This research thesis examines the emerging trends in urban social patterns in Navi Mumbai, India. Unlike the other planned cities of India, Navi Mumbai was specifically built as a planned decentralization of a large metropolitan city. The research focuses on explaining the urban social pattern of this particular case study. An urban social pattern reflects the social characteristics of the urban setting. In the case of Navi Mumbai, the government had a social agenda of promoting a social pattern based on socioeconomic distribution rather than an ethnic one. Analysis of the data provides an insight to the results of this social agenda, and provides a basis to frame new ones. Thus, the study not only addresses a basic research question, but also has policy implications. The research involves a comprehensive review of secondary source material to establish the theoretical framework for the research. The review also involves an extensive inspection of urban social patterns across the world to better contextualize this particular case study. The research puts forth a model that explains the social pattern of Navi Mumbai by social area analysis using variables, which are drawn from social aspects of any city and indigenous factors of Indian settlements. The model depends not only on statistical analysis but also on interpretation of local conditions. This research situates the emerging social pattern in geographic literature in developing countries. This research was supported in part, by a grant from the College of Architecture and Urban Studies, Virginia Tech. / Master of Urban and Regional Planning

Le paradigme d'émergence spontanée de services (Spontaneous Emergence Paradigm, SEP) pour la mise en œuvre de l’informatique omniprésente ou diffuse (pervasive computing), consiste à fournir des services aux utilisateurs en fonction de leur environnement ad hoc. Ce paradigme a prouvé son efficacité et son adéquation aux applications distribuées sensibles au contexte. Ce travail se concentre sur deux aspects liés à la mise en œuvre des services SEP. Le premier se distingue de ce qui est proposé dans la littérature, par une approche physiologique de « Dead Reckoning » (Physiological Pedestrian Dead Reckoning Approach, PDR), qui permet de corriger les erreurs de positionnement à partir de données physiologiques comme la fréquence cardiaque et la vitesse de déplacement. Cette approche utilise des modèles stochastiques, qui reposent sur la distribution des probabilités des fréquences cardiaques précédemment collectées par rapport à la vitesse de déplacement de l’utilisateur (par exemple, par apprentissage via une marche sur un tapis roulant). Le modèle proposé permet ainsi d’ajuster les vitesses lues dans n’importe quel futur système PDR. Le deuxième aspect de cette recherche concerne la détection de réseaux d’affinités (Social Relationship Detection framework, SRD). Cette approche propose d’explorer le niveau d’affinité entre personnes en fonction de leur connexions et interactions selon plusieurs conditions. Ces connexions à des bornes WAP (Wireless Access Point), par rapport à chaque condition, sont consolidées pour former des distributions de probabilités. Par la suite, ces distributions de probabilités sont introduites dans un réseau de neurones (back propagation neural network) pour détecter et déterminer les affinités entre utilisateurs. Cette approche permet une prise de décision adaptative à chaque connexion au WAP et selon le comportement de l’utilisateur, contrairement aux approches classiques reposant uniquement sur une connaissance globale au préalable de la convergence des attributs des utilisateurs concernés. / Service Emergence Paradigm (SEP), based on a pervasive computing approach, consists of providing services to users within intended applications, transparently from their intentions, relatively to their needs, and regardless of the time and devices used. This considered paradigm has been proved sufficiently in applications that have context awareness schemes and various working threads. This research focuses on two aspects for providing SEP services. This first aspect is to implement a Physiological Pedestrian Dead Reckoning Approach (PPDR) that corrects position errors in pedestrian dead reckoning systems based on the heart rate parameter. This approach uses specific stochastic models that rely on probability distributions of previously collected heart rate values with respect to their velocities of a user during a treadmill walk. The reason behind this collection is to form a pattern that contributes in adjusting currently read velocities in any future PDR system. The second aspect of this research is the Social Relationship Detection framework (SRD). This approach proposes a mean for exploring the level of relationship between people by observing the network connection pattern of each person over several conditions. These connections, with respect to each condition, are consolidated to form a set that holds different probability distributions. These distributions are formed based on the users’ Wireless Access Point (WAP) connection establishment routine. Afterwards, the distributions of the probabilities are fed into a trained back propagation neural network to detect the level of relationship between candidate users for forthcoming friendship recommendations. This approach is elaborated in a technique that achieves intelligent decision-making whenever the connection pattern to the WAP and the user behavior are changing with time. It is also distinguished from other classical approaches that rely solely on prior knowledge of the convergence of the users’ attributes.

The purpose of this study is to present an empirical pattern of social equity in Chinese higher education by investigating university students. Student socio-economic background influences access to, and socio-economic conditions in, higher education, and this, in turn, influences student career aspirations. The theoretical background of the study is interdisciplinary and a conceptual framework built on theories and previous research is used to analyse Chinese higher education in a historical, social and economic context. A questionnaire survey was administered at six public universities in the Southwest region of the country to explore students’ socio-economic background, costs and how they finance their studies, as well as their future career aspirations. The relationships between the factors investigated were examined using factor analytical techniques and linear structural relations (LISREL) analysis. The findings indicate that the students come from all socio-economic strata but a disproportionately large number are from high-income families. Students from urban areas are over-represented while rural girls are significantly under-represented. Although the gap between the lowest and highest study costs is enormous, the findings confirm that the average cost of higher education in China far exceeds the average annual income, even for urban residents. Moreover, about one-third of students and their families utilised financial resources other than family such as student loans, borrowing, and other forms of financial assistance. A structural model linking student socio-economic background, enrolment in elite institutions, costs and means of financing education with career aspirations is developed and tested in three stages in order to shed light on the conceptual framework and to present a pattern of social equity. The results show that family socio-economic status has only a modest impact on student access to and in higher education. On the other hand, having social origins in a well-developed community exerts an influential effect. Although study and living costs, and means of financing studies, are influenced by student socio-economic background, they intend to have positive impacts on student career aspirations. While enrolment in elite institutions has a strongly positive impact on costs, it has a moderately negative impact on aspirations to pursue advanced degrees. In conclusion, the study finds that the patterns of socio-economic factors influencing student upward mobility in present-day China are different from those of ancient China and from those previous Communist leaders attempted to achieve only 20 years ago.