Skeletonizing Images by Using Spiking Neural P Systems

Skeletonizing an image is representing a shape with a small amount of information by converting the initial image into a more compact representation and keeping the meaning features. In this paper we use spiking neural P systems to solve this problem. Based on such devices, a parallel software has been implemented on the GPU architecture. Some real-world applications and open lines for future research are also presented.Ministerio de Ciencia e Innovación TIN2008-04487-EMinisterio de Ciencia e Innovación TIN-2009-13192Junta de Andalucía P08-TIC-0420

A parallel algorithm for skeletonizing images by using spiking neural P systems

Skeletonization is a common type of transformation within image analysis. In general, the image B is a skeleton of the black and white image A, if the image B is made of fewer black pixels than the image A, it does preserve its topological properties and, in some sense, keeps its meaning. In this paper, we aim to use spiking neural P systems (a computational model in the framework of membrane computing) to solve the skeletonization problem. Based on such devices, a parallel software has been implemented within the Graphics Processors Units (GPU) architecture. Some of the possible real-world applications and new lines for future research will be also dealt with in this paper.Ministerio de Ciencia e Innovación TIN2008-04487-EMinisterio de Ciencia e Innovación TIN-2009-13192Junta de Andalucía P08-TIC-0420

Segmenting images with gradient-based edge detection using Membrane Computing

In this paper, we present a parallel implementation of a new algorithm for segmenting images with gradient-based edge detection by using techniques from Natural Computing. This bio-inspired parallel algorithm has been implemented in a novel device architecture called CUDA™(Compute Unified Device Architecture). The implementation has been designed via tissue P systems on the framework of Membrane Computing. Some examples and experimental results are also presented.Ministerio de Ciencia e Innovación TIN2008-04487-EMinisterio de Ciencia e Innovación TIN2009–13192Junta de Andalucía P08–TIC-04200Junta de Andalucía P06-TIC-02268Ministerio de Educación y Ciencia MTM2009-12716Universidad del Pais Vasco EHU09/0

Parallel Skeletonizing of Digital Images by Using Cellular Automata

Recent developments of computer architectures together with alternative formal descriptions provide new challenges in the study of digital Images. In this paper we present a new implementation of the Guo & Hall algorithm [8] for skeletonizing images based on Cellular Automata. The implementation is performed in a real-time parallel way by using the GPU architecture. We show also some experiments of skeletonizing traffic signals which illustrates its possible use in real life problems.Ministerio de Ciencia e Innovación TIN2008-04487-EMinisterio de Ciencia e Innovación TIN2009–13192Junta de Andalucía P08–TIC-04200Ministerio de Educación y Ciencia MTM2009-12716Universidad del Pais Vasco EHU09/0

Smoothing Problem in 2D Images with Tissue-like P Systems and Parallel Implementation

Smoothing is often used in Digital Imagery to reduce noise within an image. In this paper we present a Membrane Computing algorithm for smoothing 2D images in the framework of tissue-like P systems. The algorithm has been implemented by using a novel device architecture called CUDATM, (Compute Unified Device Architecture). We present some examples, compare the obtained time and present some research lines for the future.Ministerio de Ciencia e Innovación TIN2008-04487-EMinisterio de Ciencia e Innovación TIN-2009-13192Junta de Andalucía P08-TIC-04200Junta de Andalucía PO6-TIC-02268Ministerio de Educación y Ciencia MTM2009-1271

Self-constructing Recognizer P Systems

Usually, the changes produced in the membrane structure of a P system are considered side effects. The output of the computation is encoded as a multiset placed in a specific region and the membrane structure in the halting configuration is not considered important. In this paper we explore P systems where the target of the computation is the construction of a new membrane structure according its set of rules. The new membrane structure can be considered as the initial one of a new self-constructed P system. We focus on the self-construction of recognizer P systems and illustrates the definition with a study of the self-construction P systems working as decision trees for solving Machine Learning decision problems.Ministerio de Economía y Competitividad TIN2012-3743

Studying the Chlorophyll Fluorescence in Cyanobacteria with Membrane Computing Techniques

In this paper, we report a pioneer study of the decrease in chlorophyll uorescence produced by the reduction of MTT (a dimethyl thiazolyl diphenyl tetrazolium salt) monitored using an epi uorescence 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 inpuJunta de Andalucía P08-TIC-04200Ministerio de Economía y Competitividad TIN2012-3743

A Parallel Implementation of the Thresholding Problem by Using Tissue-Like P Systems

In this paper we present a parallel algorithm to solve the thresholding problem by using Membrane Computing techniques. This bio-inspired algorithm has been implemented in a novel device architecture called CUDATM, (Compute Unified Device Architecture). We present some examples, compare the obtained time and present some research lines for the future.Ministerio de Ciencia e Innovación TIN2008-04487-EMinisterio de Ciencia e Innovación TIN-2009-13192Junta de Andalucía P08-TIC-04200Ministerio de Educación y Ciencia MTM2009-12716Junta de Andalucía PO6-TIC-02268Universidad del País Vasco EHU09/0

Propuesta de un plan de implementación de herramientas de manufactura esbelta para la planta deshidratadora de ciruelas de la empresa Super Fruit

164 p.El proyecto de mejoramiento trata de una propuesta de un plan de implementación de herramientas de manufactura esbelta en la deshidratadora de ciruelas de la empresa Super Fruit, ubicada en Rancagua. El diagnóstico será el punto de partida para poder realizar un plan de mejora acorde a la realidad y problemática de la empresa en particular. Para esto se realizará un levantamiento de información, que consta de los diagnósticos: de calidad de ambiente laboral, de situación por áreas de la empresa, de 5S y de cómo se realiza el mantenimiento en Super Fruit. En el desarrollo se analizarán distintas metodologías que ayuden a la mejora continua de la empresa, tales como Smed, TPM, 5S, Poka Yoke, RCM y Andon. La metodología 5S será la opción que se abordará para implementar en tres áreas pilotos. La implementación de la metodología genera cambios positivos en las áreas y en los trabajadores, principalmente en clasificación, orden y limpieza de las áreas de trabajo, lo que conlleva a mejoras de eficiencia y disminución del riesgo de accidentes. El avance de la implementación se mantendrá con un seguimiento constante a través de auditorías. Por otro lado, la empresa busca constantemente mejorar la disponibilidad de los equipos y para resolver ese problema se crea una evaluación de los pilares de TPM con el propósito de evaluar el estado actual de la empresa en cada pilar y a la vez poder entregar recomendaciones para una posible implementación a futuro. Estas herramientas agregarán valor a la empresa, y si bien, demandan de bastante tiempo para que se apliquen correctamente, los beneficios son ampliamente superiores al costo de inversión, por lo que son recomendables para toda empresa que tenga su visión puesta en el mejoramiento continuo