An indexing structure and application model for vehicles moving on road networks

Moving objects database systems are the most challenging sub-category among Spatio-Temporal database systems. A database system that updates in real-time the location information of GPS-equipped moving vehicles has to meet even stricter requirements. Currently existing data storage models and indexing mechanisms work well only when the number of moving objects in the system is relatively small. This dissertation research aimed at the real-time tracking and history retrieval of massive numbers of vehicles moving on road networks. A total solution has been provided for the real-time update of the vehicles' location and motion information, range queries on current and history data, and prediction of vehicles' movement in the near future. ^ To achieve these goals, a new approach called Segmented Time Associated to Partitioned Space (STAPS) was first proposed in this dissertation for building and manipulating the indexing structures for moving objects databases. ^ Applying the STAPS approach, an indexing structure of associating a time interval tree to each road segment was developed for real-time database systems of vehicles moving on road networks. The indexing structure uses affordable storage to support real-time data updates and efficient query processing. The data update and query processing performance it provides is consistent without restrictions such as a time window or assuming linear moving trajectories. ^ An application system design based on distributed system architecture with centralized organization was developed to maximally support the proposed data and indexing structures. The suggested system architecture is highly scalable and flexible. Finally, based on a real-world application model of vehicles moving in region-wide, main issues on the implementation of such a system were addressed. ^

Structure of international cooperation in trade, investment and environment

This dissertation analyzes the obstacles against further cooperation in international economic relations. The first essay explains the gradual nature of trade liberalization. I show that existence of asymmetric information between governments provides a sufficient reason for gradualism to exist. Governments prefer starting small to reduce the cost of partner’s betrayal when there is sufficient degree of information asymmetry regarding the partner’s type. Learning about partner’s incentive structure enhances expectations, encouraging governments to increase their current level of cooperation. Specifically, the uninformed government’s subjective belief for the trading partner being good is improved as the partner acts cooperatively. This updated belief, in turn, lowers the subjective probability of future betrayal, enabling further progress in cooperation. The second essay analyzes the relationship between two countries facing two policy dilemmas in an environment with two way goods and capital flows. When issues are independent and countries are symmetric, signing separate agreements for tariffs (Free Trade Agreements-FTA) and for taxes (Tax Treaties-TT) provides the identical level of enforcement as signing a linked agreement. However, linkage can still improve the joint welfare by transferring the slack enforcement power in a case of asymmetric issues or countries. I report non-results in two cases where the policy issues are interconnected due to technological spillover effect of FDI. Moreover, I show that linking the agreements actually reduces enforcement when agreements are linked under a limited punishment rule and policy variables are strategic substitutes. The third essay investigates the welfare/enforcement consequences of linking trade and environmental agreements. In the standard literature, linking the agreements generate non-trivial results only when there is structural relation between the issues. I focus on institutional design of the linkage and show that even if environmental aspects of international trade are negligible linking the agreements might still have some interesting welfare implications under current GATT Rules. Specifically, when traded goods are substitutes in consumption, linking the environmental agreement with trade agreement under the Withdrawal of Equivalent Concession Rule (Article XXVIII) will reduce the enforcement. However, enforcement in environmental issue increases when the same rule is implemented in the absence of linkage.

Self-tuning algorithm for dsp-based motion control in cnc applications

This thesis describes the development of an adaptive control algorithm for Computerized Numerical Control (CNC) machines implemented in a multi-axis motion control board based on the TMS320C31 DSP chip. The adaptive process involves two stages: Plant Modeling and Inverse Control Application. The first stage builds a non-recursive model of the CNC system (plant) using the Least-Mean-Square (LMS) algorithm. The second stage consists of the definition of a recursive structure (the controller) that implements an inverse model of the plant by using the coefficients of the model in an algorithm called Forward-Time Calculation (FTC). In this way, when the inverse controller is implemented in series with the plant, it will pre-compensate for the modification that the original plant introduces in the input signal. The performance of this solution was verified at three different levels: Software simulation, implementation in a set of isolated motor-encoder pairs and implementation in a real CNC machine. The use of the adaptive inverse controller effectively improved the step response of the system in all three levels. In the simulation, an ideal response was obtained. In the motor-encoder test, the rise time was reduced by as much as 80%, without overshoot, in some cases. Even with the larger mass of the actual CNC machine, decrease of the rise time and elimination of the overshoot were obtained in most cases. These results lead to the conclusion that the adaptive inverse controller is a viable approach to position control in CNC machinery.

An Indexing Structure and Application Model for Vehicles Moving on Road Networks

Moving objects database systems are the most challenging sub-category among Spatio-Temporal database systems. A database system that updates in real-time the location information of GPS-equipped moving vehicles has to meet even stricter requirements. Currently existing data storage models and indexing mechanisms work well only when the number of moving objects in the system is relatively small. This dissertation research aimed at the real-time tracking and history retrieval of massive numbers of vehicles moving on road networks. A total solution has been provided for the real-time update of the vehicles’ location and motion information, range queries on current and history data, and prediction of vehicles’ movement in the near future. To achieve these goals, a new approach called Segmented Time Associated to Partitioned Space (STAPS) was first proposed in this dissertation for building and manipulating the indexing structures for moving objects databases. Applying the STAPS approach, an indexing structure of associating a time interval tree to each road segment was developed for real-time database systems of vehicles moving on road networks. The indexing structure uses affordable storage to support real-time data updates and efficient query processing. The data update and query processing performance it provides is consistent without restrictions such as a time window or assuming linear moving trajectories. An application system design based on distributed system architecture with centralized organization was developed to maximally support the proposed data and indexing structures. The suggested system architecture is highly scalable and flexible. Finally, based on a real-world application model of vehicles moving in region-wide, main issues on the implementation of such a system were addressed.