866 resultados para Reproducing kernel
Resumo:
The Hybrid approach introduced by the authors for at-site modeling of annual and periodic streamflows in earlier works is extended to simulate multi-site multi-season streamflows. It bears significance in integrated river basin planning studies. This hybrid model involves: (i) partial pre-whitening of standardized multi-season streamflows at each site using a parsimonious linear periodic model; (ii) contemporaneous resampling of the resulting residuals with an appropriate block size, using moving block bootstrap (non-parametric, NP) technique; and (iii) post-blackening the bootstrapped innovation series at each site, by adding the corresponding parametric model component for the site, to obtain generated streamflows at each of the sites. It gains significantly by effectively utilizing the merits of both parametric and NP models. It is able to reproduce various statistics, including the dependence relationships at both spatial and temporal levels without using any normalizing transformations and/or adjustment procedures. The potential of the hybrid model in reproducing a wide variety of statistics including the run characteristics, is demonstrated through an application for multi-site streamflow generation in the Upper Cauvery river basin, Southern India. (C) 2004 Elsevier B.V. All rights reserved.
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Microorganisms exist predominantly as sessile multispecies communities in natural habitats. Most bacterial species can form these matrix-enclosed microbial communities called biofilms. Biofilms occur in a wide range of environments, on every surface with sufficient moisture and nutrients, also on surfaces in industrial settings and engineered water systems. This unwanted biofilm formation on equipment surfaces is called biofouling. Biofouling can significantly decrease equipment performance and lifetime and cause contamination and impaired quality of the industrial product. In this thesis we studied bacterial adherence to abiotic surfaces by using coupons of stainless steel coated or not coated with fluoropolymer or diamond like carbon (DLC). As model organisms we used bacterial isolates from paper machines (Meiothermus silvanus, Pseudoxanthomonas taiwanensis and Deinococcus geothermalis) and also well characterised species isolated from medical implants (Staphylococcus epidermidis). We found that coating of steel surface with these materials reduced its tendency towards biofouling: Fluoropolymer and DLC coatings repelled all four biofilm formers on steel. We found great differences between bacterial species in their preference of surfaces to adhere as well as their ultrastructural details, like number and thickness of adhesion organelles they expressed. These details responded differently towards the different surfaces they adhered to. We further found that biofilms of D. geothermalis formed on titanium dioxide coated coupons of glass, steel and titanium, were effectively removed by photocatalytic action in response to irradiation at 360 nm. However, on non-coated glass or steel surfaces irradiation had no detectable effect on the amount of bacterial biomass. We showed that the adhesion organelles of bacteria on illuminated TiO2 coated coupons were complety destroyed whereas on non-coated coupons they looked intact when observed by microscope. Stainless steel is the most widely used material for industrial process equipments and surfaces. The results in this thesis showed that stainless steel is prone to biofouling by phylogenetically distant bacterial species and that coating of the steel may offer a tool for reduced biofouling of industrial equipment. Photocatalysis, on the other hand, is a potential technique for biofilm removal from surfaces in locations where high level of hygiene is required. Our study of natural biofilms on barley kernel surfaces showed that also there the microbes possessed adhesion organelles visible with electronmicroscope both before and after steeping. The microbial community of dry barley kernels turned into a dense biofilm covered with slimy extracellular polymeric substance (EPS) in the kernels after steeping in water. Steeping is the first step in malting. We also presented evidence showing that certain strains of Lactobacillus plantarum and Wickerhamomyces anomalus, when used as starter cultures in the steeping water, could enter the barley kernel and colonise the tissues of the barley kernel. By use of a starter culture it was possible to reduce the extensive production of EPS, which resulted in a faster filtration of the mash.
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A key trait of Free and Open Source Software (FOSS) development is its distributed nature. Nevertheless, two project-level operations, the fork and the merge of program code, are among the least well understood events in the lifespan of a FOSS project. Some projects have explicitly adopted these operations as the primary means of concurrent development. In this study, we examine the effect of highly distributed software development, is found in the Linux kernel project, on collection and modelling of software development data. We find that distributed development calls for sophisticated temporal modelling techniques where several versions of the source code tree can exist at once. Attention must be turned towards the methods of quality assurance and peer review that projects employ to manage these parallel source trees. Our analysis indicates that two new metrics, fork rate and merge rate, could be useful for determining the role of distributed version control systems in FOSS projects. The study presents a preliminary data set consisting of version control and mailing list data.
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A key trait of Free and Open Source Software (FOSS) development is its distributed nature. Nevertheless, two project-level operations, the fork and the merge of program code, are among the least well understood events in the lifespan of a FOSS project. Some projects have explicitly adopted these operations as the primary means of concurrent development. In this study, we examine the effect of highly distributed software development, is found in the Linux kernel project, on collection and modelling of software development data. We find that distributed development calls for sophisticated temporal modelling techniques where several versions of the source code tree can exist at once. Attention must be turned towards the methods of quality assurance and peer review that projects employ to manage these parallel source trees. Our analysis indicates that two new metrics, fork rate and merge rate, could be useful for determining the role of distributed version control systems in FOSS projects. The study presents a preliminary data set consisting of version control and mailing list data.
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According to certain arguments, computation is observer-relative either in the sense that many physical systems implement many computations (Hilary Putnam), or in the sense that almost all physical systems implement all computations (John Searle). If sound, these arguments have a potentially devastating consequence for the computational theory of mind: if arbitrary physical systems can be seen to implement arbitrary computations, the notion of computation seems to lose all explanatory power as far as brains and minds are concerned. David Chalmers and B. Jack Copeland have attempted to counter these relativist arguments by placing certain constraints on the definition of implementation. In this thesis, I examine their proposals and find both wanting in some respects. During the course of this examination, I give a formal definition of the class of combinatorial-state automata , upon which Chalmers s account of implementation is based. I show that this definition implies two theorems (one an observation due to Curtis Brown) concerning the computational power of combinatorial-state automata, theorems which speak against founding the theory of implementation upon this formalism. Toward the end of the thesis, I sketch a definition of the implementation of Turing machines in dynamical systems, and offer this as an alternative to Chalmers s and Copeland s accounts of implementation. I demonstrate that the definition does not imply Searle s claim for the universal implementation of computations. However, the definition may support claims that are weaker than Searle s, yet still troubling to the computationalist. There remains a kernel of relativity in implementation at any rate, since the interpretation of physical systems seems itself to be an observer-relative matter, to some degree at least. This observation helps clarify the role the notion of computation can play in cognitive science. Specifically, I will argue that the notion should be conceived as an instrumental rather than as a fundamental or foundational one.
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Statistical learning algorithms provide a viable framework for geotechnical engineering modeling. This paper describes two statistical learning algorithms applied for site characterization modeling based on standard penetration test (SPT) data. More than 2700 field SPT values (N) have been collected from 766 boreholes spread over an area of 220 sqkm area in Bangalore. To get N corrected value (N,), N values have been corrected (Ne) for different parameters such as overburden stress, size of borehole, type of sampler, length of connecting rod, etc. In three-dimensional site characterization model, the function N-c=N-c (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to N, value, is to be approximated in which N, value at any half-space point in Bangalore can be determined. The first algorithm uses least-square support vector machine (LSSVM), which is related to aridge regression type of support vector machine. The second algorithm uses relevance vector machine (RVM), which combines the strengths of kernel-based methods and Bayesian theory to establish the relationships between a set of input vectors and a desired output. The paper also presents the comparative study between the developed LSSVM and RVM model for site characterization. Copyright (C) 2009 John Wiley & Sons,Ltd.
First simultaneous measurement of the top quark mass in the lepton+jets and dilepton channels at CDF
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We present a measurement of the mass of the top quark using data corresponding to an integrated luminosity of 1.9fb^-1 of ppbar collisions collected at sqrt{s}=1.96 TeV with the CDF II detector at Fermilab's Tevatron. This is the first measurement of the top quark mass using top-antitop pair candidate events in the lepton + jets and dilepton decay channels simultaneously. We reconstruct two observables in each channel and use a non-parametric kernel density estimation technique to derive two-dimensional probability density functions from simulated signal and background samples. The observables are the top quark mass and the invariant mass of two jets from the W decay in the lepton + jets channel, and the top quark mass and the scalar sum of transverse energy of the event in the dilepton channel. We perform a simultaneous fit for the top quark mass and the jet energy scale, which is constrained in situ by the hadronic W boson mass. Using 332 lepton + jets candidate events and 144 dilepton candidate events, we measure the top quark mass to be mtop=171.9 +/- 1.7 (stat. + JES) +/- 1.1 (syst.) GeV/c^2 = 171.9 +/- 2.0 GeV/c^2.
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Core Vector Machine(CVM) is suitable for efficient large-scale pattern classification. In this paper, a method for improving the performance of CVM with Gaussian kernel function irrespective of the orderings of patterns belonging to different classes within the data set is proposed. This method employs a selective sampling based training of CVM using a novel kernel based scalable hierarchical clustering algorithm. Empirical studies made on synthetic and real world data sets show that the proposed strategy performs well on large data sets.
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This paper discusses a method for scaling SVM with Gaussian kernel function to handle large data sets by using a selective sampling strategy for the training set. It employs a scalable hierarchical clustering algorithm to construct cluster indexing structures of the training data in the kernel induced feature space. These are then used for selective sampling of the training data for SVM to impart scalability to the training process. Empirical studies made on real world data sets show that the proposed strategy performs well on large data sets.
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The near flow field of small aspect ratio elliptic turbulent free jets (issuing from nozzle and orifice) was experimentally studied using a 2D PIV. Two point velocity correlations in these jets revealed the extent and orientation of the large scale structures in the major and minor planes. The spatial filtering of the instantaneous velocity field using Gaussian convolution kernel shows that while a single large vortex ring circumscribing the jet seems to be present at the exit of nozzle, the orifice jet exhibited a number of smaller vortex ring pairs close to jet exit. The smaller length scale observed in the case of the orifice jet is representative of the smaller azimuthal vortex rings that generate axial vortex field as they are convected. This results in the axis-switching in the case of orifice jet and may have a mechanism different from the self induction process as observed in the case of contoured nozzle jet flow.
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Global dynamo simulations solving the equations of magnetohydrodynamics (MHD) have been a tool of astrophysicists who try to understand the magnetism of the Sun for several decades now. During recent years many fundamental issues in dynamo theory have been studied in detail by means of local numerical simulations that simplify the problem and allow the study of physical effects in isolation. Global simulations, however, continue to suffer from the age-old problem of too low spatial resolution, leading to much lower Reynolds numbers and scale separation than in the Sun. Reproducing the internal rotation of the Sun, which plays a crucual role in the dynamo process, has also turned out to be a very difficult problem. In the present paper the current status of global dynamo simulations of the Sun is reviewed. Emphasis is put on efforts to understand how the large-scale magnetic fields, i.e. whose length scale is greater than the scale of turbulence, are generated in the Sun. Some lessons from mean-field theory and local simulations are reviewed and their possible implications to the global models are discussed. Possible remedies to some of the current issues of the solar simulations are put forward.
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Many Finnish IT companies have gone through numerous organizational changes over the past decades. This book draws attention to how stability may be central to software product development experts and IT workers more generally, who continuously have to cope with such change in their workplaces. It does so by analyzing and theorizing change and stability as intertwined and co-existent, thus throwing light on how it is possible that, for example, even if ‘the walls fall down the blokes just code’ and maintain a sense of stability in their daily work. Rather than reproducing the picture of software product development as exciting cutting edge activities and organizational change as dramatic episodes, the study takes the reader beyond the myths surrounding these phenomena to the mundane practices, routines and organizings in product development during organizational change. An analysis of these ordinary practices offers insights into how software product development experts actively engage in constructing stability during organizational change through a variety of practices, including solidarity, homosociality, close relations to products, instrumental or functional views on products, preoccupations with certain tasks and humble obedience. Consequently, the study shows that it may be more appropriate to talk about varieties of stability, characterized by a multitude of practices of stabilizing rather than states of stagnation. Looking at different practices of stability in depth shows the creation of software as an arena for micro-politics, power relations and increasing pressures for order and formalization. The thesis gives particular attention to power relations and processes of positioning following organizational change: how social actors come to understand themselves in the context of ongoing organizational change, how they comply with and/or contest dominant meanings, how they identify and dis-identify with formalization, and how power relations often are reproduced despite dis-identification. Related to processes of positioning, the reader is also given a glimpse into what being at work in a male-dominated and relatively homogeneous work environment looks like. It shows how the strong presence of men or “blokes” of a particular age and education seems to become invisible in workplace talk that appears ‘non-conscious’ of gender.
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Study orientations in higher education consist of various dimensions, such as approaches to learning, conceptions of learning and knowledge (i.e. epistemologies), self-regulation, and motivation. They have also been measured in different ways. The main orientations typically reported are reproducing and meaning orientations. The present study explored dimensions of study orientations, focusing in particular on pharmacy and medicine. New versions of self-report instruments were developed and tested in various contexts and in two countries. Furthermore, the linkages between study orientations and students epistemological development were explored. The context of problem-based (PBL) small groups was investigated in order to better understand how collaboration contributes to the quality of learning. The participants of Study I (n=66) were pharmacy students, who were followed during a three-year professionally oriented program in terms of their study orientations and epistemologies. A reproducing orientation to studying diminished during studying, whereas only a few students maintained their original level of meaning orientation. Dualism was found to be associated with a reproducing orientation. In Study II practices associated with deep and surface approaches to learning were measured in two differing ways, in order to better distinguish between what students believed to be useful in studying, and the extent to which they applied their beliefs to practice when preparing for examinations. Differences between domains were investigated by including a sample of Finnish and Swedish medical students (n=956) and a Finnish non-medical sample of university students (n=865). Memorizing and rote learning appeared as differing components of a surface approach to learning, while understanding, relating, and critical evaluation of knowledge emerged as aspects of a deep approach to learning. A structural model confirmed these results in both student samples. Study III explored a wide variety of dimensions of learning in medical education. Swedish medical students (n=280) answered the questionnaire. The deep approach to learning was strongly related to collaboration and reflective learning, whereas the surface approach was associated with novice-like views of knowledge and the valuing of certain and directly applicable knowledge. PBL students aimed at understanding, but also valued the role of memorization. Study IV investigated 12 PBL tutorial groups of students (n=116) studying microbiology and pharmacology in a medical school. The educational application was expected to support a deep approach to learning: Group members course grades in a final examination were related to the perceived functioning of the PBL tutorial groups. Further, the quality of cases that had been used as triggers for learning, was associated with the quality of small group functioning. New dimensions of study orientations were discovered. In particular, novel, finer distinctions were found within the deep approach component. In medicine, critical evaluation of knowledge appeared to be less valued than understanding and relating. Further, collaboration appeared to be closely related to the deep approach, and it was also important in terms of successful PBL studying. The results of the studies confirmed the previously found associations between approaches to learning and study success, but showed interesting context- and subgroup-related differences in this respect. Students ideas about the nature of knowledge and their approaches to learning were shown to be closely related. The present study expanded our understanding of the dimensions of study orientations, of their development, and their contextual variability in pharmacy and medicine.
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To enhance the utilization of the wood, the sawmills are forced to place more emphasis on planning to master the whole production chain from the forest to the end product. One significant obstacle to integrating the forest-sawmill-market production chain is the lack of appropriate information about forest stands. Since the wood procurement point of view in forest planning systems has been almost totally disregarded there has been a great need to develop an easy and efficient pre-harvest measurement method, allowing separate measurement of stands prior to harvesting. The main purpose of this study was to develop a measurement method for pine stands which forest managers could use in describing the properties of the standing trees for sawing production planning. Study materials were collected from ten Scots pine stands (Pinus sylvestris) located in North Häme and South Pohjanmaa, in southern Finland. The data comprise test sawing data on 314 pine stems, dbh and height measures of all trees and measures of the quality parameters of pine sawlog stems in all ten study stands as well as the locations of all trees in six stands. The study was divided into four sub-studies which deal with pine quality prediction, construction of diameter and dead branch height distributions, sampling designs and applying height and crown height models. The final proposal for the pre-harvest measurement method is a synthesis of the individual sub-studies. Quality analysis resulted in choosing dbh, distance from stump height to the first dead branch (dead branch height), crown height and tree height as the most appropriate quality characteristics of Scots pine. Dbh and dead branch height are measured from each pine sample tree while height and crown height are derived from dbh measures by aid of mixed height and crown height models. Pine and spruce diameter distribution as well as dead branch height distribution are most effectively predicted by the kernel function. Roughly 25 sample trees seems to be appropriate in pure pine stands. In mixed stands the number of sample trees needs to be increased in proportion to the intensity of pines in order to attain the same level of accuracy.
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Fujikawa's method of evaluating the supercurrent and the superconformal current anomalies, using the heat-kernel regularization scheme, is extended to theories with gauge invariance, in particular, to the off-shell N=1 supersymmetric Yang-Mills (SSYM) theory. The Jacobians of supersymmetry and superconformal transformations are finite. Although the gauge-fixing term is not supersymmetric and the regularization scheme is not manifestly supersymmetric, we find that the regularized Jacobians are gauge invariant and finite and they can be expressed in such a way that there is no one-loop supercurrent anomaly for the N=1 SSYM theory. The superconformal anomaly is nonzero and the anomaly agrees with a similar result obtained using other methods.