Simulating improved combinations tillage-rotation under dryland conditions.

The adequate combination of reduced tillage and crop rotation could increase the viability of dry land agriculture in Mediterrenean zones. Crop simulation models can support to examine various tillage-rotation combinations and explore management scenarios. The decision support system for agrotechnology transfer (DSSAT) (Hoogenboom et al., 2010) provides a suite of crop models suitable for this task. The objective of this work was to simulate the effects of two tillage systems, conventional tillage (ConvT) and no tillage (NoT), and three crop rotations, continuous cereal (CC), fallow-cereal (FallowC) and legume-cereal (LegumeC), under dry conditions, on the cereal yield, soil organic carbon (SOC) and nitrogen (SON) in a 15-year experiment, comparing these simulations with field observations.

A MAUT approach for reusing ontologies

Knowledge resource reuse has become a popular approach within the ontology engineering field, mainly because it can speed up the ontology development process, saving time and money and promoting the application of good practices. The NeOn Methodology provides guidelines for reuse. These guidelines include the selection of the most appropriate knowledge resources for reuse in ontology development. This is a complex decision-making problem where different conflicting objectives, like the reuse cost, understandability, integration workload and reliability, have to be taken into account simultaneously. GMAA is a PC-based decision support system based on an additive multi-attribute utility model that is intended to allay the operational difficulties involved in the Decision Analysis methodology. The paper illustrates how it can be applied to select multimedia ontologies for reuse to develop a new ontology in the multimedia domain. It also demonstrates that the sensitivity analyses provided by GMAA are useful tools for making a final recommendation.

Implementación de una arquitectura de componentes para un sistema de apoyo a la toma de decisiones en Atención Primaria

Este Proyecto Fin de Grado tiene como objetivo fundamental el perfeccionamiento y puesta en explotación de un sistema de ayuda a la decisión que evalúa el desarrollo del lenguaje en niños de 0 a 6 años de edad. Este sistema está formado fundamentalmente por una aplicación diseñada y construida mediante una arquitectura de componentes de software modular y reutilizable. La aplicación será usada por los pediatras para realizar evaluaciones del desarrollo del lenguaje infantil y además por los neuropediatras, logopedas y miembros de equipos de Atención Temprana para consultar las evaluaciones y validar las decisiones propuestas por el sistema. El sistema es accesible vía web y almacena toda la información que maneja en una base de datos. Asimismo, el sistema se apoya en un modelo conceptual u ontología desarrollado previamente para inferir las decisiones adecuadas para las evaluaciones del lenguaje. El sistema incorpora las funciones de gestión de los usuarios del mismo. ABSTRACT This Grade End Project has as fundamental objective the improvement and deployment of a decision support system for evaluating children language development from 0 to 6 years of age. This system is mainly formed by an application designed and built using a modular and reusable software component architecture. The application will be used by pediatricians for evaluating children´s speech development and also by neuro-pediatricians, speech therapists and early childhood intervention team members, for consulting previous evaluations and for validating system´s proposed decision. The system is web based and stores its information in a database. Likewise, the system is supported by a conceptual model or ontology previously developed to infer the appropriate decision for language evaluation. The system also includes user management functions.

A Maut aprroach for reusing domain ontologies on the basis of the NeOn Methodlogy

Knowledge resource reuse has become a popular approach within the ontology engineering field, mainly because it can speed up the ontology development process, saving time and money and promoting the application of good practices. The NeOn Methodology provides guidelines for reuse. These guidelines include the selection of the most appropriate knowledge resources for reuse in ontology development. This is a complex decision-making problem where different conflicting objectives, like the reuse cost, understandability, integration workload and reliability, have to be taken into account simultaneously. GMAA is a PC-based decision support system based on an additive multi-attribute utility model that is intended to allay the operational difficulties involved in the Decision Analysis methodology. The paper illustrates how it can be applied to select multimedia ontologies for reuse to develop a new ontology in the multimedia domain. It also demonstrates that the sensitivity analyses provided by GMAA are useful tools for making a final recommendation.

Knowledge Modelling in Multiagent Systems: The Case of the Management of a National Network

This paper presents the knowledge model of a distributed decision support system, that has been designed for the management of a national network in Ukraine. It shows how advanced Artificial Intelligence techniques (multiagent systems and knowledge modelling) have been applied to solve this real-world decision support problem: on the one hand its distributed nature, implied by different loci of decision-making at the network nodes, suggested to apply a multiagent solution; on the other, due to the complexity of problem-solving for local network administration, it was useful to apply knowledge modelling techniques, in order to structure the different knowledge types and reasoning processes involved. The paper sets out from a description of our particular management problem. Subsequently, our agent model is described, pointing out the local problem-solving and coordination knowledge models. Finally, the dynamics of the approach is illustrated by an example.

Simulating improved combinations tillage-rotation under dryland conditions.

Crop simulation models allow analyzing various tillage-rotation combinations and exploring management scenarios. This study was conducted to test the DSSAT (Decision Support System for Agrotechnology Transfer) modelling system in rainfed semiarid central Spain. The focus is on the combined effect of tillage system and winter cereal-based rotations (cereal/legume/fallow) on the crop yield and soil quality. The observed data come from a 16-year field experiment. The CERES and CROPGRO models, included in DSSAT v4.5, were used to simulate crop growth and yield, and DSSAT- CENTURY was used in the soil organic carbon (SOC) and soil nitrogen (SN) simulations. Genetic coefficients were calibrated using part of the observed data. Field observations showed that barley grain yield was lower for continuous cereal (BB) than for vetch (VB) and fallow (FB) rotations for both tillage systems. The CERES-Barley model also reflected this trend. The model predicted higher yield in the conventional tillage (CT) than in the no tillage (NT) probably due to the higher nitrogen availability in the CT, shown in the simulations. The SOC and SN in the top layer only, were higher in NT than in CT, and decreased with depth in both simulated and observed values. These results suggest that CT-VB and CT-FB were the best combinations for the dry land conditions studied. However, CT presented lower SN and SOC content than NT. This study shows how models can be a useful tool for assessing and predicting crop growth and yield, under different management systems and under specific edapho-climatic conditions. Additional key words: CENTURY model; CERES-Barley; crop simulation models; DSSAT; sequential simula- tion; soil organic carbon.

Estudio del módulo icrp del sistema jrodos de ayuda a la toma de decisiones en emergencias nucleares y radiológicas

Este proyecto se basa en el sistema JRodos de ayuda a la toma de decisiones en tiempo real en caso de emergencias nucleares y radiológicas. Tras una breve descripción del mismo, se presentan los modelos de cálculo que utiliza el sistema y la organización modular en la que se estructura el programa. Concretamente este documento se centra en un módulo desarrollado recientemente denominado ICRP y caracterizado por tener en cuenta todas las vías de exposición a la contaminación radiológica, incluida la vía de la ingestión que no se había tenido en cuenta en los módulos previos. Este modelo nuevo utiliza resultados obtenidos a partir de la cadena de escala local LSMC como datos de entrada, por lo que se lleva a cabo una descripción detalla del funcionamiento y de la ejecución tanto del módulo ICRP como de la cadena previa LSMC. Finalmente, se ejecuta un ejercicio ICRP usando los datos meteorológicos y de término fuentes reales que se utilizaron en el simulacro CURIEX 2013 realizado en el mes de noviembre de 2013 en la Central Nuclear de Almaraz. Se presenta paso a paso la ejecución de este ejercicio y posteriormente se analizan y explican los resultados obtenidos acompañados de elementos visuales proporcionados por el programa. This project is based on the real time online decision support system for nuclear emergency management called JRodos. After a brief description of it, the calculation models used by the system and its modular organization are presented. In particular, this paper focuses on a newly developed module named ICRP. This module is characterized by the consideration of the fact that all terrestrial exposure pathways, including ingestion, which has not been considered in previous modules. This new model uses the results obtained in a previous local scale model chain called LSMC as input. In this document a detailed description of the operation and implementation of both the ICRP module and its previous LSMC chain is presented. To conclude, an ICRP exercise is performed with real meteorological and source term data used in the simulation exercise CURIEX 2013 carried out in the Almaraz Nuclear Power Plant in November 2013. A stepwise realization of this exercise is presented and subsequently the results are deeply explained and analyzed supplemented with illustrations provided by the program.

Improving brain injury cognitive rehabilitation by personalized telerehabilitation services: Guttmann neuropersonal trainer

Cognitive rehabilitation aims to remediate or alleviate the cognitive deficits appearing after an episode of acquired brain injury (ABI). The purpose of this work is to describe the telerehabilitation platform called Guttmann Neuropersonal Trainer (GNPT) which provides new strategies for cognitive rehabilitation, improving efficiency and access to treatments, and to increase knowledge generation from the process. A cognitive rehabilitation process has been modeled to design and develop the system, which allows neuropsychologists to configure and schedule rehabilitation sessions, consisting of set of personalized computerized cognitive exercises grounded on neuroscience and plasticity principles. It provides remote continuous monitoring of patient's performance, by an asynchronous communication strategy. An automatic knowledge extraction method has been used to implement a decision support system, improving treatment customization. GNPT has been implemented in 27 rehabilitation centers and in 83 patients' homes, facilitating the access to the treatment. In total, 1660 patients have been treated. Usability and cost analysis methodologies have been applied to measure the efficiency in real clinical environments. The usability evaluation reveals a system usability score higher than 70 for all target users. The cost efficiency study results show a relation of 1-20 compared to face-to-face rehabilitation. GNPT enables brain-damaged patients to continue and further extend rehabilitation beyond the hospital, improving the efficiency of the rehabilitation process. It allows customized therapeutic plans, providing information to further development of clinical practice guidelines.

Initializing the DSSAT-Century model: inverse calibration of carbon pools from apparent soil N mineralization

The CENTURY soil organic matter model was adapted for the DSSAT (Decision Support System for Agrotechnology Transfer), modular format in order to better simulate the dynamics of soil organic nutrient processes (Gijsman et al., 2002). The CENTURY model divides the soil organic carbon (SOC) into three hypothetical pools: microbial or active material (SOC1), intermediate (SOC2) and the largely inert and stable material (SOC3) (Jones et al., 2003). At the beginning of the simulation, CENTURY model needs a value of SOC3 per soil layer which can be estimated by the model (based on soil texture and management history) or given as an input. Then, the model assigns about 5% and 95% of the remaining SOC to SOC1 and SOC2, respectively. The model performance when simulating SOC and nitrogen (N) dynamics strongly depends on the initialization process. The common methods (e.g. Basso et al., 2011) to initialize SOC pools deal mostly with carbon (C) mineralization processes and less with N. Dynamics of SOM, SOC, and soil organic N are linked in the CENTURY-DSSAT model through the C/N ratio of decomposing material that determines either mineralization or immobilization of N (Gijsman et al., 2002). The aim of this study was to evaluate an alternative method to initialize the SOC pools in the DSSAT-CENTURY model from apparent soil N mineralization (Napmin) field measurements by using automatic inverse calibration (simulated annealing). The results were compared with the ones obtained by the iterative initialization procedure developed by Basso et al., 2011.

The impact of large-scale circulation patterns on summer crop in Iberian Peninsula

Large-scale circulations patterns (ENSO, NAO) have been shown to have a significant impact on seasonal weather, and therefore on crop yield over many parts of the world(Garnett and Khandekar, 1992; Aasa et al., 2004; Rozas and Garcia-Gonzalez, 2012). In this study, we analyze the influence of large-scale circulation patterns and regional climate on the principal components of maize yield variability in Iberian Peninsula (IP) using reanalysis datasets. Additionally, we investigate the modulation of these relationships by multidecadal patterns. This study is performed analyzing long time series of maize yield, only climate dependent, computed with the crop model CERES-maize (Jones and Kiniry, 1986) included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5).

Proposta de um modelo de sistema de apoio à decisão em vendas: uma aplicação

Este trabalho teve por objetivo o desenvolvimento de uma proposta de um modelo de sistema de apoio à decisão em vendas e sua aplicação. O levantamento sobre o perfil das vendas no mercado corporativo - de empresas-para-empresas, as técnicas de vendas, informações necessárias para a realização de uma venda eficiente, tal qual o controle das ações e resultados dos vendedores com a ajuda de relatórios, tudo isso aliado às tecnologias de data warehouse, data mart, OLAP foram essenciais na elaboração de uma proposta de modelo genérico e sua implantação. Esse modelo genérico foi aplicado levando-se em conta uma editora de listas e guias telefônicos hipotética, e foi construído buscando-se suprir os profissionais de vendas com informações que poderão melhorar a efetividade de suas vendas e dar-lhes maior conhecimento sobre seus produtos, clientes, usuários de listas e o mercado como um todo, além de suprir os gerentes de uma ferramenta rápida e confiável de auxílio à análise e coordenação dos esforços de vendas. A possibilidade de visualização rápida, confiável e personalizada das diversas informações permitidas por esse sistema, tal qual o êxito em responder às perguntas de pesquisas apresentadas no trabalho, comprova que essa aplicação poderá ser útil à empresa e em específico aos profissionais de vendas e gerentes tomadores de decisão.

Peanut farmers experience with FARMSCAPE in peninsular India

Researchers and extension officers collaborated with farmers in addressing peanut cropping and sowing decisions using on-farm experiments and cropping systems simulation in the Pollachi region of Tamil Nadu, India. The most influential variable affecting the peanut productivity in this irrigated region regard sowing date. During the 1998-1999 rabi (post rainy) season, three farmers fields in villages in Pollachi region were selected and monitored. The APSIM model was used to simulate the effect of sowing date. The APSIM-Peanut module simulation demonstrated close correspondence with the field observation in predicting yield. The model predicted that December sowing resulted in higher yield than January sowing due to longer pod filling period, and this was confirmed by farmer experience. The farmers and extension officers became comfortable with their role as owners of the collaborative experiments and custodians of the learning environment.

Construction risk management:a quantitative approach

Conventional project management techniques are not always sufficient for ensuring time, cost and quality achievement of large-scale construction projects due to complexity in planning and implementation processes. The main reasons for project non-achievement are changes in scope and design, changes in Government policies and regulations, unforeseen inflation) under-estimation and improper estimation. Projects that are exposed to such an uncertain environment can be effectively managed with the application of risk numagement throughout project life cycle. However, the effectiveness of risk management depends on the technique in which the effects of risk factors are analysed and! or quantified. This study proposes Analytic Hierarchy Process (AHP), a multiple attribute decision-making technique as a tool for risk analysis because it can handle subjective as well as objective factors in decision model that are conflicting in nature. This provides a decision support system (DSS) to project managenumt for making the right decision at the right time for ensuring project success in line with organisation policy, project objectives and competitive business environment. The whole methodology is explained through a case study of a cross-country petroleum pipeline project in India and its effectiveness in project1nana.gement is demonstrated.

Optimizing supply chain waste management through the use of RFID technology

This paper presents a Decision Support System framework based on Constrain Logic Programming and offers suggestions for using RFID technology to improve several of the critical procedures involved. This paper suggests that a widely distributed and semi-structured network of waste producing and waste collecting/processing enterprises can improve their planning both by the proposed Decision Support System, but also by implementing RFID technology to update and validate information in a continuous manner. © 2010 IEEE.