Developing an alternative response format for the script concordance test

Introduction: Clinical reasoning is essential for the practice of medicine. In theory of development of medical expertise it is stated, that clinical reasoning starts from analytical processes namely the storage of isolated facts and the logical application of the ‘rules’ of diagnosis. Then the learners successively develop so called semantic networks and illness-scripts which finally are used in an intuitive non-analytic fashion [1], [2]. The script concordance test (SCT) is an example for assessing clinical reasoning [3]. However the aggregate scoring [3] of the SCT is recognized as problematic [4]. The SCT`s scoring leads to logical inconsistencies and is likely to reflect construct-irrelevant differences in examinees’ response styles [4]. Also the expert panel judgments might lead to an unintended error of measurement [4]. In this PhD project the following research questions will be addressed: 1. How does a format look like to assess clinical reasoning (similar to the SCT but) with multiple true-false questions or other formats with unambiguous correct answers, and by this address the above mentioned pitfalls in traditional scoring of the SCT? 2. How well does this format fulfill the Ottawa criteria for good assessment, with special regards to educational and catalytic effects [5]? Methods: 1. In a first study it shall be assessed whether designing a new format using multiple true-false items to assess clinical reasoning similar to the SCT-format is arguable in a theoretically and practically sound fashion. For this study focus groups or interviews with assessment experts and students will be undertaken. 2. In an study using focus groups and psychometric data Norcini`s and colleagues Criteria for Good Assessment [5] shall be determined for the new format in a real assessment. Furthermore the scoring method for this new format shall be optimized using real and simulated data.

Macroeconomic Rationality and Lucas' Misperceptions Model: Further Evidence from Forty-One Countries

Several researchers have examined Lucas's misperceptions model as well as various propositions derived from it within a cross-section empirical framework. The cross-section approach imposes a single monetary policy regime for the entire period. Our paper innovates on existing tests of those rational expectations propositions by allowing the simultaneous effect of monetary and short run aggregate supply (oil price) shocks on output behavior and the employment of advanced panel econometric techniques. Our empirical findings, for a sample of 41 countries over 1949 to 1999, provide evidence in favor of the majority of rational expectations propositions.

A Multi-agent System for Emergency Decision Support

This paper describes the multi-agent organization of a computer system that was designed to assist operators in decision making in the presence of emergencies. The application was developed for the case of emergencies caused by river floods. It operates on real-time receiving data recorded by sensors (rainfall, water levels, flows, etc.) and applies multi-agent techniques to interpret the data, predict the future behavior and recommend control actions. The system includes an advanced knowledge based architecture with multiple symbolic representation with uncertainty models (bayesian networks). This system has been applied and validated at two particular sites in Spain (the Jucar basin and the South basin).

Nationwide impact and vehicle to grid application of electric vehicles mobility using an activity based model

This paper describes the impact of electric mobility on the transmission grid in Flanders region (Belgium), using a micro-simulation activity based models. These models are used to provide temporal and spatial estimation of energy and power demanded by electric vehicles (EVs) in different mobility zones. The increment in the load demand due to electric mobility is added to the background load demand in these mobility areas and the effects over the transmission substations are analyzed. From this information, the total storage capacity per zone is evaluated and some strategies for EV aggregator are proposed, allowing the aggregator to fulfill bids on the electricity markets.

Building a decision support system with a knowledge modeling tool

Knowledge modeling tools are software tools that follow a modeling approach to help developers in building a knowledge-based system. The purpose of this article is to show the advantages of using this type of tools in the development of complex knowledge-based decision support systems. In order to do so, the article describes the development of a system called SAIDA in the domain of hydrology with the help of the KSM modeling tool. SAIDA operates on real-time receiving data recorded by sensors (rainfall, water levels, flows, etc.). It follows a multi-agent architecture to interpret the data, predict the future behavior and recommend control actions. The system includes an advanced knowledge based architecture with multiple symbolic representation. KSM was especially useful to design and implement the complex knowledge based architecture in an efficient way.

Metodología de Ejecución y Explotación de los Ensayos en Vuelo de Flameo

El flameo o flutter es un fenómeno vibratorio debido a la interacción de fuerzas inerciales, elásticas y aerodinámicas. Consiste en un intercambio de energía, que se puede observar en el cambio de amortiguamientos, entre dos o más modos estructurales, denominados modos críticos, cuyas frecuencias tienden a acercarse (coalescencia de frecuencias). Los ensayos en vuelo de flameo suponen un gran riesgo debido a la posibilidad de una perdida brusca de estabilidad aeroelástica (flameo explosivo) con la posibilidad de destrucción de la aeronave. Además existen otros fenómenos asociados que pueden aparecer como el LCO (Limit Cycle Oscillation) y la interacción con los mandos de vuelo. Debido a esto, se deben llevar a cabo análisis exhaustivos, que incluyen GVT (vibraciones en tierra), antes de comenzar los ensayos en vuelo, y estos últimos deben ser ejecutados con robustos procedimientos. El objetivo de los ensayos es delimitar la frontera de estabilidad sin llegar a ella, manteniéndose siempre dentro de la envolvente estable de vuelo. Para lograrlo se necesitan métodos de predicción, siendo el “Flutter Margin”, el más utilizado. Para saber cuánta estabilidad aeroelástica tiene el avión y lo lejos que está de la frontera de estabilidad (a través de métodos de predicción) los parámetros modales, en particular la frecuencia y el amortiguamiento, son de vital importancia. El ensayo en vuelo consiste en la excitación de la estructura a diferentes condiciones de vuelo, la medición de la respuesta y su análisis para obtener los dos parámetros mencionados. Un gran esfuerzo se dedica al análisis en tiempo real de las señales como un medio de reducir el riesgo de este tipo de ensayos. Existen numerosos métodos de Análisis Modal, pero pocos capaces de analizar las señales procedentes de los ensayos de flameo, debido a sus especiales características. Un método novedoso, basado en la Descomposición por Valores Singulares (SVD) y la factorización QR, ha sido desarrollado y aplicado al análisis de señales procedentes de vuelos de flameo del F-18. El método es capaz de identificar frecuencia y amortiguamiento de los modos críticos. El algoritmo se basa en la capacidad del SVD para el análisis, modelización y predicción de series de datos con características periódicas y en su capacidad de identificar el rango de una matriz, así como en la aptitud del QR para seleccionar la mejor base vectorial entre un conjunto de vectores para representar el campo vectorial que forman. El análisis de señales de flameo simuladas y reales demuestra, bajo ciertas condiciones, la efectividad, robustez, resistencia al ruido y capacidad de automatización del método propuesto. ABSTRACT Flutter involves the interaction between inertial, elastic and aerodynamic forces. It consists on an exchange of energy, identified by change in damping, between two or more structural modes, named critical modes, whose frequencies tend to get closer to each other (frequency coalescence). Flight flutter testing involves high risk because of the possibility of an abrupt lost in aeroelastic stability (hard flutter) that may lead to aircraft destruction. Moreover associated phenomena may happen during the flight as LCO (Limit Cycle Oscillation) and coupling with flight controls. Because of that, intensive analyses, including GVT (Ground Vibration Test), have to be performed before beginning the flights test and during them consistent procedures have to be followed. The test objective is to identify the stability border, maintaining the aircraft always inside the stable domain. To achieve that flutter speed prediction methods have to be used, the most employed being the “Flutter Margin”. In order to know how much aeroelastic stability remains and how far the aircraft is from the stability border (using the prediction methods), modal parameters, in particular frequency and damping are paramount. So flight test consists in exciting the structure at various flight conditions, measuring the response and identifying in real-time these two parameters. A great deal of effort is being devoted to real-time flight data analysis as an effective way to reduce the risk. Numerous Modal Analysis algorithms are available, but very few are suitable to analyze signals coming from flutter testing due to their special features. A new method, based on Singular Value Decomposition (SVD) and QR factorization, has been developed and applied to the analysis of F-18 flutter flight-test data. The method is capable of identifying the frequency and damping of the critical aircraft modes. The algorithm relies on the capability of SVD for the analysis, modelling and prediction of data series with periodic features and also on its power to identify matrix rank as well as QR competence for selecting the best basis among a set of vectors in order to represent a given vector space of such a set. The analysis of simulated and real flutter flight test data demonstrates, under specific conditions, the effectiveness, robustness, noise-immunity and the capability for automation of the method proposed.

Utilizing the Internet of Things to promote energy awareness and efficiency at discrete production processes: Practices and methodology

El actual contexto de fabricación, con incrementos en los precios de la energía, una creciente preocupación medioambiental y cambios continuos en los comportamientos de los consumidores, fomenta que los responsables prioricen la fabricación respetuosa con el medioambiente. El paradigma del Internet de las Cosas (IoT) promete incrementar la visibilidad y la atención prestada al consumo de energía gracias tanto a sensores como a medidores inteligentes en los niveles de máquina y de línea de producción. En consecuencia es posible y sencillo obtener datos de consumo de energía en tiempo real proveniente de los procesos de fabricación, pero además es posible analizarlos para incrementar su importancia en la toma de decisiones. Esta tesis pretende investigar cómo utilizar la adopción del Internet de las Cosas en el nivel de planta de producción, en procesos discretos, para incrementar la capacidad de uso de la información proveniente tanto de la energía como de la eficiencia energética. Para alcanzar este objetivo general, la investigación se ha dividido en cuatro sub-objetivos y la misma se ha desarrollado a lo largo de cuatro fases principales (en adelante estudios). El primer estudio de esta tesis, que se apoya sobre una revisión bibliográfica comprehensiva y sobre las aportaciones de expertos, define prácticas de gestión de la producción que son energéticamente eficientes y que se apoyan de un modo preeminente en la tecnología IoT. Este primer estudio también detalla los beneficios esperables al adoptar estas prácticas de gestión. Además, propugna un marco de referencia para permitir la integración de los datos que sobre el consumo energético se obtienen en el marco de las plataformas y sistemas de información de la compañía. Esto se lleva a cabo con el objetivo último de remarcar cómo estos datos pueden ser utilizados para apalancar decisiones en los niveles de procesos tanto tácticos como operativos. Segundo, considerando los precios de la energía como variables en el mercado intradiario y la disponibilidad de información detallada sobre el estado de las máquinas desde el punto de vista de consumo energético, el segundo estudio propone un modelo matemático para minimizar los costes del consumo de energía para la programación de asignaciones de una única máquina que deba atender a varios procesos de producción. Este modelo permite la toma de decisiones en el nivel de máquina para determinar los instantes de lanzamiento de cada trabajo de producción, los tiempos muertos, cuándo la máquina debe ser puesta en un estado de apagada, el momento adecuado para rearrancar, y para pararse, etc. Así, este modelo habilita al responsable de producción de implementar el esquema de producción menos costoso para cada turno de producción. En el tercer estudio esta investigación proporciona una metodología para ayudar a los responsables a implementar IoT en el nivel de los sistemas productivos. Se incluye un análisis del estado en que se encuentran los sistemas de gestión de energía y de producción en la factoría, así como también se proporcionan recomendaciones sobre procedimientos para implementar IoT para capturar y analizar los datos de consumo. Esta metodología ha sido validada en un estudio piloto, donde algunos indicadores clave de rendimiento (KPIs) han sido empleados para determinar la eficiencia energética. En el cuarto estudio el objetivo es introducir una vía para obtener visibilidad y relevancia a diferentes niveles de la energía consumida en los procesos de producción. El método propuesto permite que las factorías con procesos de producción discretos puedan determinar la energía consumida, el CO2 emitido o el coste de la energía consumida ya sea en cualquiera de los niveles: operación, producto o la orden de fabricación completa, siempre considerando las diferentes fuentes de energía y las fluctuaciones en los precios de la misma. Los resultados muestran que decisiones y prácticas de gestión para conseguir sistemas de producción energéticamente eficientes son posibles en virtud del Internet de las Cosas. También, con los resultados de esta tesis los responsables de la gestión energética en las compañías pueden plantearse una aproximación a la utilización del IoT desde un punto de vista de la obtención de beneficios, abordando aquellas prácticas de gestión energética que se encuentran más próximas al nivel de madurez de la factoría, a sus objetivos, al tipo de producción que desarrolla, etc. Así mismo esta tesis muestra que es posible obtener reducciones significativas de coste simplemente evitando los períodos de pico diario en el precio de la misma. Además la tesis permite identificar cómo el nivel de monitorización del consumo energético (es decir al nivel de máquina), el intervalo temporal, y el nivel del análisis de los datos son factores determinantes a la hora de localizar oportunidades para mejorar la eficiencia energética. Adicionalmente, la integración de datos de consumo energético en tiempo real con datos de producción (cuando existen altos niveles de estandarización en los procesos productivos y sus datos) es esencial para permitir que las factorías detallen la energía efectivamente consumida, su coste y CO2 emitido durante la producción de un producto o componente. Esto permite obtener una valiosa información a los gestores en el nivel decisor de la factoría así como a los consumidores y reguladores. ABSTRACT In today‘s manufacturing scenario, rising energy prices, increasing ecological awareness, and changing consumer behaviors are driving decision makers to prioritize green manufacturing. The Internet of Things (IoT) paradigm promises to increase the visibility and awareness of energy consumption, thanks to smart sensors and smart meters at the machine and production line level. Consequently, real-time energy consumption data from the manufacturing processes can be easily collected and then analyzed, to improve energy-aware decision-making. This thesis aims to investigate how to utilize the adoption of the Internet of Things at shop floor level to increase energy–awareness and the energy efficiency of discrete production processes. In order to achieve the main research goal, the research is divided into four sub-objectives, and is accomplished during four main phases (i.e., studies). In the first study, by relying on a comprehensive literature review and on experts‘ insights, the thesis defines energy-efficient production management practices that are enhanced and enabled by IoT technology. The first study also explains the benefits that can be obtained by adopting such management practices. Furthermore, it presents a framework to support the integration of gathered energy data into a company‘s information technology tools and platforms, which is done with the ultimate goal of highlighting how operational and tactical decision-making processes could leverage such data in order to improve energy efficiency. Considering the variable energy prices in one day, along with the availability of detailed machine status energy data, the second study proposes a mathematical model to minimize energy consumption costs for single machine production scheduling during production processes. This model works by making decisions at the machine level to determine the launch times for job processing, idle time, when the machine must be shut down, ―turning on‖ time, and ―turning off‖ time. This model enables the operations manager to implement the least expensive production schedule during a production shift. In the third study, the research provides a methodology to help managers implement the IoT at the production system level; it includes an analysis of current energy management and production systems at the factory, and recommends procedures for implementing the IoT to collect and analyze energy data. The methodology has been validated by a pilot study, where energy KPIs have been used to evaluate energy efficiency. In the fourth study, the goal is to introduce a way to achieve multi-level awareness of the energy consumed during production processes. The proposed method enables discrete factories to specify energy consumption, CO2 emissions, and the cost of the energy consumed at operation, production and order levels, while considering energy sources and fluctuations in energy prices. The results show that energy-efficient production management practices and decisions can be enhanced and enabled by the IoT. With the outcomes of the thesis, energy managers can approach the IoT adoption in a benefit-driven way, by addressing energy management practices that are close to the maturity level of the factory, target, production type, etc. The thesis also shows that significant reductions in energy costs can be achieved by avoiding high-energy price periods in a day. Furthermore, the thesis determines the level of monitoring energy consumption (i.e., machine level), the interval time, and the level of energy data analysis, which are all important factors involved in finding opportunities to improve energy efficiency. Eventually, integrating real-time energy data with production data (when there are high levels of production process standardization data) is essential to enable factories to specify the amount and cost of energy consumed, as well as the CO2 emitted while producing a product, providing valuable information to decision makers at the factory level as well as to consumers and regulators.

Aplicación distribuida para la monitorización y diagnosis de automóviles

En este proyecto se va desarrollar una aplicación distribuida para la diagnosis y monitorización de automóviles. Se pretende poder realizar estas funciones en prácticamente cualquier automóvil del mercado (con fabricación a partir del año 1996 para el caso de automóviles gasolina y para el año 2000 en el caso de automóviles diésel) de manera remota, aprovechando la conectividad a Internet que actualmente brindan la mayoría de los smartphones. La viabilidad del proyecto reside en la existencia de estándares para la diagnosis de la electrónica del motor. Para poder llevar a cabo esta tarea, se empleará una interfaz de diagnóstico ELM327 bluetooth, que servirá de enlace entre el vehículo y el teléfono móvil del usuario y que a su vez se encargara de enviar los datos que reciba del vehículo a un terminal remoto. De esta manera, se tendrá la aplicación dividida en dos partes: por un lado la aplicación que se ejecuta en el terminal móvil del usuario que actuará como parte servidora, y por el otro la aplicación cliente que se ejecutará en un terminal remoto. También estará disponible una versión de la aplicación servidora para PC. El potencial del proyecto reside en la capacidad de visualización en tiempo real de los parámetros más importantes del motor del vehículo y en la detección de averías gracias a la funcionalidad de lectura de la memoria de averías residente en el vehículo. Así mismo, otras funcionalidades podrían ser implementadas en posteriores versiones de la aplicación, como podría ser el registro de dichos parámetros en una base de datos para su posterior procesado estadístico; de este modo se podría saber el consumo medio, la velocidad media, velocidad máxima alcanzada, tiempo de uso, kilometraje diario o mensual… y un sin fin de posibilidades. ABSTRACT. In this project a distributed application for car monitor and diagnostic is going to be developed. The idea is to be able to connect remotely to almost any car (with production starting in 1996 in the case of petrol engines and production starting in 2000 in case of diesel engines) using the Internet connection available in almost every smartphone. The project is viable because of the existence of standards for engine electronic unit connection. In order to do that, an ELM327 bluetooth interface is going to be used. This interface works as a link between the car and the smartphone, and it is the smartphone which sends the received data from the car to a remote terminal (computer). Thus, the application is divided into two parts: the server which is running on smartphone and the client which is running on a remote terminal. Also there is available a server application for PC. The potential of the project lies in the real-time display data capacity of the most important engine parameters and in the diagnostic capacity based on reading fault memory. In addition, other features could be implemented in later versions of the application, as the capacity of record data for future statistic analysis. By doing this, it is possible to know the average fuel consumption, average speed, maximum speed, time of use, daily or monthly mileage… and an endless number of possibilities.

Bulgarian-Russian games in the energy sector: an outcome is getting closer. OSW Commentary No. 61, 2011-10-5

Bulgaria and Russia are entering the final phase of setting the conditions of their co-operation in the energy sector. A new gas contract is being negotiated because the currently applicable agreements will have expired by the end of 2012. The fate of two major energy projects – whose implementation depends on good co-operation between Sofia and Moscow: the Burgas– –Alexandroupolis oil pipeline and the construction of a Bulgarian nuclear power plant in Belene with Russian participation – is currently being decided. Another issue ever-present on the agenda is the future of the South Stream gas pipeline promoted by Russia, which is to run through Bulgarian territory. The outcome of all the aforementioned discussions and negotiations will determine for years the model of Bulgarian-Russian relations and may strongly affect the shape of the oil, gas and electricity markets in South-Eastern Europe.

The rise of capacity mechanisms: are they inevitable in the European Union? Egmont Paper 80, September 2015

These last years, in multiple Member States, the electricity markets have seen the rapid emergence of Capacity Remuneration Mechanisms (CRMs). They are meant to guarantee the stability of the electricity system in a more uncertain context. The reactions of the European Commission were late towards them. It is thus essential to bring some clarity here, otherwise the legal uncertainty could become a new impediment for investment.

The EU power sector needs long-term price signals. CEPS Special Report No. 135/April 2016

By 2030, half of the EU’s electricity demand will be covered by renewables and will need to be accompanied by flexible conventional back-up resources. Due to the high upfront costs inherent to renewables and the progressively lower running times associated with back-up capacity, the cost of capital will have a proportionately greater impact on total costs than today. This report examines how electricity markets can be designed to provide long-term price signals, thereby reducing the cost of capital for these technologies and allowing for a more efficient transition. It finds that current market arrangements are unable to provide long-term price signals. To address this issue, we argue that a system for long-term contracts with a regulated counterparty could be implemented. A centralised system where capacity or energy or a combination of both is contracted, could be introduced for conventional and renewable capacity, based on a regional adequacy assessment and with a competitive bidding system in place to ensure cost-effectiveness. Member states face a number of legislative barriers while implementing these types of systems, however, which could be reduced by merging legislation and setting EU framework rules for the design of these contractual agreements.

Assessment of competition in the Illinois electric industry in 2002.

A report by the Illinois Commerce Commission required by Section 16-120(b) of the Electric Service Customer Choice and Rate Relief Law of 1997 which directs the Commission to monitor and analyze the state of competition in Illinois electricity markets.

Direct mesh: A multiresolution approach to terrain visualization

Terrain can be approximated by a triangular mesh consisting millions of 3D points. Multiresolution triangular mesh (MTM) structures are designed to support applications that use terrain data at variable levels of detail (LOD). Typically, an MTM adopts a tree structure where a parent node represents a lower-resolution approximation of its descendants. Given a region of interest (ROI) and a LOD, the process of retrieving the required terrain data from the database is to traverse the MTM tree from the root to reach all the nodes satisfying the ROI and LOD conditions. This process, while being commonly used for multiresolution terrain visualization, is inefficient as either a large number of sequential I/O operations or fetching a large amount of extraneous data is incurred. Various spatial indexes have been proposed in the past to address this problem, however level-by-level tree traversal remains a common practice in order to obtain topological information among the retrieved terrain data. A new MTM data structure called direct mesh is proposed. We demonstrate that with direct mesh the amount of data retrieval can be substantially reduced. Comparing with existing MTM indexing methods, a significant performance improvement has been observed for real-life terrain data.