This thesis describes a distributed system of cameras for visually tracking feature points in 3D. The concept of a network of cameras is introduced. Two or more calibrated cameras from a network of cameras are used to triangulate the location of a point in 3D based on camera positions and pan/tilt angles. A survey of methods for interior and exterior calibration is provided and a method suitable for multiple cameras in arbitrary positions has been implemented. A low-cost camera unit has been designed using off-the-shelf components that include a small CCD board camera and two servo-controlled mechanisms for pan and tilt. Experimental results demonstrate the performance of a network of cameras. / Thesis / Master of Engineering (ME)

The field of Learning Automata (LA) has been studied and analyzed extensively for more than four decades; however, almost all the papers have concentrated on the LA working in Environments that have a finite number of actions. This is a well-established model of computation, and expedient, epsilon-optimal and absolutely expedient machines have been designed for stationary and non-stationary Environments. There are only a few papers which deal with Environments possessing an infinite number of actions. These papers assume a well-defined and rather simple uni-modal functional form, like the Gaussian function, for the Environment's infinite reward probabilities. This thesis pioneers the concept and presents a series of continuous action LA (CALA) algorithms that do not require the function of the Environment's infinite reward probabilities to obey a well-established uni-modal functional form. Instead, this function can be, but not limited to, a multi-modal function as long as it satisfies some weak constraints. Moreover, as our discussion evolves, the constraints are further relaxed. In all these cases, we demonstrate that the underlying machines converge in an epsilon-optimal manner to the optimal action of an infinite action set. Based on the CALA algorithms proposed, we report a global maximum search algorithm, which can find the maximum points of a real-valued function by sampling the function's values that could be contaminated by noise. This thesis also investigates the performance limit of the action-taking scheme, sampling actions based on probability density functions, which is used by all currently available CALA algorithms. In more details, given a reward function, we define an index of the function which is the least upper bound of the performance that a CALA algorithm can possibly achieve. Besides, we also report a CALA algorithm that meets this upper bound in an epsilon-optimal manner. By investigating the problem from a different perspective, we argue that the algorithms proposed are closely related to the family of “Stochastic Point Location” problems involving either discretized steps or d-ary parallel machines. The thesis includes the detailed proofs of the assertions and highlights the niche contributions within the broader theory of learning. To the best of our knowledge, there are no comparable results reported in the literature.

Estruturas de dados (EDs) permitem operações de acesso e de modificação; operações de acesso apenas consultam um ou mais campos de uma ED, enquanto operações de modificação podem alterar os campos da estrutura. Dizemos que, ao realizar uma operação de modificação, criamos uma nova versão da ED. Uma ED é parcialmente persistente se permite apenas operações de acesso a versões anteriores e modificação apenas na versão mais nova, e totalmente persistente se também permite operações de modificação em todas as versões. Esta dissertação apresenta a descrição e implementação de uma versão total ou parcialmente persistente de várias estruturas: pilhas, filas, deques e árvores rubro-negras. Também são discutidas técnicas gerais para tornar persistentes certas classes de estruturas de dados. Por fim, é apresentada uma solução ao problema de localização de ponto, que usa uma árvore de busca binária persistente. / Data structures (DSs) allow access and update operations; access operations only allow accessing the value of one or more fields of the DS, while update operations allow modifying the fields of the structure. We say that, whenever an update operation is done, a new version of the DS is created. A DS is partially persistent if it allows access operations to previous versions of the structure and update operations only on the newest version, and totally persistent if it also allows update operations on all versions. This dissertation presents the description and implementation of totally or partially persistent versions of several data structures: stacks, queues, deques, and red-black trees. General techniques to make certain classes of DSs persistent are also discussed. At last, a solution to the point location problem, using a persistent binary search tree, is presented.

Trust in information systems stem from two key properties of responses to queries regarding the state of the system, viz., i) authoritativeness, and ii) unbiasedness. That the response is authoritative implies that i) the provider (source) of the response, and ii) the chain of delegations through which the provider obtained the authority to respond, can be verified. The property of unbiasedness implies that no system data relevant to the query is deliberately or accidentally suppressed. The need for guaranteeing these two important properties stem from the impracticality for the verifier to exhaustively verify the correctness of every system process, and the integrity of the platform on which system processes are executed. For instance, the integrity of a process may be jeopardized by i) bugs (attacks) in computing hardware like Random Access Memory (RAM), input/output channels (I/O), and Central Processing Unit( CPU), ii) exploitable defects in an operating system, iii) logical bugs in program implementation, and iv) a wide range of other embedded malfunctions, among others. A first step in ensuing AU properties of geographic queries is the need to ensure AU responses to a specific type of geographic query, viz., point-location. The focus of this dissertation is on strategies to leverage assured point-location, for i) ensuring authoritativeness and unbiasedness (AU) of responses to a wide range of geographic queries; and ii) useful applications like Secure Queryable Dynamic Maps (SQDM) and trustworthy redistricting protocol. The specific strategies used for guaranteeing AU properties of geographic services include i) use of novel Merkle-hash tree- based data structures, and ii) blockchain networks to guarantee the integrity of the processes.