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This paper presents how advanced social media platforms can be exploited to construct and share contextual spaces enabling the instantiation of agile personal learning environments or informal knowledge management solutions. The usefulness of open plugins ...
Since the invention of first camera, people have always thought of new ways to capture moments. With the advent of digital photography, not only imaging systems have progressed, but also technology provides new user experience. The recently introduced ligh ...
International Society for Optics and Photonics2014
In real-word applications, signal processing is often used to measure and control a physical field by means of sensors and sources, respectively. An aspect that has been often neglected is the optimization of the sources' locations. In this work, we discus ...
In a chip-to-chip communication system and apparatus, a set of physical signals to be conveyed over a communication bus is provided, and mapped to a codeword of a vector signaling code using the physical signals and a state information, wherein a codeword ...
This monograph contains a study of the global Cauchy problem for the Yang-Mills equations on (6+1) and higher dimensional Minkowski space, when the initial data sets are small in the critical gauge covariant Sobolev space. (H) over dot(A)((n-4)/2). Regular ...
Within a context of a social and economic crisis, the city of Lisbon is shyly starting to thrill with desire for change. Several socio-cultural spaces, with different degrees of autonomy from the state and the market forces, are having in fact an important ...
Matrix factorization techniques such as the singular value decomposition (SVD) have had great success in recommender systems. We present a new perspective of SVD for constructing a latent space from the training data, which is justified by the theory of hy ...
We propose a dimensionality reducing matrix design based on training data with constraints on its Frobenius norm and number of rows. Our design criteria is aimed at preserving the distances between the data points in the dimensionality reduced space as muc ...
Dynamic programming is an algorithmic technique to solve problems that follow the Bellman’s principle: optimal solutions depends on optimal sub-problem solutions. The core idea behind dynamic programming is to memoize intermediate results into matrices to ...
We present a variational framework, and an algorithm based on the alternating method of multipliers (ADMM), for the problem of decomposing a vector field into its curl- and divergence-free components (Helmholtz decomposition) in the presence of noise. We p ...
