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An invisible layer of knowledge is progressively growing with the emergence of situated visualizations and reality-based information retrieval systems. In essence, digital content will overlap with real-world entities, eventually providing insights into the surrounding environment and useful information for the user. The implementation of such a vision may appear close, but many subtle details separate us from its fulfillment. This kind of implementation, as the overlap between rendered virtual annotations and the camera's real-world view, requires different computer vision paradigms for object recognition and tracking which often require high computing power and large-scale datasets of images. Nevertheless, these resources are not always available, and in some specific domains, the lack of an appropriate reference dataset could be disruptive for a considered task. In this particular scenario, we here consider the problem of wine recognition to support an augmented reading of their labels. In fact, images of wine bottle labels may not be available as wineries periodically change their designs, product information regulations may vary, and specific bottles may be rare, making the label recognition process hard or even impossible. In this work, we present augmented wine recognition, an augmented reality system that exploits optical character recognition paradigms to interpret and exploit the text within a wine label, without requiring any reference image. Our experiments show that such a framework can overcome the limitations posed by image retrieval-based systems while exhibiting a comparable performance. [ABSTRACT FROM AUTHOR]

Presents a study which analyzed systems of heterogeneous parallel processing, in relation to parallel programs commencing on distributed systems. What the design of parallel processing systems requires; Importance of concurrency and synchronization with regards to queuing network analysis; Outline of a model queuing system.

The probability distribution of the overhead caused by the use of the checkpointing rollback recovery technique is evaluated in both cases of a single critical task and of an overall transaction-oriented system. This distribution is obtained in Laplace-Stieltjes transform form, from which all the moments can be easily calculated. Alternatively, inversion methods can be used to evaluate the distribution. We propose checkpointing strategies based on the above distribution in order to optimize performance criteria motivated, in the ease of critical tasks, by real time constraints, and in the case of transaction-oriented systems, by the need of guaranteeing the users about the maximum system unavailability. [ABSTRACT FROM AUTHOR]

A recursive technique is provided to compute the cycle time distribution for a cyclic two-stage queueing network with exponential servers and blocking. The blocking phenomenon occurs because of the finite capacity of the stages, which can be used to represent resource constraints. An equivalence relation between models with different finite capacity sizes is derived. The recursive scheme is characterized by a low polynomial computational complexity. [ABSTRACT FROM AUTHOR]