Combination models

Xem 1-20 trên 744 kết quả Combination models
  • Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Implementation and Validation of a New Combined Model for Outdoor to Indoor Radio Coverage Predictions

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  • Tuyển tập các báo cáo nghiên cứu về hóa học được đăng trên tạp chí hóa hoc quốc tế đề tài : Optimized combination model and algorithm of parking guidance information configuration

    pdf9p sting03 06-02-2012 30 2   Download

  • This paper presents a novel method of generating and applying hierarchical, dynamic topic-based language models. It proposes and evaluates new cluster generation, hierarchical smoothing and adaptive topic-probability estimation techniques. These combined models help capture long-distance lexical dependencies. °Experiments on the Broadcast News corpus show significant improvement in perplexity (10.5% overall and 33.5% on target vocabulary).

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  • We present a generative model for the unsupervised learning of dependency structures. We also describe the multiplicative combination of this dependency model with a model of linear constituency. The product model outperforms both components on their respective evaluation metrics, giving the best published figures for unsupervised dependency parsing and unsupervised constituency parsing. We also demonstrate that the combined model works and is robust cross-linguistically, being able to exploit either attachment or distributional regularities that are salient in the data. ...

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  • A modified combination model that used ambient temperature, relative humidity, solar radiation, air velocity and leaf area index (LAI) as inputs was developed for nursery plants, and its prediction was compared to the measured ET of the plant.

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  • Extremum (create an extremum element (point, edge, or face), which is at the minimum or maximum distance on a curve, a surface, or a pad, according to given directions. )Projection (project one or more elements onto a support. The projection can be normal to surface or along a specified direction.)Combine Curves (create a curve resulting from the intersection of the extrusion of two curves. )

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  • A 2-to-1 multiplexer – WITH-SELECT-WHEN statement A 2-to-1 multiplexer – WHEN-ELSE statement A 2-to-1 multiplexer – IF statement 4 Bit Ripple Carry Model using For Statement4 Bit Ripple Carry Model Want to write a VHDL model for a 4 bit ripple carry adder. Logic equation for each full adder is: sum

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  • “ A Developer’s Guide to Data Modeling for SQL Server explains the concepts and practice of data modeling with a clarity that makes the technology accessible to anyone building databases and data-driven applications. “Eric Johnson and Joshua Jones combine a deep understanding of the science of data modeling with the art that comes with years of experience. If you’re new to data modeling, or find the need to brush up on its concepts, this book is for you.” —Peter Varhol, Executive Editor, Redmond Magazine ...

    pdf299p ringphone 06-05-2013 53 10   Download

  • This Second Edition of the go-to reference combines the classical analysis and modern applications of applied mathematics for chemical engineers. The book introduces traditional techniques for solving ordinary differential equations (ODEs), adding new material on approximate solution methods such as perturbation techniques and elementary numerical solutions. It also includes analytical methods to deal with important classes of finite-difference equations. The last half discusses numerical solution techniques and partial differential equations (PDEs). The read...

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  • A topic model outputs a set of multinomial distributions over words for each topic. In this paper, we investigate the value of bilingual topic models, i.e., a bilingual Latent Dirichlet Allocation model for finding translations of terms in comparable corpora without using any linguistic resources. Experiments on a document-aligned English-Italian Wikipedia corpus confirm that the developed methods which only use knowledge from word-topic distributions outperform methods based on similarity measures in the original word-document space.

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  • The fundamental objects that we deal with in calculus are functions. This chapter prepares the way for calculus by discussing the basic ideas concerning functions, their graphs, and ways of transforming and combining them. We stress that a function can be represented in different ways: by an equation, in a table, by a graph, or in words.

    pdf0p vigro23 29-08-2012 85 4   Download

  • In the course of updating the earlier research, the authors reviewed the 12 regulatory categories covered in the original report and eliminated three of them (restrictions on portraying children, athletic achievement, and intoxication) because of their limited scope and the difficulty in enforcing them. Two of the earlier placement categories (outdoor ads near children and outdoor ads near schools, playgrounds, and churches) had substantial overlap and were combined into a single “outdoor ads” category.

    pdf15p nhacchovina 22-03-2013 32 4   Download

  • Content Chapter 4: A – Overview What is structural modeling Primitive gates Switches User-defined primitives B – Examples Combinational Circuit Sequential Circuit

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  • Dataflow model For complex design: number of gates is very large - need a more effective way to describe circuit Dataflow model: Level of abstraction is higher than gate-level, describe the design using expressions instead of primitive gates Circuit is designed in terms of dataflow between register, how a design processes data rather than instantiation of individual gates RTL (register transfer level): is a combination of dataflow and behavioral modeling

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  • In this paper we examine how the differences in modelling between different data driven systems performing the same NLP task can be exploited to yield a higher accuracy than the best individual system. We do this by means of an experiment involving the task of morpho-syntactic wordclass tagging. Four well-known tagger generators (Hidden Markov Model, Memory-Based, Transformation Rules and Maximum Entropy) are trained on the same corpus data. After comparison, their outputs are combined using several voting strategies and second stage classifiers. ...

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  • Reading is known to be an essential task in language learning, but finding the appropriate text for every learner is far from easy. In this context, automatic procedures can support the teacher’s work. Some tools exist for English, but at present there are none for French as a foreign language (FFL). In this paper, we present an original approach to assessing the readability of FFL texts using NLP techniques and extracts from FFL textbooks as our corpus. Two logistic regression models based on lexical and grammatical features are explored and give quite good predictions on new texts. ...

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  • The Internet has indeed helped create a global village. Yet, as more people connect to the Internet from all over the world, the reality remains; they speak different languages and have different expectations. In order to meet these expectations it makes it mandatory for companies to develop country or region specific websites. Websites should also have online translations and should be aware of different business customs. Marketers are often tempted to use their existing business models and values and introduce them to an entirely different environment. This is a mistake. ...

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  • The large combined search space of joint word segmentation and Part-of-Speech (POS) tagging makes efficient decoding very hard. As a result, effective high order features representing rich contexts are inconvenient to use. In this work, we propose a novel stacked subword model for this task, concerning both efficiency and effectiveness.

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  • We present a novel probabilistic classifier, which scales well to problems that involve a large number of classes and require training on large datasets. A prominent example of such a problem is language modeling. Our classifier is based on the assumption that each feature is associated with a predictive strength, which quantifies how well the feature can predict the class by itself. The predictions of individual features can then be combined according to their predictive strength, resulting in a model, whose parameters can be reliably and efficiently estimated.

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  • We present a global joint model for lemmatization and part-of-speech prediction. Using only morphological lexicons and unlabeled data, we learn a partiallysupervised part-of-speech tagger and a lemmatizer which are combined using features on a dynamically linked dependency structure of words. We evaluate our model on English, Bulgarian, Czech, and Slovene, and demonstrate substantial improvements over both a direct transduction approach to lemmatization and a pipelined approach, which predicts part-of-speech tags before lemmatization. ...

    pdf9p hongphan_1 14-04-2013 31 3   Download



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