Calibrazione di modelli idrologici con algoritmi multiobiettivo

Traditional procedures for rainfall-runoff model calibration are generally based on the fit of the individual values of simulated and observed hydrographs. It is used here an alternative option that is carried out by matching, in the optimisation process, a set of statistics of the river flow. Such approach has the additional, significant advantage to allow also a straightforward regional calibration of the model parameters, based on the regionalisation of the selected statistics. The minimisation of the set of objective functions is carried out by using the AMALGAM algorithm, leading to the identification of behavioural parameter sets. The procedure is applied to a set of river basins located in central Italy: the basins are treated alternatively as gauged and ungauged and, as a term of comparison, the results obtained with a traditional time-domain calibration is also presented. The results show that a suitable choice of the statistics to be optimised leads to interesting results in real world case studies as far as the reproduction of the different flow regimes is concerned.

ECM versus ICP for point registration

Iterative Closest Point (ICP) is a widely exploited method for point registration that is based on binary point-to-point assignments, whereas the Expectation Conditional Maximization (ECM) algorithm tries to solve the problem of point registration within the framework of maximum likelihood with point-to-cluster matching. In this paper, by fulfilling the implementation of both algorithms as well as conducting experiments in a scenario where dozens of model points must be registered with thousands of observation points on a pelvis model, we investigated and compared the performance (e.g. accuracy and robustness) of both ICP and ECM for point registration in cases without noise and with Gaussian white noise. The experiment results reveal that the ECM method is much less sensitive to initialization and is able to achieve more consistent estimations of the transformation parameters than the ICP algorithm, since the latter easily sinks into local minima and leads to quite different registration results with respect to different initializations. Both algorithms can reach the high registration accuracy at the same level, however, the ICP method usually requires an appropriate initialization to converge globally. In the presence of Gaussian white noise, it is observed in experiments that ECM is less efficient but more robust than ICP.

Influence of deep sternal wound infection on long-term survival after cardiac surgery

BACKGROUND: This study aimed to investigate the influence of deep sternal wound infection on long-term survival following cardiac surgery. MATERIAL AND METHODS: In our institutional database we retrospectively evaluated medical records of 4732 adult patients who received open-heart surgery from January 1995 through December 2005. The predictive factors for DSWI were determined using logistic regression analysis. Then, each patient with deep sternal wound infection (DSWI) was matched with 2 controls without DSWI, according to the risk factors identified previously. After checking balance resulting from matching, short-term mortality was compared between groups using a paired test, and long-term survival was compared using Kaplan-Meier analysis and a Cox proportional hazard model. RESULTS: Overall, 4732 records were analyzed. The mean age of the investigated population was 69.3±12.8 years. DSWI occurred in 74 (1.56%) patients. Significant independent predictive factors for deep sternal infections were active smoking (OR 2.19, CI95 1.35-3.53, p=0.001), obesity (OR 1.96, CI95 1.20-3.21, p=0.007), and insulin-dependent diabetes mellitus (OR 2.09, CI95 1.05-10.06, p=0.016). Mean follow-up in the matched set was 125 months, IQR 99-162. After matching, in-hospital mortality was higher in the DSWI group (8.1% vs. 2.7% p=0.03), but DSWI was not an independent predictor of long-term survival (adjusted HR 1.5, CI95 0.7-3.2, p=0.33). CONCLUSIONS: The results presented in this report clearly show that post-sternotomy deep wound infection does not influence long-term survival in an adult general cardio-surgical patient population.

The effects of population density on the spread of disease

The objective of this study is to identify the relationship between population density and the initial stages of the spread of disease in a local population. This study proposes to concentrate on the question of how population density affects the distribution of the susceptible individuals in a local population and thus affects the spread of the disease, measles. Population density is measured by the average of the number of contacts with susceptible individuals by each individual in the population during a fixed-length time period. The term “contact with susceptible individuals” means sufficient contact between two people for the disease to pass from an infectious person to a susceptible person. The fixed-length time period is taken to be the average length of time an infected person is infectious without symptoms of the disease. For this study of measles, the time period will be seven days. ^ While much attention has been given to modeling the entire epidemic process of measles, attempts have not been made to study the characteristics of contact rates required to initiate an epidemic. This study explores the relationship between population density, given a specific herd immunity rate in the population, and initial rate of the spread of the disease by considering the underlying distribution of contacts with susceptibles by the individuals in the population. ^ This study does not seek to model an entire measles epidemic, but to model the above stated relationship for the local population within which the first infective person is introduced. This study describes the mathematical relationship between population density parameters and contact distribution parameters. ^ The results are displayed in graphs that show the effects of different population densities on the spread of disease. The results support the idea that the number of new infectives is strongly related to the distribution of susceptible contacts. The results also show large differences in the epidemic measures between populations with densities equal to four versus three. ^

Impactos en el agua subterránea de un sistema de efluentes para riego : el Sistema Paramillos (Lavalle, Mendoza, Argentina)

En este trabajo se evalúa el impacto de un sistema de aprovechamiento de efluentes domésticos para riego en la calidad del agua subterránea. Los puntos de muestreo seleccionados son parte de un monitoreo a mayor escala del cual sólo se incluyeron aquellos relacionados con el sistema de la planta depuradora Paramillos, ubicada al Norte del aglomerado Mendoza. Esta planta consiste en una laguna de estabilización facultativa. Los resultados, presentados en gráficos, mapas y tablas, se discuten a partir del comportamiento de tres componentes del sistema hídrico: agua superficial (efluente), agua subterránea del nivel superior del acuífero (freática) y agua subterránea del acuífero profundo (confinado/ semiconfinado) y su interacción con el perfil del suelo. Se concluye que el acuífero profundo no es alcanzado por nitratos ni nitritos productos de la degradación biológica de la materia orgánica del efluente, lo que se atribuye a la capa impermeable subyacente. En el nivel superior o freático, el perfil del suelo remueve parte del N total y P total ingresado, entre el 39 y 90%. La remoción de DBO varía entre 30 y 90% y la remoción de E. coli remanente en efluente es total.

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.

Traffic sign detection and tracking using robust 3D analysis

In this paper we present an innovative technique to tackle the problem of automatic road sign detection and tracking using an on-board stereo camera. It involves a continuous 3D analysis of the road sign during the whole tracking process. Firstly, a color and appearance based model is applied to generate road sign candidates in both stereo images. A sparse disparity map between the left and right images is then created for each candidate by using contour-based and SURF-based matching in the far and short range, respectively. Once the map has been computed, the correspondences are back-projected to generate a cloud of 3D points, and the best-fit plane is computed through RANSAC, ensuring robustness to outliers. Temporal consistency is enforced by means of a Kalman filter, which exploits the intrinsic smoothness of the 3D camera motion in traffic environments. Additionally, the estimation of the plane allows to correct deformations due to perspective, thus easing further sign classification.

Captura y transformación de grafos para análisis de redes sociales

Hoy en día las redes sociales se han convertido en una parte importante en la vida de muchas personas. No sólo porque les permite mantener el contacto con familiares y amigos, sino porque también pueden mostrar al mundo sus opiniones, inquietudes, estilo de vida, habilidades, ideas… Una de las redes sociales que ha adquirido mayor importancia en los últimos años es Twitter. Actualmente cuenta con más de 320 millones de usuarios activos al mes. En ella los usuarios pueden publicar información y acceder a información publicada por otros usuarios. Se ha convertido en el medio de comunicación y difusión de noticias más rápido del mundo. Éstas son algunas de las razones por las que existe un gran interés por el análisis de datos de esta red social. En particular, el análisis de tendencias a través de redes de interacciones entre sus usuarios. Un ejemplo este tipo de redes en Twitter es una red de retweets sobre una etiqueta o hasthtag concreto. Estas redes se pueden representar como grafos, donde los nodos representan a los usuarios y las aristas los retweets entre usuarios. Aunque existen varias aplicaciones que permiten transformar y visualizar grafos a partir de un fichero, es difícil encontrar librerías de programación o aplicaciones que recopilen los datos de twitter, generen los grafos, los analicen y los exporten a ficheros concretos para poder visualizarlos con alguna aplicación. Este trabajo tiene como finalidad crear una librería en el lenguaje de programación Java que permita recopilar datos de twitter, transformar dichos datos en grafos, aplicar algoritmos para analizarlos, y exportar los grafos a ficheros con formato GEXF para que puedan ser visualizados con la aplicación Gephi. Esta librería incluye un programa para probar todas sus funcionalidades.---ABSTRACT---Today, social networks have become an important part in the life of many persons. Not only because they allow them to keep in contact with relatives and friends but also because through them they can express their opinions, interests, life- styles, hobbies or ideas to the wide world. Twitter is one of the social networks which in the last few years has achieved a particular importance. Right now, it counts with more that 320 millions of active monthly users who exchange, or have access, through it to a wide variety of informations. Twitter has become the fastest way in the world to communicate or diffuse news. This explains, among other reasons, the growing interest in the analysis of the data in this specific social network, particularly the analysis of trends through the web of interactions between its users. An example of this type of networks in Twitter is the network of retweets on a specific label or hashtag. These networks can be represented as graphs where nodes represent users and edges the retweets between users. Although there exist aldeady several applications that allow for the transformation and visualization in graphs of the contents of a data file, it is difficult to find libraries or applications to compile data from twitter, to generate graphs from them, to analyze them and to export them to a specific file that will allow its visualization with the use of some application. The purpose of this work is the creation of a library in Java language that will make posible to compile data from twitter, to transform them in grafos, to apply algorythms to analyze them and to export the graphos to files with a GEXF format, which will allow their visualization with a Gephi application. This library will include a program to test all its features.

Estudo do espectro Laplaciano na categorização de imagens

Uma imagem engloba informação que precisa ser organizada para interpretar e compreender seu conteúdo. Existem diversas técnicas computacionais para extrair a principal informação de uma imagem e podem ser divididas em três áreas: análise de cor, textura e forma. Uma das principais delas é a análise de forma, por descrever características de objetos baseadas em seus pontos fronteira. Propomos um método de caracterização de imagens, por meio da análise de forma, baseada nas propriedades espectrais do laplaciano em grafos. O procedimento construiu grafos G baseados nos pontos fronteira do objeto, cujas conexões entre vértices são determinadas por limiares T_l. A partir dos grafos obtêm-se a matriz de adjacência A e a matriz de graus D, as quais definem a matriz Laplaciana L=D -A. A decomposição espectral da matriz Laplaciana (autovalores) é investigada para descrever características das imagens. Duas abordagens são consideradas: a) Análise do vetor característico baseado em limiares e a histogramas, considera dois parâmetros o intervalo de classes IC_l e o limiar T_l; b) Análise do vetor característico baseado em vários limiares para autovalores fixos; os quais representam o segundo e último autovalor da matriz L. As técnicas foram testada em três coleções de imagens: sintéticas (Genéricas), parasitas intestinais (SADPI) e folhas de plantas (CNShape), cada uma destas com suas próprias características e desafios. Na avaliação dos resultados, empregamos o modelo de classificação support vector machine (SVM), o qual avalia nossas abordagens, determinando o índice de separação das categorias. A primeira abordagem obteve um acerto de 90 % com a coleção de imagens Genéricas, 88 % na coleção SADPI, e 72 % na coleção CNShape. Na segunda abordagem, obtém-se uma taxa de acerto de 97 % com a coleção de imagens Genéricas; 83 % para SADPI e 86 % no CNShape. Os resultados mostram que a classificação de imagens a partir do espectro do Laplaciano, consegue categorizá-las satisfatoriamente.

Improving 3D Keypoint Detection from Noisy Data Using Growing Neural Gas

3D sensors provides valuable information for mobile robotic tasks like scene classification or object recognition, but these sensors often produce noisy data that makes impossible applying classical keypoint detection and feature extraction techniques. Therefore, noise removal and downsampling have become essential steps in 3D data processing. In this work, we propose the use of a 3D filtering and down-sampling technique based on a Growing Neural Gas (GNG) network. GNG method is able to deal with outliers presents in the input data. These features allows to represent 3D spaces, obtaining an induced Delaunay Triangulation of the input space. Experiments show how the state-of-the-art keypoint detectors improve their performance using GNG output representation as input data. Descriptors extracted on improved keypoints perform better matching in robotics applications as 3D scene registration.

Students’ understanding of the function-derivative relationship when learning economic concepts

The aim of this study is to characterise students’ understanding of the function-derivative relationship when learning economic concepts. To this end, we use a fuzzy metric (Chang 1968) to identify the development of economic concept understanding that is defined by the function-derivative relationship. The results indicate that the understanding of these economic concepts is linked to students’ capacity to perform conversions and treatments between the algebraic and graphic registers of the function-derivative relationship when extracting the economic meaning of concavity/convexity in graphs of functions using the second derivative.

Overcoming schema heterogeneity between linked semantic repositories to improve coreference resolution

Schema heterogeneity issues often represent an obstacle for discovering coreference links between individuals in semantic data repositories. In this paper we present an approach, which performs ontology schema matching in order to improve instance coreference resolution performance. A novel feature of the approach is its use of existing instance-level coreference links defined in third-party repositories as background knowledge for schema matching techniques. In our tests of this approach we obtained encouraging results, in particular, a substantial increase in recall in comparison with existing sets of coreference links.

Avaliação de qualidade da unidade de diálise no Hospital Universitário Onofre Lopes - HUOL

Over the years there has been a broader definition of the term health. At the same time it was found also an evolution of the concept of health care which in turn has led to changes in the approach to delivery of health services and hence in its management. In this regard, currently the nephrology services have been searching for quality technical and social need. In view of these innovations and the quest for quality, it elaborated the general objective: to develop a quality assessment protocol for dialysis service Onofre Lopes University Hospital. It is an intervention project effected through an action research, which consisted of 4 steps. Initially was identified through a literature search in scientific literature, which quality indicators would apply to a dialysis unit being selected as follows: infection rate in hemodialysis access site, microbiological control of water used for hemodialysis and Index User satisfaction. Through critical reflection on the theme researched in the previous step, it was drawn up three data collection instruments, interview form type, applied between the months of October and November 2015. In addition to the information obtained, also made up of the use of information retrieval technique. The results were organized in graphs and tables and analyzed using qualitative and exploratory technical approach. Then a reflective analysis of the data obtained and the diagnosis of reality studied was traced and confronted with the literature was performed. The data produced in this study revealed that the Dialysis Unit of HUOL is much to be desired, considering that some weaknesses have been identified in its structure. Faced with this finding have been proposed, as a contribution and aiming to guide the development of future actions, suggestions for improvement that should be implemented and monitored to be assured overcoming these difficulties, allowing an appropriate organizational restructuring, and resulting in improved service public offered. It was concluded that for hemodialysis treatment results are achieved and positive, it is necessary to have physical structure and adequate infrastructure, multidisciplinary team specialized, trained and in sufficient quantity, well designed processes for professionals to have standards to be followed decreasing the chance to err, and a risk management system to detect and control situations that endanger patient safety.

Avaliação de qualidade da unidade de diálise no Hospital Universitário Onofre Lopes - HUOL

Over the years there has been a broader definition of the term health. At the same time it was found also an evolution of the concept of health care which in turn has led to changes in the approach to delivery of health services and hence in its management. In this regard, currently the nephrology services have been searching for quality technical and social need. In view of these innovations and the quest for quality, it elaborated the general objective: to develop a quality assessment protocol for dialysis service Onofre Lopes University Hospital. It is an intervention project effected through an action research, which consisted of 4 steps. Initially was identified through a literature search in scientific literature, which quality indicators would apply to a dialysis unit being selected as follows: infection rate in hemodialysis access site, microbiological control of water used for hemodialysis and Index User satisfaction. Through critical reflection on the theme researched in the previous step, it was drawn up three data collection instruments, interview form type, applied between the months of October and November 2015. In addition to the information obtained, also made up of the use of information retrieval technique. The results were organized in graphs and tables and analyzed using qualitative and exploratory technical approach. Then a reflective analysis of the data obtained and the diagnosis of reality studied was traced and confronted with the literature was performed. The data produced in this study revealed that the Dialysis Unit of HUOL is much to be desired, considering that some weaknesses have been identified in its structure. Faced with this finding have been proposed, as a contribution and aiming to guide the development of future actions, suggestions for improvement that should be implemented and monitored to be assured overcoming these difficulties, allowing an appropriate organizational restructuring, and resulting in improved service public offered. It was concluded that for hemodialysis treatment results are achieved and positive, it is necessary to have physical structure and adequate infrastructure, multidisciplinary team specialized, trained and in sufficient quantity, well designed processes for professionals to have standards to be followed decreasing the chance to err, and a risk management system to detect and control situations that endanger patient safety.

Cooperación internacional para la seguridad alimentaria Antioquia. 2015

El objetivo de la investigación fue analizar la cooperación internacional para la seguridad alimentaria en Suroeste y Oriente antioqueños, a través de la revisión del Convenio FAO-Gobernación de Antioquia, sus componentes y sus actividades, con el propósito de visualizar la cooperación internacional a nivel local. Estudio descriptivo cuali-cuantitativo con fuentes secundarias y primarias (entrevistas). La investigación fue autorizada por los gerentes de MANÁ y FAO, delegando en los coordinadores del convenio la entrega de la información. El investigador se desplazó a las oficinas de Medellín para su recolección. Una vez depurados los datos se procedió a elaborar las tablas para las dos subregiones estudiadas, analizar la información y presentarla en gráficos y tablas, complementando con las entrevistas semiestructuradas de los actores claves del convenio. Resultados: el convenio de cooperación internacional para la seguridad alimentaria se viene ejecutando de manera satisfactoria según los compromisos desarrollados en los componentes: emprendimiento de agricultura familiar se organizaron 16 asociaciones entre fincas; se establecieron 7.000 huertas de las oportunidades mediante procesos de capacitación y asesoría realizando para ello, 10.972 visitas y 1.483 talleres. Para el componente de plan de abastecimiento de alimentos lograron identificar los rubros pecuarios y de alimentos según la oferta y demanda local. Con el fortalecimiento institucional motivaron a las autoridades locales, familias y otras instituciones y utilizaron medios diferentes para informar los avances a 1.800 personas. Se concluye que la cooperación internacional ayuda a mejorar la seguridad alimentaria en Antioquia.