Lagrangian tools and the assessment of the predictive capacity of geophysical data sets

We examine, with recently developed Lagrangian tools, altimeter data and numerical simulations obtained from the HYCOM model in the Gulf of Mexico. Our data correspond to the months just after the Deepwater Horizon oil spill in the year 2010. Our Lagrangian analysis provides a skeleton that allows the interpretation of transport routes over the ocean surface. The transport routes are further verified by the simultaneous study of the evolution of several drifters launched during those months in the Gulf of Mexico. We find that there exist Lagrangian structures that justify the dynamics of the drifters, although the agreement depends on the quality of the data. We discuss the impact of the Lagrangian tools on the assessment of the predictive capacity of these data sets.

An autonomic framework for enhancing the quality of data grid services

Data grid services have been used to deal with the increasing needs of applications in terms of data volume and throughput. The large scale, heterogeneity and dynamism of grid environments often make management and tuning of these data services very complex. Furthermore, current high-performance I/O approaches are characterized by their high complexity and specific features that usually require specialized administrator skills. Autonomic computing can help manage this complexity. The present paper describes an autonomic subsystem intended to provide self-management features aimed at efficiently reducing the I/O problem in a grid environment, thereby enhancing the quality of service (QoS) of data access and storage services in the grid. Our proposal takes into account that data produced in an I/O system is not usually immediately required. Therefore, performance improvements are related not only to current but also to any future I/O access, as the actual data access usually occurs later on. Nevertheless, the exact time of the next I/O operations is unknown. Thus, our approach proposes a long-term prediction designed to forecast the future workload of grid components. This enables the autonomic subsystem to determine the optimal data placement to improve both current and future I/O operations.

Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: An application to predict the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39)

Multi-dimensional Bayesian network classifiers (MBCs) are probabilistic graphical models recently proposed to deal with multi-dimensional classification problems, where each instance in the data set has to be assigned to more than one class variable. In this paper, we propose a Markov blanket-based approach for learning MBCs from data. Basically, it consists of determining the Markov blanket around each class variable using the HITON algorithm, then specifying the directionality over the MBC subgraphs. Our approach is applied to the prediction problem of the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson’s Disease Questionnaire (PDQ-39) in order to estimate the health-related quality of life of Parkinson’s patients. Fivefold cross-validation experiments were carried out on randomly generated synthetic data sets, Yeast data set, as well as on a real-world Parkinson’s disease data set containing 488 patients. The experimental study, including comparison with additional Bayesian network-based approaches, back propagation for multi-label learning, multi-label k-nearest neighbor, multinomial logistic regression, ordinary least squares, and censored least absolute deviations, shows encouraging results in terms of predictive accuracy as well as the identification of dependence relationships among class and feature variables.

PROFILE AND THE QUALITY OF LIFE OF LOGGERS

RESUMO – Objetivou-se com este estudo caracterizar o perfil e avaliar o nível de satisfação que reflete na qualidade de vida no trabalho (QVT) de trabalhadores da colheita de madeira de duas contratadas (C1 e C2), por duas grandes empresas do setor florestal, sendo uma do segmento de papel e celulose (PC) e, a outra, do segmento de carvão vegetal (CV). A avaliação ocorreu a partir da percepção dos trabalhadores das contratadas em questão, utilizando um modelo pré-concebido que contempla 11 blocos ou dimensões referentes a variáveis intervenientes e definidores da QVT, englobando 48 trabalhadores em três categorias funcionais: operador de motosserra (7 trabalhadores da C1 PC e 10 da C2 CV), ajudante de motosserrista (7 trabalhadores da C1 PC e 8 da C2 CV) e operador de carregador florestal (11 trabalhadores da C1 PC e 5 da C2 CV). Os dados referentes às variáveis intervenientes na QVT foram obtidos a partir de escala fechada do tipo Likert, com os escores variando de 1 a 7, em que 1 correspondeu ao nível "bastante insatisfeito" e 7, ao nível "bastante satisfeito". O perfil dos trabalhadores é de pessoa jovem, baixo nível de escolaridade e pouco tempo de serviço na empresa. Quanto ao nível de satisfação no trabalho, constatou-se que os trabalhadores da C1 PC se encontravam "satisfeitos" e os da C2 CV, "mediamente satisfeitos" com o trabalho e as condições proporcionadas pelas respectivas empresas, apesar de estatisticamente não ter sido detectada diferença entre os valores médios encontrados nas duas situações, pelo teste de Mediana (P>0,01). Os fatores que mais contribuíram para esses resultados favoráveis foram os benefícios extras oferecidos pelas prestadoras de serviços, as condições de segurança no trabalho e o contentamento com o emprego formal. ABSTRACT – The objective of this study was to characterize profile and satisfaction level, which reflects the quality of life (QOL) of forest workers of two contracts for harvest activities, one in the pulp and paper industry (PI) and another in charcoal industry (CI). The evaluation of the satisfaction indexes was carried out according to the workers perception by using a model including 11 parameters to reflect these workers QOL. The group study of 48 workers encompassed three functional categories: chainsaw operators (7 from C1 and 10 from C2), chainsaw operator's assistant (7 from C1 and 8 from C2), and log loader operators (11 from C1 and 5 from C2). Data regarding the factors involved in QOL were collected from a closed, Likert-type scale with scores ranging from 1-7, in which level 1 corresponded to "very dissatisfied" and level 7 to "very satisfied". The general profile of the group shows that most of them are young, with low level of education and employed in the companies for a short time. Overall, the employees of contractors of the paper and pulp industry are "satisfied" and those working for the charcoal company are only "moderately satisfied" with the work and policies offered by the respective companies, although no significant statistical difference was detected between the two groups, for the median test (P> 0.01). The main reasons behind these results are the general beneficts offered by the companies, the safety measurements and the overall satisfaction for been employed.

Quality of Service (QoS) in MPLS networks

Telecommunications networks have been always expanding and thanks to it, new services have appeared. The old mechanisms for carrying packets have become obsolete due to the new service requirements, which have begun working in real time. Real time traffic requires strict service guarantees. When this traffic is sent through the network, enough resources must be given in order to avoid delays and information losses. When browsing through the Internet and requesting web pages, data must be sent from a server to the user. If during the transmission there is any packet drop, the packet is sent again. For the end user, it does not matter if the webpage loads in one or two seconds more. But if the user is maintaining a conversation with a VoIP program, such as Skype, one or two seconds of delay in the conversation may be catastrophic, and none of them can understand the other. In order to provide support for this new services, the networks have to evolve. For this purpose MPLS and QoS were developed. MPLS is a packet carrying mechanism used in high performance telecommunication networks which directs and carries data using pre-established paths. Now, packets are forwarded on the basis of labels, making this process faster than routing the packets with the IP addresses. MPLS also supports Traffic Engineering (TE). This refers to the process of selecting the best paths for data traffic in order to balance the traffic load between the different links. In a network with multiple paths, routing algorithms calculate the shortest one, and most of the times all traffic is directed through it, causing overload and packet drops, without distributing the packets in the other paths that the network offers and do not have any traffic. But this is not enough in order to provide the real time traffic the guarantees it needs. In fact, those mechanisms improve the network, but they do not make changes in how the traffic is treated. That is why Quality of Service (QoS) was developed. Quality of service is the ability to provide different priority to different applications, users, or data flows, or to guarantee a certain level of performance to a data flow. Traffic is distributed into different classes and each of them is treated differently, according to its Service Level Agreement (SLA). Traffic with the highest priority will have the preference over lower classes, but this does not mean it will monopolize all the resources. In order to achieve this goal, a set policies are defined to control and alter how the traffic flows. Possibilities are endless, and it depends in how the network must be structured. By using those mechanisms it is possible to provide the necessary guarantees to the real-time traffic, distributing it between categories inside the network and offering the best service for both real time data and non real time data. Las Redes de Telecomunicaciones siempre han estado en expansión y han propiciado la aparición de nuevos servicios. Los viejos mecanismos para transportar paquetes se han quedado obsoletos debido a las exigencias de los nuevos servicios, que han comenzado a operar en tiempo real. El tráfico en tiempo real requiere de unas estrictas garantías de servicio. Cuando este tráfico se envía a través de la red, necesita disponer de suficientes recursos para evitar retrasos y pérdidas de información. Cuando se navega por la red y se solicitan páginas web, los datos viajan desde un servidor hasta el usuario. Si durante la transmisión se pierde algún paquete, éste se vuelve a mandar de nuevo. Para el usuario final, no importa si la página tarda uno o dos segundos más en cargar. Ahora bien, si el usuario está manteniendo una conversación usando algún programa de VoIP (como por ejemplo Skype) uno o dos segundos de retardo en la conversación podrían ser catastróficos, y ninguno de los interlocutores sería capaz de entender al otro. Para poder dar soporte a estos nuevos servicios, las redes deben evolucionar. Para este propósito se han concebido MPLS y QoS MPLS es un mecanismo de transporte de paquetes que se usa en redes de telecomunicaciones de alto rendimiento que dirige y transporta los datos de acuerdo a caminos preestablecidos. Ahora los paquetes se encaminan en función de unas etiquetas, lo cual hace que sea mucho más rápido que encaminar los paquetes usando las direcciones IP. MPLS también soporta Ingeniería de Tráfico (TE). Consiste en seleccionar los mejores caminos para el tráfico de datos con el objetivo de balancear la carga entre los diferentes enlaces. En una red con múltiples caminos, los algoritmos de enrutamiento actuales calculan el camino más corto, y muchas veces el tráfico se dirige sólo por éste, saturando el canal, mientras que otras rutas se quedan completamente desocupadas. Ahora bien, esto no es suficiente para ofrecer al tráfico en tiempo real las garantías que necesita. De hecho, estos mecanismos mejoran la red, pero no realizan cambios a la hora de tratar el tráfico. Por esto es por lo que se ha desarrollado el concepto de Calidad de Servicio (QoS). La calidad de servicio es la capacidad para ofrecer diferentes prioridades a las diferentes aplicaciones, usuarios o flujos de datos, y para garantizar un cierto nivel de rendimiento en un flujo de datos. El tráfico se distribuye en diferentes clases y cada una de ellas se trata de forma diferente, de acuerdo a las especificaciones que se indiquen en su Contrato de Tráfico (SLA). EL tráfico con mayor prioridad tendrá preferencia sobre el resto, pero esto no significa que acapare la totalidad de los recursos. Para poder alcanzar estos objetivos se definen una serie de políticas para controlar y alterar el comportamiento del tráfico. Las posibilidades son inmensas dependiendo de cómo se quiera estructurar la red. Usando estos mecanismos se pueden proporcionar las garantías necesarias al tráfico en tiempo real, distribuyéndolo en categorías dentro de la red y ofreciendo el mejor servicio posible tanto a los datos en tiempo real como a los que no lo son.

A telecom analytics framework for dynamic quality of service management

Since the beginning of Internet, Internet Service Providers (ISP) have seen the need of giving to users? traffic different treatments defined by agree- ments between ISP and customers. This procedure, known as Quality of Service Management, has not much changed in the last years (DiffServ and Deep Pack-et Inspection have been the most chosen mechanisms). However, the incremen-tal growth of Internet users and services jointly with the application of recent Ma- chine Learning techniques, open up the possibility of going one step for-ward in the smart management of network traffic. In this paper, we first make a survey of current tools and techniques for QoS Management. Then we intro-duce clustering and classifying Machine Learning techniques for traffic charac-terization and the concept of Quality of Experience. Finally, with all these com-ponents, we present a brand new framework that will manage in a smart way Quality of Service in a telecom Big Data based scenario, both for mobile and fixed communications.

Social Indicators in the Sustainable Refurbishment: Calculating Quality of Life Indicator in a Residential Building in Málaga

How can we measure ‘quality of life’? The sustainable refurbishment goes beyond strictly energy aspects. Sustainability indicators are needed to facilitate data collection and to provide information which does not require too time-consuming calculations. Thus, you can offer an idea of the extent and quality of the rehabilitation before starting the project and, also, the obtained results can be evaluated in an agile way after the refurbishment. From a list of social indicators gathered from different methods, sustainability assessment tools and International and European standards, three social indicators are proposed: Users Satisfaction, Participation Agreement and Quality of Life. This paper shows the development of Quality of Life social indicator, the more closely related to the main objectives of Researchand Development Project “Sustainable Refurbishment”: improving energy efficiency and wellbeing of users in existing residential buildings. Finally, this social indicator is applied to a real case study in Málaga (Spain).