This paper describes the format of monitoring data files that are collected for external measuring sites and at laboratory experiments at the Institute for Building Climatology (IBK). The Monitoring Data Files are containers for storing time series or event driven data collected as input for transient heat and moisture transport simulations. Further applications are the documentation of real world behaviour, laboratory experiments or the collection of validation data sets for simulation results ( whole building / energy consumption / HAM ). The article also discusses the application interface towards measurement data verification tools as well as data storage solutions that can be used to archive measurement data files conveniently and efficiently.

Temperaturprognoser är av stor betydelse för många i dagens samhälle, både privatpersoner och diverse olika sektorer. Förväntan på att prognoserna håller hög träffsäkerhet är stor och god kvalitet på dessa är viktigt av många olika aspekter. De numeriska vädermodellerna, som används för att göra väderprognoser, har brister som i stort sätt alltid leder till systematiska fel i prognoserna. Bristerna beror exempelvis på dålig representation av atmosfärens fysikaliska processer och för att korrigera och reducera dessa fel efterbehandlas prognoserna med olika metoder, så kallad post-processing. För att minimera de systematiska felen och öka träffsäkerheten för prognoserna pågår ständigt en utveckling och förbättring av både modellerna och post-processingmetodiken. Uppföljning och utvärdering av prognoser är av stor nytta för denna utveckling som ska leda till minimering av prognosfel och optimering av modell och metodik. I denna studie har temperaturprognosdata, med prognoslängd 0-12 timmar, från Sveriges Meteorologiska och Hydrologiska Institut (SMHI) och norska Meteorologisk institutt (met.no) jämförts med uppmätta värden för 2 m-temperatur. Observerad temperaturdata från 22 olika synoptiska väderstationer på platser utspridda över hela Sverige har använts i studien och perioden som studien är baserad på är 20 februari till 31 maj 2018. Statistiska mått, med mest fokus på korrelationskoefficient och bias, har analyserats och jämförts för att undersöka likheter och skillnader i temperaturprognoserna från de två olika väderinstituten. Resultaten av studien visar att temperaturprognoserna från met.no generellt sett har något högre träffsäkerhet än SMHI:s för de allra flesta av de 22 geografiska platserna. Båda institutens prognoser har för flertalet av stationerna i fjällen samt norra Sverige generellt sett lägre träffsäkerhet för februari än för mars, april och maj. / Temperature forecasts are of great importance for many different reasons in today's society, both for private individuals and various sectors. The expectations that the forecasts maintain high accuracy and good quality is important in many different aspects. The weather models, which are used to make the forecasts, have deficiencies which in large part always lead to systematic errors in the forecasts. The deficiencies are for example, due to poor representation of the physical processes of the atmosphere and to correct and reduce these errors, the forecasts are post-processed by various methods. To minimize the systematic errors and increase the accuracy of the forecasts, there is an ongoing development and improvement of both the models and the post-processing methods. Evaluation of forecasts is of great benefit to this development, which will lead to minimization of forecast errors and optimization of the model and methodology. In this study, temperature forecast data, with a forecast length of 0-12 hours, from the Swedish Meteorological and Hydrological Institute (SMHI) and the Norwegian Meteorological Institute (met.no) were compared with measured 2 m-temperature values. Observed temperature data from 22 different weather stations in locations scattered all over Sweden have been used in the study and the period on which the study is based is from the 20th of February to 31st of May, 2018. Different statistical measures have been analyzed and compared to examine similarities and differences in temperature forecasts from the two different weather institutes. The results of the study show that met.no's temperature forecasts generally have slightly higher accuracy than SMHI's for most of the 22 locations. For any of the stations in the mountains and northern Sweden forecasts from both institutes generally have lower accuracy for February than March, April and May.

This thesis describes methods for lighting calculations of large scenes used in modern computer games. Forward shading and deferred shading methods are discussed and compared. Capabilities of raytracing are shortly described. There are some information about various methods for casting shadows, simulation of particle systems and applying post-processing effects. In the end there is a design of architecture for rendering complex scenes with use of XNA and description of implementation used in resulting game.

This paper describes the format of monitoring data files that are collected for external measuring sites and at laboratory experiments at the Institute for Building Climatology (IBK). The Monitoring Data Files are containers for storing time series or event driven data collected as input for transient heat and moisture transport simulations. Further applications are the documentation of real world behaviour, laboratory experiments or the collection of validation data sets for simulation results ( whole building / energy consumption / HAM ). The article also discusses the application interface towards measurement data verification tools as well as data storage solutions that can be used to archive measurement data files conveniently and efficiently.:1 Introduction 2 File Name Conventions 3 Headers 3.1 Specifics on Time Series Header Files 3.2 Specifics s on Event Driven Header Files 4 Data Section Format Description 5 SI Unit Strings 6 Competition Law Advice 7 Liability for external Links

ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada / Networked based technologies (i.e. TCP/IP) have come to play an important role in the evolution of telemetry post processing services. A paramount issue when using networking to access/move telemetry data is security. In past years papers have focused on individual security technologies and how they could be used to secure telemetry data. This paper will review currently available network based security technologies, update readers on enhancements, and discuss their appropriate uses in the various phases of telemetry post-processing and analysis activities.

Phase measuring Profilometry (PMP) is an important technique used in 3D data acquisition. Many variations of the PMP technique exist in the research world. The technique involves projecting phase shifted versions of sinusoidal patterns with known frequency. The 3D information is obtained from the amount of phase deviation that the target object introduces in the captured patterns. Using patterns based on single frequency result in projecting a large number of patterns necessary to achieve minimal reconstruction errors. By using more than one frequency, that is multi-frequency, the error is reduced with the same number of total patterns projected as in the single frequency case. The first major goal of our research work is to minimize the error in 3D reconstruction for a given scan time using multiple frequency sine wave patterns. A mathematical model to estimate the optimal frequency values and the number of phase shift patterns based on stochastic analysis is given. Experiments are conducted by implementing the mathematical model to estimate the optimal frequencies and the number of patterns projected for each frequency level used. The reduction in 3D reconstruction errors and the quality of the 3D data obtained shows the validity of the proposed mathematical model. The second major goal of our research work is the implementation of a post-processing algorithm based on stereo correspondence matching adapted to structured light illumination. Composite pattern is created by combining multiple phase shift patterns and using principles from communication theory. Composite pattern is a novel technique for obtaining real time 3D depth information. The depth obtained by the demodulation of captured composite patterns is generally noisy compared to the multi-pattern approach. In order to obtain realistic 3D depth information, we propose a post-processing algorithm based on dynamic programming. Two different communication theory principles namely, Amplitude Modulation (AM) and Double Side Band Suppressed Carrier (DSBSC) are used to create the composite patterns. As a result of this research work, we developed a series of low-cost structured light scanners based on the multi-frequency PMP technique and tested them for their accuracy in different 3D applications. Three such scanners with different camera systems have been delivered to Toyota for vehicle assembly line inspection. All the scanners use off the shelf components. Two more scanners namely, the single fingerprint and the palmprint scanner developed as part of the Department of Homeland Security grant are in prototype and testing stages.

A demanda por métodos de análise e descoberta de conhecimento em grandes bases de dados tem fortalecido a pesquisa em Mineração de Dados. Dentre as tarefas associadas a essa área, tem-se Regras de Associação. Vários algoritmos foram propostos para tratamento de Regras de Associação, que geralmente tˆem como resultado um elevado número de regras, tornando o Pós-processamento do conhecimento uma etapa bastante complexa e desafiadora. Existem medidas para auxiliar essa etapa de avaliação de regras, porém existem lacunas referentes a inexistência de um método intuitivo para priorizar e selecionar regras. Além disso, não é possível encontrar metodologias específicas para seleção de regras considerando mais de uma medida simultaneamente. Esta tese tem como objetivo a proposição, desenvolvimento e implementação de uma metodologia para o Pós-processamento de Regras de Associação. Na metodologia proposta, pequenos grupos de regras identificados como potencialmente interessantes são apresentados ao usuário especialista para avaliação. Para tanto, foram analisados métodos e técnicas utilizadas em Pós-processamento de conhecimento, medidas objetivas para avaliação de Regras de Associação e algoritmos que geram regras. Dessa perspectiva foram realizados experimentos para identificar o potencial das medidas a serem empregadas como filtros de Regras de Associação. Uma avaliação gráfica apoiou o estudo das medidas e a especificação da metodologia proposta. Aspecto inovador da metodologia proposta é a utilização do método de Pareto e a combinação de medidas para selecionar as Regras de Associação. Por fim foi implementado um ambiente para avaliação de Regras de Associação, denominado ARInE, viabilizando o uso da metodologia proposta. / The large demand of methods for knowledge discovery and analysis in large databases has continously increased the research in data mining area. Among the tasks associated to this area, one can find Association Rules. Several algorithms have been proposed for treating Association Rules. However, these algorithms give as results a huge amount of rules, making the knowledge post-processing phase very complex and challeging. There are several measures that can be used in this evaluation phase, but there are also some limitations regarding to the ausence of an intuitive method to rank and select rules. Moreover, it is not possible to find especific methodologies for selecting rules, considering more than one measure simultaneously. This thesis has as objective the proposal, development and implementation of a postprocessing methodology for Association Rules. In the proposed methodology, small groups of rules, which have been identified as potentialy interesting, are presented to the expert for evaluation. In this sense, methods and techniques for knowledge post-processing, objective measures for rules evaluation, and Association Rules algorithms have been analized. From this point of view, several experiments have been realized for identifying the potential of such measures to be used to filter Association Rules. The study of measures and the specification of the proposed methodology have been supported by a graphical evaluation. The novel aspect of the proposed methodology consists on using the Pareto’s method and combining measures for selecting Association Rules. Finally, an enviroment for evaluating Association Rules, named as ARInE, has been implemented according to the proposed methodology.

Mineração de Dados é um processo de natureza iterativa e interativa responsável por identificar padrões em grandes conjuntos de dados, objetivando extrair conhecimento válido, útil e inovador a partir desses. Em Mineração de Dados, Regras de Associação é uma técnica que consiste na identificação de padrões intrínsecos ao conjunto de dados. Essa técnica tem despertado grande interesse nos pesquisadores de Mineração de Dados e nas organizações, entretanto, a mesma possui o inconveniente de gerar grande volume de conhecimento no formato de regras, dificultando a análise e interpretação dos resultados pelo usuário. Nesse contexto, este trabalho tem como objetivo principal generalizar e eliminar Regras de Associação não interessantes e/ou redundantes, facilitando, dessa maneira, a análise das regras obtidas com relação à compreensibilidade e tamanho do conjunto de regras. A generalização das Regras de Associação é realizada com o uso de taxonomias. Entre os principais resultados deste trabalho destacam-se a proposta e a implementação do algoritmo GART e do módulo computacional RulEE-GAR. O algoritmo GART (Generalization of Association Rules using Taxonomies - Generalização de Regras de Associação usando Taxonomias) utiliza taxonomias para generalizar Regras de Associação. Já o módulo RulEE-GAR, além de facilitar o uso do algoritmo GART durante a identificação de taxonomias e generalização de regras, provê funcionalidades para analisar as Regras de Associação generalizadas. Os experimentos realizados, neste trabalho, mostraram que o uso de taxonomias na generalização de Regras de Associação pode reduzir o volume de um conjunto de regras. / Data Mining refers to the process of finding patterns in large data sets. The Association Rules in Data Mining try to identify intrinsic behaviors of the data set. This has motivated researchers of Data Mining and organizations. However, the Association Rules have the inconvenient of generating a great amount of knowledge in the form of rules. This makes the analysis and interpretation of the results difficult for the user. Taking this into account, the main objective of this research is the generalization and elimination of non-interesting and/or redundant Association Rules. This facilite the analysis of the rules with respect to the compreensibility and the size of the rule set. The generalization is realized using taxonomies. The main results of this research are the proposal and the implementation of the algorithm GART and of the computational module RulEE-GAR. The algorithm GART (Generalization of Association Rules using Taxonomies) uses taxonomies to generalize Association Rules. The module RulEE-GAR facilitates the use of the algorithm GART in the identification of taxonomies and generalization of rules and provide functionalities to the analysis of the generalized Association Rules. The results of experiments showed that the employment of taxonomies in the generalization of Association Rules can reduce the size of a rule set.

Para o sucesso do processo de mineração de dados é importante que o conhecimento extraí?do seja compreensível e interessante para que o usuário final possa utilizá-lo em um sistema inteligente ou em processos de tomada de decisão. Um grande problema, porém, é identificado quando a tarefa de mineração de dados denominada associação é utilizada: a geração de um grande volume de regras. Taxonomias podem ser utilizadas para facilitar a análise e interpretação das regras de associação, uma vez que as mesmas provêm uma visão de como os itens podem ser hierarquicamente classificados. Em função dessa hierarquia é possível obter regras mais gerais que representem um conjunto de itens. Dentro desse contexto, neste trabalho é apresentada uma metodologia para construção semi-automática de taxonomias, que inclui procedimentos automáticos e interativos para a realização dessa tarefa. Essa combinação possibilita a utilização do conhecimento do especialista e também o auxilia na identificação de grupos. Entre os principais resultados deste trabalho, pode-se destacar a proposta e implementação do algoritmo SACT (Semi-automatic Construction of Taxonomies - Construção Semi-automática de Taxonomias), que provê a utilização da metodologia proposta. Para viabilizar a utilização do algoritmo, foi desenvolvido o módulo computacional RulEESACT. Com o objetivo de viabilizar e analisar a qualidade da metodologia proposta e do módulo desenvolvido, foi realizado um estudo de caso no qual foram construída taxonomias para duas bases de dados utilizando o RulEE-SACT. Uma das taxonomias foi analisada e validada por uma especialista do domínio. Posteriormente, as taxonomias e as bases de transações foram fornecidas para dois algoritmos de generalização de regras de associação a fim de analisar a aplicação das taxonomias geradas / I n the data mining process it is important that the extracted knowledge is understandable and interesting to the final user, so it can be used to support in the decision making. However, the data mining task named association has one problem: it generates a big volume of rules. Taxonomies can be used to facilitate the analysis and interpretation of association rules, because they provide an hierarchical vision of the items. This hierarchy enables the obtainment of more general rules, which represent a set of items. In this context, a methodology to semi-automatically construct taxonomies is proposed in this work. This methodology includes automatic and interactives procedures in order to construct the taxonomies, using the specialist?s knowledge and also assisting in the identification of groups. One of the main results of this work is the proposal and implementation of the SACT (Semi-automatic Construction of Taxonomies) algorithm, which provides the use of the proposed methodology. In order to facilitate the use of this algorithm, a computational module named RulEE-SACT was developed. Aiming to analyze the viability and quality of the proposed methodology and the developed module, a case study was done. In this case study, taxonomies of two databases were constructed using the RulEE-SACT. One of them was analyzed and validated by a domain specialist. Then the taxonomies and the databases were supplied to two algorithms which generalize association rules, aiming to analyze the use of the generated taxonomies

Une des pistes majeures pour obtenir des turbines à gaz moins polluantes est l'utilisation de chambres de combustion fonctionnant en régime prémélangé pauvre. Cependant, dans de tels régimes de fonctionnement, la flamme obtenue est cependant plus facilement sujette aux instabilités thermo-acoustiques.Dans cette thèse, un brûleur étagé swirlé fonctionnant au propane a été employé pour illustrer une méthode d'analyse de la combustion prémélangée. Cette installation a été étudiée à l'aide de diagnostics classiques (micros, PLIF, film à haute cadence de la flamme).La stratégie de post-traitement développée dans cette thèse utilise par contre des outils eux aussi classiques (PSD, moyenne de phase) mais aussi une méthode d'analyse avancée, la Décomposition en Modes Dynamiques. Celle-ci est notamment étudiée em détail afin d'en cerner les avantages et les limitations dans le cadre de l'analye des instabilités de combustion. / One of the major ways of reducing pollutant emissions in gas turbines is using combustion chambers with lean premixed mixtures. However, in such operating conditions the flame is more susceptible to thermo-acoustic instabilities. In the present work, a propane-fed swirled burner using two injection stages is used to illustrate a post-processing strategy for premixed combustion analysis. This model burner has been studied using classic diagnostics (microphones, PLIF, highspeed imaging).The strategy developed in the present work uses both classic postprocessing tools (PSD, phase averaging) and an advanced method, the Dynamic Mode Decomposition. In particular, this method is studied in detail and compared to more lassic ones in order to clearly point its advantages as well as its shortcomings when used to study combustion instabilities.