927 resultados para Irregular objects
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Context.Massive stars form in dense and massive molecular cores. The exact formation mechanism is unclear, but it is possible that some massive stars are formed by processes similar to those that produce the low-mass stars, with accretion/ejection phenomena occurring at some point of the evolution of the protostar. This picture seems to be supported by the detection of a collimated stellar wind emanating from the massive protostar IRAS 16547-4247. A triple radio source is associated with the protostar: a compact core and two radio lobes. The emission of the southern lobe is clearly non-thermal. Such emission is interpreted as synchrotron radiation produced by relativistic electrons locally accelerated at the termination point of a thermal jet. Since the ambient medium is determined by the properties of the molecular cloud in which the whole system is embedded, we can expect high densities of particles and infrared photons. Because of the confirmed presence of relativistic electrons, inverse Compton and relativistic Bremsstrahlung interactions are unavoidable. Aims.We aim to make quantitative predictions of the spectral energy distribution of the non-thermal spots generated by massive young stellar objects, with emphasis on the particular case of IRAS 16547-4247. Methods.We study the high-energy emission generated by the relativistic electrons which produce the non-thermal radio source in IRAS 16547-4247. We also study the result of proton acceleration at the terminal shock of the thermal jet and make estimates of the secondary gamma rays and electron-positron pairs produced by pion decay. Results.We present spectral energy distributions for the southern lobe of IRAS 16547-4247, for a variety of conditions. We show that high-energy emission might be detectable from this object in the gamma-ray domain. The source may also be detectable in X-rays through long exposures with current X-ray instruments. Conclusions.Gamma-ray telescopes such as GLAST, and even ground-based Cherenkov arrays of new generation can be used to study non-thermal processes occurring during the formation of massive stars.
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The dual-stream model of auditory processing postulates separate processing streams for sound meaning and for sound location. The present review draws on evidence from human behavioral and activation studies as well as from lesion studies to argue for a position-linked representation of sound objects that is distinct both from the position-independent representation within the ventral/What stream and from the explicit sound localization processing within the dorsal/Where stream.
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Anthropomorphic model observers are mathe- matical algorithms which are applied to images with the ultimate goal of predicting human signal detection and classification accuracy across varieties of backgrounds, image acquisitions and display conditions. A limitation of current channelized model observers is their inability to handle irregularly-shaped signals, which are common in clinical images, without a high number of directional channels. Here, we derive a new linear model observer based on convolution channels which we refer to as the "Filtered Channel observer" (FCO), as an extension of the channelized Hotelling observer (CHO) and the nonprewhitening with an eye filter (NPWE) observer. In analogy to the CHO, this linear model observer can take the form of a single template with an external noise term. To compare with human observers, we tested signals with irregular and asymmetrical shapes spanning the size of lesions down to those of microcalfications in 4-AFC breast tomosynthesis detection tasks, with three different contrasts for each case. Whereas humans uniformly outperformed conventional CHOs, the FCO observer outperformed humans for every signal with only one exception. Additive internal noise in the models allowed us to degrade model performance and match human performance. We could not match all the human performances with a model with a single internal noise component for all signal shape, size and contrast conditions. This suggests that either the internal noise might vary across signals or that the model cannot entirely capture the human detection strategy. However, the FCO model offers an efficient way to apprehend human observer performance for a non-symmetric signal.
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The main target of the study was to find ideas for maintenance and development of supplier relations in irregular business environment. The other aim was to find out the suppliers’ opinions concerning the case company and the relationship between the companies. The study was conducted by using both qualitative and quantitative research methods. A mail survey was used to find out supplier opinions and an interview to find out suppliers’ ideas for relationship maintenance and development. It was found out that the use of relational elements is essential in the relationship maintenance in an irregular environment. In development of supplier relations the company should make better use of its suppliers’ potential, assure better flow of information and utilize the possibilities of Supplier Relationship Management.
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Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system
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We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm
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We adapt the Shout and Act algorithm to Digital Objects Preservation where agents explore file systems looking for digital objects to be preserved (victims). When they find something they “shout” so that agent mates can hear it. The louder the shout, the urgent or most important the finding is. Louder shouts can also refer to closeness. We perform several experiments to show that this system works very scalably, showing that heterogeneous teams of agents outperform homogeneous ones over a wide range of tasks complexity. The target at-risk documents are MS Office documents (including an RTF file) with Excel content or in Excel format. Thus, an interesting conclusion from the experiments is that fewer heterogeneous (varying skills) agents can equal the performance of many homogeneous (combined super-skilled) agents, implying significant performance increases with lower overall cost growth. Our results impact the design of Digital Objects Preservation teams: a properly designed combination of heterogeneous teams is cheaper and more scalable when confronted with uncertain maps of digital objects that need to be preserved. A cost pyramid is proposed for engineers to use for modeling the most effective agent combinations
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Paper presented in ISA RC23 meeting, Gothenburg July 16th 2010
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It is generally accepted that the development of the modern sciences is rooted in experiment. Yet for a long time, experimentation did not occupy a prominent role, neither in philosophy nor in history of science. With the 'practical turn' in studying the sciences and their history, this has begun to change. This paper is concerned with systems and cultures of experimentation and the consistencies that are generated within such systems and cultures. The first part of the paper exposes the forms of historical and structural coherence that characterize the experimental exploration of epistemic objects. In the second part, a particular experimental culture in the life sciences is briefly described as an example. A survey will be given of what it means and what it takes to analyze biological functions in the test tube.
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This paper presents a study on the dynamics of the rattling problem in gearboxes under non-ideal excitation. The subject has being analyzed by a number of authors such as Karagiannis and Pfeiffer (1991), for the ideal excitation case. An interesting model of the same problem by Moon (1992) has been recently used by Souza and Caldas (1999) to detect chaotic behavior. We consider two spur gears with different diameters and gaps between the teeth. Suppose the motion of one gear to be given while the motion of the other is governed by its dynamics. In the ideal case, the driving wheel is supposed to undergo a sinusoidal motion with given constant amplitude and frequency. In this paper, we consider the motion to be a function of the system response and a limited energy source is adopted. Thus an extra degree of freedom is introduced in the problem. The equations of motion are obtained via a Lagrangian approach with some assumed characteristic torque curves. Next, extensive numerical integration is used to detect some interesting geometrical aspects of regular and irregular motions of the system response.
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The recent emergence of low-cost RGB-D sensors has brought new opportunities for robotics by providing affordable devices that can provide synchronized images with both color and depth information. In this thesis, recent work on pose estimation utilizing RGBD sensors is reviewed. Also, a pose recognition system for rigid objects using RGB-D data is implemented. The implementation uses half-edge primitives extracted from the RGB-D images for pose estimation. The system is based on the probabilistic object representation framework by Detry et al., which utilizes Nonparametric Belief Propagation for pose inference. Experiments are performed on household objects to evaluate the performance and robustness of the system.
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This thesis presents a framework for segmentation of clustered overlapping convex objects. The proposed approach is based on a three-step framework in which the tasks of seed point extraction, contour evidence extraction, and contour estimation are addressed. The state-of-art techniques for each step were studied and evaluated using synthetic and real microscopic image data. According to obtained evaluation results, a method combining the best performers in each step was presented. In the proposed method, Fast Radial Symmetry transform, edge-to-marker association algorithm and ellipse fitting are employed for seed point extraction, contour evidence extraction and contour estimation respectively. Using synthetic and real image data, the proposed method was evaluated and compared with two competing methods and the results showed a promising improvement over the competing methods, with high segmentation and size distribution estimation accuracy.
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This is a sociological study of the views of officers in the Swedish Army and its Amphibious Forces on tactics in Irregular Warfare (IW), in particular, Counterinsurgency (COIN). IW comprises struggles, where the military weaker part uses an indirect approach with smaller units and integrates the civilian and military dimensions in a violence spectrum including subversion, terrorism, Guerrilla Warfare and infantry actions. IW is the main armed warfare style in insurgencies. COIN is the combined political, military, economic, social and legal actions in counter insurgencies. Data has been collected by means of interviews with almost all (n =43) officers, who were either commanding battalions or rifle and manoeuvre companies while undergoing training for general warfare and international operations. The main theoretical and methodological inspiration is the traditional one for research on social fields, inaugurated by the French sociologist Pierre Bourdieu. The statistical technique used is Multiple Correspondence Analysis. As a background and context base, an inquiry inspired by the Begriffsgechichte (Conceptual History) tradition explores the genesis and development of understandings of the term Irregular Warfare. The research question is outlined as; “how can contemporary Swedish military thought on tactics in Irregular Warfare be characterized using descriptive patterns, mapped in relation to background factors and normative standards? The most significant findings are that there are two main opposing notions separating the officers’ views on tactics in Irregular Warfare: (1) a focus on larger, combat oriented and collectively operating military units versus smaller and larger, more intelligence oriented and dispersed operating units, and (2) a focus on military tasks and kinetic effects versus military and civilian tasks as well as “soft” effects. The distribution of these views can be presented as a two-dimensional space structured by the two axes. This space represents four categories of tactics, partly diverging from normative military standards for Counterinsurgency. This social space of standpoints shows different structural tendencies for background factors of social and cultural character, particularly dominant concerning military backgrounds, international mission experiences and civilian education. Compared to military standards for Counterinsurgency, the two tactical types characterized by a Regular Warfare mind-set stands out as counter-normative. Signs of creative thought on military practice and theory, as well as a still persistent Regular Warfare doxa are apparent. Power struggles might thus develop, effecting the transformation to a broadened warfare culture with an enhanced focus also on Irregular Warfare. The result does not support research results arguing for a convergence of military thought in the European transformation of Armed Forces. The main argument goes beyond tactics and suggests sociological analysis on reciprocal effects regarding strategy, operational art, tactics as well as leadership, concerning the mind-set and preferences for Regular, Irregular and Hybrid Warfare.