90 resultados para Distance-based techniques
Resumo:
Open source is typically outside of normal commercial software procurement processes.The Challenges.Increasingly diverse and distributed set of development resources.Little/no visibility into the origins of the software.Supply Chain Comparison: Hardware vs Software.Open source has revolutionized the mobile and device landscape, other industries will follow.Supply chain management techniques from hardware are useful for managing software.SPDX A standard format for communicating a software Bill of Materials across the supply chain.Effective management and control requires training, tools, processes and standards.
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The widespread implementation of GIS-based 3D topographical models has been a great aid in the development and testing of archaeological hypotheses. In this paper, a topographical reconstruction of the ancient city of Tarraco, the Roman capital of the Tarraconensis province, is presented. This model is based on topographical data obtained through archaeological excavations, old photographic documentation, georeferenced archive maps depicting the pre-modern city topography, modern detailed topographical maps and differential GPS measurements. The addition of the Roman urban architectural features to the model offers the possibility to test hypotheses concerning the ideological background manifested in the city shape. This is accomplished mainly through the use of 3D views from the main city accesses. These techniques ultimately demonstrate the ‘theatre-shaped’ layout of the city (to quote Vitrubius) as well as its southwest oriented architecture, whose monumental character was conceived to present a striking aspect to visitors, particularly those arriving from the sea.
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Forensic archaeology has been of inestimable help in the location and excavation of clandestine burials (Hunter 1996a:16-17, 1996b; Killam 2004; Levine et al. 1984). Landscape archaeology techniques have been adapted and widely applied for such purposes. In this article, an adaptation of one of the most common applications of archaeological GIS, that is predictive site location, is applied to the detection of body dump sites and clandestine burial sites, bringing together in the process the fields of landscape archaeology, forensic sciences, and GIS.
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A beautiful smile is directly related with white teeth. Nowadays oral care has increased and developed processes for beautiful smiles. Dental bleaching is frequently used in odontology, not just for health care also for aesthetic treatment. With the possibility of teeth bleaching, now the importance is in, how white the tooth is? Because color is relate to an individual perception. In order to assets teeth correct color identification has been developed many color guides, models, spaces and analytical methods. Spite all of these useful tools the color interpretation depends on environmental factors, position of the sample in the data acquisition and most importantly the instrument sensitivity. The commons methods have proved to be useful. They are easy to handle, some are portable but they do not have a high sensitivity. The present work is based on the integration of a new analytical technique for color acquisition. High spectral Image (HSI) is able to performed image analysis with high quality and efficiency. HSI is used in many fields and we used it for color image analysis within the bleaching process. The main comparison was done with the HSI and the colorimeter through the processes of two different bleaching protocols. The results showed that HSI has higher sensitivity than the colorimeter. During the analysis the dental surface with the HSI we were able to notice surface changes. These changes were analyzed by roughness studies.
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A new method for decision making that uses the ordered weighted averaging (OWA) operator in the aggregation of the information is presented. It is used a concept that it is known in the literature as the index of maximum and minimum level (IMAM). This index is based on distance measures and other techniques that are useful for decision making. By using the OWA operator in the IMAM, we form a new aggregation operator that we call the ordered weighted averaging index of maximum and minimum level (OWAIMAM) operator. The main advantage is that it provides a parameterized family of aggregation operators between the minimum and the maximum and a wide range of special cases. Then, the decision maker may take decisions according to his degree of optimism and considering ideals in the decision process. A further extension of this approach is presented by using hybrid averages and Choquet integrals. We also develop an application of the new approach in a multi-person decision-making problem regarding the selection of strategies.
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The prediction filters are well known models for signal estimation, in communications, control and many others areas. The classical method for deriving linear prediction coding (LPC) filters is often based on the minimization of a mean square error (MSE). Consequently, second order statistics are only required, but the estimation is only optimal if the residue is independent and identically distributed (iid) Gaussian. In this paper, we derive the ML estimate of the prediction filter. Relationships with robust estimation of auto-regressive (AR) processes, with blind deconvolution and with source separation based on mutual information minimization are then detailed. The algorithm, based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics. Experimental results emphasize on the interest of this approach.
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The classical theory of collision induced emission (CIE) from pairs of dissimilar rare gas atoms was developed in Paper I [D. Reguera and G. Birnbaum, J. Chem. Phys. 125, 184304 (2006)] from a knowledge of the straight line collision trajectory and the assumption that the magnitude of the dipole could be represented by an exponential function of the inter-nuclear distance. This theory is extended here to deal with other functional forms of the induced dipole as revealed by ab initio calculations. Accurate analytical expression for the CIE can be obtained by least square fitting of the ab initio values of the dipole as a function of inter-atomic separation using a sum of exponentials and then proceeding as in Paper I. However, we also show how the multi-exponential fit can be replaced by a simpler fit using only two analytic functions. Our analysis is applied to the polar molecules HF and HBr. Unlike the rare gas atoms considered previously, these atomic pairs form stable bound diatomic molecules. We show that, interestingly, the spectra of these reactive molecules are characterized by the presence of multiple peaks. We also discuss the CIE arising from half collisions in excited electronic states, which in principle could be probed in photo-dissociation experiments.
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Chronic graft-versus-host disease (cGvHD) is the leading cause of late nonrelapse mortality (transplant-related mortality) after hematopoietic stem cell transplant. Given that there are a wide range of treatment options for cGvHD, assessment of the associated costs and efficacy can help clinicians and health care providers allocate health care resources more efficiently. OBJECTIVE: The purpose of this study was to assess the cost-effectiveness of extracorporeal photopheresis (ECP) compared with rituximab (Rmb) and with imatinib (Imt) in patients with cGvHD at 5 years from the perspective of the Spanish National Health System. METHODS: The model assessed the incremental cost-effectiveness/utility ratio of ECP versus Rmb or Imt for 1000 hypothetical patients by using microsimulation cost-effectiveness techniques. Model probabilities were obtained from the literature. Treatment pathways and adverse events were evaluated taking clinical opinion and published reports into consideration. Local data on costs (2010 Euros) and health care resources utilization were validated by the clinical authors. Probabilistic sensitivity analyses were used to assess the robustness of the model. RESULTS: The greater efficacy of ECP resulted in a gain of 0.011 to 0.024 quality-adjusted life-year in the first year and 0.062 to 0.094 at year 5 compared with Rmb or Imt. The results showed that the higher acquisition cost of ECP versus Imt was compensated for at 9 months by greater efficacy; this higher cost was partially compensated for ( 517) by year 5 versus Rmb. After 9 months, ECP was dominant (cheaper and more effective) compared with Imt. The incremental cost-effectiveness ratio of ECP versus Rmb was 29,646 per life-year gained and 24,442 per quality-adjusted life-year gained at year 2.5. Probabilistic sensitivity analysis confirmed the results. The main study limitation was that to assess relative treatment effects, only small studies were available for indirect comparison. CONCLUSION: ECP as a third-line therapy for cGvHD is a more cost-effective strategy than Rmb or Imt.
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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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This work investigates performance of recent feature-based matching techniques when applied to registration of underwater images. Matching methods are tested versus different contrast enhancing pre-processing of images. As a result of the performed experiments for various dominating in images underwater artifacts and present deformation, the outperforming preprocessing, detection and description methods are proposed
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Alzheimer׳s disease (AD) is the most common type of dementia among the elderly. This work is part of a larger study that aims to identify novel technologies and biomarkers or features for the early detection of AD and its degree of severity. The diagnosis is made by analyzing several biomarkers and conducting a variety of tests (although only a post-mortem examination of the patients’ brain tissue is considered to provide definitive confirmation). Non-invasive intelligent diagnosis techniques would be a very valuable diagnostic aid. This paper concerns the Automatic Analysis of Emotional Response (AAER) in spontaneous speech based on classical and new emotional speech features: Emotional Temperature (ET) and fractal dimension (FD). This is a pre-clinical study aiming to validate tests and biomarkers for future diagnostic use. The method has the great advantage of being non-invasive, low cost, and without any side effects. The AAER shows very promising results for the definition of features useful in the early diagnosis of AD.
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In the context of the evidence-based practices movement, the emphasis on computing effect sizes and combining them via meta-analysis does not preclude the demonstration of functional relations. For the latter aim, we propose to augment the visual analysis to add consistency to the decisions made on the existence of a functional relation without losing sight of the need for a methodological evaluation of what stimuli and reinforcement or punishment are used to control the behavior. Four options for quantification are reviewed, illustrated, and tested with simulated data. These quantifications include comparing the projected baseline with the actual treatment measurements, on the basis of either parametric or nonparametric statistics. The simulated data used to test the quantifications include nine data patterns in terms of the presence and type of effect and comprising ABAB and multiple baseline designs. Although none of the techniques is completely flawless in terms of detecting a functional relation only when it is present but not when it is absent, an option based on projecting split-middle trend and considering data variability as in exploratory data analysis proves to be the best performer for most data patterns. We suggest that the information on whether a functional relation has been demonstrated should be included in meta-analyses. It is also possible to use as a weight the inverse of the data variability measure used in the quantification for assessing the functional relation. We offer an easy to use code for open-source software for implementing some of the quantifications.
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Analyzing the state of the art in a given field in order to tackle a new problem is always a mandatory task. Literature provides surveys based on summaries of previous studies, which are often based on theoretical descriptions of the methods. An engineer, however, requires some evidence from experimental evaluations in order to make the appropriate decision when selecting a technique for a problem. This is what we have done in this paper: experimentally analyzed a set of representative state-of-the-art techniques in the problem we are dealing with, namely, the road passenger transportation problem. This is an optimization problem in which drivers should be assigned to transport services, fulfilling some constraints and minimizing some function cost. The experimental results have provided us with good knowledge of the properties of several methods, such as modeling expressiveness, anytime behavior, computational time, memory requirements, parameters, and free downloadable tools. Based on our experience, we are able to choose a technique to solve our problem. We hope that this analysis is also helpful for other engineers facing a similar problem