932 resultados para Approximation Classes
Resumo:
In this paper, we aim at predicting protein structural classes for low-homology data sets based on predicted secondary structures. We propose a new and simple kernel method, named as SSEAKSVM, to predict protein structural classes. The secondary structures of all protein sequences are obtained by using the tool PSIPRED and then a linear kernel on the basis of secondary structure element alignment scores is constructed for training a support vector machine classifier without parameter adjusting. Our method SSEAKSVM was evaluated on two low-homology datasets 25PDB and 1189 with sequence homology being 25% and 40%, respectively. The jackknife test is used to test and compare our method with other existing methods. The overall accuracies on these two data sets are 86.3% and 84.5%, respectively, which are higher than those obtained by other existing methods. Especially, our method achieves higher accuracies (88.1% and 88.5%) for differentiating the α + β class and the α/β class compared to other methods. This suggests that our method is valuable to predict protein structural classes particularly for low-homology protein sequences. The source code of the method in this paper can be downloaded at http://math.xtu.edu.cn/myphp/math/research/source/SSEAK_source_code.rar.
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The rectangular dielectric waveguide is the most commonly used structure in integrated optics, especially in semi-conductor diode lasers. Demands for new applications such as high-speed data backplanes in integrated electronics, waveguide filters, optical multiplexers and optical switches are driving technology toward better materials and processing techniques for planar waveguide structures. The infinite slab and circular waveguides that we know are not practical for use on a substrate because the slab waveguide has no lateral confinement and the circular fiber is not compatible with the planar processing technology being used to make planar structures. The rectangular waveguide is the natural structure. In this review, we have discussed several analytical methods for analyzing the mode structure of rectangular structures, beginning with a wave analysis based on the pioneering work of Marcatili. We study three basic techniques with examples to compare their performance levels. These are the analytical approach developed by Marcatili, the perturbation techniques, which improve on the analytical solutions and the effective index method with examples.
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This paper deals with the optimal load flow problem in a fixed-head hydrothermal electric power system. Equality constraints on the volume of water available for active power generation at the hydro plants as well as inequality constraints on the reactive power generation at the voltage controlled buses are imposed. Conditions for optimal load flow are derived and a successive approximation algorithm for solving the optimal generation schedule is developed. Computer implementation of the algorithm is discussed, and the results obtained from the computer solution of test systems are presented.
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The paper studies stochastic approximation as a technique for bias reduction. The proposed method does not require approximating the bias explicitly, nor does it rely on having independent identically distributed (i.i.d.) data. The method always removes the leading bias term, under very mild conditions, as long as auxiliary samples from distributions with given parameters are available. Expectation and variance of the bias-corrected estimate are given. Examples in sequential clinical trials (non-i.i.d. case), curved exponential models (i.i.d. case) and length-biased sampling (where the estimates are inconsistent) are used to illustrate the applications of the proposed method and its small sample properties.
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An adaptive learning scheme, based on a fuzzy approximation to the gradient descent method for training a pattern classifier using unlabeled samples, is described. The objective function defined for the fuzzy ISODATA clustering procedure is used as the loss function for computing the gradient. Learning is based on simultaneous fuzzy decisionmaking and estimation. It uses conditional fuzzy measures on unlabeled samples. An exponential membership function is assumed for each class, and the parameters constituting these membership functions are estimated, using the gradient, in a recursive fashion. The induced possibility of occurrence of each class is useful for estimation and is computed using 1) the membership of the new sample in that class and 2) the previously computed average possibility of occurrence of the same class. An inductive entropy measure is defined in terms of induced possibility distribution to measure the extent of learning. The method is illustrated with relevant examples.
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In this work, we theoretically examine recent pump/probe photoemission experiments on the strongly correlated charge-density-wave insulator TaS2.We describe the general nonequilibrium many-body formulation of time-resolved photoemission in the sudden approximation, and then solve the problem using dynamical mean-field theory with the numerical renormalization group and a bare density of states calculated from density functional theory including the charge-density-wave distortion of the ion cores and spin-orbit coupling. We find a number of interesting results: (i) the bare band structure actually has more dispersion in the perpendicular direction than in the two-dimensional planes; (ii) the DMFT approach can produce upper and lower Hubbard bands that resemble those in the experiment, but the upper bands will overlap in energy with other higher energy bands; (iii) the effect of the finite width of the probe pulse is minimal on the shape of the photoemission spectra; and (iv) the quasiequilibrium approximation does not fully describe the behavior in this system.
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Based on a one-year ethnographic study of a primary school in Finland with specialised classes in Finnish and English (referred to as bilingual classes by research participants), this research traces patterns of how nationed, raced, classed and gendered differences are produced and gain meaning in school. I examine several aspects of these differences: the ways the teachers and parents make sense of school and of school choice; the repertoires of self put forward by teachers, parents and pupils of the bilingual classes; and the insitutional and classroom practices in Sunny Lane School (pseudonym). My purpose is to examine how the construction of differentness is related to the policy of school choice. I approach this questions from a knowledge problematic, and explore connections and disjunctions between the interpretations of teachers and those of parents, as well as between what teachers and parents expressed or said and the practices they engaged in. My data consists of fieldnotes generated through a one-year period of ethnographic study in Sunny Lane School, and of ethnographic interviews with teachers and parents primarily of the bilingual classes. This data focuses on the initial stages of the bilingual classes, which included the application and testing processes for these classes, and on Grades 1─3. In my analysis, I pursue poststructural feminist theorisations on questions of knowledge, power and subjectivity, which foreground an understanding of the constitutive force of discourse and the performative, partial, and relational nature of knowledge. I begin by situating my ethnographic field in relation to wider developments, namely, the emergence of school choice and the rhetoric of curricular reform and language education in Finland. I move on from there to ask how teachers discuss the introduction of these specialised classes, then trace pupils paths to these classes, their parents goals related to school choice, teachers constructions of the pupils and parents of bilingual classes, and how these shape the ways in which school and classroom practices unfold. School choice, I argue, functioned as a spatial practice, defining who belongs in school and demarcating the position of teachers, parents and pupils in school. Notions of classed and ethnicised differences entered the ways teachers and parents made sense of school choice. Teachers idealised school in terms of social cohesiveness and constructed social cohesion as a task for school to perform. The hopes parents iterated were connected to ensuring their children s futurity, to their perceptions of the advantages of fluency in English, but also to the differences they believed to exist between the social milieus of different schools. Ideals such as openmindedness and cosmopolitanism were also articulated by parents, and these ideals assumed different content for ethnic majority and minority parents. Teachers discussed the introduction of bilingual classes as being a means to ensure the school s future, and emphasised bilingual classes as fitting into the rubric of Finnish comprehensive schooling which, they maintained, is committed to equality. Parents were expected to accommodate their views and adopt the position of the responsible, supportive parent that was suggested to them by teachers. Teachers assumed a posture teachers of appreciating different cultures, while maintaining Finnishness as common ground in school. Discussion on pupils knowledge and experience of other countries took place often in bilingual classes, and various cultural theme events were organized on occasion. In school, pupils are taught to identify themselves in terms of cultural belonging. The rhetoric promoted by teachers was one of inclusiveness, which was also applied to describe the task of qualifying pupils for bilingual classes, qualifying which pupils can belong. Bilingual classes were idealised as taking a neutral, impartial posture toward difference by ethnic majority teachers and parents, and the relationship of school choice to classed advantage, for example, was something teachers, as well as parents, preferred not to discuss. Pupils were addressed by teachers during lessons in ways that assumed self responsibility and diligence, and they assumed the discursive category of being good, competent pupils made available to them. While this allowed them to position themselves favourably in school, their participation in a bilingual class was marked by the pressure to succeed well in school.
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The problem of learning correct decision rules to minimize the probability of misclassification is a long-standing problem of supervised learning in pattern recognition. The problem of learning such optimal discriminant functions is considered for the class of problems where the statistical properties of the pattern classes are completely unknown. The problem is posed as a game with common payoff played by a team of mutually cooperating learning automata. This essentially results in a probabilistic search through the space of classifiers. The approach is inherently capable of learning discriminant functions that are nonlinear in their parameters also. A learning algorithm is presented for the team and convergence is established. It is proved that the team can obtain the optimal classifier to an arbitrary approximation. Simulation results with a few examples are presented where the team learns the optimal classifier.
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The maximum independent set problem is NP-complete even when restricted to planar graphs, cubic planar graphs or triangle free graphs. The problem of finding an absolute approximation still remains NP-complete. Various polynomial time approximation algorithms, that guarantee a fixed worst case ratio between the independent set size obtained to the maximum independent set size, in planar graphs have been proposed. We present in this paper a simple and efficient, O(|V|) algorithm that guarantees a ratio 1/2, for planar triangle free graphs. The algorithm differs completely from other approaches, in that, it collects groups of independent vertices at a time. Certain bounds we obtain in this paper relate to some interesting questions in the theory of extremal graphs.
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It is shown how the single-site coherent potential approximation and the averaged T-matrix approximation become exact in the calculation of the averaged single-particle Green function of the electron in the Anderson model when the site energy is distributed randomly with lorentzian distribution. Using these approximations, Lloyd's exact result is reproduced.
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This paper reviews the remarkably similar experiences of school science reported by high school students in Sweden, England, and Australia. It compares student narratives from interpretive studies by Lindahl, by Osborne and Collins, and by Lyons, identifying core themes relating to critical contemporary issues in science education. These themes revolve around the transmissive pedagogy, decontextualized content, and unnecessary difficulty of school science commonly reported by students in the studies. Their collective experiences are used as a framework for examining student conceptions of, and attitudes to, school science more generally, drawing on an extensive range of international literature. The paper argues that the experiences of students in the three studies provide important insights into the widespread declines in interest and enrolments in high school and university science courses.
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Background: Agriculture is facing enormous challenges to feed a growing population in the face of rapidly evolving pests and pathogens. The rusts, in particular, are a major pathogen of cereal crops with the potential to cause large reductions in yield. Improving stable disease resistance is an on-going major and challenging focus for many plant breeding programs, due to the rapidly evolving nature of the pathogen. Sorghum is a major summer cereal crop that is also a host for a rust pathogen which occurs in almost all sorghum growing areas of the world, causing direct and indirect yield losses in sorghum worldwide, however knowledge about its genetic control is still limited. In order to further investigate this issue, QTL and association mapping methods were implemented to study rust resistance in three bi-parental populations and an association mapping set of elite breeding lines in different environments. Results: In total, 64 significant or highly significant QTL and 21 suggestive rust resistance QTL were identified representing 55 unique genomic regions. Comparisons across populations within the current study and with rust QTL identified previously in both sorghum and maize revealed a high degree of correspondence in QTL location. Negative phenotypic correlations were observed between rust, maturity and height, indicating a trend for both early maturing and shorter genotypes to be more susceptible to rust. Conclusions: The significant amount of QTL co-location across traits, in addition to the consistency in the direction of QTL allele effects, has provided evidence to support pleiotropic QTL action across rust, height, maturity and stay-green, supporting the role of carbon stress in susceptibility to rust. Classical rust resistance QTL regions that did not co-locate with height, maturity or stay-green QTL were found to be significantly enriched for the defence-related NBS-encoding gene family, in contrast to the lack of defence-related gene enrichment in multi-trait effect rust resistance QTL. The distinction of disease resistance QTL hot-spots, enriched with defence-related gene families from QTL which impact on development and partitioning, provides plant breeders with knowledge which will allow for fast-tracking varieties with both durable pathogen resistance and appropriate adaptive traits.
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The research in model theory has extended from the study of elementary classes to non-elementary classes, i.e. to classes which are not completely axiomatizable in elementary logic. The main theme has been the attempt to generalize tools from elementary stability theory to cover more applications arising in other branches of mathematics. In this doctoral thesis we introduce finitary abstract elementary classes, a non-elementary framework of model theory. These classes are a special case of abstract elementary classes (AEC), introduced by Saharon Shelah in the 1980's. We have collected a set of properties for classes of structures, which enable us to develop a 'geometric' approach to stability theory, including an independence calculus, in a very general framework. The thesis studies AEC's with amalgamation, joint embedding, arbitrarily large models, countable Löwenheim-Skolem number and finite character. The novel idea is the property of finite character, which enables the use of a notion of a weak type instead of the usual Galois type. Notions of simplicity, superstability, Lascar strong type, primary model and U-rank are inroduced for finitary classes. A categoricity transfer result is proved for simple, tame finitary classes: categoricity in any uncountable cardinal transfers upwards and to all cardinals above the Hanf number. Unlike the previous categoricity transfer results of equal generality the theorem does not assume the categoricity cardinal being a successor. The thesis consists of three independent papers. All three papers are joint work with Tapani Hyttinen.