Development and implantation of a Thesaurus of Manufacturing Engineering terms

Present work shows the teaching-learning experience developed in the Department of Manufacturing Engineering of the University of Malaga. This experience is based on the need to generate a specific glossary of manufacturing engineering terms to be used as a study guide by the students. Eventually, it was decided to make a Thesaurus that would be aimed at a teaching activity. Also, it would take part in the educational innovation project PIE 13-025 of the University of Malaga, within the biennium 2013/2015. The first step consisted of the design of Thesaurus pattern, taking into account the kind of information that it was necessary include in it. Afterward, this pattern would be place on the Virtual Campus and the student would have to complete the information required. Finally, the results obtained in the different applications of this activity would be analyzed and evaluated.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Harmonically Trapped Quantum Gases

We solve the problem of a Bose or Fermi gas in $d$-dimensions trapped by $\delta \leq d$ mutually perpendicular harmonic oscillator potentials. From the grand potential we derive their thermodynamic functions (internal energy, specific heat, etc.) as well as a generalized density of states. The Bose gas exhibits Bose-Einstein condensation at a nonzero critical temperature $T_{c}$ if and only if $d+\delta >2$, and a jump in the specific heat at $T_{c}$ if and only if $d+\delta >4$. Specific heats for both gas types precisely coincide as functions of temperature when $d+\delta =2$. The trapped system behaves like an ideal free quantum gas in $d+\delta$ dimensions. For $\delta =0$ we recover all known thermodynamic properties of ideal quantum gases in $d$ dimensions, while in 3D for $\delta =$ 1, 2 and 3 one simulates behavior reminiscent of quantum {\it wells, wires}and{\it dots}, respectively.Comment: 14 pages including 3 figures and 3 table

Node Sampling using Random Centrifugal Walks

Sampling a network with a given probability distribution has been identified as a useful operation. In this paper we propose distributed algorithms for sampling networks, so that nodes are selected by a special node, called the \emph{source}, with a given probability distribution. All these algorithms are based on a new class of random walks, that we call Random Centrifugal Walks (RCW). A RCW is a random walk that starts at the source and always moves away from it. Firstly, an algorithm to sample any connected network using RCW is proposed. The algorithm assumes that each node has a weight, so that the sampling process must select a node with a probability proportional to its weight. This algorithm requires a preprocessing phase before the sampling of nodes. In particular, a minimum diameter spanning tree (MDST) is created in the network, and then nodes' weights are efficiently aggregated using the tree. The good news are that the preprocessing is done only once, regardless of the number of sources and the number of samples taken from the network. After that, every sample is done with a RCW whose length is bounded by the network diameter. Secondly, RCW algorithms that do not require preprocessing are proposed for grids and networks with regular concentric connectivity, for the case when the probability of selecting a node is a function of its distance to the source. The key features of the RCW algorithms (unlike previous Markovian approaches) are that (1) they do not need to warm-up (stabilize), (2) the sampling always finishes in a number of hops bounded by the network diameter, and (3) it selects a node with the exact probability distribution