Hierarchical neural network with high storage capacity

A recent method used to optimize biased neural networks with low levels of activity is applied to a hierarchical model. As a consequence, the performance of the system is strongly enhanced. The steps to achieve optimization are analyzed in detail.

Esquema criptogràfic per la gestiód'expedients mèdics

Donada la naturalesa de la informació que conté un expedient mèdic, és de vital importància que tant l'accés a les dades, com l'emmagatzemament d'aquestes, es porti a terme amb la major seguretat possible.

Expert supervision based on cases

The paper focuses on taking advantage of large amounts of data that are systematically stored in plants (by means of SCADA systems), but not exploited enough in order to achieve supervisory goals (fault detection, diagnosis and reconfiguration). The methodology of case base reasoning (CBR) is proposed to perform supervisory tasks in industrial processes by re-using the stored data. The goal is to take advantage of experiences, registered in a suitable structure as cam, avoiding the tedious task of knowledge acquisition and representation needed by other reasoning techniques as expert systems. An outlook of CBR terminology and basic concepts are presented. The adaptation of CBR in performing expert supervisory tasks, taking into account the particularities and difficulties derived from dynamic systems, is discussed. A special interest is focused in proposing a general case definition suitable for supervisory tasks. Finally, this structure and the whole methodology is tested in a application example for monitoring a real drier chamber

Synchronization reveals topological scales in complex networks

We study the relationship between topological scales and dynamic time scales in complex networks. The analysis is based on the full dynamics towards synchronization of a system of coupled oscillators. In the synchronization process, modular structures corresponding to well-defined communities of nodes emerge in different time scales, ordered in a hierarchical way. The analysis also provides a useful connection between synchronization dynamics, complex networks topology, and spectral graph analysis.

Coscheduling techniques and monitoring tools for non-dedicated cluster computing

Our efforts are directed towards the understanding of the coscheduling mechanism in a NOW system when a parallel job is executed jointly with local workloads, balancing parallel performance against the local interactive response. Explicit and implicit coscheduling techniques in a PVM-Linux NOW (or cluster) have been implemented. Furthermore, dynamic coscheduling remains an open question when parallel jobs are executed in a non-dedicated Cluster. A basis model for dynamic coscheduling in Cluster systems is presented in this paper. Also, one dynamic coscheduling algorithm for this model is proposed. The applicability of this algorithm has been proved and its performance analyzed by simulation. Finally, a new tool (named Monito) for monitoring the different queues of messages in such an environments is presented. The main aim of implementing this facility is to provide a mean of capturing the bottlenecks and overheads of the communication system in a PVM-Linux cluster.

CISNE-P: a global scheduling oriented to NOW environments

In this work, we present an integral scheduling system for non-dedicated clusters, termed CISNE-P, which ensures the performance required by the local applications, while simultaneously allocating cluster resources to parallel jobs. Our approach solves the problem efficiently by using a social contract technique. This kind of technique is based on reserving computational resources, preserving a predetermined response time to local users. CISNE-P is a middleware which includes both a previously developed space-sharing job scheduler and a dynamic coscheduling system, a time sharing scheduling component. The experimentation performed in a Linux cluster shows that these two scheduler components are complementary and a good coordination improves global performance significantly. We also compare two different CISNE-P implementations: one developed inside the kernel, and the other entirely implemented in the user space.

Toward 'Complexics' as a transdiscipline

The proposed transdisciplinary field of ‘complexics’ would bring together allcontemporary efforts in any specific disciplines or by any researchersspecifically devoted to constructing tools, procedures, models and conceptsintended for transversal application that are aimed at understanding andexplaining the most interwoven and dynamic phenomena of reality. Our aimneeds to be, as Morin says, not “to reduce complexity to simplicity, [but] totranslate complexity into theory”.New tools for the conception, apprehension and treatment of the data ofexperience will need to be devised to complement existing ones and toenable us to make headway toward practices that better fit complexictheories. New mathematical and computational contributions have alreadycontinued to grow in number, thanks primarily to scholars in statisticalphysics and computer science, who are now taking an interest in social andeconomic phenomena.Certainly, these methodological innovations put into question and againmake us take note of the excessive separation between the training receivedby researchers in the ‘sciences’ and in the ‘arts’. Closer collaborationbetween these two subsets would, in all likelihood, be much moreenergising and creative than their current mutual distance. Humancomplexics must be seen as multi-methodological, insofar as necessarycombining quantitative-computation methodologies and more qualitativemethodologies aimed at understanding the mental and emotional world ofpeople.In the final analysis, however, models always have a narrative runningbehind them that reflects the attempts of a human being to understand theworld, and models are always interpreted on that basis.

Toward 'Complexics' as a transdiscipline

The proposed transdisciplinary field of ‘complexics’ would bring together allcontemporary efforts in any specific disciplines or by any researchersspecifically devoted to constructing tools, procedures, models and conceptsintended for transversal application that are aimed at understanding andexplaining the most interwoven and dynamic phenomena of reality. Our aimneeds to be, as Morin says, not “to reduce complexity to simplicity, [but] totranslate complexity into theory”.New tools for the conception, apprehension and treatment of the data ofexperience will need to be devised to complement existing ones and toenable us to make headway toward practices that better fit complexictheories. New mathematical and computational contributions have alreadycontinued to grow in number, thanks primarily to scholars in statisticalphysics and computer science, who are now taking an interest in social andeconomic phenomena.Certainly, these methodological innovations put into question and againmake us take note of the excessive separation between the training receivedby researchers in the ‘sciences’ and in the ‘arts’. Closer collaborationbetween these two subsets would, in all likelihood, be much moreenergising and creative than their current mutual distance. Humancomplexics must be seen as multi-methodological, insofar as necessarycombining quantitative-computation methodologies and more qualitativemethodologies aimed at understanding the mental and emotional world ofpeople.In the final analysis, however, models always have a narrative runningbehind them that reflects the attempts of a human being to understand theworld, and models are always interpreted on that basis.