Thesis (Ph. D.)--Ohio State University, 2008. / Title from first page of PDF file. Includes vita. Includes bibliographical references (p. 115-133).

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Recovering a volumetric model of a person, car, or other object of interest from a single snapshot would be useful for many computer graphics applications. 3D model estimation in general is hard, and currently requires active sensors, multiple views, or integration over time. For a known object class, however, 3D shape can be successfully inferred from a single snapshot. We present a method for generating a ``virtual visual hull''-- an estimate of the 3D shape of an object from a known class, given a single silhouette observed from an unknown viewpoint. For a given class, a large database of multi-view silhouette examples from calibrated, though possibly varied, camera rigs are collected. To infer a novel single view input silhouette's virtual visual hull, we search for 3D shapes in the database which are most consistent with the observed contour. The input is matched to component single views of the multi-view training examples. A set of viewpoint-aligned virtual views are generated from the visual hulls corresponding to these examples. The 3D shape estimate for the input is then found by interpolating between the contours of these aligned views. When the underlying shape is ambiguous given a single view silhouette, we produce multiple visual hull hypotheses; if a sequence of input images is available, a dynamic programming approach is applied to find the maximum likelihood path through the feasible hypotheses over time. We show results of our algorithm on real and synthetic images of people.

Recovering a volumetric model of a person, car, or other objectof interest from a single snapshot would be useful for many computergraphics applications. 3D model estimation in general is hard, andcurrently requires active sensors, multiple views, or integration overtime. For a known object class, however, 3D shape can be successfullyinferred from a single snapshot. We present a method for generating a``virtual visual hull''-- an estimate of the 3D shape of an objectfrom a known class, given a single silhouette observed from an unknownviewpoint. For a given class, a large database of multi-viewsilhouette examples from calibrated, though possibly varied, camerarigs are collected. To infer a novel single view input silhouette'svirtual visual hull, we search for 3D shapes in the database which aremost consistent with the observed contour. The input is matched tocomponent single views of the multi-view training examples. A set ofviewpoint-aligned virtual views are generated from the visual hullscorresponding to these examples. The 3D shape estimate for the inputis then found by interpolating between the contours of these alignedviews. When the underlying shape is ambiguous given a single viewsilhouette, we produce multiple visual hull hypotheses; if a sequenceof input images is available, a dynamic programming approach isapplied to find the maximum likelihood path through the feasiblehypotheses over time. We show results of our algorithm on real andsynthetic images of people.

Link travel time plays a significant role in traffic planning, traffic management and Advanced Traveler Information Systems (ATIS). A public probe vehicle dataset is a probe vehicle dataset that is collected from public people or public transport. The appearance of public probe vehicle datasets can support travel time collection at a large temporal and spatial scale but at a relatively low cost. Traditionally, link travel time is the aggregation of travel time by different movements. A recent study proved that link travel time of different movements is significantly different from their aggregation. However, there is still not a complete framework for estimating movement-based link travel time. In addition, probe vehicle datasets usually have a low penetration rate but no previous study has solved this problem. To solve the problems above, this study proposed a detailed framework to estimate movement-based link travel time using a high sampling rate public probe vehicle dataset. Our study proposed a k-Nearest Neighbors (k-NN) regression method to increase travel time samples using incomplete trajectory. An incomplete trajectory was compared with historical complete trajectories and the link travel time of the incomplete trajectory was represented by its similar complete trajectories. The result of our study showed that the method can significantly increase link travel time samples but there are still limitations. In addition, our study investigated the performance of k-NN regression under different parameters and input data. The sensitivity analysis of k-NN algorithm showed that the algorithm performed differently under different parameters and input data. Our study suggests optimal parameters should be selected using a historical dataset before real-world application.

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / The real estate sector in Peru has been experiencing sustained growth during the last 10 years, however, due to the constant problems that occur during the development of a project, construction as an investment is increasingly far from being the best option in the market, generally reducing its opportunity cost compared to other more specific investments. To find out what these problems are, a survey was conducted of 25 real estate project managers in Lima, establishing that one of the most recurring problems in the construction sector is conflicts with external stakeholders, mainly with the neighbors surrounding the work, and how these tend to worsen due to inadequate management by project team members who are assigned to resolve the conflict situation.In this sense, this study focuses on knowing the competences that workers have within an organization and what they need to efficiently manage problems with neighbors, and then propose a management model by competences focused on improving the performance of workers of a construction company developing a set of strategies and activities that increase their competitiveness in the face of confrontation between both parts. The results obtained from a real estate construction project indicated that the proposed model manages to reduce or prevent conflicts with neighboring homes, improving the achievement indicators of the aforementioned project under analysis.

Purpose: Historically, communities have opposed the development of residential programs for adults with psychiatric disabilities. In the last two decades, national and local campaigns have made targeted efforts to improve public knowledge about mental illness, and attitudes and behaviors towards mental health clients. Supportive housing policies have also been revised to better facilitate integration and independence for clients with psychiatric disabilities. Despite these changes, the number of studies on perceptions of psychiatric supportive housing has dramatically declined in recent years. Little is known about how neighbors currently perceive psychiatric housing and neighbors with mental illness, or the role that mental health knowledge, attitudes, and behaviors play in neighborhoods where housing clients live. Methods: Knowledge, attitudes, and behaviors of 139 neighbors living in close proximity to psychiatric supportive housing sites were assessed. Follow up qualitative interviews were conducted with 16 neighbors who correctly identified the housing site in their neighborhood to understand the perceived impact of the housing site and elicit suggestions for improving relations between clients and their neighbors. Individual and neighborhood social experiences of neighbors are compared with those of 68 clients living in the referent housing sites. Results: Neighbors had high rates of personal experience with mental illness and were familiar with mental health diagnoses and facts. Neighbors had positive opinions about and neighboring intentions towards neighbors with mental illness. Increased mental health knowledge and close relationships with individuals with mental illness were associated with decreased stigma. Being able to correctly identify the housing and population was not associated with differences in opinions about individuals with mental illness. Compared to clients, neighbors perceived the neighborhood as being less safe. Clients were lonelier than their neighbors. Neighbors reported the housing had a positive impact on the neighborhood and had few concerns. They suggested awareness, education, and social contact strategies to improve relations with housing clients. Conclusions: Suggestions for improving client integration and public acceptance of psychiatric supportive housing are discussed, as well implications in light of recent policy changes and ongoing public anti-stigma campaigns.

Classification analyses are a promising way to localize signal, especially scattered signal, in functional magnetic resonance imaging data. However, there is not yet a consensus on the most effective analysis pathway. We explore the efficacy of k-Nearest Neighbors classifiers on simulated functional magnetic resonance imaging data. We utilize a novel construction of the classification data. Additionally, we vary the spatial distribution of signal, the design matrix of the linear model used to construct the classification data, and the feature set available to the classifier. Results indicate that the k-Nearest Neighbors classifier is not sufficient under the current paradigm to adequately classify neural data and localize signal. Further exploration of the data using k-means clustering indicates that this is likely due in part to the amount of noise present in each data point. Suggestions are made for further research.

Doctor of Philosophy / Department of Statistics / Haiyan Wang / Statistical tools to detect nonlinear relationship between variables are commonly needed in various practices. The first part of the dissertation presents a test of independence between a response variable, either discrete or continuous, and a continuous covariate after adjusting for heteroscedastic treatment effects. The method first involves augmenting each pair of the data for all treatments with a fixed number of nearest neighbors as pseudo-replicates. A test statistic is then constructed by taking the difference of two quadratic forms. Using such differences eliminate the need to estimate any nonlinear regression function, reducing the computational time. Although using a fixed number of nearest neighbors poses significant difficulty in the inference compared to when the number of nearest neighbors goes to infinity, the parametric standardizing rate is obtained for the asymptotic distribution of the proposed test statistics. Numerical studies show that the new test procedure maintains the intended type I error rate and has robust power to detect nonlinear dependency in the presence of outliers. The second part of the dissertation discusses the theory and numerical studies for testing the nonparametric effects of no covariate-treatment interaction and no main covariate based on the decomposition of the conditional mean of regression function that is potentially nonlinear. A similar test was discussed in Wang and Akritas (2006) for the effects defined through the decomposition of the conditional distribution function, but with the number of pseudo-replicates going to infinity. Consequently, their test statistics have slow convergence rates and computational speeds. Both test limitations are overcome using new model and tests. The last part of the dissertation develops theory and numerical studies to test for no covariate-treatment interaction, no simple covariate and no main covariate effects for cases when the number of factor levels and the number of covariate values are large.

Abstract Turkey has emerged as a major actor in the Middle East over the last decade, since the ruling party AKP came to power in 2002. Turkey is now playing a mediation role in regional conflicts and has been speaking out loudly on sensitive issues such as the Iranian nuclear program and the Palestinian- Israeli conflict. Furthermore, Turkey has established close ties with the Arab world which has suffered the relationship with its long-time ally Israel. This new presence in Middle East has been criticized by Turkey's allies in west. Critics argue that the country is about to abandon its former western relationship and strengthen their ties with the Arab world instead. This thesis has two main purposes. First, an empirical purpose which is to describe and explain changes in Turkish foreign policy towards Middle East. Second, this thesis has a theoretical purpose, aiming to make a contribution to the study field also on a theoretical level. The ambition is therefore to provide with ideas and/or modify the model of Gustavsson in order to make it more applicable of other cases of foreign policy change. The theoretical framework applied on this thesis is Jakob Gustavsson's model for explaining foreign policy change. Turkey's foreign policy change will be analyzed through a qualitative case study that focuses on the country's relations with the Middle East. Based on Gustavsson's model, possible explanations to Turkey's foreign policy change towards Middle East are structural changes in the international and national system. The end of the bipolarity system during the cold war resulted in a major structural change, thus Turkey had to adapt to the new system by hammering out a new foreign policy doctrine. In addition to this, the growing opposition to a Turkish membership within the EU is considered to be another explanation to Turkey's improved relations with the Middle East. The results shows furthermore possible explanations on a national level such as growing economy, a strong Turkish public opinion, new actors and also AKP:s ideological affinity with Muslim aspirations. The Iraq crisis, which arose in 2003 when Turkey rejected a resolution authorizing the deployment of American forces in Turkey in a war against Iraq, functions as a catalysts for the changes in Turkish foreign policy. One of the main components in the model emphasizes that the individual key actor needs to go through a change within its belief system, however the author have not found such evidence in this case and thus suggests that this part of the model becomes slightly modified or even removed. Keywords: Turkey, AKP, Ahmet Davutoglu, Middle East, foreign policy change, zero problems towards neighbors