Participation in farmer's cooperatives and its effects on agricultural incomes : evidence from vegetable-producing areas in China

Chinese agricultural cooperatives, called Farmer's Professional Cooperatives (FPCs), are expected to become a major tool to facilitate agro-industrialization for small farmers through the diffusion of new technologies, the supply of high-quality agricultural inputs and the marketing of their products. This study compares FPC participants with vegetable-producing non-participants and grain farmers in vegetable-producing areas in rural China to investigate the treatment effect of participation in FPCs as well as implementation of vegetable cultivation. I adopt parametric and nonparametric approaches to precisely estimate the treatment effects. Estimated results indicate no significant difference between participants and non-participants of FPCs on agricultural net income in both parametric and non-parametric estimations. In contrast, the comparison between vegetable and grain farmers using propensity score matching (PSM) reveals that the treatment effect of vegetable cultivation is significantly positive for total and agricultural incomes, although vegetable cultivation involves more labor-intensive efforts. These results indicate that it is the implementation of vegetable cultivation rather than the participation in an FPC that enhances the economic welfare of farmers, due to the non-excludability of FPCs' services as well as the risks involved in vegetable cultivation.

Estimadores bayesianos de la fiabilidad con muestreo censurado

El estudio de la fiabilidad de componentes y sistemas tiene gran importancia en diversos campos de la ingenieria, y muy concretamente en el de la informatica. Al analizar la duracion de los elementos de la muestra hay que tener en cuenta los elementos que no fallan en el tiempo que dure el experimento, o bien los que fallen por causas distintas a la que es objeto de estudio. Por ello surgen nuevos tipos de muestreo que contemplan estos casos. El mas general de ellos, el muestreo censurado, es el que consideramos en nuestro trabajo. En este muestreo tanto el tiempo hasta que falla el componente como el tiempo de censura son variables aleatorias. Con la hipotesis de que ambos tiempos se distribuyen exponencialmente, el profesor Hurt estudio el comportamiento asintotico del estimador de maxima verosimilitud de la funcion de fiabilidad. En principio parece interesante utilizar metodos Bayesianos en el estudio de la fiabilidad porque incorporan al analisis la informacion a priori de la que se dispone normalmente en problemas reales. Por ello hemos considerado dos estimadores Bayesianos de la fiabilidad de una distribucion exponencial que son la media y la moda de la distribucion a posteriori. Hemos calculado la expansion asint6tica de la media, varianza y error cuadratico medio de ambos estimadores cuando la distribuci6n de censura es exponencial. Hemos obtenido tambien la distribucion asintotica de los estimadores para el caso m3s general de que la distribucion de censura sea de Weibull. Dos tipos de intervalos de confianza para muestras grandes se han propuesto para cada estimador. Los resultados se han comparado con los del estimador de maxima verosimilitud, y con los de dos estimadores no parametricos: limite producto y Bayesiano, resultando un comportamiento superior por parte de uno de nuestros estimadores. Finalmente nemos comprobado mediante simulacion que nuestros estimadores son robustos frente a la supuesta distribuci6n de censura, y que uno de los intervalos de confianza propuestos es valido con muestras pequenas. Este estudio ha servido tambien para confirmar el mejor comportamiento de uno de nuestros estimadores. SETTING OUT AND SUMMARY OF THE THESIS When we study the lifetime of components it's necessary to take into account the elements that don't fail during the experiment, or those that fail by reasons which are desirable to exclude from consideration. The model of random censorship is very usefull for analysing these data. In this model the time to failure and the time censor are random variables. We obtain two Bayes estimators of the reliability function of an exponential distribution based on randomly censored data. We have calculated the asymptotic expansion of the mean, variance and mean square error of both estimators, when the censor's distribution is exponential. We have obtained also the asymptotic distribution of the estimators for the more general case of censor's Weibull distribution. Two large-sample confidence bands have been proposed for each estimator. The results have been compared with those of the maximum likelihood estimator, and with those of two non parametric estimators: Product-limit and Bayesian. One of our estimators has the best behaviour. Finally we have shown by simulation, that our estimators are robust against the assumed censor's distribution, and that one of our intervals does well in small sample situation.

Segmentación de Secuencias de Vídeo: análisis y desarrollo de estrategias para la detección de cambios de toma y para la detección de objetos móviles

The important technological advances experienced along the last years have resulted in an important demand for new and efficient computer vision applications. On the one hand, the increasing use of video editing software has given rise to a necessity for faster and more efficient editing tools that, in a first step, perform a temporal segmentation in shots. On the other hand, the number of electronic devices with integrated cameras has grown enormously. These devices require new, fast, and efficient computer vision applications that include moving object detection strategies. In this dissertation, we propose a temporal segmentation strategy and several moving object detection strategies, which are suitable for the last generation of computer vision applications requiring both low computational cost and high quality results. First, a novel real-time high-quality shot detection strategy is proposed. While abrupt transitions are detected through a very fast pixel-based analysis, gradual transitions are obtained from an efficient edge-based analysis. Both analyses are reinforced with a motion analysis that allows to detect and discard false detections. This analysis is carried out exclusively over a reduced amount of candidate transitions, thus maintaining the computational requirements. On the other hand, a moving object detection strategy, which is based on the popular Mixture of Gaussians method, is proposed. This strategy, taking into account the recent history of each image pixel, adapts dynamically the amount of Gaussians that are required to model its variations. As a result, we improve significantly the computational efficiency with respect to other similar methods and, additionally, we reduce the influence of the used parameters in the results. Alternatively, in order to improve the quality of the results in complex scenarios containing dynamic backgrounds, we propose different non-parametric based moving object detection strategies that model both background and foreground. To obtain high quality results regardless of the characteristics of the analyzed sequence we dynamically estimate the most adequate bandwidth matrices for the kernels that are used in the background and foreground modeling. Moreover, the application of a particle filter allows to update the spatial information and provides a priori knowledge about the areas to analyze in the following images, enabling an important reduction in the computational requirements and improving the segmentation results. Additionally, we propose the use of an innovative combination of chromaticity and gradients that allows to reduce the influence of shadows and reflects in the detections.

Comparative analysis of meta-analysis methods: when to use which?

Background: Several meta-analysis methods can be used to quantitatively combine the results of a group of experiments, including the weighted mean difference, statistical vote counting, the parametric response ratio and the non-parametric response ratio. The software engineering community has focused on the weighted mean difference method. However, other meta-analysis methods have distinct strengths, such as being able to be used when variances are not reported. There are as yet no guidelines to indicate which method is best for use in each case. Aim: Compile a set of rules that SE researchers can use to ascertain which aggregation method is best for use in the synthesis phase of a systematic review. Method: Monte Carlo simulation varying the number of experiments in the meta analyses, the number of subjects that they include, their variance and effect size. We empirically calculated the reliability and statistical power in each case Results: WMD is generally reliable if the variance is low, whereas its power depends on the effect size and number of subjects per meta-analysis; the reliability of RR is generally unaffected by changes in variance, but it does require more subjects than WMD to be powerful; NPRR is the most reliable method, but it is not very powerful; SVC behaves well when the effect size is moderate, but is less reliable with other effect sizes. Detailed tables of results are annexed. Conclusions: Before undertaking statistical aggregation in software engineering, it is worthwhile checking whether there is any appreciable difference in the reliability and power of the methods. If there is, software engineers should select the method that optimizes both parameters.

Moving Object Detection for Real-Time High-Quality Lightweight Applications on Smart Cameras

Here, a novel and efficient strategy for moving object detection by non-parametric modeling on smart cameras is presented. Whereas the background is modeled using only color information, the foreground model combines color and spatial information. The application of a particle filter allows the update of the spatial information and provides a priori information about the areas to analyze in the following images, enabling an important reduction in the computational requirements and improving the segmentation results

De la ciudad en vibración al ser resonante: Una investigación a propósito de los conciertos de campanas de Llorenç Barber

Este trabajo tiene la vocación de dibujar el mapa de los dominios de oportunidad que hay a disposición de un arquitecto, al imaginar el aspecto sonoro de la ciudad en relación con la campana. Muchas de las dimensiones señaladas, tanto conocidas como desconocidas, son sencillamente despertadas al estudio de lo que un diseñador del espacio sonoro, como Llorenç Barber, viene a decirnos, desde una disciplina aparentemente contactada, pero muchas veces paralela a la arquitectónica. Tomando los conciertos de campanas celebrados hasta la fecha como puestas en práctica real de la condición instrumental de más de doscientas ciudades de todo el mundo, el estudio analiza los hallazgos, éxitos y fracasos, obtenidos a lo largo de estos últimos veinticinco años de experiencia, como resultados explícitos de un trabajo sonoro en la ciudad, probado, contrastado y afinado, del que extraer indicaciones concretas susceptibles de ser aplicadas en el diseño del espacio urbano. Mediante un análisis triangular de vértices definidos: emisor-campana, medio-ciudad, receptor-ciudadano; la investigación aborda los aspectos relativos a la producción y recepción del fenómeno sonoro generado por la campana en la ciudad. En relación con la producción, una parte del trabajo se dedica al estudio de los efectos acústicos observados, ordenado por escalas graduales en las que se produce una distribución del sonido susceptible de diseño: el vaso de la campana, la sala de campanas, el campanario, el cuerpo del edificio, la ciudad y el territorio. A modo de cajas de resonancia y leídas como muñecas rusas, unas dentro de otras, los espacios identificados muestran cualidades sonoras específicas, definidas tanto por sus condiciones geométricas, formales, constructivas o de uso; como por las correspondientes a las subsiguientes cajas que alojan. A fin de esclarecer la influencia de tales cuestiones en el aspecto sonoro de la ciudad, se propone un modelo ordenado de conexión y desconexión de escalas, utilizando una paramétrica puramente técnica creada ex profeso, junto con variables metodológicas más tradicionales. Al mismo tiempo, y tratando de esclarecer cómo, al ser puesta en vibración, la ciudad es aprehendida, disfrutada y rememorada por el ciudadano-oyente, otra parte del trabajo se dedica al estudio de los aspectos relativos a su recepción aural en deambulación compartida. En este caso la investigación se propone reclamar otras dimensiones más subversivas que, si bien escapan a los modos habituales de trabajar del arquitecto, se revelan intensamente en la experiencia plurifocal, multiplicando los efectos a considerar: efectos funcionales y significativos, de reconocimiento, integración y pertenencia a un cuerpo territorial y social de coordenadas históricas y geográficas de nuevo significadas; efectos perceptuales de inmersión, ubicuidad, temporalidad o inestabilidad; efectos estéticos, de rememoración, interpretación simbólica y recreación poética; e incluso efectos políticos, descubriendo un espacio urbano en continua regeneración, lugar para la exposición en su doble acepción, para la exhibición y el peligro, o como contenedor situacional del más profundo sentido ciudadano. Para afinar la relevancia de lo obtenido en cada una de las dimensiones señaladas, el trabajo se articula en tres aproximaciones graduales: el corpus general de los conciertos celebrados hasta la fecha; los conciertos celebrados en España; los tres conciertos para Madrid: Magna Mater (1991), Festi Clamores (2000) y Aurea Catena (2007). Si bien el modelo propuesto nace a la luz de los conciertos de campanas de Llorenç Barber, a escala de una ciudad entera y con una intención compositiva individual, se entiende que sería útil para el uso ordenado de cualquier profesional interesado en el aspecto sonoro de la ciudad, faceta escasamente atendida, dicho sea de paso, desde la disciplina arquitectónica. ABSTRACT This work has the vocation of drawing out the numerous opportunities an architect has at his disposal, upon imagining the sonorous aspect of the city in relation to the bell. Many of the dimensions indicated, both known and unknown, are just awakened to the study of what a sound space designer, as Llorenç Barber, comes to tell us, from a discipline apparently contacted, but often parallel to the architecture. Taking the bell concerts held so far as actual implementation of the instrumental condition of over two hundred cities around the world, the study analyzes the findings, successes and failures, obtained over the last twenty years of experience, as explicit results of a sound work in the city, tested, verified and refined, from which to extract specific indications that can be applied in the design of urban space. By triangular analyzing of defined vertices: sender-bell, half-city, receptor-citizen; the research addresses issues relating to the production and reception of sound phenomenon generated by the bell in the city. In relation to production, part of the work is devoted to the study of observed acoustic effects, ordered gradual scale which produces a distribution of sound capable of design: the glass of the bell, the bell room, the bell tower and the body of the building, the city and territory. By way of sounding boards and read as if they were Russian dolls, one inside the other, the show spaces identified specific sound qualities, defined both for their geometric, formal, constructive use, such as those for hosting the subsequent boxes. In order to clarify the influence of such issues in the sound aspect of the city, we propose an ordered pattern of connection and disconnection of scales, using a purely parametric technique created on purpose, along with more traditional methodological variables. At the same time, and trying to clarify how, when set in vibration, the city is apprehended, enjoyed and remembered for the citizen-listener, another part of the work is devoted to the study of aspects of aural reception in shared ambulation. In this case the research aims to claim more subversive than other dimensions, but beyond the usual ways in which an architect works, the experience reveals intensely plurifocal multiplying effects to consider: functional effects and significant recognition and integration belonging to a body of territorial and social historical and geographical coordinates of new meaning and perceptual effects of immersion, ubiquity, timeliness or instability; aesthetic effects of recall, interpretation and recreation of symbolic poetic; and even political effects, revealing a continuous urban space regeneration site for the exhibition in its double meaning, for display and danger, or as a citizen sense container. To sharpen the relevance of what was obtained in each of the dimensions mentioned, the work is divided into three incremental approaches: the general corpus of the concerts held so far, the concerts in Spain, the three concerts for Madrid: Magna Mater (1991), Festi Clamores (2000) and Aurea Catena (2007). While the proposed model comes in the light of the bells concert Llorenç Barber, the scale of a whole city and individual compositional intent, it is understood that it would be useful for the orderly use of any professional interested in the sound aspect of the city, an aspect sparsely attended, incidentally, from the architectural discipline.

Ensemble transcript interaction networks: A case study on Alzheimer's disease

Systems biology techniques are a topic of recent interest within the neurological field. Computational intelligence (CI) addresses this holistic perspective by means of consensus or ensemble techniques ultimately capable of uncovering new and relevant findings. In this paper, we propose the application of a CI approach based on ensemble Bayesian network classifiers and multivariate feature subset selection to induce probabilistic dependences that could match or unveil biological relationships. The research focuses on the analysis of high-throughput Alzheimer's disease (AD) transcript profiling. The analysis is conducted from two perspectives. First, we compare the expression profiles of hippocampus subregion entorhinal cortex (EC) samples of AD patients and controls. Second, we use the ensemble approach to study four types of samples: EC and dentate gyrus (DG) samples from both patients and controls. Results disclose transcript interaction networks with remarkable structures and genes not directly related to AD by previous studies. The ensemble is able to identify a variety of transcripts that play key roles in other neurological pathologies. Classical statistical assessment by means of non-parametric tests confirms the relevance of the majority of the transcripts. The ensemble approach pinpoints key metabolic mechanisms that could lead to new findings in the pathogenesis and development of AD

Evolution and treatment of vitamin B12 deficiency as a risk factor for (cognitive and functional) neurodegenerative diseases in institutionalized elderly = Evolución y tratamiento de la deficiencia de vitamina B12 como factor de riesgo de enfermedades neurodegenerativas (cognitivas y funcionales) en las personas mayores institucionalizadas.

Prevalence of vitamin B12 deficiency is very common in elderly people and can reach values as high as 40.5% of the population. It can be the result of the interaction among several factors. Vitamin B12 deficiencies have been associated with neurological, cognitive deterioration, haematological abnormalities and cardiovascular diseases that have an important influence on the health of the elderly and their quality of life. It is necessary to approach the problems arisen from the lack of data relative to them. The main objective of this thesis was to analyse the evolution of vitamin B12 status and related parameters, lipid and haematological profiles and their relationship to health risk factors, and to functional and cognitive status over one year and to determine the effect of an oral supplementation of 500 μg of cyanocobalamin for a short period of 28 days. An additional objective was to analyze the possible effects of medicine intakes on vitamin B status. Three studies were performed: a) a one year longitudinal follow-up with four measure points; b) an intervention study providing an oral liquid supplement of 500 μg of cyanocobalamin for a 28 days period; and c) analysis of the possible effect of medication intake on vitamin B status using the ATC classification of medicines. The participants for these studies were recruited from nursing homes for the elderly in the Region of Madrid. Sixty elders (mean age 84 _ 7y, 19 men and 41 women) were recruited for Study I and 64 elders (mean age 82 _ 7y, 24 men and 40 women) for Study II. For Study III, baseline data from the initially recruited participants of the first two studies were used. An informed consent was obtained from all participants or their mentors. The studies were approved by the Ethical Committee of the University of Granada. Blood samples were obtained at each examination date and were analyzed for serum cobalamin, holoTC, serum and RBC folate and total homocysteine according to laboratory standard procedures. The haematological parameters analyzed were haematocrit, haemoglobin and MCV. For the lipid profile TG, total cholesterol, LDL- and HDLcholesterol were analyzed. Anthropometric measures (BMI, skinfolds [triceps and subscapular], waist girth and waist to hip ratio), functional tests (hand grip, arm and leg strength tests, static balance) and MMSE were obtained or administered by trained personal. The vitamin B12 supplement of Study II was administered with breakfast and the medication intake was taken from the residents’ anamnesis. Data were analyzed by parametric and non-parametric statistics depending on the obtained data. Comparisons were done using the appropriate ANOVAs or non-parametric tests. Pearsons’ partial correlations with the variable “time” as control were used to define the association of the analyzed parameters. XIII The results showed that: A) Over one year, in relationship to vitamin B status, serum cobalamin decreased, serum folate and mean corpuscular volumen increased significantly and total homocysteine concentrations were stable. Regarding blood lipid profile, triglycerides increased and HDL-cholesterol decreased significantly. Regarding selected anthropometric measurements, waist circumference increased significantly. No significant changes were observed for the rest of parameters. B) Prevalence of hyperhomocysteinemia was high in the elderly studied, ranging from 60% to 90 % over the year depending on the cut-off used for the classification. LDL-cholesterol values were high, especially among women, and showed a tendency to increase over the year. Results of the balance test showed a deficiency and a tendency to decrease; this indicates that the population studied is at high risk for falls. Lower extremity muscular function was deficient and showed a tendency to decrease. A highly significant relationship was observed between the skinfold of the triceps and blood lipid profile. C) Low cobalamin concentrations correlated significantly with low MMSE scores in the elderly studied. No correlations were observed between vitamin B12 status and functional parameters. D) Regarding vitamin B12 status, holo-transcobalamin seems to be more sensitive for diagnosis; 5-10% of the elderly had a deficiency using serum cobalamin as a criterion, and 45-52% had a deficiency when using serum holotranscobalamin as a criterion. E) 500 μg of cyanocobalamin administered orally during 28 days significantly improved vitamin B12 status and significantly decreased total homocysteine concentrations in institutionalized elderly. No effect of the intervention was observed on functional and cognitive parameters. F) The relative change (%) of improvement of vitamin B12 status was higher when using serum holo-transcobalamin as a criterion than serum cobalamin. G) Antiaenemic drug intake normalized cobalamin, urologic drugs and corticosteroids serum folate, and psychoanaleptics holo-transcobalamin levels. Drugs treating pulmonary obstruction increased total homocysteine concentration significantly. H) The daily mean drug intake was 5.1. Fiftynine percent of the elderly took medication belonging to 5 or more different ATC groups. The most prevalent were psycholeptic (53%), antiacid (53%) and antithrombotic (47%) drugs.

Regularization for sparsity in statistical analysis and machine learning

Pragmatism is the leading motivation of regularization. We can understand regularization as a modification of the maximum-likelihood estimator so that a reasonable answer could be given in an unstable or ill-posed situation. To mention some typical examples, this happens when fitting parametric or non-parametric models with more parameters than data or when estimating large covariance matrices. Regularization is usually used, in addition, to improve the bias-variance tradeoff of an estimation. Then, the definition of regularization is quite general, and, although the introduction of a penalty is probably the most popular type, it is just one out of multiple forms of regularization. In this dissertation, we focus on the applications of regularization for obtaining sparse or parsimonious representations, where only a subset of the inputs is used. A particular form of regularization, L1-regularization, plays a key role for reaching sparsity. Most of the contributions presented here revolve around L1-regularization, although other forms of regularization are explored (also pursuing sparsity in some sense). In addition to present a compact review of L1-regularization and its applications in statistical and machine learning, we devise methodology for regression, supervised classification and structure induction of graphical models. Within the regression paradigm, we focus on kernel smoothing learning, proposing techniques for kernel design that are suitable for high dimensional settings and sparse regression functions. We also present an application of regularized regression techniques for modeling the response of biological neurons. Supervised classification advances deal, on the one hand, with the application of regularization for obtaining a na¨ıve Bayes classifier and, on the other hand, with a novel algorithm for brain-computer interface design that uses group regularization in an efficient manner. Finally, we present a heuristic for inducing structures of Gaussian Bayesian networks using L1-regularization as a filter. El pragmatismo es la principal motivación de la regularización. Podemos entender la regularización como una modificación del estimador de máxima verosimilitud, de tal manera que se pueda dar una respuesta cuando la configuración del problema es inestable. A modo de ejemplo, podemos mencionar el ajuste de modelos paramétricos o no paramétricos cuando hay más parámetros que casos en el conjunto de datos, o la estimación de grandes matrices de covarianzas. Se suele recurrir a la regularización, además, para mejorar el compromiso sesgo-varianza en una estimación. Por tanto, la definición de regularización es muy general y, aunque la introducción de una función de penalización es probablemente el método más popular, éste es sólo uno de entre varias posibilidades. En esta tesis se ha trabajado en aplicaciones de regularización para obtener representaciones dispersas, donde sólo se usa un subconjunto de las entradas. En particular, la regularización L1 juega un papel clave en la búsqueda de dicha dispersión. La mayor parte de las contribuciones presentadas en la tesis giran alrededor de la regularización L1, aunque también se exploran otras formas de regularización (que igualmente persiguen un modelo disperso). Además de presentar una revisión de la regularización L1 y sus aplicaciones en estadística y aprendizaje de máquina, se ha desarrollado metodología para regresión, clasificación supervisada y aprendizaje de estructura en modelos gráficos. Dentro de la regresión, se ha trabajado principalmente en métodos de regresión local, proponiendo técnicas de diseño del kernel que sean adecuadas a configuraciones de alta dimensionalidad y funciones de regresión dispersas. También se presenta una aplicación de las técnicas de regresión regularizada para modelar la respuesta de neuronas reales. Los avances en clasificación supervisada tratan, por una parte, con el uso de regularización para obtener un clasificador naive Bayes y, por otra parte, con el desarrollo de un algoritmo que usa regularización por grupos de una manera eficiente y que se ha aplicado al diseño de interfaces cerebromáquina. Finalmente, se presenta una heurística para inducir la estructura de redes Bayesianas Gaussianas usando regularización L1 a modo de filtro.

Characterization of underground cellars in the Duero Basin by GNSS, LIDAR and GPR techniques

The underground cellars of the Duero River basin are part of spread and damaged agricultural landscape which is in danger of disappearing. These architectural complexes are allocated next to small towns. Constructions are mostly dug in the ground with a gallery down or "barrel" strait through which you access the cave or cellar. This wider space is used to make and store wine. Observation and detection of the winery both on the outside and underground is essential to make an inventory of the rural heritage. Geodetection is a non-invasive technique, suitable to determinate with precision buried structures in the ground. The undertaken works include LIDAR survey techniques, GNSS and GPR obtained data. The results are used to identify with centimetric precision construction elements forming the winery. Graphic and cartographic obtained documents allow optimum visualization of the studied field and can be used in the reconstruction of the place.

Robust regression applied to fractal/multifractal analysis.

Fractal and multifractal are concepts that have grown increasingly popular in recent years in the soil analysis, along with the development of fractal models. One of the common steps is to calculate the slope of a linear fit commonly using least squares method. This shouldn?t be a special problem, however, in many situations using experimental data the researcher has to select the range of scales at which is going to work neglecting the rest of points to achieve the best linearity that in this type of analysis is necessary. Robust regression is a form of regression analysis designed to circumvent some limitations of traditional parametric and non-parametric methods. In this method we don?t have to assume that the outlier point is simply an extreme observation drawn from the tail of a normal distribution not compromising the validity of the regression results. In this work we have evaluated the capacity of robust regression to select the points in the experimental data used trying to avoid subjective choices. Based on this analysis we have developed a new work methodology that implies two basic steps: ? Evaluation of the improvement of linear fitting when consecutive points are eliminated based on R pvalue. In this way we consider the implications of reducing the number of points. ? Evaluation of the significance of slope difference between fitting with the two extremes points and fitted with the available points. We compare the results applying this methodology and the common used least squares one. The data selected for these comparisons are coming from experimental soil roughness transect and simulated based on middle point displacement method adding tendencies and noise. The results are discussed indicating the advantages and disadvantages of each methodology.

Quantity and degree assessment in an RDF.based semantic language

This paper introduces a semantic language developed with the objective to be used in a semantic analyzer based on linguistic and world knowledge. Linguistic knowledge is provided by a Combinatorial Dictionary and several sets of rules. Extra-linguistic information is stored in an Ontology. The meaning of the text is represented by means of a series of RDF-type triples of the form predicate (subject, object). Semantic analyzer is one of the options of the multifunctional ETAP-3 linguistic processor. The analyzer can be used for Information Extraction and Question Answering. We describe semantic representation of expressions that provide an assessment of the number of objects involved and/or give a quantitative evaluation of different types of attributes. We focus on the following aspects: 1) parametric and non-parametric attributes; 2) gradable and non-gradable attributes; 3) ontological representation of different classes of attributes; 4) absolute and relative quantitative assessment; 5) punctual and interval quantitative assessment; 6) intervals with precise and fuzzy boundaries

Assessment of watercore development in apples with MRI: Effect offruit location in the canopy

tWatercore distribution inside apple fruit (block or radial), and its incidence (% of tissue) were relatedto the effect of solar radiation inside the canopy as measured by a set of low-cost irradiation sensors.221 samples were harvested in two seasons from the top and the bottom of the canopy and submittedto the non-invasive and non-destructive technique of magnetic resonance imaging (MRI) in order toobtain 20 inner tomography slices from each fruit and analyze the damaged areas using an interactive3D segmentation method. The number of fruit corresponding to each type of damage and the relevantpercentage were calculated and it was found that apples from the top of the tree were mainly of the radialtype (84%) and had more watercore (approx. 5% more) than apples from the bottom (65% radial). From theimage segmentation, the Euler number, a morphometric parameter, was extracted from the segmentedimages and related to the type of watercore symptoms. Apples with block watercore were grouped inEuler numbers between −400 and 400 with a small evolution. For apples with radial development, theEuler number was highly negative: up to −1439. Significant differences were also found regarding sugarcomposition, with higher fructose and total sugar contents in apples from the upper canopy, compared tothose in the lower canopy location. In the seasons studied (2011 and 2012), significantly higher sorbitoland lower sucrose and fructose contents were found in watercore-affected tissue compared to the healthytissue of affected apples and also compared to healthy apples.

Nonparametric generalized belief propagation based on pseudo-junction tree for cooperative localization in wireless networks

Non-parametric belief propagation (NBP) is a well-known message passing method for cooperative localization in wireless networks. However, due to the over-counting problem in the networks with loops, NBP’s convergence is not guaranteed, and its estimates are typically less accurate. One solution for this problem is non-parametric generalized belief propagation based on junction tree. However, this method is intractable in large-scale networks due to the high-complexity of the junction tree formation, and the high-dimensionality of the particles. Therefore, in this article, we propose the non-parametric generalized belief propagation based on pseudo-junction tree (NGBP-PJT). The main difference comparing with the standard method is the formation of pseudo-junction tree, which represents the approximated junction tree based on thin graph. In addition, in order to decrease the number of high-dimensional particles, we use more informative importance density function, and reduce the dimensionality of the messages. As by-product, we also propose NBP based on thin graph (NBP-TG), a cheaper variant of NBP, which runs on the same graph as NGBP-PJT. According to our simulation and experimental results, NGBP-PJT method outperforms NBP and NBP-TG in terms of accuracy, computational, and communication cost in reasonably sized networks.

PUE attack detection in CWSNs using anomaly detection techniques

Cognitive wireless sensor network (CWSN) is a new paradigm, integrating cognitive features in traditional wireless sensor networks (WSNs) to mitigate important problems such as spectrum occupancy. Security in cognitive wireless sensor networks is an important problem since these kinds of networks manage critical applications and data. The specific constraints of WSN make the problem even more critical, and effective solutions have not yet been implemented. Primary user emulation (PUE) attack is the most studied specific attack deriving from new cognitive features. This work discusses a new approach, based on anomaly behavior detection and collaboration, to detect the primary user emulation attack in CWSN scenarios. Two non-parametric algorithms, suitable for low-resource networks like CWSNs, have been used in this work: the cumulative sum and data clustering algorithms. The comparison is based on some characteristics such as detection delay, learning time, scalability, resources, and scenario dependency. The algorithms have been tested using a cognitive simulator that provides important results in this area. Both algorithms have shown to be valid in order to detect PUE attacks, reaching a detection rate of 99% and less than 1% of false positives using collaboration.