Ponencias (Ciencias de la Computación e Inteligencia Artificial)

URI permanente para esta colecciónhttps://hdl.handle.net/11441/11304

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P Systems with Membrane Creation and Rule Input
(Fénix Editora, 2005) Gutiérrez Naranjo, Miguel Ángel; Pérez Jiménez, Mario de Jesús; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial
When a uniform family of recognizer P systems is designed to solve a problem, the data of a concrete instance of the problem is usually provided via a multiset which is placed in the so-called input membrane. In this paper we present a new definition for recognizer P systems, called with rule input, where the data of the instance is provided via a set of rules which are introduced in the system at the beginning of the computation. We also discuss a new semantic for P systems with membrane creation and, as an example, a uniform family of recognizer P systems with rule input which solves the Subset Sum problem is provided.
Converting Integer Numbers from Binary to Unary Notation with P Systems
(Fénix Editora, 2005) Gutiérrez Naranjo, Miguel Ángel; Leporati, Alberto; Zandron, Claudio; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial
Current P systems which solve NP–complete numerical problems represent instances in unary notation. In classical complexity theory, based upon Turing machines, switching from binary to unary encoded instances gen erally corresponds to simplify the problem. In this paper we show that this does not occur when working with P systems. Namely, we propose a simple method to encode binary numbers using multisets, and a family of P systems which transforms such multisets into the usual unary notation
Multidimensional Sevilla carpets Associated with P Systems
(Fénix Editora, 2005) Gutiérrez Naranjo, Miguel Ángel; Pérez Jiménez, Mario de Jesús; Riscos Núñez, Agustín; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial
In this paper we address the problem of describing the complexity of the evolution of a P system. This is especially difficult in the case of P systems where the number of membranes in creases along the computation, via division or creation of membranes. In these cases the number of steps of a computation is not sufficient to evaluate the complexity. Sevilla Carpets were introduced in [1℄, and they describe the space-time complexity of P systems. Based on them, we de ne a four-dimensional manifold whih can be used to compare evolutions of P systems.
Multidimensional descriptional complexity of P systems
(Univ. degli Studi di Milano, 2005) Gutiérrez Naranjo, Miguel Ángel; Pérez Jiménez, Mario de Jesús; Riscos Núñez, Agustín; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial
Membrane Computing is a branch of Natural Computing which starts from the assumption that the processes taking place in the compartmental structure of a living cell can be interpreted as computations. The description of the complexity of the computations of the membrane devices (P systems) is a hard task which goes beyond the usual parameters of time and space. This is especially hard in the case of P systems where the number of membranes increases along the computation, via division or creation of membranes. In this paper we show that a four-dimensional carpet can be a useful tool to describe and compare evolutions of P systems, even in such cases.
A new way to obtain homology groups in Binary 2D images using membrane computing
(Universidad de Santiago de Compostela, 2010) Díaz Pernil, Daniel; Gutiérrez Naranjo, Miguel Ángel; Real Jurado, Pedro; Sánchez Canales, Vanesa; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial
Membrane Computing is a computational model inspired in the structure and function of living cells and tissues. In this paper we use Membrane Computing techniques to solve the Homology Groups of Binary 2D Image (HGB2I) Problem. This is a classical problem in Homology Theory which tries to calculate the number of connected components and the representative curves of the holes of these components of a given binary 2D image. To this aim, we use a family of P systems whih solves all the instances of the problem in the framework of Tissue-like P systems with catalysts.
Studying the Chlorophyll Fluorescence in Cyanobacteria with Membrane Computing Techniques
(Research Group of Natural Computing, 2013) Ardelean, Ioan I.; Díaz Pernil, Daniel; Gutiérrez Naranjo, Miguel Ángel; Peña Cantillana, Francisco; Sarchizian, Iris; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial
In this paper, we report a pioneer study of the decrease in chlorophyll fluorescence produced by the reduction of MTT (a dimethyl thiazolyl diphenyl tetrazolium salt) monitored using an epifluorescence microscope coupled to automate image analysis in the framework of P systems. Such analysis has been performed by a family of tissue P systems working on the images as data input.
The metric-aware kernel-width choice for LIME
(CEUR-WS, 2023) Barrera Vicent, Aurelio; Paluzo Hidalgo, Eduardo; Gutiérrez Naranjo, Miguel Ángel; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial
Local Interpretable Model-Agnostic Explanations (LIME) are a well-known approach to provide local interpretability to Machine Learning models. LIME uses an exponential smoothing kernel based on the kernel width value, which defines the width of the local neighbourhood. In this paper, we study the influence of the distances for these local explanations, and we explore the choice of kernel width to guarantee a fair performance comparison between the distances.
A stacked deep convolutional neural network to predict the remaining useful life of a turbofan engine
(PHM Society, 2021) Solís Martín, David; Galán Páez, Juan; Borrego Díaz, Joaquín; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial; Agencia Estatal de Investigación. España; Universidad de Sevilla. TIC-137: Lógica, Computación e Ingeniería del Conocimiento
his paper presents the data-driven techniques and method ologies used to predict the remaining useful life (RUL) of a fleet of aircraft engines that can suffer failures of diverse nature. The solution presented is based on two Deep Con volutional Neural Networks (DCNN) stacked in two levels. The first DCNN is used to extract a low-dimensional feature vector using the normalized raw data as input. The second DCNN ingests a list of vectors taken from the former DCNN and estimates the RUL. Model selection was carried out by means of Bayesian optimization using a repeated random subsampling validation approach. The proposed methodol ogy was ranked in the third place of the 2021 PHM Confer ence Data Challenge.
Building knowledge layers and networks from urban digital information
(Universitat Politécnica de Catalunya, 2013) Borrego Díaz, Joaquín; Galán Páez, Juan; Miguel Rodríguez, Jaime de; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial
The understanding and management of complex digital information on cities need the use of tools providing experts with new insights about the knowledge hidden within this great amount of data. In this paper a methodology to provide such a kind of knowledge is presented. This methodology is based on Formal Concept Analysis and allows visualizing abstract concepts that can be interpreted (and hence discovered) by city researchers.
Atlas de terapias urbanas basado en casos reales
(AMPS. Universidad de Sevilla, 2015) Rodríguez Estévez, Sergio; Mendoza Muro, Salas; Fernández-Valderrama, Luz; Ureta Muñoz, Carolina; Rovira Caballero, Ignacio; Duarte Sastre, José Antonio; Aranda Corral, Gonzalo A.; Pazos-García, Francisco; Fernández Perea, Macarena; López Casado, David; Martín-Mariscal, Amanda; Universidad de Sevilla. Departamento de Proyectos Arquitectónicos; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial; Universidad de Sevilla. Departamento de Geografía Humana; Universidad de Sevilla. Departamento de Ingeniería del Diseño; Universidad de Sevilla. HUM958: In-Gentes [investigación en Generación de Territorios]; Universidad de Sevilla. TIC137: Lógica, Computación e Ingeniería del Conocimiento; Universidad de Sevilla. HUM177: Geografía y Desarrollo Regional y Urbano
El “Atlas de terapias urbanas1 ” se propone como una herramienta encaminada a facilitar la identificación y evaluación de mejoras urbanas adaptadas a las vocaciones de los diferentes entornos. El objeto de su creación está encaminado a servir en la toma de decisiones inteligentes a las instituciones y actores involucrados en la revitalización de los barrios andaluces. Proponemos una herramienta de mediación, que no solo se base en deficiencias barriales sino también en potencialidades; no solo en los deseos de la ciudadanía, sino también en las vocaciones de los entornos. El presente artículo trata de compendiar, de forma resumida, los avances y documentos internos desarrollados hasta la fecha por los autores que conforman esta investigación. En él se explican los conceptos y procesos fundamentales sobre los que se asienta el diseño de la herramienta buscada.
P Systems as a Modeling Framework for Molecular Systems Biology
(Huazhong University of Science and Technology, 2012) Romero Campero, Francisco José; Pérez Jiménez, Mario de Jesús; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial; Universidad de Sevilla. TIC193 : Computación Natural
The P versus NP problem: Unconventional insights from Membrane Computing
(IMCS: International Membrane Computing Society, 2013) Pérez Jiménez, Mario de Jesús; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial; Universidad de Sevilla. TIC193 : Computación Natural
: The P ?=NP question is one of the outstanding open problems in theoretical computer science. The relevance of this question is not only the inherent pleasure of solving a mathematical problem, since an answer to it would provide information of high economical interest. On the one hand, a negative answer to this question would confirm that the majority of current cryptographic systems are secure from a practical point of view. On the other hand, a positive answer would not only show the uncertainty about the secureness of these systems, but also this kind of answer is expected to come together with a general procedure such that it will provide a deterministic algorithm solving any NP-complete problem in polynomial time. In this talk, new approaches/tools to attack the previous problem are given by using Membrane Computing, a branch of Natural Computing aiming to abstract computing models from the structure and functioning of the living cell as well as from the organization of cells in tissues, organs, and other higher order structures. The devices of this paradigm constitute models for distributed, parallel and non-deterministic computing. Specifically, different borderlines between efficiency and non-efficiency are shown in terms of syntactical ingredients of cell-like and tissue like membrane systems. Each of them provide appealing characterizations of the P̸=NP conjecture within the framework of this bioinspired and unconventional computing model.
Editorial. Foreword. Special Issue: A selection of papers from the 10th Brainstorming Week on Membrane Computing
(Taylor and Francis, 2013) Paun, Gheorghe; Pérez Jiménez, Mario de Jesús; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial; Universidad de Sevilla. TIC193 : Computación Natural
Fault Diagnosis Models for Electric Locomotive Systems Based on Fuzzy Reasoning Spiking Neural P Systems
(Springer, 2014) Wang, Tao; Zhang, Gexiang; Pérez Jiménez, Mario de Jesús; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial; Ministerio de Economía y Competitividad (MINECO). España; Universidad de Sevilla. TIC193 : Computación Natural
This paper discusses the application of fuzzy reasoning spiking neural P systems with real numbers (rFRSN P systems) to fault diagnosis of electric locomotive systems. Relationships among breakdown signals and faulty sections in subsystems of electric locomotive systems are described in the form of fuzzy production rules firstly and then fault diagnosis models based on rFRSN P systems for these subsystems are built according to these rules. Fuzzy production rules for diagnosing electric locomotive systems are abstracted from the fault diagnosis analysis of the subsystems and the causality among faulty sections, faulty subsystems and electric locomotive systems. Finally, a diagnosis model based on rFRSN P systems for electric locomotive systems is proposed.
A bioinspired computing approach to model complex systems
(Springer, 2014) Pérez Jiménez, Mario de Jesús; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial; Ministerio de Economía y Competitividad (MINECO). España; Universidad de Sevilla. TIC193 : Computación Natural
The use of models is intrinsic to any scientific activity. In particular, formal/mathematical models provide a relevant tool for scientific investigation. This paper presents a new Membrane Computing based computational paradigm as a framework for modelling processes and real-life phenomena. P systems, devices in Membrane Computing, are not used as a computing paradigm, but rather as a formalism for describing the behaviour of the system to be modelled. They offer an approach to the development of models for biological systems that meets the requirements of a good modelling framework: relevance, understandability, extensibility and computability.
P Systems based Computing Polynomials: Design and Formal Verification
(IMCS: International Membrane Computing Society, 2015) Yuan, Weitao; Zhang, Gexiang; Pérez Jiménez, Mario de Jesús; Wang, Tao; Huang, Zhiwei; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial; Ministerio de Economía y Competitividad (MINECO). España; Universidad de Sevilla. TIC193 : Computación Natural
Automatic design of P systems is an attractive research topic in the community of membrane computing. Differing from the previous work that used evolutionary algorithms to fulfill the task, this paper presents the design of a simple (deterministic transition) P system (without input membrane) of degree 1, capturing the value of the k- order (k 2) polynomial by using a reasoning method. Specifically, the values of polynomial p(n) corresponding to a natural number t is equal to the multiplicity of a distinguished object of the system (the output object) in the configuration at instant t. We also discuss the descriptive computational resources required by the designed k-order polynomial P system.
Temporal Fuzzy Reasoning Spiking Neural P Systems with Real Numbers for Power System Fault Diagnosis
(IMCS: International Membrane Computing Society, 2015) Huang, Kang; Wang, Tao; He, Yangyang; Zhang, Gexiang; Pérez Jiménez, Mario de Jesús; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial; Ministerio de Economía y Competitividad (MINECO). España; Universidad de Sevilla. TIC193 : Computación Natural
This paper proposes a temporal fuzzy reasoning spiking neural P sys- tem with real numbers (rTFRSN P system) and its corresponding fault diagnosis method called FDTSNP to diagnose faults in a power system. The introduction of the rTFRSN P system is to make full use of the temporal order information of alarm messages so as to model candidate fault sections. The presentation of the reasoning algorithm within the framework of an rTFRSN P system tries to obtain confidence levels of candidate faulty sections. Thus, FDTSNP offers an intuitive illustration based on a strictly mathematical expression and a good ability to han- dle incomplete and uncertain alarm messages with temporal order information. The effectiveness of FDTSNP is verified in various fault cases including single and multiple fault situations with/without incomplete and uncertain alarm mes- sages. Experimental results show that FDTSNP is better than several methods reported in the literature, in terms of the correctness of diagnosis results.
CuSNP: Spiking Neural P Systems Simulators in CUDA
(IMCS: International Membrane Computing Society, 2016) Carandang, Jym Paul; Villaflores, John Matthew B.; Cabarle, Francis George C.; Adorna, Henry N.; Martínez del Amor, Miguel Ángel; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial; Universidad de Sevilla. TIC193 : Computación Natural
Spiking neural P systems (in short, SN P systems) are models of computation inspired by biological neurons. In this work, we report our ongoing e orts to improve simulators for SN P systems. CuSNP is a project involving sequential and parallel simulators, and in this work we include a PLingua le parser. The PLingua le parser is for ease of use when performing simulations to be executed either in the CPU or in CUDA graphics processing units (in short, GPUs). Our results also include a comparison and analysis of the simulator we developed by simulating two types of parallel soring networks: generalized and bitonic. At present, our GPU simulator is better suited on the former type based on the pro ling of our GPU kernel functions, i.e. our GPU simulators run up to 50 faster than the sequential simulator but simulations of bitonic networks run slightly slower than generalized networks. We also implemented an algorithm based on nite automata to allow more forms of regular expressions in the simulated SN P systems.
A Software Tool for Computer-Aided Design of Cell-like Spiking Neural P Systems
(IMCS: International Membrane Computing Society, 2016) Valencia Cabrera, Luis; Wu, TingFang; Zhang, ZhiQiang; Pan, Linqiang; Pérez Jiménez, Mario de Jesús; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial; National Natural Science Foundation of China; Universidad de Sevilla. TIC193 : Computación Natural
Spiking neural P systems (SN P systems, for short) constitute a class of computing models in the research eld of membrane computing. Inspired by the interactions among neurons in the brain, they have attracted much attention since their appearance in 2006. Many variants have emerged, presenting a graph-based structure, and several software simulators were developed for them. Recently, a di erent approach was followed by the so-called cell-like spiking neural P systems. Unlike previous SN P systems, this new model includes a tree-based structure, taking elements from traditional rewriting rules in the original P systems. As described in this work, a software tool was developed to aid in the analysis of solutions in this new computing model. Integrated within the framework of P-Lingua and MeCoSim, this software may play an important role assisting in tasks related with the design, simulation and experimental validation.
Borderlines of efficiency: what’s up?
(IMCS: International Membrane Computing Society, 2016) Riscos Núñez, Agustín; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial; Universidad de Sevilla. TIC193 : Computación Natural
Some of the theoretical open problems and current challenges concerning P systems from a theoretical perspective will be discussed, focusing on results related to searching bounds for computational com- plexity classes in general, and to the P vs NP problem and the P ̆aun’s conjecture in particular. Membrane computing is already a mature field, and the research commu- nity around it is becoming more interdisciplinary and diverse. Although nowadays it seems that practical applications receive a rapidly increasing attention, there are still key theoretical issues that need to be addressed

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