Thesis (Ph. D.)--Michigan State University. Dept. of Sociology, 1981. / Includes bibliographical references (p. 191-199).

Riyadh City, the capital of Saudi Arabia, presents an interesting context of problems in its urbanisation process, which started pronouncedly during the 1970s. The main factor that prompted urbanisation was the discovery and production of crude oil accompanied with the strong political desire for urbanisation and modernisation. This has enabled the country to embark on profound national development in all aspects of life. The fast growth in population and urban land expansion led to several challenges to the urbanisation process and to urban land policy. These started to occur as a result of high land demand and the absence of measures able to control urban land expansion. Surprisingly, land urban expansion exceeded the increase in urban population which itself was uncontrolled. Similarly, the increase in urban land use also generated empty urban lands scattered randomly in Riyadh City. Thus, the main thrust of this thesis is to investigate the nature of the urbanisation process and the role of urban land policy with emphasis on the impact of urban land expansion in Riyadh City, despite the policies that aimed at controlling and directing urban growth. The main objective of the study has been to provide a broad perspective on the urbanisation process in Riyadh City and examine five proposed hypotheses associated with the urbanisation problem. Other objectives were to understand the concept that most likely reflects the real nature of the urbanisation process from social and governmental perspectives, and to illustrate the concepts that govern urban land expansion with particular emphasis on how the residents perceive urban land expansion in view of services and infrastructure of their City. Following these objectives, the study has adopted a combined approach involving firstly acquiring the necessary background for the literature, which helped to set up the study. A total of 781 (or 78.1%) respondents to questionnaire in four groups: Land authority, Estate agents, Landowners and Residents indicated general agreement between land authority and residents, which was likely to disagree with perceptions of landowners and Estate agents on the majority of the 33 statements of the questionnaire. Results of the statistical analysis indicated that the proposed hypotheses were most likely to be rejected because of disagreement on urban land policies and their mechanism for the development and control urbanisation process. Results also indicated that urbanisation growth in Riyadh City was not organised, and land development not regulated and implemented by the municipality under control measures. The existing urbanisation problems can be attributed to the constitution, system of granting land, land ownership, view of people towards land and urbanisation in general make it difficult to apply measures to control urban land expansion. Other problems such as ineffective management, coordination on planning between the municipality and other organisations, inconsistency between urban land policy and lack of coordination between authorities in distributing land have greatly contributed to the urbanisation problem in Riyadh City. Thus, unless there is co-operation between people and authorities on one hand, and involvement of people in their city development on the other, the problem of urban land growth is perhaps a bigger challenge to comprehend in the future.

This philosophical-descriptive dissertation makes a detailed analysis of the background and problems of the adult literacy program in Riyadh, Saudi Arabia, and proposes recommendations for improvement of this program. The purpose of the study is to describe and critically analyze the Islamic religious tradition, Saudi Arabian social structure, the roles of Saudi Arabian men and women, the role of nomads in Saudi society, usage of Classical and modern Arabian dialects, current instructional materials and media used in adult literacy education and current educational resources, finance and personnel.

This dissertation resituates C. A. Doxiadis in Post-War urban design history with a detailed examination of how urban growth and change was addressed by urban design strategies as applied in the master plan for Riyadh Saudi Arabia, undertaken between 1968 and 1972. The Riyadh master plan commission is important within Doxiadis' career, occurring in the midst of his prolific writing projects and approximately eight years after he completed the Islamabad master plan, his most renowned project. Most Post-War architects focused on the socio-spatial components of urban life, elaborating architectural projects that intertwined transportation, infrastructure, and concentrated on mass housing strategies. This dissertation argues that Doxiadis' contribution to urban design theory and practice during the Post-War period was to define a rational scientific methodology for urban design that would restructure settlements to enable urban expansion and change while addressing issues of community building, governance and processes of development. The applied urban design for Riyadh Saudi Arabia strongly exemplifies Doxiadis' rational strategy and methodology as outlined in Ekistics theory and the conceptual model of Dynapolis. The comparative analysis examines how Doxiadis applies the Dynapolis model in the urban spatial planning of Riyadh to organize urban territory at the macro and local urban scales, define neighborhood communities, and connect the new master plan to the existing spatial territory of the city. The longitudinal analysis contrasts the Doxiadis master plan, Riyadh's first urban development strategy, to the most recent comprehensive approach MEDSTAR to understand how the Doxaidis' urban design has sustained its spatial continuity over time. This dissertation makes two significant contributions. The first is to broaden knowledge of Post-War urban design specific to the spatial problem of urban expansion and change, and second to resituate Doxiadis within the Post-War history of urban design specifically revealing his previously unrecognized project of the Riyadh master plan undertaken from 1968-1972.

This study examined the perception of managers in the Institute of Public Administration (IPA), Riyadh, Saudi Arabia as to the way public relations is practiced within Saudi Arabia based on a comparison with Grunig's four models of public relations. Out of a population of 38 directors and director generals, 30 participated in a personal interview for a 79 percent response rate.A Q-sort analysis revealed two perceptions of public relations performance in the Institute. Perceptions differed based on educational experience, and managerial levels. Top managers with Ph.Ds tended to view performance as related to Grunig's Press Agentry and One-Way Information models. Fewer level employees saw performance related to the Two-Way Asymmetrical and Symmetrical models. The researcher concluded that the more higher educated level managers had a better understanding of the reality of performance of public relations in IPA. Main attitudes from the sorts of the participants showing a significantly and different attitude in how directors generals and directors perceived public relations was being practiced in the IPA. The directors generals and directors strongly held different views concerning the practice of public relations in the IPA. / Department of Journalism

The selection of the most appropriate traffic control actions to solve non-recurrent traffic congestion is a complex task which requires significant expert knowledge and experience. In this thesis we develop and investigate the application of an intelligent traffic control decision support system for road traffic management to assist the human operator to identify the most suitable control actions in order to deal with non-recurrent and non-predictable traffic congestion in a real-time situation. Our intelligent system employs a Fuzzy Neural Networks (FNN) Tool that combines the capabilities of fuzzy reasoning in measuring imprecise and dynamic factors and the capabilities of neural networks in terms of learning processes. In this work we present an effective learning approach with regard to the FNN-Tool, which consists of three stages: initializing the membership functions of both input and output variables by determining their centres and widths using self-organizing algorithms; employing an evolutionary Genetic Algorithm (GA) based learning method to identify the fuzzy rules; tune the derived structure and parameters using the back-propagation learning algorithm. We evaluate experimentally the performance and the prediction capability of this three-stage learning approach using well-known benchmark examples. Experimental results demonstrate the ability of the learning approach to identify all relevant fuzzy rules from the training data. A comparative analysis shows that the proposed learning approach has a higher degree of predictive capability than existing models. We also address the scalability issue of our intelligent traffic control decision support system by using a multi-agent based approach. The large network is divided into sub-networks, each of which has its own associated agent. Finally, our intelligent traffic control decision support system is applied to a number of road traffic case studies using the traffic network in Riyadh, in Saudi Arabia. The results obtained are promising and show that our intelligent traffic control decision support system can provide an effective support for real-time traffic control.

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The selection of the most appropriate traffic control actions to solve non-recurrent traffic congestion is a complex task which requires significant expert knowledge and experience. In this thesis we develop and investigate the application of an intelligent traffic control decision support system for road traffic management to assist the human operator to identify the most suitable control actions in order to deal with non-recurrent and non-predictable traffic congestion in a real-time situation. Our intelligent system employs a Fuzzy Neural Networks (FNN) Tool that combines the capabilities of fuzzy reasoning in measuring imprecise and dynamic factors and the capabilities of neural networks in terms of learning processes. In this work we present an effective learning approach with regard to the FNN-Tool, which consists of three stages: initializing the membership functions of both input and output variables by determining their centres and widths using self-organizing algorithms; employing an evolutionary Genetic Algorithm (GA) based learning method to identify the fuzzy rules; tune the derived structure and parameters using the back-propagation learning algorithm. We evaluate experimentally the performance and the prediction capability of this three-stage learning approach using well-known benchmark examples. Experimental results demonstrate the ability of the learning approach to identify all relevant fuzzy rules from the training data. A comparative analysis shows that the proposed learning approach has a higher degree of predictive capability than existing models. We also address the scalability issue of our intelligent traffic control decision support system by using a multi-agent based approach. The large network is divided into sub-networks, each of which has its own associated agent. Finally, our intelligent traffic control decision support system is applied to a number of road traffic case studies using the traffic network in Riyadh, in Saudi Arabia. The results obtained are promising and show that our intelligent traffic control decision support system can provide an effective support for real-time traffic control.