3,036 research outputs found

    The dual-frequency scatterometer reexamined

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    The utility of dual frequency scatterometers in measuring ocean wave directional spectra can be increased by adding third frequency to the system. The background which effectively limits signal detectability in dual frequency operation can be made a part of the signal through the addition of this third frequency. Signal detectability is limited only by system thermal noise and space based operation becomes more feasible

    Study of an engine flow diverter system for a large scale ejector powered aircraft model

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    Requirements were established for a conceptual design study to analyze and design an engine flow diverter system and to include accommodations for an ejector system in an existing 3/4 scale fighter model equipped with YJ-79 engines. Model constraints were identified and cost-effective limited modification was proposed to accept the ejectors, ducting and flow diverter valves. Complete system performance was calculated and a versatile computer program capable of analyzing any ejector system was developed

    A PC parallel port button box provides millisecond response time accuracy under Linux

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    For psychologists, it is sometimes necessary to measure people's reaction times to the nearest millisecond. This article describes how to use the PC parallel port to receive signals from a button box to achieve millisecond response time accuracy. The workings of the parallel port, the corresponding port addresses, and a simple Linux program for controlling the port are described. A test of the speed and reliability of button box signal detection is reported. If the reader is moderately familiar with Linux, this article should provide sufficient instruction for him or her to build and test his or her own parallel port button box. This article also describes how the parallel port could be used to control an external apparatus

    Millisecond accuracy video display using OpenGL under Linux

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    To measure people’s reaction times to the nearest millisecond, it is necessary to know exactly when a stimulus is displayed. This article describes how to display stimuli with millisecond accuracy on a normal CRT monitor, using a PC running Linux. A simple C program is presented to illustrate how this may be done within X Windows using the OpenGL rendering system. A test of this system is reported that demonstrates that stimuli may be consistently displayed with millisecond accuracy. An algorithm is presented that allows the exact time of stimulus presentation to be deduced, even if there are relatively large errors in measuring the display time

    Spatial algorithm for detecting disease outbreaks in Australia

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    La detección temprana de brotes de enfermedades es esencial de cara a una intervención pronta en problemas de salud pública. Actualmente en Australia, las enfermedades notificables son recogidas y almacenadas, y referenciadas geográfica y temporalmente. Sin embargo, el proceso para la búsqueda de brotes de enfermedad sobre escalas espaciales distintas no está bien definido. Los brotes son de detección difícil. Algunas enfermedades aparecen relativamente rápido, mientras otras requieren más tiempo para su incubación y sólo se hacen evidentes sobre largos intervalos temporales. En la práctica, los epidemiólogos combinan diferentes conjuntos de evidencias para determinar la probabilidad de la existencia de un brote. Gracias al progresivo incremento de disponibilidad de bases de datos electrónicas y de los Sistemas de Información Geográfica (SIG), el potencial para la utilización de técnicas de análisis espacial para la visualización, exploración y modelado de notificaciones de enfermedades para la detección temprana de brotes, es hoy mayor que en el pasado. En este artículo, los autores presentan un algoritmo que emplea bases de datos de la administración, análisis espacial y SIG para la detección de clusters de enfermedades en el Estado de Australia Occidental. El algoritmo revisa los códigos postales de forma rutinaria hasta encontrar un número de casos que supera los valores que serían esperados en la región considerada. El algoritmo está diseñado para su uso por profesionales de la salud pública para asistir en la identificación y seguimiento de clusters en tiempo real.The early detection of disease outbreaks is essential for early intervention in potential public health problems. Currently in Australia, disease notifications are recorded, temporally and geographically referenced; however, the process of searching for outbreaks over different spatial scales is not well defined. Disease outbreaks are difficult to detect. Some diseases appear relatively rapidly, while others take time to gestate and become apparent over long time intervals. In practice, epidemiologists combine different sets of evidence in different ways and apply reasoning to determine the likelihood of an outbreak. With an increase in the availability of electronic health-care data and geographic information systems (GIS), there is great potential to use spatial analysis techniques for the visualisation, exploration and modelling of disease notifications for the early detection of disease outbreaks. In this paper, the authors present an algorithm that uses administrative databases, spatial analysis and GIS for the detection of disease clusters in Western Australia (WA). The algorithm routinely tests administrative areas (postcodes) and highlights the areas in which counts exceed the expected number for the particular region. This algorithm is intended to be used by public health officials to identify and track clusters in localised geographic areas in real-time

    Intuitivno pretraživanje baze slike kao potpora označavanju slika

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    Image annotation is typically performed manually since automatic image annotation approaches have not matured yet to be used in practice. Consequently, image annotation is a labour intensive and time consuming task. In this paper, we show how an image browsing system can be employed to support efficient and effective (manual) annotation of image databases. In contrast to other approaches, which typically present images in a linear fashion, we employ a visualisation where images are arranged by mutual visual similarity. Since in this arrangement similar images are close to each other, they can easily be selected and annotated together. Organisation on a grid layout prevents image overlap and thus contributes to a clear presentation. Large image databases are handled through a hierarchical data structure where each image in the visualisation can correspond to a cluster of images that can be expanded by the user. Experimental results indicate that annotation can be performed faster on our proposed system.Označavanje slika obično se obavlja ručno jer automatski pristupi još nisu dovoljno kvalitetni kako bi se koristili u praksi. Zbog toga je označavanje slika u bazi vremenski zahtjevno. U ovom radu pokazat ćemo kako se sustav za pregled slika u bazi može koristiti kao učinkovita potpora ručnom označavanju slika. Za razliku od drugih pristupa, koji prikazuju slike u linearnom poretku, korištena je vizualizacija u kojoj su slike složene po međusobnoj sličnosti. Budući da su na taj način slične slike međusobno blizu jedna drugoj, lako ih je selektirati i zajednički označiti. Slike su organizirane u mrežni prikaz radi sprječavanja preklapanja i jasnije prezentacije. Velike baze podataka organizirane su u hijerarhijsku strukturu gdje svaka slika u pojedinoj vizualizaciji može pripadati skupu slika čiji prikaz korisnik po želji može proširivati. Rezultati provedenih eksperimenata pokazuju da se označavanje slika pomoću predloženog sustava može obavljati brže nego na uobičajeni način

    Spatial algorithm for detecting disease outbreaks in Australia

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    La detección temprana de brotes de enfermedades es esencial de cara a una intervención pronta en problemas de salud pública. Actualmente en Australia, las enfermedades notificables son recogidas y almacenadas, y referenciadas geográfica y temporalmente. Sin embargo, el proceso para la búsqueda de brotes de enfermedad sobre escalas espaciales distintas no está bien definido. Los brotes son de detección difícil. Algunas enfermedades aparecen relativamente rápido, mientras otras requieren más tiempo para su incubación y sólo se hacen evidentes sobre largos intervalos temporales. En la práctica, los epidemiólogos combinan diferentes conjuntos de evidencias para determinar la probabilidad de la existencia de un brote. Gracias al progresivo incremento de disponibilidad de bases de datos electrónicas y de los Sistemas de Información Geográfica (SIG), el potencial para la utilización de técnicas de análisis espacial para la visualización, exploración y modelado de notificaciones de enfermedades para la detección temprana de brotes, es hoy mayor que en el pasado. En este artículo, los autores presentan un algoritmo que emplea bases de datos de la administración, análisis espacial y SIG para la detección de clusters de enfermedades en el Estado de Australia Occidental. El algoritmo revisa los códigos postales de forma rutinaria hasta encontrar un número de casos que supera los valores que serían esperados en la región considerada. El algoritmo está diseñado para su uso por profesionales de la salud pública para asistir en la identificación y seguimiento de clusters en tiempo real.The early detection of disease outbreaks is essential for early intervention in potential public health problems. Currently in Australia, disease notifications are recorded, temporally and geographically referenced; however, the process of searching for outbreaks over different spatial scales is not well defined. Disease outbreaks are difficult to detect. Some diseases appear relatively rapidly, while others take time to gestate and become apparent over long time intervals. In practice, epidemiologists combine different sets of evidence in different ways and apply reasoning to determine the likelihood of an outbreak. With an increase in the availability of electronic health-care data and geographic information systems (GIS), there is great potential to use spatial analysis techniques for the visualisation, exploration and modelling of disease notifications for the early detection of disease outbreaks. In this paper, the authors present an algorithm that uses administrative databases, spatial analysis and GIS for the detection of disease clusters in Western Australia (WA). The algorithm routinely tests administrative areas (postcodes) and highlights the areas in which counts exceed the expected number for the particular region. This algorithm is intended to be used by public health officials to identify and track clusters in localised geographic areas in real-time

    Dimensions for the assessment of ethical leadership : an internal audit perspective

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    Ethical leadership is regarded as the key to building trust and sustaining organisations. However, monitoring the effectiveness of organisations in promoting ethical leadership poses a challenge to assurance providers, in particular internal auditors. Although attempts have been made to provide internal auditors with guidelines on how to assess the tone-at-the-top, these efforts are still based on the traditional compliance approach that in the past has fallen short of expectations when applied to questions of ethics. This paper proposes additional dimensions, to be included in a value-based approach to the assessment of ethical leadership. The foundation on which these dimensions are assessed is the Integrated Control Framework prepared by The Committee of Sponsoring Organisations of the Treadway Commission (COSO).http://reference.sabinet.co.za/sa_epublication/sajaaram201
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