Exploring Hidden Coherent Feature Groups and Temporal Semantics for Multimedia Big Data Analysis

Thanks to the advanced technologies and social networks that allow the data to be widely shared among the Internet, there is an explosion of pervasive multimedia data, generating high demands of multimedia services and applications in various areas for people to easily access and manage multimedia data. Towards such demands, multimedia big data analysis has become an emerging hot topic in both industry and academia, which ranges from basic infrastructure, management, search, and mining to security, privacy, and applications. Within the scope of this dissertation, a multimedia big data analysis framework is proposed for semantic information management and retrieval with a focus on rare event detection in videos. The proposed framework is able to explore hidden semantic feature groups in multimedia data and incorporate temporal semantics, especially for video event detection. First, a hierarchical semantic data representation is presented to alleviate the semantic gap issue, and the Hidden Coherent Feature Group (HCFG) analysis method is proposed to capture the correlation between features and separate the original feature set into semantic groups, seamlessly integrating multimedia data in multiple modalities. Next, an Importance Factor based Temporal Multiple Correspondence Analysis (i.e., IF-TMCA) approach is presented for effective event detection. Specifically, the HCFG algorithm is integrated with the Hierarchical Information Gain Analysis (HIGA) method to generate the Importance Factor (IF) for producing the initial detection results. Then, the TMCA algorithm is proposed to efficiently incorporate temporal semantics for re-ranking and improving the final performance. At last, a sampling-based ensemble learning mechanism is applied to further accommodate the imbalanced datasets. In addition to the multimedia semantic representation and class imbalance problems, lack of organization is another critical issue for multimedia big data analysis. In this framework, an affinity propagation-based summarization method is also proposed to transform the unorganized data into a better structure with clean and well-organized information. The whole framework has been thoroughly evaluated across multiple domains, such as soccer goal event detection and disaster information management.

A qualitative case study of teacher perceptions and concerns during the implementation of literacy folders in a select elementary school in Broward County, Florida

Classroom teachers are often required to implement new procedures or practices in response to local or federal education mandates. Attempts to implement innovations, often do not take into account the personal side of change; the perceptions, concerns and needs of those required to implement the innovation. One innovation that was required by the School Board of Broward County, Florida for all elementary classroom teachers was the implementation of Literacy Folders. ^ This study attempted to address the personal side of change by identifying teacher concerns during the implementation of Literacy Folders in a select elementary school in Broward County Florida. The Concerns Based Adoption model (CBAM) for change was used as the conceptual framework for this qualitative case study. ^ Sources of data for this study included participant interviews, observations and analysis of documents. Informal conversations with the participants and unscheduled classroom visits were also sources of data. Seven classroom teachers were interviewed using a predesigned interview guide developed based on the CBAM of change, specifically the Stages of Concern Dimension. Participant responses were coded into two categories, (a) recollections of past perceptions, and (b) present perceptions regarding the innovation. ^ Data analysis resulted in the emergence of one major theme and two subordinate themes. The themes were related to time and purpose of the innovation. The researcher also discovered that the participants exhibited responses typically representative of the CBAM for individuals who are in the process of adjusting to a new innovation. ^ Recommendations based on participant concerns are made for improving the implementation of the innovation. Recommendations for alternatives to the innovation and suggestions regarding areas for further research in the field of educational change are also made. ^

Belowground decomposition of mangrove roots in Florida coastal everglades

Mangrove root decomposition rates were measured by distributing mesh bags containing fine root material across six sites with different soil fertility and hydroperiod to compare ambient differences to substrate quality. Roots from a site with lower soil phosphorus concentration were used as a reference and compared to ambient roots at five other sites with increased phosphorus concentration. Four mesh bags of each root type (ambient versus reference), separated into four 10-cm replicate intervals, were buried up to 42 cm depth at each site and incubated for 250 d (initiation in May 2004). Mass loss of ambient mangrove roots was significant at all study sites and ranged from 17% to 54%; there was no significant difference with depth at any one site. Reference decomposition constants (−k) ranged from 0.0012 to 0.0018 d−1 among Taylor Slough sites compared to 0.0023–0.0028 d−1 among Shark River sites, indicating slower decomposition rates associated with lower soil phosphorous and longer flood duration. Reference roots had similar decomposition rates as ambient roots in four of the six sites, and there were no significant correlations between indices of root substrate quality and decomposition rates. Among these distinct landscape gradients of south Florida mangroves, soil environmental conditions have a greater effect on belowground root decomposition than root substrate quality.

A qualitative analysis of the lived experience of nursing staff developers in the process of changing to a new educational model

The purpose of this study was to document and critically analyze the lived experience of selected nursing staff developers in the process of moving toward a new model for hospital nursing education. Eleven respondents were drawn from a nation-wide population of about two hundred individuals involved in nursing staff development. These subjects were responsible for the implementation of the Performance Based Development System (PBDS) in their institutions.^ A purposive, criterion-based sampling technique was used with respondents being selected according to size of hospital, primary responsibility for orchestration of the change, influence over budgetary factors and managerial responsibility for PBDS. Data were gathered by the researcher through both in-person and telephone interviews. A semi-structured interview guide, designed by the researcher was used, and respondents were encouraged to amplify on their recollections as desired. Audiotapes were transcribed and resulting computer files were analyzed using the program "Martin". Answers to interview questions were compiled and reported across cases. The data was then reviewed a second time and interpreted for emerging themes and patterns.^ Two types of verification were used in the study. Internal verification was done through interview transcript review and feedback by respondents. External verification was done through review and feedback on data analysis by readers who were experienced in management of staff development departments.^ All respondents were female, so Gilligan's concept of the "ethic of care" was examined as a decision making strategy. Three levels of caring which influenced decision making were found. They were caring: (a) for the organization, (b) for the employee, and (c) for the patient. The four existentials of the lived experience, relationality, corporeality, temporality and spatiality were also examined to reveal the everydayness of making change. ^

Quantifying the effects of temperature and concentration on variable-density flow in numerical modeling of groundwater systems: Implications for predictive uncertainty and data collection

Groundwater systems of different densities are often mathematically modeled to understand and predict environmental behavior such as seawater intrusion or submarine groundwater discharge. Additional data collection may be justified if it will cost-effectively aid in reducing the uncertainty of a model's prediction. The collection of salinity, as well as, temperature data could aid in reducing predictive uncertainty in a variable-density model. However, before numerical models can be created, rigorous testing of the modeling code needs to be completed. This research documents the benchmark testing of a new modeling code, SEAWAT Version 4. The benchmark problems include various combinations of density-dependent flow resulting from variations in concentration and temperature. The verified code, SEAWAT, was then applied to two different hydrological analyses to explore the capacity of a variable-density model to guide data collection. ^ The first analysis tested a linear method to guide data collection by quantifying the contribution of different data types and locations toward reducing predictive uncertainty in a nonlinear variable-density flow and transport model. The relative contributions of temperature and concentration measurements, at different locations within a simulated carbonate platform, for predicting movement of the saltwater interface were assessed. Results from the method showed that concentration data had greater worth than temperature data in reducing predictive uncertainty in this case. Results also indicated that a linear method could be used to quantify data worth in a nonlinear model. ^ The second hydrological analysis utilized a model to identify the transient response of the salinity, temperature, age, and amount of submarine groundwater discharge to changes in tidal ocean stage, seasonal temperature variations, and different types of geology. The model was compared to multiple kinds of data to (1) calibrate and verify the model, and (2) explore the potential for the model to be used to guide the collection of data using techniques such as electromagnetic resistivity, thermal imagery, and seepage meters. Results indicated that the model can be used to give insight to submarine groundwater discharge and be used to guide data collection. ^

Comparison of Cardiovascular Disease Risk Factors between Single and Partnered Mothers: Data from the 2006 Health Survey of Adults and Children in Bermuda

Women are a high-risk population for cardiovascular diseases (CVD); however relationships between CVD and subpopulations of mothers are sparse. A secondary data analysis of the 2006 Health Survey of Adults and Children in Bermuda was conducted to compare the prevalence of CVD risk factors in single (n=77) and partnered (n=241) mothers. A higher percentage of single mothers were Black (p25 kg/m2 (p=0.01) and reported high blood pressure (p=0.004) and high cholesterol (0.017). Single mothers were nearly three times (OR=2.66) more likely to experience high blood pressure and two times (OR= 2.22) more likely to have high cholesterol. Single mothers may benefit from nutrition education programs related to lowering CVD risk.