SPECIAL ISSUE ON MEMBRANE COMPUTING, Seventh Brainstorming Week on Membrane Computing

The present volume contains a selection of papers resulting from the Seventh Brainstorming Week on Membrane Computing (BWMC7), held in Sevilla, from February 2 to February 6, 2009. The meeting was organized by the Research Group on Natural Computing (RGNC) from Department of Computer Science and Artificial Intelligence of Sevilla University. The previous editions of this series of meetings were organized in Tarragona (2003), and Sevilla (2004 – 2008). After the first BWMC, a special issue of Natural Computing – volume 2, number 3, 2003, and a special issue of New Generation Computing – volume 22, number 4, 2004, were published; papers from the second BWMC have appeared in a special issue of Journal of Universal Computer Science – volume 10, number 5, 2004, as well as in a special issue of Soft Computing – volume 9, number 5, 2005; a selection of papers written during the third BWMC has appeared in a special issue of International Journal of Foundations of Computer Science – volume 17, number 1, 2006); after the fourth BWMC a special issue of Theoretical Computer Science was edited – volume 372, numbers 2-3, 2007; after the fifth edition, a special issue of International Journal of Unconventional Computing was edited – volume 5, number 5, 2009; finally, a selection of papers elaborated during the sixth BWMC has appeared in a special issue of Fundamenta Informatica

Some Open Problems Collected During 7th BWMC

A few open problems and research topics collected during the 7th Brain- storming Week on Membrane Computing are briefly presented; further details can be found in the papers included in the volume.Junta de Andalucía P08 – TIC 0420

Notes About Spiking Neural P Systems

Spiking neural P systems (SN P systems, for short) are much investigated in the last years in membrane computing, but still many open problems and research topics are open in this area. Here, we first recall two such problems (both related to neural biology) from. One of them asks to build an SN P system able to store a number, and to provide it to a reader without losing it, so that the number is available for a further reading. We build here such a memory module and we discuss its extension to model/implement more general operations, specific to (simple) data bases. Then, we formulate another research issue, concerning pattern recognition in terms of SN P systems. In the context, we define a recent version of SN P systems, enlarged with rules able to request spikes from the environment; based on this version, so-called SN dP systems were recently introduced, extending to neural P systems the idea of a distributed dP automaton. Some details about such devices are also given, as a further invitation to the reader to this area of research.Junta de Andalucía P08 – TIC 0420

Spiking Neural P Systems: A Short Introduction and New Normal Forms

Spiking neural P systems are a class of P systems inspired from the way the neurons communicate with each other by means of electrical impulses (called \spikes"). In the few years since this model was introduced, many results related to the computing power and e ciency of these computing devices were reported. The present paper quickly surveys the basic ideas of this research area and the basic results, then, as typical proofs about the universality of spiking neural P systems, we present some new normal forms for them. Speci cally, we consider a natural restriction in the architecture of a spiking neural P system, to have neurons of a small number of types (i.e., using a small number of sets of rules). We prove that three types of neurons are su cient in order to generate each recursively enumerable set of numbers as the distance between the rst two spikes emitted by the system; the problem remains open for accepting SN P systems. The paper ends with the complete bibliography of this domain, at the level of April 2009.Ministerio de Educación y Ciencia TIN2006-13452Junta de Andalucía P08-TIC-0420

Frontiers of Membrane Computing: Open Problems and Research Topics

This is a list of open problems and research topics collected after the Twelfth Conference on Membrane Computing, CMC 2012 (Fontainebleau, France (23 - 26 August 2011), meant initially to be a working material for Tenth Brainstorming Week on Membrane Computing, Sevilla, Spain (January 30 - February 3, 2012). The result was circulated in several versions before the brainstorming and then modified according to the discussions held in Sevilla and according to the progresses made during the meeting. In the present form, the list gives an image about key research directions currently active in membrane computing

Tissue-like p system for region-based and edge-based image segmentations

Membrane Computing (MC), a relatively recent branch of natural computing is an emerging field in molecular computing. MC aims at abstracting models, called membrane systems or P systems, which mimic the function and structure of a biological cell. Many studies have utilized MC in various applications such as image segmentation. Due to the high computational cost of conventional segmentation techniques, bio-inspired models including MC may be applicable to tackle this limitation. In this study, tissue-like P systems, a variant of MC, with sophisticated communication rules were developed to improve regionbased and edge-based segmentation algorithms for manual and automatic segmenting of 2D artificial and real images. Manual segmentation was applied for artificial images, whereas, the automatic segmentation was applied for artificial and real medical images. The manual segmentation of 2D artificial images was achieved using four, six and eight adjacency pixel connectivity relationships, whereas, the automatic segmentation of 2D artificial and real medical images were achieved using four and eight adjacency pixel connectivity relationships. Two methods were used to realize the automatic edge-based and region-based segmentations. The first method is for 2D artificial images using P-lingua linked to Java Netbeans using the P-linguaCore4 Java Library. The second method is for the 2D real and real medical images using C# linked to P-linguaCore4 Java library. The results of the second method demonstrated the ability of the system to automatically segment 2D real and real medical images with arbitrary sizes and different image formats. The experimental results statistically proved that the methods markedly outpaced the state-of-the-art methods of 2D real image segmentation using the same data set. Furthermore, the methods showed better segmentation accuracy and ability to deal with images of different sizes and types. Extra efficient results such as reducing the number of rules and computational steps were achieved for 2D hexagonal artificial images based on Tissue-like P systems. The main contributions of this study are automatic loading and codifying of the input image as well as automatic visualization of output images after segmentation. Furthermore, six and eight adjacency pixel connectivity relationships should be considered for reducing computational steps, number of rules used and processing time in molecular computing

Narrowing Frontiers of Efficiency with Evolutional Communication Rules and Cell Separation

In the framework of Membrane Computing, several efficient solutions to computationally hard problems have been given. To find new borderlines between families of P systems that can solve them and the ones that cannot is an important way to tackle the P versus NP problem. Adding syntactic and/or semantic ingredients can mean passing from non-efficiency to presumably efficiency. Here, we try to get narrow frontiers, setting the stage to adapt efficient solutions from a family of P systems to another one. In order to do that, a solution to the SAT problem is given by means of a family of tissue P systems with evolutional symport/antiport rules and cell separation with the restriction that both the left-hand side and the right-hand side of the rules have at most two objects.Ministerio de Economía y Competitividad TIN2017-89842-PNational Natural Science Foundation of China No 6132010600

Implementing P Systems Parallelism by Means of GPUs

Software development for Membrane Computing is growing up yielding new applications. Nowadays, the efficiency of P systems simulators have become a critical point when working with instances of large size. The newest generation of GPUs (Graphics Processing Units) provide a massively parallel framework to compute general purpose computations. We present GPUs as an alternative to obtain better performance in the simulation of P systems and we illustrate it by giving a solution to the N-Queens problem as an example.Ministerio de Educación y Ciencia TIN2006-13425Junta de Andalucía P08–TIC-0420

Solving complex problems with a bioinspired model

Membrane systems are parallel and bioinspired systems which simulate membranes behavior when processing information. As a part of unconventional computing, P-systems are proven to be effective in solvingcomplexproblems. A software technique is presented here that obtain good results when dealing with such problems. The rules application phase is studied and updated accordingly to obtain the desired results. Certain rules are candidate to be eliminated which can make the model improving in terms of time

Some Applications of Spiking Neural P Systems

In this paper we investigate some applications of spiking neural P systems regarding their capability to solve some classical computer science problems. In this respect versatility of such systems is studied to simulate a well known parallel computational model, namely the Boolean circuits. In addition, another notorious application -- sorting -- is considered within this framework