Video analysis based vehicle detection and tracking using an MCMC sampling framework

This article presents a probabilistic method for vehicle detection and tracking through the analysis of monocular images obtained from a vehicle-mounted camera. The method is designed to address the main shortcomings of traditional particle filtering approaches, namely Bayesian methods based on importance sampling, for use in traffic environments. These methods do not scale well when the dimensionality of the feature space grows, which creates significant limitations when tracking multiple objects. Alternatively, the proposed method is based on a Markov chain Monte Carlo (MCMC) approach, which allows efficient sampling of the feature space. The method involves important contributions in both the motion and the observation models of the tracker. Indeed, as opposed to particle filter-based tracking methods in the literature, which typically resort to observation models based on appearance or template matching, in this study a likelihood model that combines appearance analysis with information from motion parallax is introduced. Regarding the motion model, a new interaction treatment is defined based on Markov random fields (MRF) that allows for the handling of possible inter-dependencies in vehicle trajectories. As for vehicle detection, the method relies on a supervised classification stage using support vector machines (SVM). The contribution in this field is twofold. First, a new descriptor based on the analysis of gradient orientations in concentric rectangles is dened. This descriptor involves a much smaller feature space compared to traditional descriptors, which are too costly for real-time applications. Second, a new vehicle image database is generated to train the SVM and made public. The proposed vehicle detection and tracking method is proven to outperform existing methods and to successfully handle challenging situations in the test sequences.

Learning an L1-regularized Gaussian Bayesian Network in the Equivalence Class Space

Learning the structure of a graphical model from data is a common task in a wide range of practical applications. In this paper, we focus on Gaussian Bayesian networks, i.e., on continuous data and directed acyclic graphs with a joint probability density of all variables given by a Gaussian. We propose to work in an equivalence class search space, specifically using the k-greedy equivalence search algorithm. This, combined with regularization techniques to guide the structure search, can learn sparse networks close to the one that generated the data. We provide results on some synthetic networks and on modeling the gene network of the two biological pathways regulating the biosynthesis of isoprenoids for the Arabidopsis thaliana plant

A combined measure for quantifying and qualifying the topology preservation of growing self-organizing maps

The Self-OrganizingMap (SOM) is a neural network model that performs an ordered projection of a high dimensional input space in a low-dimensional topological structure. The process in which such mapping is formed is defined by the SOM algorithm, which is a competitive, unsupervised and nonparametric method, since it does not make any assumption about the input data distribution. The feature maps provided by this algorithm have been successfully applied for vector quantization, clustering and high dimensional data visualization processes. However, the initialization of the network topology and the selection of the SOM training parameters are two difficult tasks caused by the unknown distribution of the input signals. A misconfiguration of these parameters can generate a feature map of low-quality, so it is necessary to have some measure of the degree of adaptation of the SOM network to the input data model. The topologypreservation is the most common concept used to implement this measure. Several qualitative and quantitative methods have been proposed for measuring the degree of SOM topologypreservation, particularly using Kohonen's model. In this work, two methods for measuring the topologypreservation of the Growing Cell Structures (GCSs) model are proposed: the topographic function and the topology preserving map

Forecasting Electricity Prices and their volatilities using Unobserved Components.

The liberalization of electricity markets more than ten years ago in the vast majority of developed countries has introduced the need of modelling and forecasting electricity prices and volatilities, both in the short and long term. Thus, there is a need of providing methodology that is able to deal with the most important features of electricity price series, which are well known for presenting not only structure in conditional mean but also time-varying conditional variances. In this work we propose a new model, which allows to extract conditionally heteroskedastic common factors from the vector of electricity prices. These common factors are jointly estimated as well as their relationship with the original vector of series, and the dynamics affecting both their conditional mean and variance. The estimation of the model is carried out under the state-space formulation. The new model proposed is applied to extract seasonal common dynamic factors as well as common volatility factors for electricity prices and the estimation results are used to forecast electricity prices and their volatilities in the Spanish zone of the Iberian Market. Several simplified/alternative models are also considered as benchmarks to illustrate that the proposed approach is superior to all of them in terms of explanatory and predictive power.

A Model of Emotion as Patterned Metacontrol

Adaptive systems use feedback as a key strategy to cope with uncertainty and change in their environments. The information fed back from the sensorimotor loop into the control architecture can be used to change different elements of the controller at four different levels: parameters of the control model, the control model itself, the functional organization of the agent and the functional components of the agent. The complexity of such a space of potential configurations is daunting. The only viable alternative for the agent ?in practical, economical, evolutionary terms? is the reduction of the dimensionality of the configuration space. This reduction is achieved both by functionalisation —or, to be more precise, by interface minimization— and by patterning, i.e. the selection among a predefined set of organisational configurations. This last analysis let us state the central problem of how autonomy emerges from the integration of the cognitive, emotional and autonomic systems in strict functional terms: autonomy is achieved by the closure of functional dependency. In this paper we will show a general model of how the emotional biological systems operate following this theoretical analysis and how this model is also of applicability to a wide spectrum of artificial systems.

On the monitoring of surface displacement in connection with volcano reactivation in Tenerife, Canary Islands, using space techniques

Geodetic volcano monitoring in Tenerife has mainly focused on the Las Cañadas Caldera, where a geodetic micronetwork and a levelling profile are located. A sensitivity test of this geodetic network showed that it should be extended to cover the whole island for volcano monitoring purposes. Furthermore, InSAR allowed detecting two unexpected movements that were beyond the scope of the traditional geodetic network. These two facts prompted us to design and observe a GPS network covering the whole of Tenerife that was monitored in August 2000. The results obtained were accurate to one centimetre, and confirm one of the deformations, although they were not definitive enough to confirm the second one. Furthermore, new cases of possible subsidence have been detected in areas where InSAR could not be used to measure deformation due to low coherence. A first modelling attempt has been made using a very simple model and its results seem to indicate that the deformation observed and the groundwater level variation in the island may be related. Future observations will be necessary for further validation and to study the time evolution of the displacements, carry out interpretation work using different types of data (gravity, gases, etc) and develop models that represent the island more closely. The results obtained are important because they might affect the geodetic volcano monitoring on the island, which will only be really useful if it is capable of distinguishing between displacements that might be linked to volcanic activity and those produced by other causes. One important result in this work is that a new geodetic monitoring system based on two complementary techniques, InSAR and GPS, has been set up on Tenerife island. This the first time that the whole surface of any of the volcanic Canary Islands has been covered with a single network for this purpose. This research has displayed the need for further similar studies in the Canary Islands, at least on the islands which pose a greater risk of volcanic reactivation, such as Lanzarote and La Palma, where InSAR techniques have been used already.

A Model of Emotion as Patterned Metacontrol

Adaptive agents use feedback as a key strategy to cope with un- certainty and change in their environments. The information fed back from the sensorimotor loop into the control subsystem can be used to change four different elements of the controller: parameters associated to the control model, the control model itself, the functional organization of the agent and the functional realization of the agent. There are many change alternatives and hence the complexity of the agent’s space of potential configurations is daunting. The only viable alternative for space- and time-constrained agents —in practical, economical, evolutionary terms— is to achieve a reduction of the dimensionality of this configuration space. Emotions play a critical role in this reduction. The reduction is achieved by func- tionalization, interface minimization and by patterning, i.e. by selection among a predefined set of organizational configurations. This analysis lets us state how autonomy emerges from the integration of cognitive, emotional and autonomic systems in strict functional terms: autonomy is achieved by the closure of functional dependency. Emotion-based morphofunctional systems are able to exhibit complex adaptation patterns at a reduced cognitive cost. In this article we show a general model of how emotion supports functional adaptation and how the emotional biological systems operate following this theoretical model. We will also show how this model is also of applicability to the construction of a wide spectrum of artificial systems1.

Estructura de una red esencial de señalización que regula la homeostasis iónica en plantas

Las plantas son organismos sésiles que han desarrollado la capacidad para detectar variaciones sutiles en su ambiente y producir respuestas adaptativas mediante rutas de señalización. Los estímulos causados por el estrés biótico y abiótico son numerosos y dependiendo del tiempo de exposición y su intensidad, pueden reducir la tasa de crecimiento de las plantas y la producción. Los cambios en la concentración del calcio citosólico libre constituyen una de las primeras reacciones intracelulares a las situaciones de estrés abiótico. En esta situación, el calcio actúa como segundo mensajero y las variaciones en su concentración son descodificadas por proteínas de unión a calcio. Las más conocidas son las manos-EF y los dominios C2. Los dominios C2 han sido descritos como dominios de unión a lípidos dependientes de calcio. Estos dominios se consideran proteínas periféricas solubles en agua que se asocian de manera reversible a los lípidos de la membrana mediante una o dos regiones funcionales: el sitio de unión a calcio y el sitio polibásico. A pesar de que se conoce la estructura molecular de algunos dominios C2, se desconocen aspectos relacionados como las reglas que dirigen su forma de interaccionar con los diferentes fosfolípidos y proteínas, la posición que ocupan en la bicapa lipídica y su papel en la transmisión de señales. En esta tesis se ha estudiado una proteína de Arabidopsis thaliana (At3g17980) representativa de una nueva familia de proteínas con dominios C2, que consiste únicamente de un dominio C2. Esta proteína, llamada AtC2.1, ha sido clonada en el vector pETM11, expresada en E. coli y purificada a homogeneidad en dos pasos cromatográficos. Se obtuvieron cristales de AtC2.1 de buena calidad mediante técnicas de difusión de vapor. La proteína fue co-cristalizada con calcio, fosfocolina (POC) y el fosfolípido 1,2-dihexanoil-sn-glicero-3-fosfo-L-serina (PSF). Se recogieron ocho conjuntos de datos de difracción de rayos X empleando radiación sincrotrón. Los cristales difractaron hasta 1.6 Å de resolución. Siete de ellos pertenecían al grupo ortorrómbico P212121, con las dimensiones de la celdilla unidad a = 35.3, b = 88.9, c = 110.6 Å, y un cristal pertenecía al grupo espacial monoclínico C2, con a = 124.84, b = 35.27, c = 92.32 Å y = 121.70º. La estructura se resolvió mediante la técnica MR-SAD utilizando el cinc como dispersor anómalo. La estructura cristalina mostró que la molécula forma un dímero en el que cada protómero se pliega como un dominio C2 típico, con la topología tipo II y presenta una inserción de 43 aminoácidos que la diferencia de los dominios C2 conocidos. El mapa de densidad electrónica mostró dos átomos de calcio por protómero. Se resolvieron las estructuras de AtC2.1 en complejo con POC o PSF. En ambos complejos, el análisis cristalográfico detectó máximos de densidad electrónica en la región correspondiente al sitio polibásico formado por las hebras 2, 3 5 y el lazo 3. Éstos se interpretaron correctamente como dos moléculas de POC y un átomo de cinc, en un complejo, y como la cabeza polar del PSF en el otro. AtC2.1 define un sitio de interacción con lípidos dependiente de cinc. En conclusión, en este trabajo se presenta la estructura tridimensional de AtC2.1, miembro representativo de una familia de proteínas de Arabidopsis thaliana, identificadas como proteínas que interaccionan con los receptores de ABA. Estas proteínas están constituidas únicamente por un dominio C2. El análisis conjunto de los datos biofísicos y cristalográficos muestra que AtC2.1 es un sensor de calcio que une lípidos usando dos sitios funcionales. Estos datos sugieren un mecanismo de inserción en membrana dependiente de calcio que trae consigo la disociación de la estructura dimérica y, por consiguiente, un cambio en las propiedades de superficie de la molécula. Este mecanismo proporciona las bases del reconocimiento y transporte de los receptores de ABA y/o otras moléculas a la membrana celular. Plants are sessile organisms that have developed the capacity to detect slight variations of their environment. They are able to perceive biotic and abiotic stress signals and to transduce them by signaling pathways in order to trigger adaptative responses. Stress factors are numerous and, depending on their exposition time and their concentration, can reduce plant growth rate, limiting the productivity of crop plants. Changes in the cytosolic free calcium concentration are observed as one of the earliest intracellular reactions to abiotic stress signals. Calcium plays a key role as a second messenger, and calcium concentration signatures, called calcium signals, are decodified by calcium binding proteins. The main calcium binding structures are the EF-hand motif and the C2 domains. C2 domain is a calcium dependent lipid-binding domain of approximately 130 amino acids. C2 domain displays two functional regions: the Ca-binding region and the polybasic cluster. Both of them can interact with the membrane phospholipids. Despite the number of C2 domain 3D structures currently available, questions about how they interact with the different target phospholipids, their precise spatial position in the lipid bilayer, interactions with other proteins and their role in transmitting signals downstream, have not yet been explored. In this work we have studied an uncharacterized protein from Arabidopsis thaliana (At3g17980) consisting of only a single C2 domain, as member of a new protein C2-domain family. This protein called AtC2.1 was cloned into the pETM11 vector and expressed in E. coli, allowing the purification to homogeneity in two chromatographic steps. Good quality diffracting crystals were obtained using vapor-diffusion techniques. Crystals were co-crystalized with calcium; phosphocholine (POC) and/or the phospholipid 1,2-dihexanoyl-sn-glycero-3-phospho-L-serine (PSF). Eight data set were collected with synchrotron radiation. Crystals diffracted up to 1.6 Å resolution and seven of them belong to the orthorhombic space group P212121, with unit-cell parameters a = 35.3, b = 88.9, c = 110.6 Å. Another crystal was monoclinic, space group C2, with a = 124.84, b = 35.27, c = 92.32 Å and = 121.70º. The structural model was solved by MR-SAD using Zn2+ as anomalous scatterer. The crystal structure shows that the molecule is a dimer. Each monomer was folded as a canonical C2 domain with the topology II with a 43 residues insertion. The electron density map reveals two calcium ions per molecule. Structures of AtC2.1, complexed with POC and PSF, have been solved. Well-defined extra electron densities were found, in both complexes, within the concave surface formed by strands 2, 3, 5 and loop 3 of AtC2.1. These densities were clearly explained by the presence of the two POC molecules, one zinc atom and head groups of PSF, occupying the cavity of the polybasic site. AtC2.1 defines a new metal dependent lipid-binding site into the polybasic site. In conclusion, in this thesis it is presented the molecular structure of AtC2.1, a representative member of a family of Arabidopsis thaliana C2 domain proteins, of unknown function, but identified as a molecular interacting unit of the ABA receptors. The joint analyses of the biophysical and crystallographic data show that AtC2.1 is a calcium sensor that binds lipids in two sites and suggest a model of calcium-dependent membrane insertion mechanism that will involve either dimer dissociation or a strong rearrangement of the dimeric structure. This mechanism may be the basis for the recognition and delivery of ABA receptors or other protein molecules to cell membranes.

An abstract machine based execution model for computer architecture design and efficient implementation of logic programs in parallel.

The term "Logic Programming" refers to a variety of computer languages and execution models which are based on the traditional concept of Symbolic Logic. The expressive power of these languages offers promise to be of great assistance in facing the programming challenges of present and future symbolic processing applications in Artificial Intelligence, Knowledge-based systems, and many other areas of computing. The sequential execution speed of logic programs has been greatly improved since the advent of the first interpreters. However, higher inference speeds are still required in order to meet the demands of applications such as those contemplated for next generation computer systems. The execution of logic programs in parallel is currently considered a promising strategy for attaining such inference speeds. Logic Programming in turn appears as a suitable programming paradigm for parallel architectures because of the many opportunities for parallel execution present in the implementation of logic programs. This dissertation presents an efficient parallel execution model for logic programs. The model is described from the source language level down to an "Abstract Machine" level suitable for direct implementation on existing parallel systems or for the design of special purpose parallel architectures. Few assumptions are made at the source language level and therefore the techniques developed and the general Abstract Machine design are applicable to a variety of logic (and also functional) languages. These techniques offer efficient solutions to several areas of parallel Logic Programming implementation previously considered problematic or a source of considerable overhead, such as the detection and handling of variable binding conflicts in AND-Parallelism, the specification of control and management of the execution tree, the treatment of distributed backtracking, and goal scheduling and memory management issues, etc. A parallel Abstract Machine design is offered, specifying data areas, operation, and a suitable instruction set. This design is based on extending to a parallel environment the techniques introduced by the Warren Abstract Machine, which have already made very fast and space efficient sequential systems a reality. Therefore, the model herein presented is capable of retaining sequential execution speed similar to that of high performance sequential systems, while extracting additional gains in speed by efficiently implementing parallel execution. These claims are supported by simulations of the Abstract Machine on sample programs.

Aircraft trajectory simulator using a three degrees of freedom aircraft point mass model

Aircraft Operators Companies (AOCs) are always willing to keep the cost of a flight as low as possible. These costs could be modelled using a function of the fuel consumption, time of flight and fixed cost (over flight cost, maintenance, etc.). These are strongly dependant on the atmospheric conditions, the presence of winds and the aircraft performance. For this reason, much research effort is being put in the development of numerical and graphical techniques for defining the optimal trajectory. This paper presents a different approach to accommodate AOCs preferences, adding value to their activities, through the development of a tool, called aircraft trajectory simulator. This tool is able to simulate the actual flight of an aircraft with the constraints imposed. The simulator is based on a point mass model of the aircraft. The aim of this paper is to evaluate 3DoF aircraft model errors with BADA data through real data from Flight Data Recorder FDR. Therefore, to validate the proposed simulation tool a comparative analysis of the state variables vector is made between an actual flight and the same flight using the simulator. Finally, an example of a cruise phase is presented, where a conventional levelled flight is compared with a continuous climb flight. The comparison results show the potential benefits of following user-preferred routes for commercial flights.

Model-Driven Methodology for Rapid Deployment of Smart Spaces based on Resource-Oriented Architectures

Advances in electronics nowadays facilitate the design of smart spaces based on physical mash-ups of sensor and actuator devices. At the same time, software paradigms such as Internet of Things (IoT) and Web of Things (WoT) are motivating the creation of technology to support the development and deployment of web-enabled embedded sensor and actuator devices with two major objectives: (i) to integrate sensing and actuating functionalities into everyday objects, and (ii) to easily allow a diversity of devices to plug into the Internet. Currently, developers who are applying this Internet-oriented approach need to have solid understanding about specific platforms and web technologies. In order to alleviate this development process, this research proposes a Resource-Oriented and Ontology-Driven Development (ROOD) methodology based on the Model Driven Architecture (MDA). This methodology aims at enabling the development of smart spaces through a set of modeling tools and semantic technologies that support the definition of the smart space and the automatic generation of code at hardware level. ROOD feasibility is demonstrated by building an adaptive health monitoring service for a Smart Gym.

Novel Gravity Distortion Evaluation on Large Antenna Array for Deep Space Communication

This paper presents a simple gravity evaluation model for large reflector antennas and the experimental example for a case study of one uplink array of 4x35-m antennas at X and Ka band. This model can be used to evaluate the gain reduction as a function of the maximum gravity distortion, and also to specify this at system designer level. The case study consists of one array of 35-m antennas for deep space missions. Main issues due to the gravity effect have been explored with Monte Carlo based simulation analysis.

Including hardware/software co-design in the ASSERT model driven engineering process.

Abstract. The ASSERT project de?ned new software engineering methods and tools for the development of critical embedded real-time systems in the space domain. The ASSERT model-driven engineering process was one of the achievements of the project and is based on the concept of property- preserving model transformations. The key element of this process is that non-functional properties of the software system must be preserved during model transformations. Properties preservation is carried out through model transformations compliant with the Ravenscar Pro?le and provides a formal basis to the process. In this way, the so-called Ravenscar Computational Model is central to the whole ASSERT process. This paper describes the work done in the HWSWCO study, whose main objective has been to address the integration of the Hardware/Software co-design phase in the ASSERT process. In order to do that, non-functional properties of the software system must also be preserved during hardware synthesis. Keywords : Ada 2005, Ravenscar pro?le, Hardware/Software co-design, real- time systems, high-integrity systems, ORK

Time and space partition platform for safe and secure flight software.

There are a number of research and development activities that are exploring Time and Space Partition (TSP) to implement safe and secure flight software. This approach allows to execute different real-time applications with different levels of criticality in the same computer board. In order to do that, flight applications must be isolated from each other in the temporal and spatial domains. This paper presents the first results of a partitioning platform based on the Open Ravenscar Kernel (ORK+) and the XtratuM hypervisor. ORK+ is a small, reliable real-time kernel supporting the Ada Ravenscar Computational model that is central to the ASSERT development process. XtratuM supports multiple virtual machines, i.e. partitions, on a single computer and is being used in the Integrated Modular Avionics for Space study. ORK+ executes in an XtratuM partition enabling Ada applications to share the computer board with other applications.

Damping models in the truncated derivative nonlinear Schrödinger equation

Four-dimensional flow in the phase space of three amplitudes of circularly polarized Alfven waves and one relative phase, resulting from a resonant three-wave truncation of the derivative nonlinear Schrödinger equation, has been analyzed; wave 1 is linearly unstable with growth rate , and waves 2 and 3 are stable with damping 2 and 3, respectively. The dependence of gross dynamical features on the damping model as characterized by the relation between damping and wave-vector ratios, 2 /3, k2 /k3, and the polarization of the waves, is discussed; two damping models, Landau k and resistive k2, are studied in depth. Very complex dynamics, such as multiple blue sky catastrophes and chaotic attractors arising from Feigenbaum sequences, and explosive bifurcations involving Intermittency-I chaos, are shown to be associated with the existence and loss of stability of certain fixed point P of the flow. Independently of the damping model, P may only exist as against flow contraction just requiring.In the case of right-hand RH polarization, point P may exist for all models other than Landau damping; for the resistive model, P may exist for RH polarization only if 2+3/2.