption in the …

Modeling Joint Survival Probabilities Of Runs Scored And Balls Faced In Limited Overs Cricket Using Copulas, Lochana K. Palayangoda, Hasika W. Senevirathne, Ananda B. Manage

Mathematics & Statistics Faculty Publications

In limited overs cricket, the goal of a batsman is to score a maximum number of runs within a limited number of balls. Therefore, the number of runs scored and the number of balls faced are the two key statistics used to evaluate the performance of a batsman. In cricket, as the batsmen play as pairs, having longer partnerships is also key to building strong innings. Moreover, having a steady opening partnership is extremely important as a team aims to build such a stronger innings. In this study, we have shown a way to evaluate the performance of opening partnerships …

Frameless-Finding And Refining A Sampling Frame For Surveying Recreational Fisheries: Lessons From Estimating Swedish Harvest Of Western Baltic Cod, Hege Sande, Nuno Prista, Annica De Groote, Michele Casini, Cynthia Jones, Andreas Sundelöf

OES Faculty Publications

To achieve sustainable fisheries, advice to management should be based on reliable science and unbiased data. Attaining quality data (i.e. precise and unbiased) on recreational fishing can be challenging, particularly when prior knowledge of the sector is limited and a proper sample frame of recreational fishers or vessels does not exist. In this study, a registry of access points was constructed for the Swedish south–west coast and used as a spatial sample frame in determining both effort and catches of the private boat fishery. Sampling dates, times for sampling, and access points visited were selected using probabilistic methods, ensuring unbiased …

Using Short Bursts To Optimize Redistricting In Georgia, Vedika Vishweshwar

CMC Senior Theses

Identifying extreme outliers in large state spaces is a difficult prob-
lem. I consider this problem in the context of finding political district-
ing plans that maximize the number of districts in which the majority
of the population is from a minority group, such as African Americans.
Since the set of all possible districting plans is enormous and unfeasi-
ble to examine in practice, this paper proposes a sampling method to
find these outlying plans. Specifically, this paper experiments with short
bursts in the context of minority voting rights in Georgia. Short bursts
are a type of Markov Chain in …

Exclusion Cycles: Reinforcing Disparities In Medicine, Ana Bracic, Shawneequa L. Callier, Nicholson Price

Articles

Minoritized populations face exclusion across contexts from politics to welfare to medicine. In medicine, exclusion manifests in substantial disparities in practice and in outcome. While these disparities arise from many sources, the interaction between institutions, dominant-group behaviors, and minoritized responses shape the overall pattern and are key to improving it. We apply the theory of exclusion cycles to medical practice, the collection of medical big data, and the development of artificial intelligence in medicine. These cycles are both self-reinforcing and other-reinforcing, leading to dismayingly persistent exclusion. The interactions between such cycles offer lessons and prescriptions for effective policy.

Mindfulness And Pain Regulation: The Role Of Acceptance And Commitment Therapy For Individuals With Chronic Pain, Ariana C. White

Honors Theses and Capstones

Chronic pain is a significant and widely prevalent health condition which requires comprehensive care to address the many facets contributing to symptomatology. In 2016, 20% of American adults (about 50 million) reported experiencing chronic pain, of which 7.4% indicated that chronic pain frequently limited their life and participation in activities within the past 3 months (CDC, 2018). As a result, many individuals with chronic pain turn to opioid-based medication for pain relief, but long-term use of opioids actually increases pain sensation (Tobin, 2019). Moreover, opioid medication is unable to target underlying mental health components which emerge as part of chronic …

Private And Federated Deep Learning: System, Theory, And Applications For Social Good, Han Hu

Dissertations

During the past decade, drug abuse continues to accelerate towards becoming the most severe public health problem in the United States. The ability to detect drug­abuse risk behavior at a population scale, such as among the population of Twitter users, can help to monitor the trend of drug­abuse incidents. However, traditional methods do not effectively detect drug­abuse risk behavior in tweets, mainly due to the sparsity of such tweets and the noisy nature of tweets. In the first part of this dissertation work, the task of classifying tweets as containing drug­abuse risk behavior or not, is studied. Millions of public …

Forecasting Locational Marginal Prices In Electricity Markets By Using Artificial Neural Networks, Kim Jay R. Rosano, Allan C. Nerves

Journal of Economics, Management and Agricultural Development

Electricity price forecasting is an important tool used by market players in decision-making and strategizing their participation in the electricity market. In most studies, market-clearing price is forecasted as it gives an aggregated overview of system price. However, locational marginal price (LMP) gives better outlook of the price particular to the customer location in the electrical power grid. This study utilizes Artificial Neural Networks to forecast weekday LMP of generator and load nodes. Various inputs such as historical prices and demand, and temporal indices were used. Using data for selected nodes of the Philippine Wholesale Electricity Spot Market, forecast Mean …

Usf Jamovi Tutorial Project: Open Education Resource, Aline Hitti, Saera Khan

USF OER Faculty Grant Projects

Jamovi is an open source free software that USF staff, faculty and student can download to carry out any statistical analyses. The current report summarizes the progress made on an Open Education Resource Grant funded project, which aimed to created Jamovi tutorials. In this report, student feedback and faculty reaction are summarized after one semester of using the tutorials created.

A Novel Arabic Corpus For Text Classification Using Deep Learning And Word Embedding, Roua A. Abou Khachfeh, Islam El Kabani, Ziad Osman

BAU Journal - Science and Technology

Over the last years, Natural Language Processing (NLP) for Arabic language has obtained increasing importance due to the massive textual information available online in an unstructured text format, and its capability in facilitating and making information retrieval easier. One of the widely used NLP task is “Text Classification”. Its goal is to employ machine learning technics to automatically classify the text documents into one or more predefined categories. An important step in machine learning is to find suitable and large data for training and testing an algorithm. Moreover, Deep Learning (DL), the trending machine learning research, requires a lot of …

Dynamic Relationship Study Between The Observed Seismicity And Spatiotemporal Pattern Of Lineament Changes In Palghar, North Maharashtra (India), Biswajit Nath, Ramesh P. Singh, Vineet K. Gahalaut, Ajay P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The Palghar region (north Maharashtra, India), located in the northwestern part of the stable continental region of India, experienced a low magnitude earthquake swarm, which was initiated in September 2018 and is continuing to date (as of October 2021). From December 2018 to December 2020, ~5000 earthquakes with magnitudes from M1.2 to M3.8 occurred in a small region of 20 × 10 km². These earthquakes were probably triggered by fluid migration during seasonal rainfall. In this study, we have used multi-temporal Landsat satellite data of the year 2000, 2015, 2018, 2019, and 2020, extracted lineaments, and studied the …

What Interactive Web Features Are Most Used, Travis Tyler

Experiential Learning Projects

The use of interactive features in websites has become common place on the internet. People use these tools to help navigate and understand the content related to that website. However, due the large variety of websites it can be tricky to understand what features are best to utilize based on the topic of your site. This paper seeks to address this issue by researching how users interact and utilized different features on different websites. Research is gathered via scholarly articles and direct data gathered from volunteers. This data shows users tend to favor more interactive tools to help with navigation, …

Development And Validation Of A New Scale To Assess Air Quality Knowledge (Aqiq), Alessandro Del Ponte, Lina Ang, Lianjun Li, Noah Lim, Wilson Wai San Tam, Wei Jie Seow

Political Science Faculty Articles and Research

Background

Methods

Application Of Competitive Intelligence For Insular Territories: Automatic Analysis Of Scientific And Technology Trends To Fight The Negative Effects Of Climate Change, Henri Dou, Pierre Fournie

International Journal of Islands Research

Islands are fragile territories because of their geographical position. As a result, climate impacts can have serious consequences, of which some are irreversible. Therefore, it is necessary to allow insular territories to benefit from the latest scientific and technological advances in combating climate effects. The current article shows how to deal with automatic analysis of scientific information on the one hand, but also its applications via patents. We will analyse the latest scientific results as well as their possible applications using patent analysis. We will also focus on experts, laboratories, and leading companies, that are active on the field. The …

Climate Change-Induced Effects On Beach Degradation And Tourist Behaviour: A Review Of Previous Studies With Potential In An Island Tourism Context, Yen E. Lam González, Carmen Garcia, Matias M. González Hernández, Carmelo J. Leon

International Journal of Islands Research

This article conducts a qualitative meta-analysis of papers addressing the topic of climate change impacts on beach loss and degradation, and its relation to tourist behaviour (destination choice, willingness to re-visit, expenditure and willingness to pay). The main aim is to identify values that can be used in future research works in the context of island tourism. We found that the strong specialisation and fragmentation of data and methods limit the transferability potential of previous research analysing climate-induced effects on beaches and tourist behaviour. Researchers from different fields bring their own conceptual models which often address similar problems but use …

Progressive Destabilization And Triggering Mechanism Analysis Using Multiple Data For Chamoli Rockslide Of 7 February 2021, Wenfei Mao, Lixin Wu, Ramesh P. Singh, Yuan Qi, Busheng Xie, Yingjia Liu, Yifan Ding, Zilong Zhou, Jia Li

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

A catastrophic rockslide occurred on 7 February 2021 in Chamoli area in the high Himalaya. In the absence of field data, multiple satellites data of decade span have been used to investigate and understand the progressive destabilization of rockslide body. A 3D geometric model was developed using geospatial information about geology, terrain, and ice cover to understand the triggering mechanism. Several causes are uncovered as: the pronounced long-term change of land surface temperature facilitated local permafrost degradation and led to ice cover shrinking since 2010; the occurrence of ice avalanche nearby in 2016 accompanying with sidewall-to-bedrock fracturing enhanced the ice …

Teaching Computer Science Csc 222, Harrison Dekker

Library Impact Statements

No abstract provided.

Development Experience Of International Open Source And Its Enlightenment To Construction Of Open Source Innovation System In China, Yuntao Long, Xiaoming Wang, Rong Gu, Yungang Bao

Bulletin of Chinese Academy of Sciences (Chinese Version)

Open source has become an essential innovation model for global technological progress and the construction of an open source innovation system is an important path for China to achieve self-reliance and self-improvement in science and technology. As an indispensable part of the global software value chain and high-tech industry chain, China needs to improve its open source innovation ecosystem. The paper, based on a systematic review of the related development policies and successful experiences on the open source work in US and Europe, puts forward a series of policy suggestions to solve the practical problems faced by the construction of …

2021 - The Second Annual Fall Symposium Of Student Scholars

Symposium of Student Scholars Program Books

The full program book from the Fall 2021 Symposium of Student Scholars, held on November 18, 2021. Includes abstracts from the presentations and posters.

Paleoindian Response To Climate Change In The Northern Jornada Del Muerto, Christopher Wayne Merriman

Anthropology ETDs

Human-environment interaction is a long-standing and productive line of inquiry that includes the study of cultural responses to climate change. However, demonstrating a causal relationship between climate change and the consequent culture change is rarely straightforward for numerous reasons. In this dissertation I develop an optimality model to predict how Paleoindians should have responded to changes in precipitation across the Late Pleistocene-Early Holocene. The water supply model (WSM) ranks water supplies much like the diet breadth model ranks food resources. To adjust the WSM for climate change, paleoclimate records from playas in the northern Jornada del Muerto were used in …

Introduction To Using Python In The Digital Humanities, Elisabeth Shook

Library Faculty Publications and Presentations

The materials here are from the Python for Digital Humanities Workshop taught on December 13, 2021 for the Boise State University Digital Humanities Group. This 3-hour workshop was created to provide both a very brief introduction to the various capabilities of Python and a small lesson in using Python to pull meaningful insight out of text files.

How Can Stem Retention Rates At Bgsu Be Increased Both In And Out Of The Classroom?, Josalyn A. Coffee

Honors Projects

Previous research in STEM student retention rates showed a gap in knowledge regarding why this group of student experience higher rates of burnout than other groups of students. This study investigated the barriers STEM students at BGSU experienced. A survey was sent out to STEM and non-STEM students alike that asked questions regarding student’s personal history before attending BGSU, their course experiences at BGSU, and the levels of support they have outside of BGSU. The survey data showed that there was little difference in the rates that students switch majors solely based on being in the STEM field. The data …

Aspect-Based Sentiment Analysis Of Movie Reviews, Samuel Onalaja, Eric Romero, Bosang Yun

SMU Data Science Review

This study investigates a comparison of classification models used to determine aspect based separated text sentiment and predict binary sentiments of movie reviews with genre and aspect specific driving factors. To gain a broader classification analysis, five machine and deep learning algorithms were compared: Logistic Regression (LR), Naive Bayes (NB), Support Vector Machine (SVM), and Recurrent Neural Network Long-Short-Term Memory (RNN LSTM). The various movie aspects that are utilized to separate the sentences are determined through aggregating aspect words from lexicon-base, supervised and unsupervised learning. The driving factors are randomly assigned to various movie aspects and their impact tied to …