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.

Monitoring Neurological disease in Phonation

It is well known that many neurological diseases leave a fingerprint in voice and speech production. The dramatic impact of these pathologies in life quality is a growing concert. Many techniques have been designed for the detection, diagnose and monitoring the neurological disease. Most of them are costly or difficult to extend to primary services. The present paper shows that some neurological diseases can be traced a the level of voice production. The detection procedure would be based on a simple voice test. The availability of advanced tools and methodologies to monitor the organic pathology of voice would facilitate the implantation of these tests. The paper hypothesizes some of the underlying mechanisms affecting the production of voice and presents a general description of the methodological foundations for the voice analysis system which can estimate correlates to the neurological disease. A case of study is presented from spasmodic dysphonia to illustrate the possibilities of the methodology to monitor other neurological problems as well.

Neuromorphic Detection of Vowel Representation Spaces

In this paper a layered architecture to spot and characterize vowel segments in running speech is presented. The detection process is based on neuromorphic principles, as is the use of Hebbian units in layers to implement lateral inhibition, band probability estimation and mutual exclusion. Results are presented showing how the association between the acoustic set of patterns and the phonologic set of symbols may be created. Possible applications of this methodology are to be found in speech event spotting, in the study of pathological voice and in speaker biometric characterization, among others.

A Prediction Model to Diabetes using Artificial Metaplasticity

Diabetes is the most common disease nowadays in all populations and in all age groups. Different techniques of artificial intelligence has been applied to diabetes problem. This research proposed the artificial metaplasticity on multilayer perceptron (AMMLP) as prediction model for prediction of diabetes. The Pima Indians diabetes was used to test the proposed model AMMLP. The results obtained by AMMLP were compared with other algorithms, recently proposed by other researchers, that were applied to the same database. The best result obtained so far with the AMMLP algorithm is 89.93%

Spectral Biomimetic Technique for Wood Classification

Palatal clicks are most interesting for human echolocation. Moreover, these sounds are suitable for other acoustic applications due to their regular mathematical properties and reproducibility. Simple and nondestructive techniques, bioinspired by synthetized pulses whose form reproduces the best features of palatal clicks, can be developed. The use of synthetic palatal pulses also allows detailed studies of the real possibilities of acoustic human echolocation without the problems associated with subjective individual differences. These techniques are being applied to the study of wood. As an example, a comparison of the performance of both natural and synthetic human echolocation to identify three different species of wood is presented. The results show that human echolocation has a vast potential.

Inner-Hair Cells Parameterized-Hardware Implementation for Personalized Auditory Nerve Stimulation

In this paper the hardware implementation of an inner hair cell model is presented. Main features of the design are the use of Meddis’ transduction structure and the methodology for Design with Reusability. Which allows future migration to new hardware and design refinements for speech processing and custom-made hearing aids

Amplificador de señal analógico basado en conceptos biomiméticos. Desarrollo de modelos computacionales y validación experimental

La presente tesis doctoral estudia las características de un transductor acústico bioinspirado en la estructura del maxilar inferior de un Zifio de Couvier (Ziphius cavirostris). El mecanismo de funcionamiento del sensor se basa en las características de un sistema acoplado formado por los distintos componentes acústicos identificados en el maxilar. Para analizar las características del sensor se propone un modelo simplificado 2D que consta de una cavidad cerrada con forma de bocina acoplada a una lengüeta. Una parte de la lengüeta se encuentra dentro de la cavidad y otra en el exterior. Dicha lengüeta detecta los cambios de presión acústica y las vibraciones generadas por el sonido y las transmite con ondas de flexión al interior de la cavidad. La excitación prolongada sobre la placa puede provocar la activación de los modos propios del sistema acoplado. Dichos modos se caracterizan porque presentan un máximo de presión en el cono de la bocina la cual a su vez actúa como un amplificador acústico. Mediante el Método de los elementos Finitos se analizan las características acústicas del sensor y se construye un prototipo experimental para validar los resultados evaluados en el modelo numérico. Se propone una metodología numérica que permite desarrollar y validar un elemento tetraédrico para caracterizar el comportamiento isotrópico de los medios porosos. La metodología permite construir elementos de línea y bidimensionales. A partir de esta metodología se desarrolla un elemento plano ortotrópico. Se realiza un modelo de la cavidad en el que una de las paredes de la bocina está constituida por material poroso y se une la parte exterior de la lengüeta a dicho material para que constituya una viga sobre un apoyo elástico. Se calcula la respuesta modal y se discuten los efectos del material poroso en la eficiencia del transductor y las posibles mejoras a introducir en el mismo. SUMMARY This Thesis studies the characteristics of an acoustic transducer bioinspired by the structure of the lower maxilla of an odontoceto. In this case a Cuvier’s beaked whale (Ziphius cavirostris). The transducer working mechanism is based in a coupled system, with components identified in the maxilla. To analyze the transducer a simplified 2D model composed by a horn shaped closed cavity is modeled. The cavity is coupled with a flat belt. The belt has one part inside the cavity and the other part outside of it. The belt traverses the cavity wall and it is in charge to pick the vibrations from outside and introduce it inside the cavity. The transmission is obtained through the belt bending. A sustained external load with the right frequency contents will allow the system to reach a stationary pressure intensity distribution inside the cavity. Frequencies with modal shapes that show an important intensity increase at the horn tip are of special interest because of the signal amplification. A finite element model is constructed to study the transducer coupled modes and a prototype is constructed to validate the numerical results. A numerical methodology to construct and validate a tetrahedral finite element for isotropic porous materials is presented. The methodology allows constructing linear and 2D elements. It is extended to model orthotropic porous materials behavior. At the end, one of the horn walls is made of an orthotropic material and the external belt is glued to it in order to configure a belt over an elastic foundation. Modal response is evaluated and the porous material effects in the transducer efficiency and further improvements are discussed.

An ecological approach to anomaly detection: the EIA Model.

The presented work proposes a new approach for anomaly detection. This approach is based on changes in a population of evolving agents under stress. If conditions are appropriate, changes in the population (modeled by the bioindicators) are representative of the alterations to the environment. This approach, based on an ecological view, improves functionally traditional approaches to the detection of anomalies. To verify this assertion, experiments based on Network Intrussion Detection Systems are presented. The results are compared with the behaviour of other bioinspired approaches and machine learning techniques.

Some aspects of amacrine neuron simulation for motion detection

As it is known, there are five types of neurons in the mammalian retinal layer allowing the detection of several important characteristics of the visual image impinging onto the visual system, namely, photoreceptors, horizontal cells, amacrine, bipolar and ganglion cells. And it is a well known fact too, that the amacrine neuron architecture allows a first detection for objects motion, being the most important retinal cell to this function. We have already studied and simulated the Dowling retina model and we have verified that many complex processes in visual detection is performed with the basis of the amacrine cell synaptic connections. This work will show how this structure may be employed for motion detection

Modeling, simulation and application of bacterial transduction in genetic algorithms

At present, all methods in Evolutionary Computation are bioinspired by the fundamental principles of neo-Darwinism, as well as by a vertical gene transfer. Virus transduction is one of the key mechanisms of horizontal gene propagation in microorganisms (e.g. bacteria). In the present paper, we model and simulate a transduction operator, exploring the possible role and usefulness of transduction in a genetic algorithm. The genetic algorithm including transduction has been named PETRI (abbreviation of Promoting Evolution Through Reiterated Infection). Our results showed how PETRI approaches higher fitness values as transduction probability comes close to 100%. The conclusion is that transduction improves the performance of a genetic algorithm, assuming a population divided among several sub-populations or ?bacterial colonies?.

A Multi Ant Colony Optimization algorithm for a Mixed Car Assembly Line

This paper presents an ant colony optimization algorithm to sequence the mixed assembly lines considering the inventory and the replenishment of components. This is a NP-problem that cannot be solved to optimality by exact methods when the size of the problem growth. Groups of specialized ants are implemented to solve the different parts of the problem. This is intended to differentiate each part of the problem. Different types of pheromone structures are created to identify good car sequences, and good routes for the replenishment of components vehicle. The contribution of this paper is the collaborative approach of the ACO for the mixed assembly line and the replenishment of components and the jointly solution of the problem.

Offline GA-Based optimization for heterogeneous modular multi-configurable chained microrobots

This paper presents a GA-based optimization procedure for bioinspired heterogeneous modular multiconfigurable chained microrobots. When constructing heterogeneous chained modular robots that are composed of several different drive modules, one must select the type and position of the modules that form the chain. One must also develop new locomotion gaits that combine the different drive modules. These are two new features of heterogeneous modular robots that they do not share with homogeneous modular robots. This paper presents an offline control system that allows the development of new configuration schemes and locomotion gaits for these heterogeneous modular multiconfigurable chained microrobots. The offline control system is based on a simulator that is specifically designed for chained modular robots and allows them to develop and learn new locomotion patterns.

Nuevas operaciones binarias sobre los conjuntos borrosos de tipo 2

Walker et al. ([19], [20]) definieron dos familias de operaciones binarias sobre M (conjunto de las funciones de [0,1] en [0,1]), y determinaron que, bajo ciertas condiciones, estas operaciones son tnormas (normas triangulares) o t-conormas sobre L (subconjunto de las funciones normales y convexas de M). En este trabajo se introducen dos operaciones binarias sobre M, diferentes a las dadas por Walker et al., y se estudian varias propiedades de las mismas, con el objeto de deducir nuevas t-normas y t-conormas sobre L y sobre M.