The 50 most-cited articles in Journal of International Crisis and Risk Communication Research, 2019

Confronted with rising citizen discontent, the Reinventing Government movement, and new technological challenges, public organizations everywhere are seeking means of improving their performance. Their quest is not new, rather, the concern with improving the performance of government organizations has existed since the Scientific Management Movement. Public Sector Performance brings together in a single volume the classic, enduring principles and processes that have defined the field of public sector performance, as written in the words of leading practitioners and scholars. Taken as a whole, this volume provides a performance compass for today’s public managers, helping them to reconstruct the public’s confidence in, and support of, government.Defined here as managing public organizations for outcomes, performance is examined in all its varied dimensions: organizing work, managing workers, measuring performance, and overcoming resistance to performance-enhancing innovations. The selected articles are interesting, thought provoking, and instructive. They are classics in that they…

This study first refines the conceptual framework of publics’ communicative behavior in social mediated health crises. Then two multiple-item scales for measuring publics’ health crisis information seeking and sharing (CISS) are developed and tested by employing online survey data sets from a random national sample of 279 adults and 280 adults in the United States, respectively. Results indicate seven types of crisis information seeking behavior and 17 types of crisis information sharing behavior crossing over platforms, channels, and information sources. The CISS scales provide a valid and reliable tool for crisis communication researchers and practitioners to measure publics’ information seeking and sharing activities in social-mediated public health crisis communication.

This study examines stigma from the perspective of residents of Fukushima prefecture following the 2011 nuclear disaster in Fukushima, Japan, to better understand effective crisis communication strategies that can mitigate the negative effects of self-stigma and promote sustainable psychosocial recovery. Social cognitive theory was employed to explore cognitive, affective, and behavioral changes faced by Fukushima residents in response to the stigma imposed upon them after the disaster. The study result based on in-depth interviews with residents of Shinchimachi, Fukushima, indicates that affectively, participants experienced a remarkable amount of fear and sadness. Cognitively, they focused on concerns about outsiders’ negative images or misinformation about Fukushima, changed priorities or values, and self-efficacy. Behaviorally, they actively resisted the stigma while strengthening their connections and belonging to their own community. Additionally, residents felt that they were branded as polluted and contagious and attributed the creation of a Fukushima stigma to a lack of…

This study proposed a definition of perceived crisis severity and created a valid and reliable scale to measure the construct following Churchill’s scale development procedure. The proposed scale, after rigorous pilot testing and exploratory and confirmatory factor analysis, contains 3 factors with 12 items. This study discusses potential applications of the developed measures and provides future research directions.

Hoaxes have long been a reputational threat to organizations. For example, false claims that syringes had been found in bottles of Pepsi-Cola products, that a portion of a fi nger had been found in Wendy’s chili, and that Domino’s employees had intentionally served contaminated food to customers have topped the media’s agenda. More recently, the hoax phenomenon has been tactically reversed. Heavily trafficked Internet sites and controversial television personalities frequently argue that well-documented crises themselves are hoaxes. The potential for claims of crisis as hoax to disrupt the discourse of crisis renewal is examined through an analysis of three cases. We argue that overcoming such disruptions requires corporate social responsibility, a focus on the issues rather than the hoaxers, and continued eff orts to improve media literacy for all audiences.

How do European Union (EU) member states communicate risks to their citizens? In this study, we define risk communication as the information provided by different levels of government to citizens regarding possible future crises to which the general public might be subjected. We seek to answer the following questions: Are there any patterns in the risk communication strategies among EU member states in terms of the sender of information, the message conveyed, the method used, and the intended audience? Finally, to what extent is the state involved in ensuring the safety of its citizens? To tackle these questions, we examine the risk communication strategy of eight countries: Sweden, Finland, Germany, England, France, Estonia, Greece, and Cyprus. Our data consist of governmental web sites, publications, campaigns, and other modes of communication, such as videos posted on YouTube, with questions centering on institutional actors, methods of delivery, content, and effectiveness. We find that the institutional architecture of risk communication aligns with the broad administrative…

The World Health Organization (WHO) commissioned systematic reviews to assist with the development of new emergency risk communication guidelines that will impact responses and distribution of resources at all levels. This mixed-method evidence synthesis, guided by Cochrane principles and methods, examined the extant research in countries throughout the world, published from 2003 to 2016, related to the best practices to engage communities in preparing for and responding to emergency events with public health implications. Although few studies directly examined which strategies or tactics effectively engage public participation, many studies reinforced the importance of community participation. The findings support the perspective that emergency events are communicatively understood by all publics and that they benefit from emergency risk communication before, during, and after such events, especially when grounded in local contexts. Although the importance of local context limits the generalizability of risk communication, it is important to continue studying strategies and tactics…

This study aims to understand the dynamic evolvement of frames in news media coverage of the Ebola crisis (2014–2015) and their interplay with narratives put forth in press releases from governmental organizations (GOs). An automated content analysis was applied to U.S. newspapers and GOs’ press releases on the Ebola epidemic. Time series analyses illustrate how the scope of frames in news media becomes narrower (decreased diversity) with the presence of immediate and problem-focused crisis frames and wider (increased diversity) with more progressive frames. Additionally, the results imply that a level of shared interpretation (frame alignment) between media and GOs fosters the openness of news media for a variety of frames, which in turn might lead to a communicative shift that eases the crisis atmosphere.

This article applies critical race theory to an institutional analysis of writing curricular outcomes to assist two-year college writing program administrators, curriculum coordinators, and instructors with examining the racist implications of writing curriculum outcomes and to develop antiracist curricula that support the academic, professional, and civic success of the majority of their students.

In August of 2018 a group of academic, government, and industry experts in the field of Augmented Reality gathered for four days to consider potential technological and societal issues and opportunities that could accompany a future where AR is pervasive in location and duration of use. This report is intended to summarize some of the most novel and potentially impactful insights and opportunities identified by the group. Our target audience includes AR researchers, government leaders, and thought leaders in general. It is our intent to share some compelling technological and societal questions that we believe are unique to AR, and to engender new thinking about the potentially impactful synergies associated with the convergence of AR and some other conventionally distinct areas of research.

Much of the Ismaili settlement in Eastern Africa, together with several other immigrant communities of Indian origin, took place in the late nineteenth century and early twentieth centuries. This thesis argues that the primary mover of the migration were the edicts, or Farmans, of the Ismaili spiritual leader. They were instrumental in motivating Ismailis to go to East Africa. Although there were other Indian groups from the general geographical area of Western Indian and Gujarat who also migrated to East Africa, the crucial factor in the migration of Ismailis were the edicts or Farmans of the Imams. My thesis argues that the Farmans or edicts played a very important role in persuading Ismailis to move to East Africa. Though other groups from Gujarat and Western India also moved to East Africa, the Ismailis followed the edicts or Farmans of the Imam and this was the major factor for the Ismailis to move. Ismaili history is replete with migratory movements, whether due to persecution or economic reasons. The religious leader of the Ismailis, the Imam or the "Imam of the Time" as he…

In this letter, we investigate the geometrically tailorable elasticity in the twisting behavior of biomimetic scale-covered slender soft substrate. Motivated by qualitative experiments showing a significant torsional rigidity increase, we develop an analytical model and carry out extensive finite element simulations to validate our model. We discover a regime differentiated and reversible mechanical response straddling linear, nonlinear, and rigid behavior. The response is tailorable through the geometric arrangement and orientation of the scales. The work outlines analytical relationships between geometry, deformation and kinematics, which can be used for designing bio-inspired scale-covered materials.

Fear of infectious disease has the potential to damage local economies, disrupt health care delivery systems, and diminish immune functioning, whether or not the risk is objectively high. The appearance of Ebola in the United States offered an opportunity to study the causes of fear in a real-world event. Shortly after the death of the first Ebola patient diagnosed in the United States, survey data were gathered (N = 849) from residents of Dallas and U.S. citizens outside of Texas. Fear was positively associated with age (younger), gender (female), and ethnicity (non-White), but not geographic proximity (Dallas vs. not Dallas). Exposure to Ebola-related information via interpersonal channels (friends/family, acquaintances/coworkers) corresponded with higher levels of fear, but the findings for media channels were more varied, showing positive effects (newspapers/magazines), negative effects (Internet), and null effects (TV/radio). The study provides insight into the personal, interpersonal, and media correlates of fear of Ebola.

This study explores the Samsung Galaxy Note 7 explosion crisis by analyzing posts on Twitter in three nations: the United States, Australia, and South Korea. Using the perspectives of generic frames, issue-specific frames, cross-national frames, and user sentiment on Twitter, this study analyzes 600 posts (200 from each nation). Results reveal that Twitter posts frequently framed the crisis using attribution, morality, and conflict frames. Posts about the explosion were more professional frame oriented than national frame oriented. Negative sentiment was dominant in Twitter posts about the explosion. Morality, corporate breakdown, and customer concerns were highly associated with negative sentiment. The results demonstrate how global users respond to a corporate crisis. Study implications and suggestions are discussed.

This thesis presents an automated traffic safety diagnostics solution using deep learning techniques to process traffic videos by Unmanned Aerial Vehicle (UAV). Mask R-CNN is employed to better detect vehicles in UAV videos after video stabilization. The vehicle trajectories are generated when tracking the detected vehicle by Channel and Spatial Reliability Tracking (CSRT) algorithm. During the detection process, missing vehicles could be tracked by the process of identifying stopped vehicles and comparing Intersect of Union (IOU) between the tracking results and the detection results. In addition, rotated bounding rectangles based on the pixel-to- pixel manner masks that are generated by Mask R-CNN detection, which are also introduced to obtain precise vehicle size and location data. Moreover, surrogate safety measures (i.e. post- encroachment time (PET)) are calculated for each conflict event at the pixel level. Therefore, conflicts could be identified through the process of comparing the PET values and the threshold. To be more specific, conflict types that include rear-end,…

Risk and crisis communication are growing areas of scholarship ripe for multidisciplinary contributions. In this essay, the Volume 2 editor reflects on the primary purpose of the Journal of International Crisis and Risk Communication Research and the areas of scholarship the journal promotes. The editor offers advice for researchers and professionals interested in publishing in the journal. Additionally, the editor calls for the community to continue to submit their best research and to support the development of the next generation of risk and crisis communication scholars.

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Educational Data Mining (EDM) is a developing research field that involves many techniques to explore data relating to educational background. EDM can analyze and resolve educational data with computational methods to address educational questions. Similar to EDM, neural networks have been utilized in widespread and successful data mining applications. In this paper, synthetic datasets are employed since this paper aims to explore the methodologies such as decision tree classifiers and neural networks to predict student performance in the context of EDM. Firstly, it introduces EDM and some relative works that have been accomplished previously in this field along with their datasets and computational results. Then, it demonstrates how the synthetic student dataset is generated, analyzes some input attributes from the dataset such as gender and high school GPA, and delivers with some visualization results to determine which classification methods approaches are the most efficient. After testing the data with decision tree classifiers and neural networks methodologies, it concludes the…

Many of the research skills needed to succeed in higher education are never explicitly taught. Most students learn through experience and exposure. However, working-class students don’t always grow up in academic environments that provide the same exposure to these skills. In fact, at the University of Central Florida one of every five of our students is the first in their family to attend college. Using the University of Central Florida’s “Research Tips Tuesdays” webinar series as a case study, participants in this session will explore ways to help working-class students develop fundamental research skills while respecting their busy schedules. We will discuss how to identify skill gaps, design scaffolded skill building programs and brainstorm potential campus partners.

This thesis presents different data mining/machine learning techniques to analyze the vulnerable road users' (i.e., pedestrian and bicycle) crashes by developing crash prediction models at macro-level. In this study, we developed data mining approach (i.e., decision tree regression (DTR) models) for both pedestrian and bicycle crash counts. To author knowledge, this is the first application of DTR models in the growing traffic safety literature at macro-level. The empirical analysis is based on the Statewide Traffic Analysis Zones (STAZ) level crash count data for both pedestrian and bicycle from the state of Florida for the year of 2010 to 2012. The model results highlight the most significant predictor variables for pedestrian and bicycle crash count in terms of three broad categories: traffic, roadway, and socio demographic characteristics. Furthermore, spatial predictor variables of neighboring STAZ were utilized along with the targeted STAZ variables in order to improve the prediction accuracy of both DTR models. The DTR model considering spatial predictor variables (spatial…

Through the comparison of flow structures, velocity contours, turbulence statistics, and additional flow quantities, the error sources of RANS are qualitatively described. The findings in this work will help gas turbine design engineers to tweak their turbulence models and give guidance on the interpretation of their results. The novelty is the application of the transient TLC method on this type of geometry as well as the near-wall PIV measurements. The advancements in additive manufacturing disrupt the classic turbine cooling development for casted airfoils. More and more complicated shapes and cooling schemes are possible. Nonetheless, a detailed physical understanding of fundamental cases - as provided in this study - is required for physics-based optimization of cooling designs.

The desire to understand the causes of complex societal phenomena is fundamental to the social sciences. Society, at a macro-scale has many measurable characteristics in the form of statistical distributions and aggregate measures; data which is increasingly abundant with the proliferation of online social media, mobile devices, and the internet of things. However, the decision-making processes and limits of the individuals who interact to generate these statistical patterns are often difficult to unravel. Furthermore, multiple causal factors often interact to determine the outcome of a particular behavior. Quantifying the importance of these causal factors and their interactions, which make up a particular decision-making process, towards a societal outcome of interest helps extract explanations that provide a deeper understanding of social behavior. Holistic, generative modeling techniques, in particular agent-based modeling, are able to 'grow' artificial societies that replicate emergent patterns seen in the real world. Driving the autonomous agents of these models are rules,…

This study presents a comprehensive investigation of methods and technologies for developing a computer vision-based framework for Structural Health Monitoring (SHM) and Structural Identification (St-Id) for civil infrastructure systems, with particular emphasis on various types of bridges. SHM is implemented on various structures over the last two decades, yet, there are some issues such as considerable cost, field implementation time and excessive labor needs for the instrumentation of sensors, cable wiring work and possible interruptions during implementation. These issues make it only viable when major investments for SHM are warranted for decision making. For other cases, there needs to be a practical and effective solution, which computer-vision based framework can be a viable alternative. Computer vision based SHM has been explored over the last decade. Unlike most of the vision-based structural identification studies and practices, which focus either on structural input (vehicle location) estimation or on structural output (structural displacement and strain responses)…

Connected and automated vehicle (CAV) technologies have recently drawn an increasing attention from governments, vehicle manufacturers, and researchers. Connected vehicle (CV) technologies provide real-time information about the surrounding traffic condition (i.e., position, speed, acceleration) and the traffic management center's decisions. The CV technologies improve the safety by increasing driver situational awareness and reducing crashes through vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I). Vehicle platooning with CV technologies is another key element of the future transportation systems which helps to simultaneously enhance traffic operations and safety. CV technologies can also further increase the efficiency and reliability of automated vehicles (AV) by collecting real-time traffic information through V2V and V2I. However, the market penetration rate (MPR) of CAVs and the higher level of automation might not be fully available in the foreseeable future. Hence, it is worthwhile to study the safety benefits of CAV technologies under different MPRs and lower…

Deep learning systems are increasingly being adopted for safety critical tasks such as autonomous driving. These systems can be exposed to adverse weather conditions such as fog, rain and snow. Vulnerability of deep learning systems to synthetic adversarial attacks has been extensively studied and demonstrated, but the impact of natural weather conditions on these systems has not been studied in detail. In this paper, we study the effects of fog on classification accuracy of the popular Inception deep learning model. We use stereo images from the Cityscapes dataset and computer graphics techniques to mimic realistic naturally occurring fog. We show that the Inception deep learning model is vulnerable to the addition of fog in images.

An increasing number of people are taking advantage of health tourism to access medical services abroad. For the U.S. to be competitive in the lucrative health tourism environment, it is essential to target the right markets. Until now the information available to do this has been limited. This knowledge gap is being addressed by Dr. Jorge Ridderstaat and Dr. Dipendra Singh from Rosen College of Hospitality Management and colleagues. These researchers have developed a microeconomic elasticity approach that offers an understanding of the effects of individual tourism markets on the total health tourism spending in the U.S.

As Zika emerged as a major global health threat, public information officers (PIOs) at local public health departments across the United States prepared for outbreaks of the virus amid great uncertainty. Using the crisis and risk emergency communication (CERC) model to inform this study, PIOs (n = 226) at public health departments were surveyed to assess how community size, perceived control over health agenda, and other considerations such as resources and federal influences affected their satisfaction with Zika preparedness in their departments. These contextual, indirect factors may moderate planning efforts for Zika and other health emergencies and thus should be considered in crisis management and planning models such as CERC.

In this article, the investigators present a new method using a deep learning approach to diagnose schizophrenia. In the experiment presented, the investigators have used a secondary dataset provided by National Institutes of Health. The aforementioned experimentation involves analyzing this dataset for existence of schizophrenia using traditional machine learning approaches such as logistic regression, support vector machine, and random forest. This is followed by application of deep learning techniques using three hidden layers in the model. The results obtained indicate that deep learning provides state-of-the-art accuracy in diagnosing schizophrenia. Based on these observations, there is a possibility that deep learning may provide a paradigm shift in diagnosing schizophrenia.

Using quadcopters for analysis of an environment has been an intriguing subject of study recently. The purpose of this work is to develop a fully autonomous UAV platform for Railroad inspection The dynamics of the quadrotor is derived using Euler's and Newton's laws and then linearized around the hover position. A PID controller is designed to control the states of the quadrotor in a manner to effectively follow a vision-based path, using the down facing camera on a Parrot Mambo quadrotor. Using computer vision the distance from the position of the quadrotor to the position of the center of the path was found. Using the yaw controller to minimize this distance was found to be an adequate method of vision-based path following, by keeping the area of interest in the field of view of the camera. The downfacing camera is also simultaneously observing the path to detect defects using machine learning. This technique was able to detect simulated defects on the path with around 90% accuracy.

This research examined how corporate social advocacy (CSA) and corporate social responsibility (CSR) efforts impacted perceptions of authenticity. Using an experimental survey, participants were randomly exposed to Nike's actions related to the Black Lives Matter (BLM) movement via mock-online news articles. Participants completed a survey that contained Likert-type scale items regarding attitudes (perceived corporate intent, perceived authenticity, brand trust, and brand credibility) and behavioral intentions (word of mouth intentions (WOM), and purchase intention (PI)). Results indicated that positive attitudes significantly increased when Nike implemented an action step after taking a public stance on a controversial social-political issue. Further, results revealed significant differences for positive WOM intentions and PI, given the experimental prompt. This study extends public relations scholarship through expanding our understanding of stakeholder perceptions of authenticity when companies engage in CSA and CSR practices. To earn legitimacy, companies must meet stakeholder…

Medical image segmentation is one of the fundamental processes to understand and assess the functionality of different organs and tissues as well as quantifying diseases and helping treatment planning. With ever increasing number of medical scans, the automated, accurate, and efficient medical image segmentation is as unmet need for improving healthcare. Recently, deep learning has emerged as one the most powerful methods for almost all image analysis tasks such as segmentation, detection, and classification and so in medical imaging. In this regard, this dissertation introduces new algorithms to perform medical image segmentation for different (a) imaging modalities, (b) number of objects, (c) dimensionality of images, and (d) under varying labeling conditions. First, we study dimensionality problem by introducing a new 2.5D segmentation engine that can be used in single and multi-object settings. We propose new fusion strategies and loss functions for deep neural networks to generate improved delineations. Later, we expand the proposed idea into 3D and 4D medical images and…

Detection of developmental dysplasia of the hip (DDH) in infants and children is important as it leads to permanent hip instability. Current methods for detecting DDH, such as ultrasound and x-rays, are relatively expensive and need qualified medical personnel to administer the test. Furthermore, x-ray ionizing radiation can have potential harmful effects. In the current study, an acoustic non-invasive and simple approach was investigated for detection of DDH. Different benchtop simplified models and pig models were constructed and tested. Models were stimulated with band-limited white acoustic noise (10-2500 Hz) and the response of the models was measured. The power spectrum density, transfer function, and coherence were determined for different hip dysplasia levels and for normal cases. Results showed that the power spectrum density, transfer function, and coherence were affected by dysplasia occurrence. Effects appear larger for more severe dysplastic hips. This suggests that the proposed approach may have potential for DDH detection.

The present study focused on preservice teachers’ grammar knowledge and its importance for their future students’ understanding and use of language, particularly English Learners. This quasi-experimental one-group pretest-posttest study investigated the grammar knowledge of preservice teachers who were enrolled in an undergraduate applied linguistics course at an urban university in the southern United States. The results confirmed prior research which found that preservice teachers are not knowledgeable enough about English grammar when explaining sentence level errors. This study demonstrated that preservice teachers’ basic understanding of English grammar can be increased in a short time, particularly in the recognition of simple grammatical items. However, the findings also indicated that more time is needed to ensure a higher level of metalinguistic awareness, conceptualized as the participants’ ability to understand and analyze common grammar errors using metalanguage. The main implication for preservice teacher programs, especially those inclusive of English Learner teaching…

This research examined how information regarding a robot teammate's reliability and the consequences for mistakes made by a robot in its task influence reliance on the robot by a human teammate. Of interest in this research was the notion of appropriate reliance: relying on a robot teammate's decisions when it is performing well and not relying on its decisions when it is performing poorly. An experiment was conducted in which participants interacted with an autonomous robot teammate while performing a cordon and search operation within a virtual reality simulation environment. Participants were responsible for monitoring the perimeter of a search area while their robot teammate searched the area for target objects. The robot's reliability shifted between 90% (good) or 10% (poor) based on the environment it was currently searching. Participants were assigned to one of four experimental groups that differed according to: (a) the information they were provided about the robot teammate's reliability and which factors influenced it (minimal information or complete information), and (b)…

At the time of the Deepwater Horizon oil spill in 2010, very little was known about the inshore bottlenose dolphin (Tursiops truncatus) populations hit hardest by the spill. Without previous population demographic data impacts were challenging to assess. My dissertation was designed to build research capacity moving forward by helping to fill data gaps in the western Florida Panhandle. The first study presented here resulted in the first system-wide assessment of seasonal abundance, survival, and site fidelity patterns of bottlenose dolphins that inhabit the Pensacola Bay system. In contrast to a previous study that reported only 33 dolphins, results from mark-recapture analyses estimated abundance ranging from 220-310 individuals, which consisted of a high proportion (43%) of transients. The second study revealed fine-scale genetic population structure (detected using both microsatellite and mitochondrial DNA markers) among five inshore systems in the Florida Panhandle. Migration rates were variable among populations with higher gene flow moving from east to west than in the…

The purpose of this quantitative study was to identify and describe the nature and extent of the relationships, if any, that existed between a Community Partnership Schools™ (CPS) model community school and the outcomes of graduation and attendance rates at one public high school in Florida. An evaluation study utilizing an interrupted time series (ITS) design addressed this problem by identifying and describing the relationship between the CPS model and the key outcome measures using visual analysis and descriptive statistics. Graduation and attendance rates for seven years before the CPS model was introduced (2003-2010) and seven years after the CPS model was introduced (2010-2017) at the CPS school were compared to the graduation and attendance rates for the same time frames of five other matched comparison high schools that had not implemented a CPS model community school. Findings of this study, though mixed, suggest the Community Partnership Schools™ model may have provided a positive environment for improvement in key measures at the targeted CPS high school. Though no…

A global challenge is to develop environmentally friendly, affordable, compact and sustainable technologies to provide heating and cooling power. Adsorption cooling (AC) technology is one of the most promising ways to solve the environmental issues and cut down the energy consumption related to the traditional air conditioning and refrigeration systems. However, AC systems still suffer from poor heat and mass transfer inside the adsorption bed, which is the main obstacle to commercialization of adsorption cooling units. The main goal of this study is designing an efficient adsorption cooling cycle. In this research work, an in-depth scaling analysis of heat and mass transfer in an adsorption packed bed has been performed to identify and quantify how the effective thermal diffusivity of an adsorption bed and the surface diffusion rate of an adsorbate in a nanoporous adsorbent affect the specific cooling power of an adsorption cooling system. The main goal of this study is to derive new scaling parameters that can be used to specify the optimal bed dimensions and select the…

It is generally believed that a victim of an intimate partner homicide, who faced ongoing physical violence prior to the killing, would have contacted authorities for assistance or protection some time prior to their death. However, the results of this study show that this notion that a victim of ongoing abuse will, more than likely, request help is a misconception. Through qualitative and quantitative methods analysis, this study reveals the dearth of prior reporting of physical violence to law enforcement or the court when an intimate partner homicide takes place between heterosexual spouses in Florida between 2006 and 2016. Additionally, "coercive control," a term that is not nearly as recognizable as domestic violence or intimate partner violence but that should be understood and regulated, was conceptualized and operationalized using NVivo Pro 12, a qualitative social sciences software package. By constructing an original data set from secondary data from the Florida Department of Law Enforcement Uniform Crime Report Supplemental Homicide Report, multiple law enforcement…

These two companion studies theoretically and empirically examine managers' use of different cognitive frames in decision-making related to corporate sustainability. Study I is a theoretical undertaking aimed at highlighting potential zones of investigation arising from the introduction of paradox theory into managerial accounting. First, I examine extant literature on paradoxes to garner an understanding of its evolution and application in the management and psychology domains. Second, I use current constructs and typologies to identify multiple sustainability and managerial accounting tensions as paradoxical. Third, I make recommendations on how to apply paradox theory more effectively to the corporate sustainability tensions I identified. I conclude the first paper with research questions pertaining to managerial accounting in corporate sustainability. Study II is a behavioral experiment. In this study I examine the effects of business case and paradoxical case cognition on managers and seek to uncover which organizational performance measures better support each cognition.…

Ceramics are ubiquitous in man-made and natural structures. Their mechanical properties highly depend on their composition, microstructure and level of defects in the bulk of the material, the latter affecting the integrity of the components; such is the case of boron-rich ceramics where large agglomerates create high stressed regions, or coral skeleton where porosity determines their strength against hydrodynamic forces present in the ocean tides. Therefore, studying the properties of ceramic materials using invasive and non-invasive methods helps in the understanding of the link between the properties and the performance of the structures. The aim of this research was to test the novel ceramic component ZrB2-30wt%SiB6 and Acropora cervicornis coral skeleton using non-conventional techniques that allow for the study of their mechanical properties and their behavior when exposed to external loads present in their environments of application. The first part of this study focuses on understanding the effects of adding SiB6 to enhance the mechanical properties of ZrB2 ceramics for…

This interdisciplinary dissertation explores perceptions of control in modded and unmodded versions of Bethesda's sandbox video game Skyrim. Sandbox games are known for greater choice options that suggest greater perceptions of control for gamers. Sandbox games also generally encourage the use of user-generated creations called modifications (mods) that users can download to personalize their games. While we need philosophy to understand and define control as a concept, we also need psychology to understand how users perceive control in media studies. At present, qualitative academic research that measures gamer perceptions of control is non-existent as is research on how users articulate their experiences with mods. Interviews were conducted with twenty-seven individuals who identified as gamers to analyze these perceptions of control in a game like Skyrim. The first chapter is introductory and outlines key terms for the dissertation as well as the play study's methodology. The second chapter examines philosophical and psychological perceptions of control that correspond with…

For this thesis, a study was completed on two different structures on the UCF Orlando campus through the use of both structural plans and point cloud technology. The results sought to understand the viability of point cloud technology as an accurate tool for the static and dynamic modal analysis of existing structures. For static analysis, a portion of the framing of Spectrum Stadium was rendered, modeled, analyzed and compared to a previous case study. The results emphasized how different users can render dissimilar member sizes and lengths due to human judgment on point cloud visuals. The study also found that structural plans cannot always be relied upon as the most accurate source for analysis as the new point cloud produced more accurate results than the structural plans when compared to the control model. For the pedestrian bridge, the structure was scanned, rendered and modeled for both static and dynamic modal analysis. The point cloud produced from scanning the bridge was modified twice in order to have three distinct point clouds with varying densities: fine, medium and…

This study investigates the extent to which the fluent life partners (LPs) of persons who stutter (PWS) understand the effect stuttering has on their partner who stutters' communication attitude. This was accomplished by administering the Communication Attitude Test for Adults Who Stutter (BigCAT; Vanryckeghem & Brutten, 2018), a subtest of the Behavior Assessment Battery (BAB; Vanryckeghem & Brutten, 2018). The BigCAT was administered to 33 PWS and a modified version was administered to their LPs via Qualtrics, an online survey software system. Between-group total score comparison revealed no significant difference in total scores, and a low-medium score correlation was evidenced. Within both groups, participants age and gender did not have a significant effect on total scores. The perception of stuttering severity was found to significantly influence BigCAT scores within each group. No differential effect of duration of relationship on score agreement was found to exist. A high Cronbach Alpha coefficient was obtained for both test forms. Between-group item score comparison…

The emergence of digital currency is becoming prevalent in the age of globalization – specifically, cryptocurrencies. Cryptocurrencies and blockchain are two recently discovered concepts currently being explored by researchers and developers. Cryptocurrency is a subset of digital currency that encompasses revolutionary technology, shifting political and economic spheres in nation-states. Certain governments are more prone to the adoption of cryptocurrencies and three comparative case study countries, Iran, Russia, and Venezuela, have shared attributes that result in adoption. Observed factors that result in the adoption of cryptocurrencies include corruption, GDP level, economic volatility, and Western sanctions. These factors will be applied in the case study countries to analyze the adoption of native government-backed cryptocurrency.

Lithium ion batteries (LIBs) have been used in various applications such as portable electronics, grid storages, and electric vehicles (EVs). Despite its commercial success, further advancement of the battery is necessary to satisfy the increasing demands for low-cost and high- performance energy storage devices as LIB is reaching its theoretical limits. Lithium sulfur battery (LSB) is one of the promising candidates for the next generation energy storage technologies. LSB uses sulfur cathode which is a low-cost and earth abundant material with an extremely high theoretical capacity of 2600 Wh kg-1. Although there have been numerous researches aiming to establish the LSB technology, it is still in a development stage. Some of the major challenges are; low-electric conductivity, dissolution of the intermediate lithium-polysulfide reactants, and the low Coulombic efficiency. These issues must be overcome before LSBs can become practical. The objective of this work is to develop an LSB cathode that solves the above issues and contributes to advancing the development of the LSB…

The recruitment success of mangroves is influenced by a variety of factors, including propagule availability, desiccation, herbivory, and hydraulic habitat limitations. Hydrodynamic forces (waves and currents) act as obstacles to mangrove recruitment, restricting the successful colonization of mangrove species. We evaluated the biological and physical limitations to mangrove recruitment through monthly shoreline surveys and lateral pull-tests. Surveys followed mangroves from propagule release through recruitment along the shorelines of De Soto National Memorial (Bradenton, FL), capturing differences in propagule availability and recruitment along natural areas and across differing forms of shoreline stabilization ("living shorelines" and revetments). Propagule densities were highest along "living shorelines", followed by natural areas and revetments. Seedling densities were similar across treatments, mirroring densities found in disturbed mangrove systems in the Philippines ( < 1 seedling per m2). Pull-tests, simulating wave forces, quantified the physical thresholds for uprooting…

The revolution in chip manufacturing processes spanning five decades has proliferated high performance and energy-efficient nano-electronic devices across all aspects of daily life. In recent years, CMOS technology scaling has realized billions of transistors within large-scale VLSI chips to elevate performance. However, these advancements have also continually augmented the impact of Single-Event Transient (SET) and Single-Event Upset (SEU) occurrences which precipitate a range of Soft-Error (SE) dependability issues. Consequently, soft-error mitigation techniques have become essential to improve systems' reliability. Herein, first, we proposed optimized soft-error resilience designs to improve robustness of sub-micron computing systems. The proposed approaches were developed to deliver energy-efficiency and tolerate double/multiple errors simultaneously while incurring acceptable speed performance degradation compared to the prior work. Secondly, the impact of Process Variation (PV) at the Near-Threshold Voltage (NTV) region on redundancy-based SE-mitigation approaches for…

Ytterbia (Yb2O3) is an oxide ceramic, whose magnetic properties and crystal structure were studied to some extent in the past. However, the information on Yb2O3's catalytic properties is lacking. Therefore, in this work, the sintering behavior and catalytic properties of Yb2O3 were examined. Yb2O3 ceramic samples were made using pressureless sintering of the commercially available Yb2O3 with 99.99% purity powder. The powder was first uniaxially pressed at 20 MPa in a steel die followed by pressureless sintering at different temperatures of 900 ⁰C to 1600 ⁰C for 4 hours. The densities of these samples were measured, and the sample sintered at 1600 ⁰C had the largest density of 62.88% and 900 ⁰C samples had the lowest of 45%. To improve the density of samples, three samples were uniaxially pressed same as the previous samples; however, they were also cold isostatically pressed at 260 MPa. These samples yielded the highest density of 90% after sintering at 1700 ⁰C for 4 hours. Raman spectra of sintered Yb2O3 were collected, which corresponded very well to those published in the…

A successful event or festival can be a huge draw to a tourist destination. As lesbian, gay, bisexual, and transgender (LGBT) travelers are increasingly recognized as a growing market for tourism, events aimed at this demographic are expanding in number and scale. It is therefore useful to understand what factors influence attendance. In a study designed to do just this, Dr. Jeeyeon Hahm and Dr. Heejung Ro from the Rosen College of Hospitality Management looked at psychological variables related to social identity to examine what influences satisfaction and repeat attendance at LGBT events.

Smart initiatives are gaining popularity from the development of smart homes and smart communities to the emergence of smart cities all around the world. Smart technologies like AI-powered digital assistants are becoming more widespread within the tourism industry, giving rise to the concept of smart destinations. Despite the growing awareness, the theoretical and practical knowledge of smart destinations remains fragmented and mostly speculative. The primary objectives of this research study are: 1) to develop a comprehensive framework of smart destinations through multiple case studies of the emerging smart destinations and interviews with the industry stakeholders, and 2) to construct and apply a smartness index based on the framework that could serve as a practical tool to assess the smartness level of various tourism destinations. The study adopts a Destination Marketing/Management Organization (DMO) perspective as these organizations are uniquely positioned to fulfill the key roles in coordination, facilitation, and governance of smart tourism. That is, the technological…