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.

Advanced Placement and American education: A Foucauldian analysis of the Advanced Placement Program of the college board

Advanced Placement is a series of courses and tests designed to determine mastery over introductory college material. It has become part of the American educational system. The changing conception of AP was examined using critical theory to determine what led to a view of continual success. The study utilized David Armstrong's variation of Michel Foucault's critical theory to construct an analytical framework. Black and Ubbes' data gathering techniques and Braun and Clark's data analysis were utilized as the analytical framework. Data included 1135 documents: 641 journal articles, 421 newspaper articles and 82 government documents. ^ The study revealed three historical ruptures correlated to three themes containing subthemes. The first rupture was the Sputnik launch in 1958. Its correlated theme was AP leading to school reform with subthemes of AP as reform for able students and AP's gaining of acceptance from secondary schools and higher education. The second rupture was the Nation at Risk report published in 1983. Its correlated theme was AP's shift in emphasis from the exam to the course with the subthemes of AP as a course, a shift in AP's target population, using AP courses to promote equity, and AP courses modifying curricula. The passage of the No Child Left Behind Act of 2001 was the third rupture. Its correlated theme was AP as a means to narrow the achievement gap with the subthemes of AP as a college preparatory program and the shifting of AP to an open access program. ^ The themes revealed a perception that progressively integrated the program into American education. The AP program changed emphasis from tests to curriculum, and is seen as the nation's premier academic program to promote reform and prepare students for college. It has become a major source of income for the College Board. In effect, AP has become an agent of privatization, spurring other private entities into competition for government funding. The change and growth of the program over the past 57 years resulted in a deep integration into American education. As such the program remains an intrinsic part of the system and continues to evolve within American education. ^

Flood risk analysis of the White Oak Creek watershed in Oak Ridge, Tennessee using MIKE SHE and MIKE 11 software

The purpose of this study was to determine the flooding potential of contaminated areas within the White Oak Creek watershed in the Oak Ridge Reservation in Tennessee. The watershed was analyzed with an integrated surface and subsurface numerical model based on MIKE SHE/MIKE 11 software. The model was calibrated and validated using five decades of historical data. A series of simulations were conducted to determine the watershed response to 25 year, 100 year and 500 year precipitation forecasts; flooding maps were generated for those events. Predicted flood events were compared to Log Pearson III flood flow frequency values for validation. This investigation also provides an improved understanding of the water fluxes between the surface and subsurface subdomains as they affect flood frequencies. In sum, this study presents crucial information to further assess the environmental risks of potential mobilization of contaminants of concern during extreme precipitation events.

Advanced Placement and American Education: A Foucauldian Analysis of the Advanced Placement Program of the College Board

Advanced Placement is a series of courses and tests designed to determine mastery over introductory college material. It has become part of the American educational system. The changing conception of AP was examined using critical theory to determine what led to a view of continual success. The study utilized David Armstrong’s variation of Michel Foucault’s critical theory to construct an analytical framework. Black and Ubbes’ data gathering techniques and Braun and Clark’s data analysis were utilized as the analytical framework. Data included 1135 documents: 641 journal articles, 421 newspaper articles and 82 government documents. The study revealed three historical ruptures correlated to three themes containing subthemes. The first rupture was the Sputnik launch in 1958. Its correlated theme was AP leading to school reform with subthemes of AP as reform for able students and AP’s gaining of acceptance from secondary schools and higher education. The second rupture was the Nation at Risk report published in 1983. Its correlated theme was AP’s shift in emphasis from the exam to the course with the subthemes of AP as a course, a shift in AP’s target population, using AP courses to promote equity, and AP courses modifying curricula. The passage of the No Child Left Behind Act of 2001 was the third rupture. Its correlated theme was AP as a means to narrow the achievement gap with the subthemes of AP as a college preparatory program and the shifting of AP to an open access program. The themes revealed a perception that progressively integrated the program into American education. The AP program changed emphasis from tests to curriculum, and is seen as the nation’s premier academic program to promote reform and prepare students for college. It has become a major source of income for the College Board. In effect, AP has become an agent of privatization, spurring other private entities into competition for government funding. The change and growth of the program over the past 57 years resulted in a deep integration into American education. As such the program remains an intrinsic part of the system and continues to evolve within American education.

Geospatial Data Indexing Analysis and Visualization via Web Services with Autonomic Resource Management

With the exponential growth of the usage of web-based map services, the web GIS application has become more and more popular. Spatial data index, search, analysis, visualization and the resource management of such services are becoming increasingly important to deliver user-desired Quality of Service. First, spatial indexing is typically time-consuming and is not available to end-users. To address this, we introduce TerraFly sksOpen, an open-sourced an Online Indexing and Querying System for Big Geospatial Data. Integrated with the TerraFly Geospatial database [1-9], sksOpen is an efficient indexing and query engine for processing Top-k Spatial Boolean Queries. Further, we provide ergonomic visualization of query results on interactive maps to facilitate the user’s data analysis. Second, due to the highly complex and dynamic nature of GIS systems, it is quite challenging for the end users to quickly understand and analyze the spatial data, and to efficiently share their own data and analysis results with others. Built on the TerraFly Geo spatial database, TerraFly GeoCloud is an extra layer running upon the TerraFly map and can efficiently support many different visualization functions and spatial data analysis models. Furthermore, users can create unique URLs to visualize and share the analysis results. TerraFly GeoCloud also enables the MapQL technology to customize map visualization using SQL-like statements [10]. Third, map systems often serve dynamic web workloads and involve multiple CPU and I/O intensive tiers, which make it challenging to meet the response time targets of map requests while using the resources efficiently. Virtualization facilitates the deployment of web map services and improves their resource utilization through encapsulation and consolidation. Autonomic resource management allows resources to be automatically provisioned to a map service and its internal tiers on demand. v-TerraFly are techniques to predict the demand of map workloads online and optimize resource allocations, considering both response time and data freshness as the QoS target. The proposed v-TerraFly system is prototyped on TerraFly, a production web map service, and evaluated using real TerraFly workloads. The results show that v-TerraFly can accurately predict the workload demands: 18.91% more accurate; and efficiently allocate resources to meet the QoS target: improves the QoS by 26.19% and saves resource usages by 20.83% compared to traditional peak load-based resource allocation.