T��cnicas de computa����o natural para segmenta����o de imagens m��dicas

Image segmentation is one of the image processing problems that deserves special attention from the scientific community. This work studies unsupervised methods to clustering and pattern recognition applicable to medical image segmentation. Natural Computing based methods have shown very attractive in such tasks and are studied here as a way to verify it's applicability in medical image segmentation. This work treats to implement the following methods: GKA (Genetic K-means Algorithm), GFCMA (Genetic FCM Algorithm), PSOKA (PSO and K-means based Clustering Algorithm) and PSOFCM (PSO and FCM based Clustering Algorithm). Besides, as a way to evaluate the results given by the algorithms, clustering validity indexes are used as quantitative measure. Visual and qualitative evaluations are realized also, mainly using data given by the BrainWeb brain simulator as ground truth

Phylogenomic analysis of natural products biosynthetic gene clusters allows discovery of arseno-organic metabolites in model streptomycetes

We are indebted with Marnix Medema, Paul Straight and Sean Rovito, for useful discussions and critical reading of the manuscript, as well as with Alicia Chagolla and Yolanda Rodriguez of the MS Service of Unidad Irapuato, Cinvestav, and Araceli Fernandez for technical support in high-performance computing. This work was funded by Conacyt Mexico (grants No. 179290 and 177568) and FINNOVA Mexico (grant No. 214716) to FBG. PCM was funded by Conacyt scholarship (No. 28830) and a Cinvestav posdoctoral fellowship. JF and JFK acknowledge funding from the College of Physical Sciences, University of Aberdeen, UK.

Personal Storytelling : Using Natural Language Generation for Children with Complex Communication Needs, in the Wild...

Acknowledgements The authors thank the children, their parents and school staff, who participated in this research, and who so willingly gave us their time, help and support. They also thank Steven Knox and Alan Clelland for their work on programming the mobile phone application. Additional thanks to DynaVox Inc. for supplying the Vmax communication devices to run our system on and Sensory Software Ltd for supplying us with their AAC software. This research was supported by the Research Council UKs Digittal Economy Programme and EPSRC (Grant numbers EP/F067151/1, EP/F066880/1, EP/E011764/1, EP/H022376/1, and EP/H022570 /1).

Computing the Oja Median in R : The Package OjaNP

Acknowledgements The work of Klaus Nordhausen was supported by the Academy of Finland (grant 268703). Oleksii Pokotylo is supported by the Cologne Graduate School of Management, Economics and Social Sciences. The work of Daniel Vogel was supported by the DFG collaborate research grant SFB 823

Natural Language Generation and Fuzzy Sets : An Exploratory Study on Geographical Referring Expression Generation

This work was supported by the Spanish Ministry for Economy and Competitiveness (grant TIN2014-56633-C3-1-R) and by the European Regional Development Fund (ERDF/FEDER) and the Galician Ministry of Education (grants GRC2014/030 and CN2012/151). Alejandro Ramos-Soto is supported by the Spanish Ministry for Economy and Competitiveness (FPI Fellowship Program) under grant BES-2012-051878.

The 9th European Conference on Marine Natural Products

Acknowledgments This work was supported by grants from the European Commission within its FP7 Programme, under the thematic area KBBE.2012.3.2-01 with Grant Number Nos. 311932 ���SeaBioTech���, 311848 ���BlueGenics���, and 312184 PharmaSea.

Computational models for and from biology : simple gene assembly and reaction systems

The advancement of science and technology makes it clear that no single perspective is any longer sufficient to describe the true nature of any phenomenon. That is why the interdisciplinary research is gaining more attention overtime. An excellent example of this type of research is natural computing which stands on the borderline between biology and computer science. The contribution of research done in natural computing is twofold: on one hand, it sheds light into how nature works and how it processes information and, on the other hand, it provides some guidelines on how to design bio-inspired technologies. The first direction in this thesis focuses on a nature-inspired process called gene assembly in ciliates. The second one studies reaction systems, as a modeling framework with its rationale built upon the biochemical interactions happening within a cell. The process of gene assembly in ciliates has attracted a lot of attention as a research topic in the past 15 years. Two main modelling frameworks have been initially proposed in the end of 1990s to capture ciliates��� gene assembly process, namely the intermolecular model and the intramolecular model. They were followed by other model proposals such as templatebased assembly and DNA rearrangement pathways recombination models. In this thesis we are interested in a variation of the intramolecular model called simple gene assembly model, which focuses on the simplest possible folds in the assembly process. We propose a new framework called directed overlap-inclusion (DOI) graphs to overcome the limitations that previously introduced models faced in capturing all the combinatorial details of the simple gene assembly process. We investigate a number of combinatorial properties of these graphs, including a necessary property in terms of forbidden induced subgraphs. We also introduce DOI graph-based rewriting rules that capture all the operations of the simple gene assembly model and prove that they are equivalent to the string-based formalization of the model. Reaction systems (RS) is another nature-inspired modeling framework that is studied in this thesis. Reaction systems��� rationale is based upon two main regulation mechanisms, facilitation and inhibition, which control the interactions between biochemical reactions. Reaction systems is a complementary modeling framework to traditional quantitative frameworks, focusing on explicit cause-effect relationships between reactions. The explicit formulation of facilitation and inhibition mechanisms behind reactions, as well as the focus on interactions between reactions (rather than dynamics of concentrations) makes their applicability potentially wide and useful beyond biological case studies. In this thesis, we construct a reaction system model corresponding to the heat shock response mechanism based on a novel concept of dominance graph that captures the competition on resources in the ODE model. We also introduce for RS various concepts inspired by biology, e.g., mass conservation, steady state, periodicity, etc., to do model checking of the reaction systems based models. We prove that the complexity of the decision problems related to these properties varies from P to NP- and coNP-complete to PSPACE-complete. We further focus on the mass conservation relation in an RS and introduce the conservation dependency graph to capture the relation between the species and also propose an algorithm to list the conserved sets of a given reaction system.

Estado situacional de los algoritmos gen��ticos en los negocios internacionales

La computaci��n evolutiva y muy especialmente los algoritmos gen��ticos son cada vez m��s empleados en las organizaciones para resolver sus problemas de gesti��n y toma de decisiones (Apoteker & Barthelemy, 2000). La literatura al respecto es creciente y algunos estados del arte han sido publicados. A pesar de esto, no hay un trabajo expl��cito que eval��e de forma sistem��tica el uso de los algoritmos gen��ticos en problemas espec��ficos de los negocios internacionales (ejemplos de ello son la log��stica internacional, el comercio internacional, el mercadeo internacional, las finanzas internacionales o estrategia internacional). El prop��sito de este trabajo de grado es, por lo tanto, realizar un estado situacional de las aplicaciones de los algoritmos gen��ticos en los negocios internacionales.

Evolutionary fuzzy clustering of relational data

This paper is concerned with the computational efficiency of fuzzy clustering algorithms when the data set to be clustered is described by a proximity matrix only (relational data) and the number of clusters must be automatically estimated from such data. A fuzzy variant of an evolutionary algorithm for relational clustering is derived and compared against two systematic (pseudo-exhaustive) approaches that can also be used to automatically estimate the number of fuzzy clusters in relational data. An extensive collection of experiments involving 18 artificial and two real data sets is reported and analyzed. (C) 2011 Elsevier B.V. All rights reserved.

Fundamentos de otimiza����o por intelig��ncia de enxames: uma vis��o geral

Este artigo apresenta uma breve revis��o de alguns dos mais recentes m��todos bioinspirados baseados no comportamento de popula����es para o desenvolvimento de t��cnicas de solu����o de problemas. As metaheur��sticas tratadas aqui correspondem ��s estrat��gias de otimiza����o por col��nia de formigas, otimiza����o por enxame de part��culas, algoritmo shuffled frog-leaping, coleta de alimentos por bact��rias e col��nia de abelhas. Os princ��pios biol��gicos que motivaram o desenvolvimento de cada uma dessas estrat��gias, assim como seus respectivos algoritmos computacionais, s��o introduzidos. Duas aplica����es diferentes foram conduzidas para exemplificar o desempenho de tais algoritmos. A finalidade �� enfatizar perspectivas de aplica����o destas abordagens em diferentes problemas da ��rea de engenharia.

Algoritmos culturais com abordagem mem��tica e multipopulacional aplicados a problemas de otimiza����o

Em muitos problemas de otimiza����o h�� dificuldades em alcan��ar um resultado ��timo ou mesmo um resultado pr��ximo ao valor ��timo em um tempo vi��vel, principalmente quando se trabalha em grande escala. Por isso muitos desses problemas s��o abordados por heur��sticas ou metaheur��sticas que executam buscas por melhores solu����es dentro do espa��o de busca definido. Dentro da computa����o natural est��o os Algoritmos Culturais e os Algoritmos Gen��ticos, que s��o considerados metaheur��sticas evolutivas que se complementam devido ao mecanismo dual de heran��a cultura/gen��tica. A proposta do presente trabalho �� estudar e utilizar tais mecanismos acrescentando tanto heur��sticas de busca local como multipopula����es aplicados em problemas de otimiza����o combinat��ria (caixeiro viajante e mochila), fun����es multimodais e em problemas restritos. Ser��o executados alguns experimentos para efetuar uma avalia����o em rela����o ao desempenho desses mecanismos h��bridos e multipopulacionais com outros mecanismos dispostos na literatura de acordo com cada problema de otimiza����o aqui abordado.

Algoritmos de distribuci��n de cargas de proceso en computaci��n con membranas

Con el surgir de los problemas irresolubles de forma eficiente en tiempo polinomial en base al dato de entrada, surge la Computaci��n Natural como alternativa a la computaci��n cl��sica. En esta disciplina se trata de o bien utilizar la naturaleza como base de c��mputo o bien, simular su comportamiento para obtener mejores soluciones a los problemas que los encontrados por la computaci��n cl��sica. Dentro de la computaci��n natural, y como una representaci��n a nivel celular, surge la Computaci��n con Membranas. La primera abstracci��n de las membranas que se encuentran en las c��lulas, da como resultado los P sistemas de transici��n. Estos sistemas, que podr��an ser implementados en medios biol��gicos o electr��nicos, son la base de estudio de esta Tesis. En primer lugar, se estudian las implementaciones que se han realizado, con el fin de centrarse en las implementaciones distribuidas, que son las que pueden aprovechar las caracter��sticas intr��nsecas de paralelismo y no determinismo. Tras un correcto estudio del estado actual de las distintas etapas que engloban a la evoluci��n del sistema, se concluye con que las distribuciones que buscan un equilibrio entre las dos etapas (aplicaci��n y comunicaci��n), son las que mejores resultados presentan. Para definir estas distribuciones, es necesario definir completamente el sistema, y cada una de las partes que influyen en su transici��n. Adem��s de los trabajos de otros investigadores, y junto a ellos, se realizan variaciones a los proxies y arquitecturas de distribuci��n, para tener completamente definidos el comportamiento din��mico de los P sistemas. A partir del conocimiento est��tico ���configuraci��n inicial��� del P sistema, se pueden realizar distribuciones de membranas en los procesadores de un cl��ster para obtener buenos tiempos de evoluci��n, con el fin de que la computaci��n del P sistema sea realizada en el menor tiempo posible. Para realizar estas distribuciones, hay que tener presente las arquitecturas ���o forma de conexi��n��� de los procesadores del cl��ster. La existencia de 4 arquitecturas, hace que el proceso de distribuci��n sea dependiente de la arquitectura a utilizar, y por tanto, aunque con significativas semejanzas, los algoritmos de distribuci��n deben ser realizados tambi��n 4 veces. Aunque los propulsores de las arquitecturas han estudiado el tiempo ��ptimo de cada arquitectura, la inexistencia de distribuciones para estas arquitecturas ha llevado a que en esta Tesis se probaran las 4, hasta que sea posible determinar que en la pr��ctica, ocurre lo mismo que en los estudios te��ricos. Para realizar la distribuci��n, no existe ning��n algoritmo determinista que consiga una distribuci��n que satisfaga las necesidades de la arquitectura para cualquier P sistema. Por ello, debido a la complejidad de dicho problema, se propone el uso de metaheur��sticas de Computaci��n Natural. En primer lugar, se propone utilizar Algoritmos Gen��ticos, ya que es posible realizar alguna distribuci��n, y basada en la premisa de que con la evoluci��n, los individuos mejoran, con la evoluci��n de dichos algoritmos, las distribuciones tambi��n mejorar��n obteni��ndose tiempos cercanos al ��ptimo te��rico. Para las arquitecturas que preservan la topolog��a arb��rea del P sistema, han sido necesarias realizar nuevas representaciones, y nuevos algoritmos de cruzamiento y mutaci��n. A partir de un estudio m��s detallado de las membranas y las comunicaciones entre procesadores, se ha comprobado que los tiempos totales que se han utilizado para la distribuci��n pueden ser mejorados e individualizados para cada membrana. As��, se han probado los mismos algoritmos, obteniendo otras distribuciones que mejoran los tiempos. De igual forma, se han planteado el uso de Optimizaci��n por Enjambres de Part��culas y Evoluci��n Gramatical con reescritura de gram��ticas (variante de Evoluci��n Gramatical que se presenta en esta Tesis), para resolver el mismo cometido, obteniendo otro tipo de distribuciones, y pudiendo realizar una comparativa de las arquitecturas. Por ��ltimo, el uso de estimadores para el tiempo de aplicaci��n y comunicaci��n, y las variaciones en la topolog��a de ��rbol de membranas que pueden producirse de forma no determinista con la evoluci��n del P sistema, hace que se deba de monitorizar el mismo, y en caso necesario, realizar redistribuciones de membranas en procesadores, para seguir obteniendo tiempos de evoluci��n razonables. Se explica, c��mo, cu��ndo y d��nde se deben realizar estas modificaciones y redistribuciones; y c��mo es posible realizar este rec��lculo. Abstract Natural Computing is becoming a useful alternative to classical computational models since it its able to solve, in an efficient way, hard problems in polynomial time. This discipline is based on biological behaviour of living organisms, using nature as a basis of computation or simulating nature behaviour to obtain better solutions to problems solved by the classical computational models. Membrane Computing is a sub discipline of Natural Computing in which only the cellular representation and behaviour of nature is taken into account. Transition P Systems are the first abstract representation of membranes belonging to cells. These systems, which can be implemented in biological organisms or in electronic devices, are the main topic studied in this thesis. Implementations developed in this field so far have been studied, just to focus on distributed implementations. Such distributions are really important since they can exploit the intrinsic parallelism and non-determinism behaviour of living cells, only membranes in this case study. After a detailed survey of the current state of the art of membranes evolution and proposed algorithms, this work concludes that best results are obtained using an equal assignment of communication and rules application inside the Transition P System architecture. In order to define such optimal distribution, it is necessary to fully define the system, and each one of the elements that influence in its transition. Some changes have been made in the work of other authors: load distribution architectures, proxies definition, etc., in order to completely define the dynamic behaviour of the Transition P System. Starting from the static representation ���initial configuration��� of the Transition P System, distributions of membranes in several physical processors of a cluster is algorithmically done in order to get a better performance of evolution so that the computational complexity of the Transition P System is done in less time as possible. To build these distributions, the cluster architecture ���or connection links��� must be considered. The existence of 4 architectures, makes that the process of distribution depends on the chosen architecture, and therefore, although with significant similarities, the distribution algorithms must be implemented 4 times. Authors who proposed such architectures have studied the optimal time of each one. The non existence of membrane distributions for these architectures has led us to implement a dynamic distribution for the 4. Simulations performed in this work fix with the theoretical studies. There is not any deterministic algorithm that gets a distribution that meets the needs of the architecture for any Transition P System. Therefore, due to the complexity of the problem, the use of meta-heuristics of Natural Computing is proposed. First, Genetic Algorithm heuristic is proposed since it is possible to make a distribution based on the premise that along with evolution the individuals improve, and with the improvement of these individuals, also distributions enhance, obtaining complexity times close to theoretical optimum time. For architectures that preserve the tree topology of the Transition P System, it has been necessary to make new representations of individuals and new algorithms of crossover and mutation operations. From a more detailed study of the membranes and the communications among processors, it has been proof that the total time used for the distribution can be improved and individualized for each membrane. Thus, the same algorithms have been tested, obtaining other distributions that improve the complexity time. In the same way, using Particle Swarm Optimization and Grammatical Evolution by rewriting grammars (Grammatical Evolution variant presented in this thesis), to solve the same distribution task. New types of distributions have been obtained, and a comparison of such genetic and particle architectures has been done. Finally, the use of estimators for the time of rules application and communication, and variations in tree topology of membranes that can occur in a non-deterministic way with evolution of the Transition P System, has been done to monitor the system, and if necessary, perform a membrane redistribution on processors to obtain reasonable evolution time. How, when and where to make these changes and redistributions, and how it can perform this recalculation, is explained.

MEIA SYSTEMS: Membrane Encrypted Information Applications Systems

Membrane computing is a recent area that belongs to natural computing. This field works on computational models based on nature's behavior to process the information. Recently, numerous models have been developed and implemented with this purpose. P-systems are the structures which have been defined,developed and implemented to simulate the behavior and the evolution of membrane systems which we find in nature. What we show in this paper is a new model that deals with encrypted information which provides security the membrane systems communication. Moreover we find non deterministic and random applications in nature that are suitable to MEIA systems. The inherent parallelism and non determinism make this applications perfect object to implement MEIA systems.

M��todos acotados de aplicaci��n de reglas de evoluci��n para la implementaci��n de Sistemas P de Transici��n

La caracter��stica fundamental de la Computaci��n Natural se basa en el empleo de conceptos, principios y mecanismos del funcionamiento de la Naturaleza. La Computaci��n Natural -y dentro de ��sta, la Computaci��n de Membranas- surge como una posible alternativa a la computaci��n cl��sica y como resultado de la b��squeda de nuevos modelos de computaci��n que puedan superar las limitaciones presentes en los modelos convencionales. En concreto, la Computaci��n de Membranas se origin�� como un intento de formular un nuevo modelo computacional inspirado en la estructura y el funcionamiento de las c��lulas biol��gicas: los sistemas basados en este modelo constan de una estructura de membranas que act��an a la vez como separadores y como canales de comunicaci��n, y dentro de esa estructura se alojan multiconjuntos de objetos que evolucionan de acuerdo a unas determinadas reglas de evoluci��n. Al conjunto de dispositivos contemplados por la Computaci��n de Membranas se les denomina gen��ricamente como Sistemas P. Hasta el momento los Sistemas P s��lo han sido estudiados a nivel te��rico y no han sido plenamente implementados ni en medios electr��nicos, ni en medios bioqu��micos, s��lo han sido simulados o parcialmente implementados. Por tanto, la implantaci��n de estos sistemas es un reto de investigaci��n abierto. Esta tesis aborda uno de los problemas que debe ser resuelto para conseguir la implantaci��n de los Sistemas P sobre plataformas hardware. El problema concreto se centra en el modelo de los Sistemas P de Transici��n y surge de la necesidad de disponer de algoritmos de aplicaci��n de reglas que, independientemente de la plataforma hardware sobre la que se implementen, cumplan los requisitos de ser no deterministas, masivamente paralelos y adem��s su tiempo de ejecuci��n est�� est��ticamente acotado. Como resultado se ha obtenido un conjunto de algoritmos (tanto para plataformas secuenciales, como para plataformas paralelas) que se adec��an a las diferentes configuraciones de los Sistemas P. ABSTRACT The main feature of Natural Computing is the use of concepts, principles and mechanisms inspired by Nature. Natural Computing and within it, Membrane Computing emerges as an potential alternative to conventional computing and as from the search for new models of computation that may overcome the existing limitations in conventional models. Specifically, Membrane Computing was created to formulate a new computational paradigm inspired by the structure and functioning of biological cells: it consists of a membrane structure, which acts as separators as well as communication channels, and within this structure are stored multisets of objects that evolve according to certain evolution rules. The set of computing devices addressed by Membrane Computing are generically known P systems. Up to now, no P systems have been fully implemented yet in electronic or biochemical means. They only have been studied in theory, simulated or partially implemented. Therefore, the implementation of these systems is an open research challenge. This thesis addresses one of the problems to be solved in order to deploy P systems on hardware platforms. This specific problem is focused on the Transition P System model and emerges from the need of providing application rules algorithms that independently on the hardware platform on which they are implemented, meets the requirements of being nondeterministic, massively parallel and runtime-bounded. As a result, this thesis has developed a set of algorithms for both platforms, sequential and parallel, adapted to all possible configurations of P systems.

Dise��o de un Procesador de Membranas Paralelo para los Sistemas P de Transici��n

La computaci��n con membranas surge como una alternativa a la computaci��n tradicional. Dentro de este campo se sit��an los denominados Sistemas P de Transici��n que se basan en la existencia de regiones que contienen recursos y reglas que hacen evolucionar a dichos recursos para poder llevar a cada una de las regiones a una nueva situaci��n denominada configuraci��n. La sucesi��n de las diferentes configuraciones conforman la computaci��n. En este campo, el Grupo de Computaci��n Natural de la Universidad Polit��cnica de Madrid lleva a cabo numerosas investigaciones al amparo de las cuales se han publicado numerosos art��culos y realizado varias tesis doctorales. Las principales v��as de investigaci��n han sido, hasta el momento, el estudio del modelo te��rico sobre el que se definen los Sistemas P, el estudio de los algoritmos que se utilizan para la aplicaci��n de las reglas de evoluci��n en las regiones, el dise��o de nuevas arquitecturas que mejoren las comunicaciones entre las diferentes membranas (regiones) que componen el sistema y la implantaci��n de estos sistemas en dispositivos hardware que pudiesen definir futuras m��quinas basadas en este modelo. Dentro de este ��ltimo campo, es decir, dentro del objetivo de construir finalmente m��quinas que puedan llevar a cabo la funcionalidad de la computaci��n con Sistemas P, la presente tesis doctoral se centra en el dise��o de dos procesadores paralelos que, aplicando variantes de algoritmos existentes, favorezcan el crecimiento en el nivel de intra-paralelismo a la hora de aplicar las reglas. El dise��o y creaci��n de ambos procesadores presentan novedosas aportaciones al entorno de investigaci��n de los Sistemas P de Transici��n en tanto en cuanto se utilizan conceptos que aunque previamente definidos de manera te��rica, no hab��an sido introducidos en el hardware dise��ado para estos sistemas. As��, los dos procesadores mantienen las siguientes caracter��sticas: - Presentan un alto rendimiento en la fase de aplicaci��n de reglas, manteniendo por otro lado una flexibilidad y escalabilidad medias que son dependientes de la tecnolog��a final sobre la que se sinteticen dichos procesadores. - Presentan un alto nivel de intra-paralelismo en las regiones al permitir la aplicaci��n simult��nea de reglas. - Tienen car��cter universal en tanto en cuanto no depende del car��cter de las reglas que componen el Sistema P. - Tienen un comportamiento indeterminista que es inherente a la propia naturaleza de estos sistemas. El primero de los circuitos utiliza el conjunto potencia del conjunto de reglas de aplicaci��n as�� como el concepto de m��xima aplicabilidad para favorecer el intra-paralelismo y el segundo incluye, adem��s, el concepto de dominio de aplicabilidad para determinar el conjunto de reglas que son aplicables en cada momento con los recursos existentes. Ambos procesadores se dise��an y se prueban mediante herramientas de dise��o electr��nico y se preparan para ser sintetizados sobre FPGAs. ABSTRACT Membrane computing appears as an alternative to traditional computing. P Systems are placed inside this field and they are based upon the existence of regions called ���membranes��� that contain resources and rules that describe how the resources may vary to take each of these regions to a new situation called "configuration". Successive configurations conform computation. Inside this field, the Natural Computing Group of the Universidad Polit��cnica of Madrid develops a large number of works and researches that provide a lot of papers and some doctoral theses. Main research lines have been, by the moment, the study of the theoretical model over which Transition P Systems are defined, the study of the algorithms that are used for the evolution rules application in the regions, the design of new architectures that may improve communication among the different membranes (regions) that compose the whole system and the implementation of such systems over hardware devices that may define machines based upon this new model. Within this last research field, this is, within the objective of finally building machines that may accomplish the functionality of computation with P Systems, the present thesis is centered on the design of two parallel processors that, applying several variants of some known algorithms, improve the level of the internal parallelism at the evolution rule application phase. Design and creation of both processors present innovations to the field of Transition P Systems research because they use concepts that, even being known before, were never used for circuits that implement the applying phase of evolution rules. So, both processors present the following characteristics: - They present a very high performance during the application rule phase, keeping, on the other hand, a level of flexibility and scalability that, even known it is not very high, it seems to be acceptable. - They present a very high level of internal parallelism inside the regions, allowing several rule to be applied at the same time. - They present a universal character meaning this that they are not dependent upon the active rules that compose the P System. - They have a non-deterministic behavior that is inherent to this systems nature. The first processor uses the concept of "power set of the application rule set" and the concept of "maximal application" number to improve parallelism, and the second one includes, besides the previous ones, the concept of "applicability domain" to determine the set of rules that may be applied in each moment with the existing resources.. Both processors are designed and tested with the design software by Altera Corporation and they are ready to be synthetized over FPGAs.