968 resultados para Transformations


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Geological fluids exist in every geosphere of the Earth and play important roles in many processes of material transformations, energetic interchanges and geochemical interactions. To study the physicochemical properties and geochemical behaviors of geological fluids turn Girt to be one of the challenging issues in geosciences. Compared with conventional approaches of experiments and semi-theoretical modeling, computer simulation on molecular level shows its advantages on quantitative predictions of the physicochemical properties of geological fluids under extreme conditions and emerges as a promising approach to find the characteristics of geological fluids and their interactions in different geospheres of the Earth interior.This dissertation systematically discusses the physicochemical properties of typical geological fluids with state-of-the-art computer simulation techniques. The main results can be summarized as follows: (1) The experimental phase behaviors of the systems CH4-C2H6 and. CO2 have been successfully reproduced with Monte Carlo simulations. (2) Through comprehensive isothermal-isobaric molecular dynamics simulations, the PVT data of water hia^e been extended beyond experimental range to about 2000 K and 20 GPa and an improved equation of state for water has been established. (3) Based on extensive computer simulations, am optimized molecular potential for carbon dioxide have been proposed, this model is expected to predict different properties of carbon dioxide (volumetric properties, phase equilibria, heat of vaporization, structural and dynamical properties) with improved accuracies. (4) On the basis of the above researches of the end-members, a set of parameters for unlike interactions has been proposed by non-linear fitting to the ab initio potential surface of CO2-H2O and is superior to the common used mixing rule and the results of prior workers vs/Ith remarkable accuracies, then a number of simulations of the mixture have been carried out to generate data under high temperatures and pressures as an important complement to the limited experiments. (5) With molecular dynamics simulations, various structural, dynamical and thermodynamical properties of ionic solvations and associations have been oomprehensively analyzed, these results not only agree well with experimental data and first principle calculation results, but also reveal some new insights into the microscopic ionic solvation and association processes.

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北欧和北美的研究发现水库是典型的汞敏感生态系统,新建水库而引起的鱼的甲基汞污染问题已经受到科学家的高度重视,而我国在这方面的研究比较薄弱。本论文以乌江流域上游的东风水库为研究对象,于夏季(2007 年8月)、冬季(2007 年12 月)和春季(2008年4月)分别对水库不同深度分层水体、沉积物间隙水、沉积柱剖面中不同形态汞的含量、分布特征以及迁移转化规律进行了详细的研究。研究结果发现: 1.东风水库水体中各种形态汞浓度均表现出季节性变化。总汞(THg)浓度变化范 围为1.1-2.3ng/L,平均为1.6ng/L;溶解态汞(THg)浓度变化范围为0.3-1.3ng/L,平均为0.6ng/L;颗粒态汞(PHg)浓度范围为0.3-1.5ng/L,平均为0.8ng/L;活性汞(RHg)浓度范围为0.2-0.6ng/L,平均为0.4ng/L;总甲基汞(TMHg)浓度变化范 围为0.04-1.01ng/L,平均为0.27ng/L;溶解态甲基汞(DMHg)浓度变化范围为0.03-0.48ng/L,平均为0.12ng/L;颗粒态甲基汞汞(PMHg)浓度范围为0.01-0.7ng/L,平均为0.16ng/L。 2.东风水库水体颗粒态总汞与总汞呈极显著相关,说明东风水库水体的颗粒态汞强烈影响着总汞迁移和分布。水库水体总甲基汞与溶解态甲基汞汞和颗粒态甲基汞之间存在极显著正线性相关,证明水库水体中的甲基汞的产生和迁移与溶解态甲基汞和颗粒态甲基汞均有着密切的关系。但是,水体甲基汞与总汞之间并不存在相关性。 3.东风水库水体夏季溶解态汞、活性汞、溶解态甲基汞浓度均远高于冬春两季,除了外源异重径流输入的影响外,很大程度与夏季水库底部缺氧环境密不可分。沉积物释放大量吸附的汞进入水体,造成水体溶解态汞、活性汞、溶解态甲基汞的升高。 4.东风水库沉积物间隙水中总汞和甲基汞浓度出现明显的季节性变化,夏季大于冬春两季。沉积物甲基汞的浓度分布与沉积物中有机质含量相关性明显(r=0.219*,n=133)。东风水库沉积物中甲基汞的含量随沉积物深度增加浓度梯度不明显。 5.东风水库沉积物总汞含量基本没有季节变化,浓度变化范围为97-354ng/g,平均为180ng/g。东风水库沉积物中总汞含量大大高于其他未受污染地区水库沉积物中总汞含量。甲基汞含量变化范围为0.1-5.5ng/g,平均为2.1ng/g 。 6.东风水库沉积物间隙水中总汞、甲基汞浓度均显著高于其上覆水体的总汞和甲基汞的浓度,二者之间存在显著的浓度梯度,沉积物中总汞和甲基汞的释放是水库水体的重要来源。

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Visual object recognition requires the matching of an image with a set of models stored in memory. In this paper we propose an approach to recognition in which a 3-D object is represented by the linear combination of 2-D images of the object. If M = {M1,...Mk} is the set of pictures representing a given object, and P is the 2-D image of an object to be recognized, then P is considered an instance of M if P = Eki=aiMi for some constants ai. We show that this approach handles correctly rigid 3-D transformations of objects with sharp as well as smooth boundaries, and can also handle non-rigid transformations. The paper is divided into two parts. In the first part we show that the variety of views depicting the same object under different transformations can often be expressed as the linear combinations of a small number of views. In the second part we suggest how this linear combinatino property may be used in the recognition process.

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Affine transformations are often used in recognition systems, to approximate the effects of perspective projection. The underlying mathematics is for exact feature data, with no positional uncertainty. In practice, heuristics are added to handle uncertainty. We provide a precise analysis of affine point matching, obtaining an expression for the range of affine-invariant values consistent with bounded uncertainty. This analysis reveals that the range of affine-invariant values depends on the actual $x$-$y$-positions of the features, i.e. with uncertainty, affine representations are not invariant with respect to the Cartesian coordinate system. We analyze the effect of this on geometric hashing and alignment recognition methods.

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A polynomial time algorithm (pruned correspondence search, PCS) with good average case performance for solving a wide class of geometric maximal matching problems, including the problem of recognizing 3D objects from a single 2D image, is presented. Efficient verification algorithms, based on a linear representation of location constraints, are given for the case of affine transformations among vector spaces and for the case of rigid 2D and 3D transformations with scale. Some preliminary experiments suggest that PCS is a practical algorithm. Its similarity to existing correspondence based algorithms means that a number of existing techniques for speedup can be incorporated into PCS to improve its performance.

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This paper presents a model for the general flow in the neocortex. The basic process, called "sequence-seeking," is a search for a sequence of mappings or transformations, linking source and target representations. The search is bi-directional, "bottom-up" as well as "top-down," and it explores in parallel a large numbe rof alternative sequences. This operation is implemented in a structure termed "counter streams," in which multiple sequences are explored along two separate, complementary pathways which seeking to meet. The first part of the paper discusses the general sequence-seeking scheme and a number of related processes, such as the learning of successful sequences, context effects, and the use of "express lines" and partial matches. The second part discusses biological implications of the model in terms of connections within and between cortical areas. The model is compared with existing data, and a number of new predictions are proposed.

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The task of shape recovery from a motion sequence requires the establishment of correspondence between image points. The two processes, the matching process and the shape recovery one, are traditionally viewed as independent. Yet, information obtained during the process of shape recovery can be used to guide the matching process. This paper discusses the mutual relationship between the two processes. The paper is divided into two parts. In the first part we review the constraints imposed on the correspondence by rigid transformations and extend them to objects that undergo general affine (non rigid) transformation (including stretch and shear), as well as to rigid objects with smooth surfaces. In all these cases corresponding points lie along epipolar lines, and these lines can be recovered from a small set of corresponding points. In the second part of the paper we discuss the potential use of epipolar lines in the matching process. We present an algorithm that recovers the correspondence from three contour images. The algorithm was implemented and used to construct object models for recognition. In addition we discuss how epipolar lines can be used to solve the aperture problem.

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In order to recognize an object in an image, we must determine the best transformation from object model to the image. In this paper, we show that for features from coplanar surfaces which undergo linear transformations in space, there exist projections invariant to the surface motions up to rotations in the image field. To use this property, we propose a new alignment approach to object recognition based on centroid alignment of corresponding feature groups. This method uses only a single pair of 2D model and data. Experimental results show the robustness of the proposed method against perturbations of feature positions.

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The need to generate new views of a 3D object from a single real image arises in several fields, including graphics and object recognition. While the traditional approach relies on the use of 3D models, we have recently introduced techniques that are applicable under restricted conditions but simpler. The approach exploits image transformations that are specific to the relevant object class and learnable from example views of other "prototypical" objects of the same class. In this paper, we introduce such a new technique by extending the notion of linear class first proposed by Poggio and Vetter. For linear object classes it is shown that linear transformations can be learned exactly from a basis set of 2D prototypical views. We demonstrate the approach on artificial objects and then show preliminary evidence that the technique can effectively "rotate" high- resolution face images from a single 2D view.

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The inferior temporal cortex (IT) of monkeys is thought to play an essential role in visual object recognition. Inferotemporal neurons are known to respond to complex visual stimuli, including patterns like faces, hands, or other body parts. What is the role of such neurons in object recognition? The present study examines this question in combined psychophysical and electrophysiological experiments, in which monkeys learned to classify and recognize novel visual 3D objects. A population of neurons in IT were found to respond selectively to such objects that the monkeys had recently learned to recognize. A large majority of these cells discharged maximally for one view of the object, while their response fell off gradually as the object was rotated away from the neuron"s preferred view. Most neurons exhibited orientation-dependent responses also during view-plane rotations. Some neurons were found tuned around two views of the same object, while a very small number of cells responded in a view- invariant manner. For five different objects that were extensively used during the training of the animals, and for which behavioral performance became view-independent, multiple cells were found that were tuned around different views of the same object. No selective responses were ever encountered for views that the animal systematically failed to recognize. The results of our experiments suggest that neurons in this area can develop a complex receptive field organization as a consequence of extensive training in the discrimination and recognition of objects. Simple geometric features did not appear to account for the neurons" selective responses. These findings support the idea that a population of neurons -- each tuned to a different object aspect, and each showing a certain degree of invariance to image transformations -- may, as an assembly, encode complex 3D objects. In such a system, several neurons may be active for any given vantage point, with a single unit acting like a blurred template for a limited neighborhood of a single view.

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In this report, I discuss the use of vision to support concrete, everyday activity. I will argue that a variety of interesting tasks can be solved using simple and inexpensive vision systems. I will provide a number of working examples in the form of a state-of-the-art mobile robot, Polly, which uses vision to give primitive tours of the seventh floor of the MIT AI Laboratory. By current standards, the robot has a broad behavioral repertoire and is both simple and inexpensive (the complete robot was built for less than $20,000 using commercial board-level components). The approach I will use will be to treat the structure of the agent's activity---its task and environment---as positive resources for the vision system designer. By performing a careful analysis of task and environment, the designer can determine a broad space of mechanisms which can perform the desired activity. My principal thesis is that for a broad range of activities, the space of applicable mechanisms will be broad enough to include a number mechanisms which are simple and economical. The simplest mechanisms that solve a given problem will typically be quite specialized to that problem. One thus worries that building simple vision systems will be require a great deal of {it ad-hoc} engineering that cannot be transferred to other problems. My second thesis is that specialized systems can be analyzed and understood in a principled manner, one that allows general lessons to be extracted from specialized systems. I will present a general approach to analyzing specialization through the use of transformations that provably improve performance. By demonstrating a sequence of transformations that derive a specialized system from a more general one, we can summarize the specialization of the former in a compact form that makes explicit the additional assumptions that it makes about its environment. The summary can be used to predict the performance of the system in novel environments. Individual transformations can be recycled in the design of future systems.

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Techniques, suitable for parallel implementation, for robust 2D model-based object recognition in the presence of sensor error are studied. Models and scene data are represented as local geometric features and robust hypothesis of feature matchings and transformations is considered. Bounds on the error in the image feature geometry are assumed constraining possible matchings and transformations. Transformation sampling is introduced as a simple, robust, polynomial-time, and highly parallel method of searching the space of transformations to hypothesize feature matchings. Key to the approach is that error in image feature measurement is explicitly accounted for. A Connection Machine implementation and experiments on real images are presented.

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This thesis addresses the problem of recognizing solid objects in the three-dimensional world, using two-dimensional shape information extracted from a single image. Objects can be partly occluded and can occur in cluttered scenes. A model based approach is taken, where stored models are matched to an image. The matching problem is separated into two stages, which employ different representations of objects. The first stage uses the smallest possible number of local features to find transformations from a model to an image. This minimizes the amount of search required in recognition. The second stage uses the entire edge contour of an object to verify each transformation. This reduces the chance of finding false matches.

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A large computer program has been developed to aid applied mathematicians in the solution of problems in non-numerical analysis which involve tedious manipulations of mathematical expressions. The mathematician uses typed commands and a light pen to direct the computer in the application of mathematical transformations; the intermediate results are displayed in standard text-book format so that the system user can decide the next step in the problem solution. Three problems selected from the literature have been solved to illustrate the use of the system. A detailed analysis of the problems of input, transformation, and display of mathematical expressions is also presented.

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Though one is led to believe that program transformation systems which perform source-to-source transformations enable the user to understand and appreciate the resulting source program, this is not always the case. Transformations are capable of behaving and/or interacting in unexpected ways. The user who is interested in understanding the whats, whys, wheres, and hows of the transformation process is left without tools for discovering them. I provide an initial step towards the solution of this problem in the form of an accountable source-to-source transformation system. It carefully records the information necessary to answer such questions, and provides mechanisms for the retrieval of this information. It is observed that though this accountable system allows the user access to relevant facts from which he may draw conclusions, further study is necessary to make the system capable of analyzing these facts itself.