Abstract
Machine Facial Recognition is a problem that consists in exploring still or video images of a scene to identify or verify one or more persons in the scene using stored databases of faces. Research in Facial Recognition is multidisciplinary including disciplines like pattern recognition, image processing and analysis, computer graphics, machine learning and data mining. Sometimes applications include not only facial recognition but also facial expression characteristics identification and classification like blinking of the eyes, open/close mouth among others. This paper presents a comparative study of three algorithms for classification basic facial expressions.

Abstract
Depth of an object concerns a tradeoff between computation time and excess of program length over the shortest program length required to obtain the object. It gives an unconditional lower bound on the computation time from a given program in absence of auxiliary information. Variants known as logical depth and computational depth are expressed in Kolmogorov complexity theory. We derive quantitative relation between logical depth and computational depth and unify the different depth notions by relating them to A. Kolmogorov and L. Levin's fruitful notion of randomness deficiency. Subsequently, we revisit the computational depth of infinite strings, study the notion of super deep sequences and relate it with other approaches.

Abstract

Abstract
Acoustic emission monitoring is often used in the diagnosis of electrical and mechanical incipient faults in high voltage apparatus. A great number of methods are available for condition monitoring and diagnosis of power transformer insulation, but only a few can take direct measurements inside a transformer. Partial discharges are a major source of insulation failure in power transformers and their detection can be achieved through the associated acoustic emissions. This paper reports the development of two sensing head configurations based on extrinsic and intrinsic fiber Fabry-Perot interferometers for the detection of incipient faults in oil-filled power transformers. These sensors can be placed inside the transformer tank without affecting the insulation integrity, improving fault detection and location. The performances of the sensing heads are characterized and compared with the situations where it operates in air, water and oil and promising results are obtained, which will allow the industrial development of practical solutions.

Abstract
Human observation and memory are not reliable enough to provide accurate and objective information from athletes in high-performance environments. In this context analysis tools constitute an important instrument for professional coaches, as they provide information on player's behavior statistically compiled. Most of the tools presented for the soccer universe, offer non-real time information and, with the hardware devices being quite costly. In many cases these systems (specially camera based solutions) also present some technical issues mainly in what concerns occlusion and computational demands. This research work presents a real time soccer analysis system based on a Wi-Fi location approach that can be used by a soccer coach in a training session or even a match. Using a Wi-Fi network, inexpensive tags and a positioning engine on top of it, this portable system provides a visualization tool for such data on a real time basis. The results are quite satisfactory, because this system was able to track the players during a training exercise and display this data on a real time bases and it was also able to provide information on players' movements and their interaction all over the exercise.

Abstract
This paper reports on the implementation of a cooperative personal agenda integrated into a collaborative team environment. Concerning developers, traditional project management tools are mainly focused on tasks exclusively related to the project, failing to provide users with the capability of managing tasks not necessarily associated with the work at hand. Scheduling tasks from divergent domains towards a more efficient user planning becomes unfeasible. To overcome this inaptness, we have extended the Redmine platform with an agenda-like behaviour bearing in mind each user's individual constraints.