967 resultados para Orientation of space


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A scheme for denoting the absolute spatial orientation of molecules and molecular fragments is presented; this is based on three angular deviations - one for each spatial dimension - with respect to a reference orientation, which is itself defined with the help of certain features of the Cahn-Ingold-Prelog stereochemical notation. The new scheme helps in reconstructing the three-dimensional characteristics of molecules from purely verbal descriptors, and may thus find application in various information storage and retrieval processes (e.,-. encrypting holograms, etc.).

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This paper provides four viewpoints on the narratives of space, allowing us to think about possible relations between sites and sounds, reflecting on how places might tell stories, or how practitioners embed themselves in a place in order to shape cultural, social and/or political narratives through the use of sound. I propose four viewpoints that investigate the relationship between sites and sounds, where narratives are shaped and made through the exploration of specific sonic activities. These are:
- sonic activism
- sonic preservation
- sonic participatory action
- sonic narrative of space

I examine each of these ideas in turn before focusing in more detail on the final viewpoint, which provides the context for discussing and analysing a recent site-specific music improvisation project, entitled ‘Museum City’, a work that aligns closely with my proposal for a ‘sonic narrative of space’.
The work ‘Museum City’ by Pedro Rebelo, Franziska Schroeder, Ricardo Jacinto and André Cepeda specifically enables me to reflect on how derelict and/or transitional spaces might be re-examined through the use of sound, particularly through means of live music improvisation. The spaces examined as part ‘Museum City’ constitute either deserted sites or sites about to undergo changes in their architectural layout, their use and sonic make-up. The practice in ‘Museum City’ was born out of a performative engagement with[in] those sites, but specifically out of an intimate listening relationship by three improvisers situated within those spaces.
The theoretical grounding for this paper is situated within a wider context of practising and cognising musical spatiality, as proposed by Georgina Born (2013), particularly her proposition for three distinct lineages that provide an understanding of space in/and music. Born’s third lineage, which links more closely with practices of sound art and challenges a Euclidean orientation of pitch and timbre space, makes way for a heightened consideration of listening and ‘the place’ of sound. This lineage is particularly crucial for my discussion, since it positions music in relation to social experiences and the everyday, which the work ‘Museum City’ endeavoured to embrace.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Image orientation is a basic problem in Digital Photogrammetry. While interior and relative orientations were succesfully automated, the same can not be said about absolute orientation. This process can be automated by using an approach based on relational matching and a heuristic that uses the analytical relation between straight features in the object space and its homologous in the image space. A build-in self-diagnosis is also used in this method, that is based on the implementation of data snooping statistic test in the process of spatial resection, using the Iterated Extended Kalman Filtering (IEKF). The aim of this paper is to present the basic principles of the proposed approach and results based on real data.

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This paper presents a method for indirect orientation of aerial images using ground control lines extracted from airborne Laser system (ALS) data. This data integration strategy has shown good potential in the automation of photogrammetric tasks, including the indirect orientation of images. The most important characteristic of the proposed approach is that the exterior orientation parameters (EOP) of a single or multiple images can be automatically computed with a space resection procedure from data derived from different sensors. The suggested method works as follows. Firstly, the straight lines are automatically extracted in the digital aerial image (s) and in the intensity image derived from an ALS data-set (S). Then, correspondence between s and S is automatically determined. A line-based coplanarity model that establishes the relationship between straight lines in the object and in the image space is used to estimate the EOP with the iterated extended Kalman filtering (IEKF). Implementation and testing of the method have employed data from different sensors. Experiments were conducted to assess the proposed method and the results obtained showed that the estimation of the EOP is function of ALS positional accuracy.

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The paper presents and evaluates three methods for automatically estimating the main orientation of Martian dust devil tracks in MOC and HiRISE images. Inferring such information about dust devils from their tracks is important to better understand the near surface wind. The methods considered were based on gradient direction, directional openings and morphological granulometry. The accuracy of the methods was asserted by comparing the results to a set of directions estimated visually and assumed to be the ground truth. The higher accuracy was reached using directional openings. Besides, the directions inferred by this method were compared to those predicted by the GCM and the results agreed. © 2013 COSPAR.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The population of space debris increased drastically during the last years. These objects have become a great threat for active satellites. Because the relative velocities between space debris and satellites are high, space debris objects may destroy active satellites through collisions. Furthermore, collisions involving massive objects produce large number of fragments leading to significant growth of the space debris population. The long term evolution of the debris population is essentially driven by so-called catastrophic collisions. An effective remediation measure in order to stabilize the population in Low Earth Orbit (LEO) is therefore the removal of large, massive space debris. To remove these objects, not only precise orbits, but also more detailed information about their attitude states will be required. One important property of an object targeted for removal is its spin period, spin axis orientation and their change over time. Rotating objects will produce periodic brightness variations with frequencies which are related to the spin periods. Such a brightness variation over time is called a light curve. Collecting, but also processing light curves is challenging due to several reasons. Light curves may be undersampled, low frequency components due to phase angle and atmospheric extinction changes may be present, and beat frequencies may occur when the rotation period is close to a multiple of the sampling period. Depending on the method which is used to extract the frequencies, also method-specific properties have to be taken into account. The astronomical Institute of the University of Bern (AIUB) light curve database will be introduced, which contains more than 1,300 light curves acquired over more than seven years. We will discuss properties and reliability of different time series analysis methods tested and currently used by AIUB for the light curve processing. Extracted frequencies and reconstructed phases for some interesting targets, e.g. GLONASS satellites, for which also SLR data were available for the period confirmation, will be presented. Finally we will present the reconstructed phase and its evolution over time of a High-Area-to-Mass-Ratio (HAMR) object, which AIUB observed for several years.

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Every space launch increases the overall amount of space debris. Satellites have limited awareness of nearby objects that might pose a collision hazard. Astrometric, radiometric, and thermal models for the study of space debris in low-Earth orbit have been developed. This modeled approach proposes analysis methods that provide increased Local Area Awareness for satellites in low-Earth and geostationary orbit. Local Area Awareness is defined as the ability to detect, characterize, and extract useful information regarding resident space objects as they move through the space environment surrounding a spacecraft. The study of space debris is of critical importance to all space-faring nations. Characterization efforts are proposed using long-wave infrared sensors for space-based observations of debris objects in low-Earth orbit. Long-wave infrared sensors are commercially available and do not require solar illumination to be observed, as their received signal is temperature dependent. The characterization of debris objects through means of passive imaging techniques allows for further studies into the origination, specifications, and future trajectory of debris objects. Conclusions are made regarding the aforementioned thermal analysis as a function of debris orbit, geometry, orientation with respect to time, and material properties. Development of a thermal model permits the characterization of debris objects based upon their received long-wave infrared signals. Information regarding the material type, size, and tumble-rate of the observed debris objects are extracted. This investigation proposes the utilization of long-wave infrared radiometric models of typical debris to develop techniques for the detection and characterization of debris objects via signal analysis of unresolved imagery. Knowledge regarding the orbital type and semi-major axis of the observed debris object are extracted via astrometric analysis. This knowledge may aid in the constraint of the admissible region for the initial orbit determination process. The resultant orbital information is then fused with the radiometric characterization analysis enabling further characterization efforts of the observed debris object. This fused analysis, yielding orbital, material, and thermal properties, significantly increases a satellite's Local Area Awareness via an intimate understanding of the debris environment surrounding the spacecraft.

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Urban wayfinding technology offers many possibilities by which older people and mobility-impaired users can overcome the barriers encountered on every-day journeys in the built environment. Previous work has highlighted the extent to which personal mobility and independence are significant determinants of the quality of life amongst both elderly and visually impaired groups. The paper outlines the development of the auditory location finder (ALF), which is a beacon-based local information system designed to enhance the wayfinding activities of these, and potentially other, user-groups in the community. The proposed system provides the user with an audio message, which is obtained on request via a small portable hand unit. The messages inform the user of their whereabouts and give information about the area that they are currently in. The development of the device involves issues such as message content and structure, route choice, orientation, landmarks, clues and the extent of user reliance on technology. Preliminary trials have been carried out in a UK city and have obtained initial user feedback to help underpin the technological development of the device and its potential application. The paper concludes by outlining the importance of new urban technology and the way in which such local information systems can potentially contribute to overcoming particular patterns of exclusion experienced by mobility-impaired groups, such as the visually impaired

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Every space launch increases the overall amount of space debris. Satellites have limited awareness of nearby objects that might pose a collision hazard. Astrometric, radiometric, and thermal models for the study of space debris in low-Earth orbit have been developed. This modeled approach proposes analysis methods that provide increased Local Area Awareness for satellites in low-Earth and geostationary orbit. Local Area Awareness is defined as the ability to detect, characterize, and extract useful information regarding resident space objects as they move through the space environment surrounding a spacecraft. The study of space debris is of critical importance to all space-faring nations. Characterization efforts are proposed using long-wave infrared sensors for space-based observations of debris objects in low-Earth orbit. Long-wave infrared sensors are commercially available and do not require solar illumination to be observed, as their received signal is temperature dependent. The characterization of debris objects through means of passive imaging techniques allows for further studies into the origination, specifications, and future trajectory of debris objects. Conclusions are made regarding the aforementioned thermal analysis as a function of debris orbit, geometry, orientation with respect to time, and material properties. Development of a thermal model permits the characterization of debris objects based upon their received long-wave infrared signals. Information regarding the material type, size, and tumble-rate of the observed debris objects are extracted. This investigation proposes the utilization of long-wave infrared radiometric models of typical debris to develop techniques for the detection and characterization of debris objects via signal analysis of unresolved imagery. Knowledge regarding the orbital type and semi-major axis of the observed debris object are extracted via astrometric analysis. This knowledge may aid in the constraint of the admissible region for the initial orbit determination process. The resultant orbital information is then fused with the radiometric characterization analysis enabling further characterization efforts of the observed debris object. This fused analysis, yielding orbital, material, and thermal properties, significantly increases a satellite’s Local Area Awareness via an intimate understanding of the debris environment surrounding the spacecraft.