A multimedia indexing and retrieval framework for multimedia database systems

The main challenges of multimedia data retrieval lie in the effective mapping between low-level features and high-level concepts, and in the individual users' subjective perceptions of multimedia content. ^ The objectives of this dissertation are to develop an integrated multimedia indexing and retrieval framework with the aim to bridge the gap between semantic concepts and low-level features. To achieve this goal, a set of core techniques have been developed, including image segmentation, content-based image retrieval, object tracking, video indexing, and video event detection. These core techniques are integrated in a systematic way to enable the semantic search for images/videos, and can be tailored to solve the problems in other multimedia related domains. In image retrieval, two new methods of bridging the semantic gap are proposed: (1) for general content-based image retrieval, a stochastic mechanism is utilized to enable the long-term learning of high-level concepts from a set of training data, such as user access frequencies and access patterns of images. (2) In addition to whole-image retrieval, a novel multiple instance learning framework is proposed for object-based image retrieval, by which a user is allowed to more effectively search for images that contain multiple objects of interest. An enhanced image segmentation algorithm is developed to extract the object information from images. This segmentation algorithm is further used in video indexing and retrieval, by which a robust video shot/scene segmentation method is developed based on low-level visual feature comparison, object tracking, and audio analysis. Based on shot boundaries, a novel data mining framework is further proposed to detect events in soccer videos, while fully utilizing the multi-modality features and object information obtained through video shot/scene detection. ^ Another contribution of this dissertation is the potential of the above techniques to be tailored and applied to other multimedia applications. This is demonstrated by their utilization in traffic video surveillance applications. The enhanced image segmentation algorithm, coupled with an adaptive background learning algorithm, improves the performance of vehicle identification. A sophisticated object tracking algorithm is proposed to track individual vehicles, while the spatial and temporal relationships of vehicle objects are modeled by an abstract semantic model. ^

Capacity-based cost modeling for light rail and bus rapid transit systems

Choosing between Light Rail Transit (LRT) and Bus Rapid Transit (BRT) systems is often controversial and not an easy task for transportation planners who are contemplating the upgrade of their public transportation services. These two transit systems provide comparable services for medium-sized cities from the suburban neighborhood to the Central Business District (CBD) and utilize similar right-of-way (ROW) categories. The research is aimed at developing a method to assist transportation planners and decision makers in determining the most feasible system between LRT and BRT. ^ Cost estimation is a major factor when evaluating a transit system. Typically, LRT is more expensive to build and implement than BRT, but has significantly lower Operating and Maintenance (OM) costs than BRT. This dissertation examines the factors impacting capacity and costs, and develops cost models, which are a capacity-based cost estimate for the LRT and BRT systems. Various ROW categories and alignment configurations of the systems are also considered in the developed cost models. Kikuchi's fleet size model (1985) and cost allocation method are used to develop the cost models to estimate the capacity and costs. ^ The comparison between LRT and BRT are complicated due to many possible transportation planning and operation scenarios. In the end, a user-friendly computer interface integrated with the established capacity-based cost models, the LRT and BRT Cost Estimator (LBCostor), was developed by using Microsoft Visual Basic language to facilitate the process and will guide the users throughout the comparison operations. The cost models and the LBCostor can be used to analyze transit volumes, alignments, ROW configurations, number of stops and stations, headway, size of vehicle, and traffic signal timing at the intersections. The planners can make the necessary changes and adjustments depending on their operating practices. ^

Design and fabrication of two switched superconductivity microstrip hairpin filters using series micro-electro-mechanical systems (MEMS) switches

Series Micro-Electro-Mechanical System (MEMS) switches based on superconductor are utilized to switch between two bandpass hairpin filters with bandwidths of 365 MHz and nominal center frequencies of 2.1 GHz and 2.6 GHz. This was accomplished with 4 switches actuated in pairs, one pair at a time. When one pair was actuated the first bandpass filter was coupled to the input and output ports. When the other pair was actuated the second bandpass filter was coupled to the input and output ports. The device is made of a YBa2Cu 3O7 thin film deposited on a 20 mm x 20 mm LaAlO3 substrate by pulsed laser deposition. BaTiO3 deposited by RF magnetron sputtering in utilized as the insulation layer at the switching points of contact. These results obtained assured great performance showing a switchable device at 68 V with temperature of 40 K for the 2.1 GHz filter and 75 V with temperature of 30 K for the 2.6 GHz hairpin filter. ^

The unintended [or intended?] political consequences of electoral systems: The case of Bolivia

The present study was concerned with evaluating one basic institution in Bolivian democracy: its electoral system. The study evaluates the impact of electoral systems on the interaction between presidents and assemblies. It sought to determine whether it is possible to have electoral systems that favor multipartism but can also moderate the likelihood of executive-legislative confrontation by producing the necessary conditions for coalition building. ^ This dissertation utilized the case study method as a methodology. Using the case of Bolivia, the research project studied the variations in executive-legislative relations and political outcomes from 1985 to the present through a model of executive-legislative relations that provided a typology of presidents and assemblies based on the strategies available to them to bargain with each other for support. A complementary model that evaluated the state of their inter-institutional interaction was also employed. ^ Results indicated that executive-legislative relations are profoundly influenced by the choice of the electoral system. Similarly, the project showed that although the Bolivian mixed system for legislative elections, and executive formula favor multipartism, these electoral systems do not necessarily engender executive-legislative confrontation in Bolivia. This was mainly due to the congressional election of the president, and the formulas utilized to translate the popular vote into legislative seats. However, the study found that the electoral system has also allowed for anti-systemic forces to emerge and gain political space both within and outside of political institutions. ^ The study found that government coalitions in Bolivia that are promoted by the system of congressional election of the president and the D'Hondt system to allocate legislative seats have helped ameliorate one of the typical problems of presidential systems in Latin America: the presence of a minority government that is blocked in its capacity to govern. This study was limited to evaluating the impact of the electoral system, as the independent variable, on executive-legislative interaction. However, the project revealed a need for more theoretical and empirical work on executive-legislative bargaining models in order to understand how institutional reforms can have an impact on the incentives of presidents and legislators to form coherent coalitions. ^

Next generation high density three-dimensional magnetic recording systems

This work is the first work using patterned soft underlayers in multilevel three-dimensional vertical magnetic data storage systems. The motivation stems from an exponentially growing information stockpile, and a corresponding need for more efficient storage devices with higher density. The world information stockpile currently exceeds 150EB (ExaByte=1x1018Bytes); most of which is in analog form. Among the storage technologies (semiconductor, optical and magnetic), magnetic hard disk drives are posed to occupy a big role in personal, network as well as corporate storage. However; this mode suffers from a limit known as the Superparamagnetic limit; which limits achievable areal density due to fundamental quantum mechanical stability requirements. There are many viable techniques considered to defer superparamagnetism into the 100's of Gbit/in2 such as: patterned media, Heat-Assisted Magnetic Recording (HAMR), Self Organized Magnetic Arrays (SOMA), antiferromagnetically coupled structures (AFC), and perpendicular magnetic recording. Nonetheless, these techniques utilize a single magnetic layer; and can thusly be viewed as two-dimensional in nature. In this work a novel three-dimensional vertical magnetic recording approach is proposed. This approach utilizes the entire thickness of a magnetic multilayer structure to store information; with potential areal density well into the Tbit/in2 regime. ^ There are several possible implementations for 3D magnetic recording; each presenting its own set of requirements, merits and challenges. The issues and considerations pertaining to the development of such systems will be examined, and analyzed using empirical and numerical analysis techniques. Two novel key approaches are proposed and developed: (1) Patterned soft underlayer (SUL) which allows for enhanced recording of thicker media, (2) A combinatorial approach for 3D media development that facilitates concurrent investigation of various film parameters on a predefined performance metric. A case study is presented using combinatorial overcoats of Tantalum and Zirconium Oxides for corrosion protection in magnetic media. ^ Feasibility of 3D recording is demonstrated, and an emphasis on 3D media development is emphasized as a key prerequisite. Patterned SUL shows significant enhancement over conventional "un-patterned" SUL, and shows that geometry can be used as a design tool to achieve favorable field distribution where magnetic storage and magnetic phenomena are involved. ^

Molecular markers and human history: A tale of two haplogroup systems

To chronicle demographic movement across African Asian corridors, a variety of molecular (sequence analysis, restriction mapping and denaturing high performance liquid chromatography etc.) and statistical (correspondence analysis, AMOVA, calculation of diversity indices and phylogenetic inference, etc.) techniques were employed to assess the phylogeographic patterns of mtDNA control region and Y chromosomal variation among 14 sub-Saharan, North African and Middle Eastern populations. The patterns of genetic diversity revealed evidence of multiple migrations across several African Asian passageways as well within the African continent itself. The two-part analysis uncovered several interesting results which include the following: (1) a north (Egypt and Middle East Asia) to south (sub-Saharan Africa) partitioning of both mtDNA and Y chromosomal haplogroup diversity, (2) a genetic diversity gradient in sub-Saharan Africa from east to west, (3) evidence in favor of the Levantine Corridor over the Horn of Africa as the major genetic conduit since the Last Glacial Maximum, (4) a substantially higher mtDNA versus Y chromosomal sub-Saharan component in the Middle East collections, (5) a higher representation of East versus West African mtDNA haplotypes in the Arabian Peninsula populations versus no such bias in the Levant groups and lastly, (6) genetic remnants of the Bantu demographic expansion in sub-Saharan Africa. ^

Framework for enterprise systems engineering

This research aimed at developing a research framework for the emerging field of enterprise systems engineering (ESE). The framework consists of an ESE definition, an ESE classification scheme, and an ESE process. This study views an enterprise as a system that creates value for its customers. Thus, developing the framework made use of system theory and IDEF methodologies. This study defined ESE as an engineering discipline that develops and applies systems theory and engineering techniques to specification, analysis, design, and implementation of an enterprise for its life cycle. The proposed ESE classification scheme breaks down an enterprise system into four elements. They are work, resources, decision, and information. Each enterprise element is specified with four system facets: strategy, competency, capacity, and structure. Each element-facet combination is subject to the engineering process of specification, analysis, design, and implementation, to achieve its pre-specified performance with respect to cost, time, quality, and benefit to the enterprise. This framework is intended for identifying research voids in the ESE discipline. It also helps to apply engineering and systems tools to this emerging field. It harnesses the relationships among various enterprise aspects and bridges the gap between engineering and management practices in an enterprise. The proposed ESE process is generic. It consists of a hierarchy of engineering activities presented in an IDEF0 model. Each activity is defined with its input, output, constraints, and mechanisms. The output of an ESE effort can be a partial or whole enterprise system design for its physical, managerial, and/or informational layers. The proposed ESE process is applicable to a new enterprise system design or an engineering change in an existing system. The long-term goal of this study aims at development of a scientific foundation for ESE research and development.

A method for enhancing digital information displayed to computer users with visual refractive errors via spatial and spectral processing

This research pursued the conceptualization, implementation, and verification of a system that enhances digital information displayed on an LCD panel to users with visual refractive errors. The target user groups for this system are individuals who have moderate to severe visual aberrations for which conventional means of compensation, such as glasses or contact lenses, does not improve their vision. This research is based on a priori knowledge of the user's visual aberration, as measured by a wavefront analyzer. With this information it is possible to generate images that, when displayed to this user, will counteract his/her visual aberration. The method described in this dissertation advances the development of techniques for providing such compensation by integrating spatial information in the image as a means to eliminate some of the shortcomings inherent in using display devices such as monitors or LCD panels. Additionally, physiological considerations are discussed and integrated into the method for providing said compensation. In order to provide a realistic sense of the performance of the methods described, they were tested by mathematical simulation in software, as well as by using a single-lens high resolution CCD camera that models an aberrated eye, and finally with human subjects having various forms of visual aberrations. Experiments were conducted on these systems and the data collected from these experiments was evaluated using statistical analysis. The experimental results revealed that the pre-compensation method resulted in a statistically significant improvement in vision for all of the systems. Although significant, the improvement was not as large as expected for the human subject tests. Further analysis suggest that even under the controlled conditions employed for testing with human subjects, the characterization of the eye may be changing. This would require real-time monitoring of relevant variables (e.g. pupil diameter) and continuous adjustment in the pre-compensation process to yield maximum viewing enhancement.

Knowledge assisted data management and retrieval in multimedia database systems

With the proliferation of multimedia data and ever-growing requests for multimedia applications, there is an increasing need for efficient and effective indexing, storage and retrieval of multimedia data, such as graphics, images, animation, video, audio and text. Due to the special characteristics of the multimedia data, the Multimedia Database management Systems (MMDBMSs) have emerged and attracted great research attention in recent years. Though much research effort has been devoted to this area, it is still far from maturity and there exist many open issues. In this dissertation, with the focus of addressing three of the essential challenges in developing the MMDBMS, namely, semantic gap, perception subjectivity and data organization, a systematic and integrated framework is proposed with video database and image database serving as the testbed. In particular, the framework addresses these challenges separately yet coherently from three main aspects of a MMDBMS: multimedia data representation, indexing and retrieval. In terms of multimedia data representation, the key to address the semantic gap issue is to intelligently and automatically model the mid-level representation and/or semi-semantic descriptors besides the extraction of the low-level media features. The data organization challenge is mainly addressed by the aspect of media indexing where various levels of indexing are required to support the diverse query requirements. In particular, the focus of this study is to facilitate the high-level video indexing by proposing a multimodal event mining framework associated with temporal knowledge discovery approaches. With respect to the perception subjectivity issue, advanced techniques are proposed to support users' interaction and to effectively model users' perception from the feedback at both the image-level and object-level.

Actionable pattern analysis in computing and business intelligence systems

With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.

Development of surface flaw thresholds for pre-cured fiber reinforced polymer and groove size tolerance for near surface mounted fiber reinforced polymer retrofit systems

Since the introduction of fiber reinforced polymers (FRP) for the repair and retrofit of concrete structures in the 1980’s, considerable research has been devoted to the feasibility of their application and predictive modeling of their performance. However, the effects of flaws present in the constitutive components and the practices in substrate preparation and treatment have not yet been thoroughly studied. This research aims at investigating the effect of surface preparation and treatment for the pre-cured FRP systems and the groove size tolerance for near surface mounted (NSM) FRP systems; and to set thresholds for guaranteed system performance. This study was conducted as part of the National Cooperative Highway Research Program (NCHRP) Project 10-59B to develop construction specifications and process control manual for repair and retrofit of concrete structures using bonded FRP systems. The research included both analytical and experimental components. The experimental program for the pre-cured FRP systems consisted of a total of twenty-four (24) reinforced concrete (RC) T-beams with various surface preparation parameters and surface flaws, including roughness, flatness, voids and cracks (cuts). For the NSM FRP systems, a total of twelve (12) additional RC T-beams were tested with different grooves sizes for FRP bars and strips. The analytical program included developing an elaborate nonlinear finite element model using the general purpose software ANSYS. The bond interface between FRP and concrete was modeled by a series of nonlinear springs. The model was validated against test data from the present study as well as those available from the literature. The model was subsequently used to extend the experimental range of parameters for surface flatness in pre-cured FRP systems and for groove size study in the NSM FRP systems. Test results, confirmed by further analyses, indicated that contrary to the general belief in the industry, the impact of surface roughness on the global performance of pre-cured FRP systems was negligible. The study also verified that threshold limits set for wet lay-up FRP systems can be extended to pre-cured systems. The study showed that larger surface voids and cracks (cuts) can adversely impact both the strength and ductility of pre-cured FRP systems. On the other hand, frequency (or spacing) of surface cracks (cuts) may only affect system ductility rather than its strength. Finally, within the range studied, groove size tolerance of ±1/8 in. does not appear to have an adverse effect on the performance of NSM FRP systems.

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. ^

Seismic performance of hybrid fiber reinforced polymer-concrete pier frame systems

As an alternative to transverse spiral or hoop steel reinforcement, fiber reinforced polymers (FRPs) were introduced to the construction industry in the 1980’s. The concept of concrete-filled FRP tube (CFFT) has raised great interest amongst researchers in the last decade. FRP tube can act as a pour form, protective jacket, and shear and flexural reinforcement for concrete. However, seismic performance of CFFT bridge substructure has not yet been fully investigated. Experimental work in this study included four two-column bent tests, several component tests and coupon tests. Four 1/6-scale bridge pier frames, consisting of a control reinforced concrete frame (RCF), glass FRP-concrete frame (GFF), carbon FRP-concrete frame (CFF), and hybrid glass/carbon FRP-concrete frame (HFF) were tested under reverse cyclic lateral loading with constant axial loads. Specimen GFF did not show any sign of cracking at a drift ratio as high as 15% with considerable loading capacity, whereas Specimen CFF showed that lowest ductility with similar load capacity as in Specimen GFF. FRP-concrete columns and pier cap beams were then cut from the pier frame specimens, and were tested again in three point flexure under monotonic loading with no axial load. The tests indicated that bonding between FRP and concrete and yielding of steel both affect the flexural strength and ductility of the components. The coupon tests were carried out to establish the tensile strength and elastic modulus of each FRP tube and the FRP mold for the pier cap beam in the two principle directions of loading. A nonlinear analytical model was developed to predict the load-deflection responses of the pier frames. The model was validated against test results. Subsequently, a parametric study was conducted with variables such as frame height to span ratio, steel reinforcement ratio, FRP tube thickness, axial force, and compressive strength of concrete. A typical bridge was also simulated under three different ground acceleration records and damping ratios. Based on the analytical damage index, the RCF bridge was most severely damaged, whereas the GFF bridge only suffered minor repairable damages. Damping ratio was shown to have a pronounced effect on FRP-concrete bridges, just the same as in conventional bridges. This research was part of a multi-university project, which is founded by the National Science Foundation (NSF) - Network for Earthquake Engineering Simulation Research (NEESR) program.

Cognitive and noncognitive variables that predict Florida community college radiography program graduates' success on the Registry

This study examined the predictive merits of selected cognitive and noncognitive variables on the national Registry exam pass rate using 2008 graduates (n = 175) from community college radiography programs in Florida. The independent variables included two GPAs, final grades in five radiography courses, self-efficacy, and social support. The dependent variable was the first-attempt results on the national Registry exam. The design was a retrospective predictive study that relied on academic data collected from participants using the self-report method and on perceptions of students' success on the national Registry exam collected through a questionnaire developed and piloted in the study. All independent variables except self-efficacy and social support correlated with success on the national Registry exam ( p < .01) using the Pearson Product-Moment Correlation analysis. The strongest predictor of the national Registry exam success was the end-of-program GPA, r = .550, p < .001. The GPAs and scores for self-efficacy and social support were entered into a logistic regression analysis to produce a prediction model. The end-of-program GPA (p = .015) emerged as a significant variable. This model predicted 44% of the students who failed the national Registry exam and 97.3% of those who passed, explaining 45.8% of the variance. A second model included the final grades for the radiography courses, self efficacy, and social support. Three courses significantly predicted national Registry exam success; Radiographic Exposures, p < .001; Radiologic Physics, p = .014; and Radiation Safety & Protection, p = .044, explaining 56.8% of the variance. This model predicted 64% of the students who failed the national Registry exam and 96% of those who passed. The findings support the use of in-program data as accurate predictors of success on the national Registry exam.

Improving novice analyst performance in modeling the sequence diagram in systems analysis: A cognitive complexity approach

The Unified Modeling Language (UML) has quickly become the industry standard for object-oriented software development. It is being widely used in organizations and institutions around the world. However, UML is often found to be too complex for novice systems analysts. Although prior research has identified difficulties novice analysts encounter in learning UML, no viable solution has been proposed to address these difficulties. Sequence-diagram modeling, in particular, has largely been overlooked. The sequence diagram models the behavioral aspects of an object-oriented software system in terms of interactions among its building blocks, i.e. objects and classes. It is one of the most commonly-used UML diagrams in practice. However, there has been little research on sequence-diagram modeling. The current literature scarcely provides effective guidelines for developing a sequence diagram. Such guidelines will be greatly beneficial to novice analysts who, unlike experienced systems analysts, do not possess relevant prior experience to easily learn how to develop a sequence diagram. There is the need for an effective sequence-diagram modeling technique for novices. This dissertation reports a research study that identified novice difficulties in modeling a sequence diagram and proposed a technique called CHOP (CHunking, Ordering, Patterning), which was designed to reduce the cognitive load by addressing the cognitive complexity of sequence-diagram modeling. The CHOP technique was evaluated in a controlled experiment against a technique recommended in a well-known textbook, which was found to be representative of approaches provided in many textbooks as well as practitioner literatures. The results indicated that novice analysts were able to perform better using the CHOP technique. This outcome seems have been enabled by pattern-based heuristics provided by the technique. Meanwhile, novice analysts rated the CHOP technique more useful although not significantly easier to use than the control technique. The study established that the CHOP technique is an effective sequence-diagram modeling technique for novice analysts.