7 resultados para Dynamic search fireworks algorithm with covariance mutation

em Digital Commons at Florida International University


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The primary purpose of this thesis was to design and develop a prototype e-commerce system where dynamic parameters are included in the decision-making process and execution of an online transaction. The system developed and implemented takes into account previous usage history, priority and associated engineering capabilities. The system was developed using three-tiered client server architecture. The interface was the Internet browser. The middle tiered web server was implemented using Active Server Pages, which form a link between the client system and other servers. A relational database management system formed the data component of the three-tiered architecture. It includes a capability for data warehousing which extracts needed information from the stored data of the customers as well as their orders. The system organizes and analyzes the data that is generated during a transaction to formulate a client's behavior model during and after a transaction. This is used for making decisions like pricing, order rescheduling during a client's forthcoming transaction. The system helps among other things to bring about predictability to a transaction execution process, which could be highly desirable in the current competitive scenario.

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This dissertation introduced substance abuse to the Dynamic Vulnerability Formulation (DVF) and the social competence model to determine if the relationship between schizophrenic symptomatology and coping ability in the DVF applied also to the dually diagnosed schizophrenic or if these variables needed to be modified. It compared the coping abilities of dually and singly diagnosed clients in day treatment and identified, examined, and assessed the relative influence of relevant mediating variables on two dimensions of coping ability of the dually diagnosed: coping skills and coping effort. These variables were: presence of negative and nonnegative symptoms, duration of mental illness, type of substance used, and age of first substance use.^ A priori effect sizes based on previous empirical research were used to interpret the results related to the comparison of demographic, socioeconomic, and treatment characteristics between the singly and dually diagnosed study samples. The data suggested that the singly diagnosed group had higher coping skills than the dually diagnosed group, particularly in the areas of housing stability, work affect, and total social adjustment. The dually diagnosed group had lower scores on one aspect of coping effort--agency or self-efficacy. The data supported the presence of an inverse relationship between symptom severity and coping skills, particularly for the dually diagnosed group. The data did not support the presence of an inverse relationship between symptom severity and coping effort, but did suggest a positive relationship between symptom severity and one measure of coping effort, agency, for the dually diagnosed group. Regression equations using each summary measure of coping skill--social adjustment and role functioning--yielded statistically significant F-ratios. Thirty-six percent of the variance in social adjustment and thirty-one percent of the variance in role functioning were explained by the relative influence of the relevant variables. Both negative and non-negative symptoms were the only significant predictors of social adjustment. The non-negative symptoms variable was the sole significant predictor of role functioning. The results of this study provided partial support for the use of the Dynamic Vulnerability Formulation (DVF) with the dually diagnosed. ^

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The design of interfaces to facilitate user search has become critical for search engines, ecommercesites, and intranets. This study investigated the use of targeted instructional hints to improve search by measuring the quantitative effects of users' performance and satisfaction. The effects of syntactic, semantic and exemplar search hints on user behavior were evaluated in an empirical investigation using naturalistic scenarios. Combining the three search hint components, each with two levels of intensity, in a factorial design generated eight search engine interfaces. Eighty participants participated in the study and each completed six realistic search tasks. Results revealed that the inclusion of search hints improved user effectiveness, efficiency and confidence when using the search interfaces, but with complex interactions that require specific guidelines for search interface designers. These design guidelines will allow search designers to create more effective interfaces for a variety of searchapplications.

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This dissertation establishes a novel system for human face learning and recognition based on incremental multilinear Principal Component Analysis (PCA). Most of the existing face recognition systems need training data during the learning process. The system as proposed in this dissertation utilizes an unsupervised or weakly supervised learning approach, in which the learning phase requires a minimal amount of training data. It also overcomes the inability of traditional systems to adapt to the testing phase as the decision process for the newly acquired images continues to rely on that same old training data set. Consequently when a new training set is to be used, the traditional approach will require that the entire eigensystem will have to be generated again. However, as a means to speed up this computational process, the proposed method uses the eigensystem generated from the old training set together with the new images to generate more effectively the new eigensystem in a so-called incremental learning process. In the empirical evaluation phase, there are two key factors that are essential in evaluating the performance of the proposed method: (1) recognition accuracy and (2) computational complexity. In order to establish the most suitable algorithm for this research, a comparative analysis of the best performing methods has been carried out first. The results of the comparative analysis advocated for the initial utilization of the multilinear PCA in our research. As for the consideration of the issue of computational complexity for the subspace update procedure, a novel incremental algorithm, which combines the traditional sequential Karhunen-Loeve (SKL) algorithm with the newly developed incremental modified fast PCA algorithm, was established. In order to utilize the multilinear PCA in the incremental process, a new unfolding method was developed to affix the newly added data at the end of the previous data. The results of the incremental process based on these two methods were obtained to bear out these new theoretical improvements. Some object tracking results using video images are also provided as another challenging task to prove the soundness of this incremental multilinear learning method.

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In many species, particular individuals consistently lead group travel. While benefits to followers often are relatively obvious, including access to resources, benefits to leaders are often less obvious. This is especially true for species that feed on patchy mobile resources where all group members may locate prey simultaneously and food intake likely decreases with increasing group size. Leaders in highly complex habitats, however, could provide access to foraging resources for less informed relatives, thereby gaining indirect benefits by helping kin. Recently, leadership has been documented in a population of bottlenose dolphins (Tursiops truncatus) where direct benefits to leaders appear unlikely. To test whether leaders could benefit indirectly we examined relatedness between leader-follower pairs and compared these levels to pairs who associated but did not have leader-follower relationship (neither ever led the other). We found the average relatedness value for leader-follower pairs was greater than expected based on chance. The same was not found when examining non leader-follower pairs. Additionally, relatedness for leader-follower pairs was positively correlated with association index values, but no correlation was found for this measure in non leader-follower pairs. Interestingly, haplotypes were not frequently shared between leader-follower pairs (25%). Together, these results suggest that bottlenose dolphin leaders have the opportunity to gain indirect benefits by leading relatives. These findings provide a potential mechanism for the maintenance of leadership in a highly dynamic fission-fusion population with few obvious direct benefits to leaders.

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The aim of this work is to present a methodology to develop cost-effective thermal management solutions for microelectronic devices, capable of removing maximum amount of heat and delivering maximally uniform temperature distributions. The topological and geometrical characteristics of multiple-story three-dimensional branching networks of microchannels were developed using multi-objective optimization. A conjugate heat transfer analysis software package and an automatic 3D microchannel network generator were developed and coupled with a modified version of a particle-swarm optimization algorithm with a goal of creating a design tool for 3D networks of optimized coolant flow passages. Numerical algorithms in the conjugate heat transfer solution package include a quasi-ID thermo-fluid solver and a steady heat diffusion solver, which were validated against results from high-fidelity Navier-Stokes equations solver and analytical solutions for basic fluid dynamics test cases. Pareto-optimal solutions demonstrate that thermal loads of up to 500 W/cm2 can be managed with 3D microchannel networks, with pumping power requirements up to 50% lower with respect to currently used high-performance cooling technologies.

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The purpose of this dissertation is to examine three distributional issues in macroeconomics. First I explore the effects fiscal federalism on economic growth across regions in China. Using the comprehensive official data set of China for 31 regions from 1952 until 1999, I investigate a number of indicators used by the literature to measure federalism and find robust support for only one such measure: the ratio of local total revenue to local tax revenue. Using a difference-in-difference approach and exploiting the two-year gap in the implementation of a tax reform across different regions of China, I also identify a positive relationship between fiscal federalism and regional economic growth. The second paper hypothesizes that an inequitable distribution of income negatively affects the rule of law in resource-rich economies and provides robust evidence in support of this hypothesis. By investigating a data set that contains 193 countries and using econometric methodologies such as the fixed effects estimator and the generalized method of moments estimator, I find that resource-abundance improves the quality of institutions, as long as income and wealth disparity remains below a certain threshold. When inequality moves beyond this threshold, the positive effects of the resource-abundance level on institutions diminish quickly and turn negative eventually. This paper, thus, provides robust evidence about the endogeneity of institutions and the role income and wealth inequality plays in the determination of long-run growth rates. The third paper sets up a dynamic general equilibrium model with heterogeneous agents to investigate the causal channels which run from a concern for international status to long-run economic growth. The simulation results show that the initial distribution of income and wealth play an important role in whether agents gain or lose from globalization.