Configuration Analysis for Large Scale Feature Models: Towards Speculative-Based Solutions

Los sistemas de alta variabilidad son sistemas de software en los que la gestión de la variabilidad es una actividad central. Algunos ejemplos actuales de sistemas de alta variabilidad son el sistema web de gesión de contenidos Drupal, el núcleo de Linux, y las distribuciones Debian de Linux. La configuración en sistemas de alta variabilidad es la selección de opciones de configuración según sus restricciones de configuración y los requerimientos de usuario. Los modelos de características son un estándar “de facto” para modelar las funcionalidades comunes y variables de sistemas de alta variabilidad. No obstante, el elevado número de componentes y configuraciones que un modelo de características puede contener hacen que el análisis manual de estos modelos sea una tarea muy costosa y propensa a errores. Así nace el análisis automatizado de modelos de características con mecanismos y herramientas asistidas por computadora para extraer información de estos modelos. Las soluciones tradicionales de análisis automatizado de modelos de características siguen un enfoque de computación secuencial para utilizar una unidad central de procesamiento y memoria. Estas soluciones son adecuadas para trabajar con sistemas de baja escala. Sin embargo, dichas soluciones demandan altos costos de computación para trabajar con sistemas de gran escala y alta variabilidad. Aunque existan recusos informáticos para mejorar el rendimiento de soluciones de computación, todas las soluciones con un enfoque de computación secuencial necesitan ser adaptadas para el uso eficiente de estos recursos y optimizar su rendimiento computacional. Ejemplos de estos recursos son la tecnología de múltiples núcleos para computación paralela y la tecnología de red para computación distribuida. Esta tesis explora la adaptación y escalabilidad de soluciones para el analisis automatizado de modelos de características de gran escala. En primer lugar, nosotros presentamos el uso de programación especulativa para la paralelización de soluciones. Además, nosotros apreciamos un problema de configuración desde otra perspectiva, para su solución mediante la adaptación y aplicación de una solución no tradicional. Más tarde, nosotros validamos la escalabilidad y mejoras de rendimiento computacional de estas soluciones para el análisis automatizado de modelos de características de gran escala. Concretamente, las principales contribuciones de esta tesis son: • Programación especulativa para la detección de un conflicto mínimo y 1 2 preferente. Los algoritmos de detección de conflictos mínimos determinan el conjunto mínimo de restricciones en conflicto que son responsables de comportamiento defectuoso en el modelo en análisis. Nosotros proponemos una solución para, mediante programación especulativa, ejecutar en paralelo y reducir el tiempo de ejecución de operaciones de alto costo computacional que determinan el flujo de acción en la detección de conflicto mínimo y preferente en modelos de características de gran escala. • Programación especulativa para un diagnóstico mínimo y preferente. Los algoritmos de diagnóstico mínimo determinan un conjunto mínimo de restricciones que, por una adecuada adaptación de su estado, permiten conseguir un modelo consistente o libre de conflictos. Este trabajo presenta una solución para el diagnóstico mínimo y preferente en modelos de características de gran escala mediante la ejecución especulativa y paralela de operaciones de alto costo computacional que determinan el flujo de acción, y entonces disminuir el tiempo de ejecución de la solución. • Completar de forma mínima y preferente una configuración de modelo por diagnóstico. Las soluciones para completar una configuración parcial determinan un conjunto no necesariamente mínimo ni preferente de opciones para obtener una completa configuración. Esta tesis soluciona el completar de forma mínima y preferente una configuración de modelo mediante técnicas previamente usadas en contexto de diagnóstico de modelos de características. Esta tesis evalua que todas nuestras soluciones preservan los valores de salida esperados, y también presentan mejoras de rendimiento en el análisis automatizado de modelos de características con modelos de gran escala en las operaciones descrita

CLM-Assembly 2018 Conference proceedings

From September 18 to 21, the 13th General Assembly of the CLM community (https://www.clm-community.eu/) took place at Campus South of the Karlsruhe Institute of Technology. Nearly 60 international participants learned over these four days about the latest results and developments of the COSMO-CLM and ICON model systems in 23 plenary lectures and 21 posters. The premises in building 10.81 (“altes Ingenieursgebäude”) also offered the opportunity to engage in parallel sessions in in-depth discussions in the individual working groups of the CLM community. The present conference proceedings hold all the abstracts of the oral and poster presentations during the assembly and gives a good insight in the broad work and applications of the CLM Community. Herewith, the organizing team would like to sincerely thank • the participants of the conference, • the CLM working group leaders, • the scientific advisory board, • the catering service, • the janitors of building 10.81, • the student assistants, and • all others involved in organizing the assembly

Towards Flexible and Cognitive Production—Addressing the Production Challenges

Globalization in the field of industry is fostering the need for cognitive production systems. To implement modern concepts that enable tools and systems for such a cognitive production system, several challenges on the shop floor level must first be resolved. This paper discusses the implementation of selected cognitive technologies on a real industrial case-study of a construction machine manufacturer. The partner company works on the concept of mass customization but utilizes manual labour for the high-variety assembly stations or lines. Sensing and guidance devices are used to provide information to the worker and also retrieve and monitor the working, with respecting data privacy policies. Next, a specified process of data contextualization, visual analytics, and causal discovery is used to extract useful information from the retrieved data via sensors. Communications and safety systems are explained further to complete the loop of implementation of cognitive entities on a manual assembly line. This deepened involvement of cognitive technologies are human-centered, rather than automated systems. The explained cognitive technologies enhance human interaction with the processes and ease the production methods. These concepts form a quintessential vision for an effective assembly line. This paper revolutionizes the existing industry 4.0 with an even-intensified human–machine interaction and moving towards cognitivity

Towards customization : Evaluation of integrated sales, product, and production configuration

Acknowledgement We are grateful to the anonymous reviewers for their constructive comments, which helped us improve both the quality and presentation of the paper.Peer reviewedPostprin

Magnetic loop emergence within a granule

We investigate the temporal evolution of magnetic flux emerging within a granule in the quiet-Sun internetwork at disk center. We combined IR spectropolarimetry performed in two Fe I lines at 1565 nm with speckle-reconstructed G-band imaging. We determined the magnetic field parameters by a LTE inversion of the full Stokes vector using the SIR code, and followed their evolution in time. To interpret the observations, we created a geometrical model of a rising loop in 3D. The relevant parameters of the loop were matched to the observations where possible. We then synthesized spectra from the 3D model for a comparison to the observations. We found signatures of magnetic flux emergence within a growing granule. In the early phases, a horizontal magnetic field with a distinct linear polarization signal dominated the emerging flux. Later on, two patches of opposite circular polarization signal appeared symmetrically on either side of the linear polarization patch, indicating a small loop-like structure. The mean magnetic flux density of this loop was roughly 450 G, with a total magnetic flux of around 3x10^17 Mx. During the ~12 min episode of loop occurrence, the spatial extent of the loop increased from about 1 to 2 arcsec. The middle part of the appearing feature was blueshifted during its occurrence, supporting the scenario of an emerging loop. The temporal evolution of the observed spectra is reproduced to first order by the spectra derived from the geometrical model. The observed event can be explained as a case of flux emergence in the shape of a small-scale loop.Comment: 10 pages, 13 figures; accepted for Astronomy and Astrophysics; ps and eps figures in full resolution are available at http://www.astro.sk/~koza/figures/aa2009_loop

Research priorities in immersive learning technology: the perspectives of the iLRN community

This paper presents the perspectives of the immersive learning research network community on the relevance of various challenges to the adoption of immersive learning technology, along three dimensions: access, content production, and deployment. Using a previously validated questionnaire, we surveyed this community of 622 researchers and practitioners during the summer of 2018, attaining 54 responses. By ranking the challenges individually and within each dimension, the results point towards higher relevance being placed on aspects that link immersive environments with learning management systems and pedagogical tasks, alongside aspects that empower non-technical users (educational actors) to produce interactive stories, objects, and characters.The work presented herein has been partially funded under the European H2020 program H2020-ICT-2015, BEACONING project, grant agreement nr. 687676.info:eu-repo/semantics/acceptedVersio

Accuracy Characterization of a MEMS Accelerometer for Vibration Monitoring in a Rotating Framework

Active and passive vibration control systems are of paramount importance in many engineering applications. If an external load excites a structure’s resonance and the damping is too low, detrimental events, such as crack initiation, growth and, in the worst case, fatigue failure, can be entailed. Damping systems can be commonly found in applications such as industrial machines, vehicles, buildings, turbomachinery blades, and so forth. Active control systems usually achieve higher damping effectiveness than passive ones, but they need a sensor to detect the working conditions that require damping system activation. Recently, the development of such systems in rotating structures has received considerable interest among designers. As a result, the development of vibration monitoring equipment in rotating structures is also a topic of particular interest. In this respect, a reliable, inexpensive and wireless monitoring system is of utmost importance. Typically, optical systems are used to measure vibrations, but they are expensive and require rather complex processing algorithms. In this paper, a wireless system based on a commercial MEMS accelerometer is developed for rotating blade vibration monitoring. The proposed system measurement accuracy was assessed by means of comparison with a reference wired measurement setup based on a mini integrated circuit piezoelectric (ICP) accelerometer adapted for data acquisition in a rotating frame. Both the accelerometers were mounted on the tip of the blade and, in order to test the structure under different conditions, the first four blade resonances were excited by means of piezoelectric actuators, embedded in a novel experimental setup. The frequency and amplitude of acceleration, simultaneously measured by the reference and MEMS sensors, were compared with each other in order to investigate the viability and accuracy of the proposed wireless monitoring system. The rotor angular speed was varied from 0 to 300 rpm, and the data acquisitions were repeated six times for each considered condition. The outcomes reveal that the wireless measurement system may be successfully used for vibration monitoring in rotating blades

Measurement of head-related transfer functions : A review

A head-related transfer function (HRTF) describes an acoustic transfer function between a point sound source in the free-field and a defined position in the listener's ear canal, and plays an essential role in creating immersive virtual acoustic environments (VAEs) reproduced over headphones or loudspeakers. HRTFs are highly individual, and depend on directions and distances (near-field HRTFs). However, the measurement of high-density HRTF datasets is usually time-consuming, especially for human subjects. Over the years, various novel measurement setups and methods have been proposed for the fast acquisition of individual HRTFs while maintaining high measurement accuracy. This review paper provides an overview of various HRTF measurement systems and some insights into trends in individual HRTF measurements