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Đến với nội dung đề tài "Conservative Synchronization of Large-Scale Network Simulations (Đồng bộ thận trọng trong mô phỏng mạng truyền thông quy mô lớn)" để nắm bắt được những nội dung tổng quan về mô phỏng mạng truyền thông, phân tích các mô hình CMB, áp dụng mô hình phân tích null message để dự đoán hiệu suất mô phỏng, phần mềm mô phỏng network simulation,... Mời các bạn cùng tham khảo để nắm bắt nội dung chi tiết.
Synchronization is the coordination of events to operate a system in unison. The familiar conductor of an orchestra serves to keep the orchestra in time.
Systems operating with all their parts in synchrony are said to be synchronous or in sync.
Firefighters marching in a parade
Some systems may be only approximately synchronized, or plesiochronous. For some applications relative offsets between events need to be determined, for others only the order of the event is important.
Today, synchronization can occur on a global basis due to GPS-enabled timekeeping systems....
[ Team LiB ] Recipe 8.3 Synchronizing a DataSet with an XML Document Problem You need to work with both a DataSet and its XML representation. Solution Use a synchronized DataSet and XmlDataDocument. The sample code contains two event handlers and one method:
[ Team LiB ] Recipe 7.6 Synchronizing Master-Detail Web Forms DataGrids Problem You need to create a master-detail pair of DataGrid controls and synchronize them so that when you select a record in the master, the child grid is updated with the corresponding records. Solution Fill a DataSet with results from both tables
We discuss some of the practical issues that arise from decoding with general synchronous context-free grammars. We examine problems caused by unary rules and we also examine how virtual nonterminals resulting from binarization can best be handled. We also investigate adding more ﬂexibility to synchronous context-free grammars by adding glue rules and phrases.
Machine transliteration is deﬁned as automatic phonetic translation of names across languages. In this paper, we propose synchronous adaptor grammar, a novel nonparametric Bayesian learning approach, for machine transliteration. This model provides a general framework without heuristic or restriction to automatically learn syllable equivalents between languages.
Glial cells, especially astrocytes, are not merely supportive cells, but are
important partners to neighboring cells, including neurons, vascular cells,
and other glial cells. Although glial cells are not excitable in terms of
electrophysiology, they have been shown to generate synchronized Ca
oscillations) through mechanisms of chemical coupling.
We describe our experiments with training algorithms for tree-to-tree synchronous tree-substitution grammar (STSG) for monolingual translation tasks such as sentence compression and paraphrasing. These translation tasks are characterized by the relative ability to commit to parallel parse trees and availability of word alignments, yet the unavailability of large-scale data, calling for a Bayesian tree-to-tree formalism.
This paper proposes a method of correcting annotation errors in a treebank. By using a synchronous grammar, the method transforms parse trees containing annotation errors into the ones whose errors are corrected. The synchronous grammar is automatically induced from the treebank. We report an experimental result of applying our method to the Penn Treebank.
We present a novel approach to deciding whether two sentences hold a paraphrase relationship. We employ a generative model that generates a paraphrase of a given sentence, and we use probabilistic inference to reason about whether two sentences share the paraphrase relationship. The model cleanly incorporates both syntax and lexical semantics using quasi-synchronous dependency grammars (Smith and Eisner, 2006).
We present a phrasal synchronous grammar model of translational equivalence. Unlike previous approaches, we do not resort to heuristics or constraints from a word-alignment model, but instead directly induce a synchronous grammar from parallel sentence-aligned corpora. We use a hierarchical Bayesian prior to bias towards compact grammars with small translation units. Inference is performed using a novel Gibbs sampler over synchronous derivations.
We combine the strengths of Bayesian modeling and synchronous grammar in unsupervised learning of basic translation phrase pairs. The structured space of a synchronous grammar is a natural ﬁt for phrase pair probability estimation, though the search space can be prohibitively large. Therefore we explore efﬁcient algorithms for pruning this space that lead to empirically effective results.
This paper presents the ﬁrst empirical results to our knowledge on learning synchronous grammars that generate logical forms. Using statistical machine translation techniques, a semantic parser based on a synchronous context-free grammar augmented with λoperators is learned given a set of training sentences and their correct logical forms. The resulting parser is shown to be the bestperforming system so far in a database query domain.
In applications such as translation and paraphrase, operations are carried out on grammars at the meta level. This paper shows how a meta-grammar, defining structure at the meta level, is useful in the case of such operations; in particular, how it solves problems in the current definition of Synchronous TAG (Shieber, 1994) caused by ignoring such structure in mapping between grammars, for applications such as translation. Moreover, essential properties of the formalism remain unchanged.
This paper looks at representing paraphrases using the formalism of Synchronous TAGs; it looks particularly at comparisons with machine translation and the modifications it is necessary to make to Synchronous TAGs for paraphrasing. A more detailed version is in Dras (1997a).
According to Dr. Goldratt, synchronous manufacturing refers to the entire production process working together in harmony to achieve the goals of the firm. Synchronous manufacturing logic attempts to coordinate all resources so that they work together and are in harmony or are "synchronized." The goal is on total system performance, not on localized measures such as labor or machine utilization.
A characterization of the expressive power of synchronous tree-adjoining grammars (STAGs) in terms of tree transducers (or equivalently, synchronous tree substitution grammars) is developed. Essentially, a STAG corresponds to an extended tree transducer that uses explicit substitution in both the input and output. This characterization allows the easy integration of STAG into toolkits for extended tree transducers. Moreover, the applicability of the characterization to several representational and algorithmic problems is demonstrated. ...
We present a method for the computation of preﬁx probabilities for synchronous contextfree grammars. Our framework is fairly general and relies on the combination of a simple, novel grammar transformation and standard techniques to bring grammars into normal forms.
We take a multi-pass approach to machine translation decoding when using synchronous context-free grammars as the translation model and n-gram language models: the ﬁrst pass uses a bigram language model, and the resulting parse forest is used in the second pass to guide search with a trigram language model. The trigram pass closes most of the performance gap between a bigram decoder and a much slower trigram decoder, but takes time that is insigniﬁcant in comparison to the bigram pass.