Enhancing Guideline-based decision support with distributed computation through local mobile application

We introduce the need for a distributed guideline-based decision sup-port (DSS) process, describe its characteristics, and explain how we implement-ed this process within the European Union?s MobiGuide project. In particular, we have developed a mechanism of sequential, piecemeal projection, i.e., 'downloading' small portions of the guideline from the central DSS server, to the local DSS in the patient's mobile device, which then applies that portion, us-ing the mobile device's local resources. The mobile device sends a callback to the central DSS when it encounters a triggering pattern predefined in the pro-jected module, which leads to an appropriate predefined action by the central DSS, including sending a new projected module, or directly controlling the rest of the workflow. We suggest that such a distributed architecture that explicitly defines a dialog between a central DSS server and a local DSS module, better balances the computational load and exploits the relative advantages of the cen-tral server and of the local mobile device.

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).

Deployment and validation of a smart system for screening of language disorders in primary care

Neuro-evolutive development from birth until the age of six years is a decisive factor in a child?s quality of life. Early detection of development disorders in early childhood can facilitate necessary diagnosis and/or treatment. Primary-care pediatricians play a key role in its detection as they can undertake the preventive and therapeutic actions requested to promote a child?s optimal development. However, the lack of time and little specific knowledge at primary-care avoid to applying continuous early-detection anomalies procedures. This research paper focuses on the deployment and evaluation of a smart system that enhances the screening of language disorders in primary care. Pediatricians get support to proceed with early referral of language disorders. The proposed model provides them with a decision-support tool for referral actions to trigger essential diagnostic and/or therapeutic actions for a comprehensive individual development. The research was conducted by starting from a sample of 60 cases of children with language disorders. Validation was carried out through two complementary steps: first, by including a team of seven experts from the fields of neonatology, pediatrics, neurology and language therapy, and, second, through the evaluation of 21 more previously diagnosed cases. The results obtained show that therapist positively accepted the system proposal in 18 cases (86%) and suggested system redesign for single referral to a speech therapist in three remaining cases.

Continuous multi-criteria methods for crop and soil conservation planning on La Colacha (Río Cuarto, Province of Cordoba, Argentina)

Agro-areas of Arroyos Menores (La Colacha) west and south of Rand south of R?o Cuarto (Prov. of Cordoba, Argentina) basins are very fertile but have high soil loses. Extreme rain events, inundations and other severe erosions forming gullies demand urgently actions in this area to avoid soil degradation and erosion supporting good levels of agro production. The authors first improved hydrologic data on La Colacha, evaluated the systems of soil uses and actions that could be recommended considering the relevant aspects of the study area and applied decision support systems (DSS) with mathematic tools for planning of defences and uses of soils in these areas. These were conducted here using multi-criteria models, in multi-criteria decision making (MCDM); first of discrete MCDM to chose among global types of use of soils, and then of continuous MCDM to evaluate and optimize combined actions, including repartition of soil use and the necessary levels of works for soil conservation and for hydraulic management to conserve against erosion these basins. Relatively global solutions for La Colacha area have been defined and were optimised by Linear Programming in Goal Programming forms that are presented as Weighted or Lexicographic Goal Programming and as Compromise Programming. The decision methods used are described, indicating algorithms used, and examples for some representative scenarios on La Colacha area are given.

AUTOFLY-Aid: Flight Deck Automation Support with Dynamic 4D Trajectory Management for Responsive and Adaptive Airborne Collision Avoidance

AUTOFLY-Aid Project aims to develop and demonstrate novel automation support algorithms and tools to the flight crew for flight critical collision avoidance using “dynamic 4D trajectory management”. The automation support system is envisioned to improve the primary shortcomings of TCAS, and to aid the pilot through add-on avionics/head-up displays and reality augmentation devices in dynamically evolving collision avoidance scenarios. The main theoretical innovative and novel concepts to be developed by AUTOFLY-Aid project are a) design and development of the mathematical models of the full composite airspace picture from the flight deck’s perspective, as seen/measured/informed by the aircraft flying in SESAR 2020, b) design and development of a dynamic trajectory planning algorithm that can generate at real-time (on the order of seconds) flyable (i.e. dynamically and performance-wise feasible) alternative trajectories across the evolving stochastic composite airspace picture (which includes new conflicts, blunder risks, terrain and weather limitations) and c) development and testing of the Collision Avoidance Automation Support System on a Boeing 737 NG FNPT II Flight Simulator with synthetic vision and reality augmentation while providing the flight crew with quantified and visual understanding of collision risks in terms of time and directions and countermeasures.

Consolidation of a wsn and minimax method to rapidly neutralise intruders in strategic installations

Due to the sensitive international situation caused by still-recent terrorist attacks, there is a common need to protect the safety of large spaces such as government buildings, airports and power stations. To address this problem, developments in several research fields, such as video and cognitive audio, decision support systems, human interface, computer architecture, communications networks and communications security, should be integrated with the goal of achieving advanced security systems capable of checking all of the specified requirements and spanning the gap that presently exists in the current market. This paper describes the implementation of a decision system for crisis management in infrastructural building security. Specifically, it describes the implementation of a decision system in the management of building intrusions. The positions of the unidentified persons are reported with the help of a Wireless Sensor Network (WSN). The goal is to achieve an intelligent system capable of making the best decision in real time in order to quickly neutralise one or more intruders who threaten strategic installations. It is assumed that the intruders’ behaviour is inferred through sequences of sensors’ activations and their fusion. This article presents a general approach to selecting the optimum operation from the available neutralisation strategies based on a Minimax algorithm. The distances among different scenario elements will be used to measure the risk of the scene, so a path planning technique will be integrated in order to attain a good performance. Different actions to be executed over the elements of the scene such as moving a guard, blocking a door or turning on an alarm will be used to neutralise the crisis. This set of actions executed to stop the crisis is known as the neutralisation strategy. Finally, the system has been tested in simulations of real situations, and the results have been evaluated according to the final state of the intruders. In 86.5% of the cases, the system achieved the capture of the intruders, and in 59.25% of the cases, they were intercepted before they reached their objective.