A new DSATUR-based algorithm for exact vertex coloring

This paper describes a new exact algorithm PASS for the vertex coloring problem based on the well known DSATUR algorithm. At each step DSATUR maximizes saturation degree to select a new candidate vertex to color, breaking ties by maximum degree w.r.t. uncolored vertices. Later Sewell introduced a new tiebreaking strategy, which evaluated available colors for each vertex explicitly. PASS differs from Sewell in that it restricts its application to a particular set of vertices. Overall performance is improved when the new strategy is applied selectively instead of at every step. The paper also reports systematic experiments over 1500 random graphs and a subset of the DIMACS color benchmark.

Efficient Model-based 3D Tracking by Using Direct Image Registration

This thesis deals with the problem of efficiently tracking 3D objects in sequences of images. We tackle the efficient 3D tracking problem by using direct image registration. This problem is posed as an iterative optimization procedure that minimizes a brightness error norm. We review the most popular iterative methods for image registration in the literature, turning our attention to those algorithms that use efficient optimization techniques. Two forms of efficient registration algorithms are investigated. The first type comprises the additive registration algorithms: these algorithms incrementally compute the motion parameters by linearly approximating the brightness error function. We centre our attention on Hager and Belhumeur’s factorization-based algorithm for image registration. We propose a fundamental requirement that factorization-based algorithms must satisfy to guarantee good convergence, and introduce a systematic procedure that automatically computes the factorization. Finally, we also bring out two warp functions to register rigid and nonrigid 3D targets that satisfy the requirement. The second type comprises the compositional registration algorithms, where the brightness function error is written by using function composition. We study the current approaches to compositional image alignment, and we emphasize the importance of the Inverse Compositional method, which is known to be the most efficient image registration algorithm. We introduce a new algorithm, the Efficient Forward Compositional image registration: this algorithm avoids the necessity of inverting the warping function, and provides a new interpretation of the working mechanisms of the inverse compositional alignment. By using this information, we propose two fundamental requirements that guarantee the convergence of compositional image registration methods. Finally, we support our claims by using extensive experimental testing with synthetic and real-world data. We propose a distinction between image registration and tracking when using efficient algorithms. We show that, depending whether the fundamental requirements are hold, some efficient algorithms are eligible for image registration but not for tracking.

Towards a ground navigation system based in visual feedback provided by a mini UAV

This paper addresses initial efforts to develop a navigation system for ground vehicles supported by visual feedback from a mini aerial vehicle. A visual-based algorithm computes the ground vehicle pose in the world frame, as well as possible obstacles within the ground vehicle pathway. Relying on that information, a navigation and obstacle avoidance system is used to re-plan the ground vehicle trajectory, ensuring an optimal detour. Finally, some experiments are presented employing a unmanned ground vehicle (UGV) and a low cost mini unmanned aerial vehicle (UAV).

Artificial pancreas using a personalized rule-based controller achieves overnight normoglycemia in patients with type 1 diabetes

Objective: This study assessed the efficacy of a closed-loop (CL) system consisting of a predictive rule-based algorithm (pRBA) on achieving nocturnal and postprandial normoglycemia in patients with type 1 diabetes mellitus (T1DM). The algorithm is personalized for each patient’s data using two different strategies to control nocturnal and postprandial periods. Research Design and Methods: We performed a randomized crossover clinical study in which 10 T1DM patients treated with continuous subcutaneous insulin infusion (CSII) spent two nonconsecutive nights in the research facility: one with their usual CSII pattern (open-loop [OL]) and one controlled by the pRBA (CL). The CL period lasted from 10 p.m. to 10 a.m., including overnight control, and control of breakfast. Venous samples for blood glucose (BG) measurement were collected every 20 min. Results: Time spent in normoglycemia (BG, 3.9–8.0 mmol/L) during the nocturnal period (12 a.m.–8 a.m.), expressed as median (interquartile range), increased from 66.6% (8.3–75%) with OL to 95.8% (73–100%) using the CL algorithm (P<0.05). Median time in hypoglycemia (BG, <3.9 mmol/L) was reduced from 4.2% (0–21%) in the OL night to 0.0% (0.0–0.0%) in the CL night (P<0.05). Nine hypoglycemic events (<3.9 mmol/L) were recorded with OL compared with one using CL. The postprandial glycemic excursion was not lower when the CL system was used in comparison with conventional preprandial bolus: time in target (3.9–10.0 mmol/L) 58.3% (29.1–87.5%) versus 50.0% (50–100%). Conclusions: A highly precise personalized pRBA obtains nocturnal normoglycemia, without significant hypoglycemia, in T1DM patients. There appears to be no clear benefit of CL over prandial bolus on the postprandial glycemia

Lifetime maximization for beamforming applications in wireless sensor networks

Energy efficiency is a major design issue in the context of Wireless Sensor Networks (WSN). If data is to be sent to a far-away base station, collaborative beamforming by the sensors may help to dis- tribute the load among the nodes and reduce fast battery depletion. However, collaborative beamforming techniques are far from opti- mality and in many cases may be wasting more power than required. In this contribution we consider the issue of energy efficiency in beamforming applications. Using a convex optimization framework, we propose the design of a virtual beamformer that maximizes the network's lifetime while satisfying a pre-specified Quality of Service (QoS) requirement. A distributed consensus-based algorithm for the computation of the optimal beamformer is also provided

Diffusion Gradient Temporal Difference for Cooperative Reinforcement Learning with Linear Function Approximation

We introduce a diffusion-based algorithm in which multiple agents cooperate to predict a common and global statevalue function by sharing local estimates and local gradient information among neighbors. Our algorithm is a fully distributed implementation of the gradient temporal difference with linear function approximation, to make it applicable to multiagent settings. Simulations illustrate the benefit of cooperation in learning, as made possible by the proposed algorithm.

Codificador de voz MIDI

El presente proyecto tiene el objetivo de facilitar la composición de canciones mediante la creación de las distintas pistas MIDI que la forman. Se implementan dos controladores. El primero, con objeto de transcribir la parte melódica, convierte la voz cantada o tarareada a eventos MIDI. Para ello, y tras el estudio de las distintas técnicas del cálculo del tono (pitch), se implementará una técnica con ciertas variaciones basada en la autocorrelación. También se profundiza en el segmentado de eventos, en particular, una técnica basada en el análisis de la derivada de la envolvente. El segundo, dedicado a la base rítmica de la canción, permite la creación de la percusión mediante el golpe rítmico de objetos que disponga el usuario, que serán asignados a los distintos elementos de percusión elegidos. Los resultados de la grabación de estos impactos serán señales de corta duración, no lineales y no armónicas, dificultando su discriminación. La herramienta elegida para la clasificación de los distintos patrones serán las redes neuronales artificiales (RNA). Se realizara un estudio de la metodología de diseño de redes neuronales especifico para este tipo de señales, evaluando la importancia de las variables de diseño como son el número de capas ocultas y neuronas en cada una de ellas, algoritmo de entrenamiento y funciones de activación. El estudio concluirá con la implementación de dos redes de diferente naturaleza. Una red de Elman, cuyas propiedades de memoria permiten la clasificación de patrones temporales, procesará las cualidades temporales analizando el ataque de su forma de onda. Una red de propagación hacia adelante feed-forward, que necesitará de robustas características espectrales y temporales para su clasificación. Se proponen 26 descriptores como los derivados de los momentos del espectro: centroide, curtosis y simetría, los coeficientes cepstrales de la escala de Mel (MFCCs), y algunos temporales como son la tasa de cruces por cero y el centroide de la envolvente temporal. Las capacidades de discriminación inter e intra clase de estas características serán evaluadas mediante un algoritmo de selección, habiéndose elegido RELIEF, un método basado en el algoritmo de los k vecinos mas próximos (KNN). Ambos controladores tendrán función de trabajar en tiempo real y offline, permitiendo tanto la composición de canciones, como su utilización como un instrumento más junto con mas músicos. ABSTRACT. The aim of this project is to make song composition easier by creating each MIDI track that builds it. Two controllers are implemented. In order to transcribe the melody, the first controler converts singing voice or humming into MIDI files. To do this a technique based on autocorrelation is implemented after having studied different pitch detection methods. Event segmentation has also been dealt with, to be more precise a technique based on the analysis of the signal's envelope and it's derivative have been used. The second one, can be used to make the song's rhythm . It allows the user, to create percussive patterns by hitting different objects of his environment. These recordings results in short duration, non-linear and non-harmonic signals. Which makes the classification process more complicated in the traditional way. The tools to used are the artificial neural networks (ANN). We will study the neural network design to deal with this kind of signals. The goal is to get a design methodology, paying attention to the variables involved, as the number of hidden layers and neurons in each, transfer functions and training algorithm. The study will end implementing two neural networks with different nature. Elman network, which has memory properties, is capable to recognize sequences of data and analyse the impact's waveform, precisely, the attack portion. A feed-forward network, needs strong spectral and temporal features extracted from the hit. Some descriptors are proposed as the derivates from the spectrum moment as centroid, kurtosis and skewness, the Mel-frequency cepstral coefficients, and some temporal features as the zero crossing rate (zcr) and the temporal envelope's centroid. Intra and inter class discrimination abilities of those descriptors will be weighted using the selection algorithm RELIEF, a Knn (K-nearest neighbor) based algorithm. Both MIDI controllers can be used to compose, or play with other musicians as it works on real-time and offline.

Diseño e implementación de un módulo para la anotación de imágenes médicas

Se comenzó el trabajo recabando información sobre los distintos enfoques que se le había dado a la anotación a lo largo del tiempo, desde anotación de imágenes a mano, pasando por anotación de imágenes utilizando características de bajo nivel, como color y textura, hasta la anotación automática. Tras entrar en materia, se procedió a estudiar artículos relativos a los diferentes algoritmos utilizados para la anotación automática de imágenes. Dado que la anotación automática es un campo bastante abierto, hay un gran numero de enfoques. Teniendo las características de las imágenes en particular en las que se iba a centrar el proyecto, se fueron descartando los poco idoneos, bien por un coste computacional elevado, o porque estaba centrado en un tipo diferente de imágenes, entre otras cosas. Finalmente, se encontró un algoritmo basado en formas (Active Shape Model) que se consideró que podría funcionar adecuadamente. Básicamente, los diferentes objetos de la imagen son identicados a partir de un contorno base generado a partir de imágenes de muestra, siendo modicado automáticamente para cubrir la zona deseada. Dado que las imágenes usadas son todas muy similares en composición, se cree que puede funcionar bien. Se partió de una implementación del algoritmo programada en MATLAB. Para empezar, se obtuvieron una serie de radiografías del tórax ya anotadas. Las imágenes contenían datos de contorno para ambos pulmones, las dos clavículas y el corazón. El primer paso fue la creación de una serie de scripts en MATLAB que permitieran: - Leer y transformar las imágenes recibidas en RAW, para adaptarlas al tamaño y la posición de los contornos anotados - Leer los archivos de texto con los datos de los puntos del contorno y transformarlos en variables de MATLAB - Unir la imagen transformada con los puntos y guardarla en un formato que la implementación del algoritmo entendiera. Tras conseguir los ficheros necesarios, se procedió a crear un modelo para cada órgano utilizando para el entrenamiento una pequeña parte de las imágenes. El modelo obtenido se probó con varias imágenes de las restantes. Sin embargo, se encontro bastante variación dependiendo de la imagen utilizada y el órgano detectado. ---ABSTRACT---The project was started by procuring information about the diferent approaches to image annotation over time, from manual image anotation to automatic annotation. The next step was to study several articles about the diferent algorithms used for automatic image annotation. Given that automatic annotation is an open field, there is a great number of approaches. Taking into account the features of the images that would be used, the less suitable algorithms were rejected. Eventually, a shape-based algorithm (Active Shape Model) was found. Basically, the diferent objects in the image are identified from a base contour, which is generated from training images. Then this contour is automatically modified to cover the desired area. Given that all the images that would be used are similar in object placement, the algorithm would probably work nicely. The work started from a MATLAB implementation of the algorithm. To begin with, a set of chest radiographs already annotated were obtained. These images came with contour data for both lungs, both clavicles and the heart. The first step was the creation of a series of MATLAB scripts to join the RAW images with the annotation data and transform them into a format that the algorithm could read. After obtaining the necessary files, a model for each organ was created using part of the images for training. The trained model was tested on several of the reimaining images. However, there was much variation in the results from one image to another. Generally, lungs were detected pretty accurately, whereas clavicles and the heart gave more problems. To improve the method, a new model was trained using half of the available images. With this model, a significant inprovement of the results can be seen.

DAEDALUS at RepLab 2014: Detecting RepTrak reputation dimensions on tweets

This paper describes our participation at the RepLab 2014 reputation dimensions scenario. Our idea was to evaluate the best combination strategy of a machine learning classifier with a rule-based algorithm based on logical expressions of terms. Results show that our baseline experiment using just Naive Bayes Multinomial with a term vector model representation of the tweet text is ranked second among runs from all participants in terms of accuracy.

Contribución a la caracterización espacial de canales con sistemas MIMO-OFDM en la banda de 2,45 Ghz

La tecnología de múltiples antenas ha evolucionado para dar soporte a los actuales y futuros sistemas de comunicaciones inalámbricas en su afán por proporcionar la calidad de señal y las altas tasas de transmisión que demandan los nuevos servicios de voz, datos y multimedia. Sin embargo, es fundamental comprender las características espaciales del canal radio, ya que son las características del propio canal lo que limita en gran medida las prestaciones de los sistemas de comunicación actuales. Por ello surge la necesidad de estudiar la estructura espacial del canal de propagación para poder diseñar, evaluar e implementar de forma más eficiente tecnologías multiantena en los actuales y futuros sistemas de comunicación inalámbrica. Las tecnologías multiantena denominadas antenas inteligentes y MIMO han generado un gran interés en el área de comunicaciones inalámbricas, por ejemplo los sistemas de telefonía celular o más recientemente en las redes WLAN (Wireless Local Area Network), principalmente por la mejora que proporcionan en la calidad de las señales y en la tasa de transmisión de datos, respectivamente. Las ventajas de estas tecnologías se fundamentan en el uso de la dimensión espacial para obtener ganancia por diversidad espacial, como ya sucediera con las tecnologías FDMA (Frequency Division Multiplexing Access), TDMA (Time Division Multiplexing Access) y CDMA (Code Division Multiplexing Access) para obtener diversidad en las dimensiones de frecuencia, tiempo y código, respectivamente. Esta Tesis se centra en estudiar las características espaciales del canal con sistemas de múltiples antenas mediante la estimación de los perfiles de ángulos de llegada (DoA, Direction-of- Arrival) considerando esquemas de diversidad en espacio, polarización y frecuencia. Como primer paso se realiza una revisión de los sistemas con antenas inteligentes y los sistemas MIMO, describiendo con detalle la base matemática que sustenta las prestaciones ofrecidas por estos sistemas. Posteriormente se aportan distintos estudios sobre la estimación de los perfiles de DoA de canales radio con sistemas multiantena evaluando distintos aspectos de antenas, algoritmos de estimación, esquemas de polarización, campo lejano y campo cercano de las fuentes. Así mismo, se presenta un prototipo de medida MIMO-OFDM-SPAA3D en la banda ISM (Industrial, Scientific and Medical) de 2,45 Ghz, el cual está preparado para caracterizar experimentalmente el rendimiento de los sistemas MIMO, y para caracterizar espacialmente canales de propagación, considerando los esquemas de diversidad espacial, por polarización y frecuencia. Los estudios aportados se describen a continuación. Los sistemas de antenas inteligentes dependen en gran medida de la posición de los usuarios. Estos sistemas están equipados con arrays de antenas, los cuales aportan la diversidad espacial necesaria para obtener una representación espacial fidedigna del canal radio a través de los perfiles de DoA (DoA, Direction-of-Arrival) y por tanto, la posición de las fuentes de señal. Sin embargo, los errores de fabricación de arrays así como ciertos parámetros de señal conlleva un efecto negativo en las prestaciones de estos sistemas. Por ello se plantea un modelo de señal parametrizado que permite estudiar la influencia que tienen estos factores sobre los errores de estimación de DoA, tanto en acimut como en elevación, utilizando los algoritmos de estimación de DOA más conocidos en la literatura. A partir de las curvas de error, se pueden obtener parámetros de diseño para sistemas de localización basados en arrays. En un segundo estudio se evalúan esquemas de diversidad por polarización con los sistemas multiantena para mejorar la estimación de los perfiles de DoA en canales que presentan pérdidas por despolarización. Para ello se desarrolla un modelo de señal en array con sensibilidad de polarización que toma en cuenta el campo electromagnético de ondas planas. Se realizan simulaciones MC del modelo para estudiar el efecto de la orientación de la polarización como el número de polarizaciones usadas en el transmisor como en el receptor sobre la precisión en la estimación de los perfiles de DoA observados en el receptor. Además, se presentan los perfiles DoA obtenidos en escenarios quasiestáticos de interior con un prototipo de medida MIMO 4x4 de banda estrecha en la banda de 2,45 GHz, los cuales muestran gran fidelidad con el escenario real. Para la obtención de los perfiles DoA se propone un método basado en arrays virtuales, validado con los datos de simulación y los datos experimentales. Con relación a la localización 3D de fuentes en campo cercano (zona de Fresnel), se presenta un tercer estudio para obtener con gran exactitud la estructura espacial del canal de propagación en entornos de interior controlados (en cámara anecóica) utilizando arrays virtuales. El estudio analiza la influencia del tamaño del array y el diagrama de radiación en la estimación de los parámetros de localización proponiendo, para ello, un modelo de señal basado en un vector de enfoque de onda esférico (SWSV). Al aumentar el número de antenas del array se consigue reducir el error RMS de estimación y mejorar sustancialmente la representación espacial del canal. La estimación de los parámetros de localización se lleva a cabo con un nuevo método de búsqueda multinivel adaptativo, propuesto con el fin de reducir drásticamente el tiempo de procesado que demandan otros algoritmos multivariable basados en subespacios, como el MUSIC, a costa de incrementar los requisitos de memoria. Las simulaciones del modelo arrojan resultados que son validados con resultados experimentales y comparados con el límite de Cramer Rao en términos del error cuadrático medio. La compensación del diagrama de radiación acerca sustancialmente la exactitud de estimación de la distancia al límite de Cramer Rao. Finalmente, es igual de importante la evaluación teórica como experimental de las prestaciones de los sistemas MIMO-OFDM. Por ello, se presenta el diseño e implementación de un prototipo de medida MIMO-OFDM-SPAA3D autocalibrado con sistema de posicionamiento de antena automático en la banda de 2,45 Ghz con capacidad para evaluar la capacidad de los sistemas MIMO. Además, tiene la capacidad de caracterizar espacialmente canales MIMO, incorporando para ello una etapa de autocalibración para medir la respuesta en frecuencia de los transmisores y receptores de RF, y así poder caracterizar la respuesta de fase del canal con mayor precisión. Este sistema incorpora un posicionador de antena automático 3D (SPAA3D) basado en un scanner con 3 brazos mecánicos sobre los que se desplaza un posicionador de antena de forma independiente, controlado desde un PC. Este posicionador permite obtener una gran cantidad de mediciones del canal en regiones locales, lo cual favorece la caracterización estadística de los parámetros del sistema MIMO. Con este prototipo se realizan varias campañas de medida para evaluar el canal MIMO en términos de capacidad comparando 2 esquemas de polarización y tomando en cuenta la diversidad en frecuencia aportada por la modulación OFDM en distintos escenarios. ABSTRACT Multiple-antennas technologies have been evolved to be the support of the actual and future wireless communication systems in its way to provide the high quality and high data rates required by new data, voice and data services. However, it is important to understand the behavior of the spatial characteristics of the radio channel, since the channel by itself limits the performance of the actual wireless communications systems. This drawback raises the need to understand the spatial structure of the propagation channel in order to design, assess, and develop more efficient multiantenna technologies for the actual and future wireless communications systems. Multiantenna technologies such as ‘Smart Antennas’ and MIMO systems have generated great interest in the field of wireless communications, i.e. cellular communications systems and more recently WLAN (Wireless Local Area Networks), mainly because the higher quality and the high data rate they are able to provide. Their technological benefits are based on the exploitation of the spatial diversity provided by the use of multiple antennas as happened in the past with some multiaccess technologies such as FDMA (Frequency Division Multiplexing Access), TDMA (Time Division Multiplexing Access), and CDMA (Code Division Multiplexing Access), which give diversity in the domains of frequency, time and code, respectively. This Thesis is mainly focus to study the spatial channel characteristics using schemes of multiple antennas considering several diversity schemes such as space, polarization, and frequency. The spatial characteristics will be study in terms of the direction-of-arrival profiles viewed at the receiver side of the radio link. The first step is to do a review of the smart antennas and MIMO systems technologies highlighting their advantages and drawbacks from a mathematical point of view. In the second step, a set of studies concerning the spatial characterization of the radio channel through the DoA profiles are addressed. The performance of several DoA estimation methods is assessed considering several aspects regarding antenna array structure, polarization diversity, and far-field and near-field conditions. Most of the results of these studies come from simulations of data models and measurements with real multiantena prototypes. In the same way, having understand the importance of validate the theoretical data models with experimental results, a 2,4 GHz MIMO-OFDM-SPAA2D prototype is presented. This prototype is intended for evaluating MIMO-OFDM capacity in indoor and outdoor scenarios, characterize the spatial structure of radio channels, assess several diversity schemes such as polarization, space, and frequency diversity, among others aspects. The studies reported are briefly described below. As is stated in Chapter two, the determination of user position is a fundamental task to be resolved for the smart antenna systems. As these systems are equipped with antenna arrays, they can provide the enough spatial diversity to accurately draw the spatial characterization of the radio channel through the DoA profiles, and therefore the source location. However, certain real implementation factors related to antenna errors, signals, and receivers will certainly reduce the performance of such direction finding systems. In that sense, a parameterized narrowband signal model is proposed to evaluate the influence of these factors in the location parameter estimation through extensive MC simulations. The results obtained from several DoA algorithms may be useful to extract some parameter design for directing finding systems based on arrays. The second study goes through the importance that polarization schemes can have for estimating far-field DoA profiles in radio channels, particularly for scenarios that may introduce polarization losses. For this purpose, a narrowband signal model with polarization sensibility is developed to conduct an analysis of several polarization schemes at transmitter (TX) and receiver (RX) through extensive MC simulations. In addition, spatial characterization of quasistatic indoor scenarios is also carried out using a 2.45 GHz MIMO prototype equipped with single and dual-polarized antennas. A good agreement between the measured DoA profiles with the propagation scenario is achieved. The theoretical and experimental evaluation of polarization schemes is performed using virtual arrays. In that case, a DoA estimation method is proposed based on adding an phase reference to properly track the DoA, which shows good results. In the third study, the special case of near-field source localization with virtual arrays is addressed. Most of DoA estimation algorithms are focused in far-field source localization where the radiated wavefronts are assume to be planar waves at the receive array. However, when source are located close to the array, the assumption of plane waves is no longer valid as the wavefronts exhibit a spherical behavior along the array. Thus, a faster and effective method of azimuth, elevation angles-of-arrival, and range estimation for near-field sources is proposed. The efficacy of the proposed method is evaluated with simulation and validated with measurements collected from a measurement campaign carried out in a controlled propagation environment, i.e. anechoic chamber. Moreover, the performance of the method is assessed in terms of the RMSE for several array sizes, several source positions, and taking into account the effect of radiation pattern. In general, better results are obtained with larger array and larger source distances. The effect of the antennas is included in the data model leading to more accurate results, particularly for range rather than for angle estimation. Moreover, a new multivariable searching method based on the MUSIC algorithm, called MUSA (multilevel MUSIC-based algorithm), is presented. This method is proposed to estimate the 3D location parameters in a faster way than other multivariable algorithms, such as MUSIC algorithm, at the cost of increasing the memory size. Finally, in the last chapter, a MIMO-OFDM-SPAA3D prototype is presented to experimentally evaluate different MIMO schemes regarding antennas, polarization, and frequency in different indoor and outdoor scenarios. The prototype has been developed on a Software-Defined Radio (SDR) platform. It allows taking measurements where future wireless systems will be developed. The novelty of this prototype is concerning the following 2 subsystems. The first one is the tridimensional (3D) antenna positioning system (SPAA3D) based on three linear scanners which is developed for making automatic testing possible reducing errors of the antenna array positioning. A set of software has been developed for research works such as MIMO channel characterization, MIMO capacity, OFDM synchronization, and so on. The second subsystem is the RF autocalibration module at the TX and RX. This subsystem allows to properly tracking the spatial structure of indoor and outdoor channels in terms of DoA profiles. Some results are draw regarding performance of MIMO-OFDM systems with different polarization schemes and different propagation environments.

Image Segmentation Using Ant System-based Clustering Algorithm

Industrial applications of computer vision sometimes require detection of atypical objects that occur as small groups of pixels in digital images. These objects are difficult to single out because they are small and randomly distributed. In this work we propose an image segmentation method using the novel Ant System-based Clustering Algorithm (ASCA). ASCA models the foraging behaviour of ants, which move through the data space searching for high data-density regions, and leave pheromone trails on their path. The pheromone map is used to identify the exact number of clusters, and assign the pixels to these clusters using the pheromone gradient. We applied ASCA to detection of microcalcifications in digital mammograms and compared its performance with state-of-the-art clustering algorithms such as 1D Self-Organizing Map, k-Means, Fuzzy c-Means and Possibilistic Fuzzy c-Means. The main advantage of ASCA is that the number of clusters needs not to be known a priori. The experimental results show that ASCA is more efficient than the other algorithms in detecting small clusters of atypical data.

Self-organizing Routing Algorithm fo Wireless Sensors Networks (WSN) using Ant Colony Optimization (ACO) with Tinyos.

This paper describes the basic tools to work with wireless sensors. TinyOShas a componentbased architecture which enables rapid innovation and implementation while minimizing code size as required by the severe memory constraints inherent in sensor networks. TinyOS's component library includes network protocols, distributed services, sensor drivers, and data acquisition tools ? all of which can be used asia or be further refined for a custom application. TinyOS was originally developed as a research project at the University of California Berkeley, but has since grown to have an international community of developers and users. Some algorithms concerning packet routing are shown. Incar entertainment systems can be based on wireless sensors in order to obtain information from Internet, but routing protocols must be implemented in order to avoid bottleneck problems. Ant Colony algorithms are really useful in such cases, therefore they can be embedded into the sensors to perform such routing task.

Improved Animal Tracking Algorithm using Distributed Kalman Filter-based Algortihms

Animal tracking has been addressed by different initiatives over the last two decades. Most of them rely on satellite connectivity on every single node and lack of energy-saving strategies. This paper presents several new contributions on the tracking of dynamic heterogeneous asynchronous networks (primary nodes with GPS and secondary nodes with a kinetic generator) motivated by the animal tracking paradigm with random transmissions. A simple approach based on connectivity and coverage intersection is compared with more sophisticated algorithms based on ad-hoc implementations of distributed Kalman-based filters that integrate measurement information using Consensus principles in order to provide enhanced accuracy. Several simulations varying the coverage range, the random behavior of the kinetic generator (modeled as a Poisson Process) and the periodic activation of GPS are included. In addition, this study is enhanced with HW developments and implementations on commercial off-the-shelf equipment which show the feasibility for performing these proposals on real hardware.

An image segmentation based on a genetic algorithm for determining soil coverage by crop residues

Determination of the soil coverage by crop residues after ploughing is a fundamental element of Conservation Agriculture. This paper presents the application of genetic algorithms employed during the fine tuning of the segmentation process of a digital image with the aim of automatically quantifying the residue coverage. In other words, the objective is to achieve a segmentation that would permit the discrimination of the texture of the residue so that the output of the segmentation process is a binary image in which residue zones are isolated from the rest. The RGB images used come from a sample of images in which sections of terrain were photographed with a conventional camera positioned in zenith orientation atop a tripod. The images were taken outdoors under uncontrolled lighting conditions. Up to 92% similarity was achieved between the images obtained by the segmentation process proposed in this paper and the templates made by an elaborate manual tracing process. In addition to the proposed segmentation procedure and the fine tuning procedure that was developed, a global quantification of the soil coverage by residues for the sampled area was achieved that differed by only 0.85% from the quantification obtained using template images. Moreover, the proposed method does not depend on the type of residue present in the image. The study was conducted at the experimental farm “El Encín” in Alcalá de Henares (Madrid, Spain).

Multi-objective Estimation of Distribution Algorithm Based on Joint Modeling of Objectives and Variables

This paper proposes a new multi-objective estimation of distribution algorithm (EDA) based on joint modeling of objectives and variables. This EDA uses the multi-dimensional Bayesian network as its probabilistic model. In this way it can capture the dependencies between objectives, variables and objectives, as well as the dependencies learnt between variables in other Bayesian network-based EDAs. This model leads to a problem decomposition that helps the proposed algorithm to find better trade-off solutions to the multi-objective problem. In addition to Pareto set approximation, the algorithm is also able to estimate the structure of the multi-objective problem. To apply the algorithm to many-objective problems, the algorithm includes four different ranking methods proposed in the literature for this purpose. The algorithm is applied to the set of walking fish group (WFG) problems, and its optimization performance is compared with an evolutionary algorithm and another multi-objective EDA. The experimental results show that the proposed algorithm performs significantly better on many of the problems and for different objective space dimensions, and achieves comparable results on some compared with the other algorithms.