2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)最新文献_第7页

Continuation Semantics for Dynamic Hierarchical Systems 动态层次系统的延拓语义

2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2015-09-01 DOI: 10.1109/SYNASC.2015.52

Gabriel Ciobanu, E. Todoran

{"title":"Continuation Semantics for Dynamic Hierarchical Systems","authors":"Gabriel Ciobanu, E. Todoran","doi":"10.1109/SYNASC.2015.52","DOIUrl":"https://doi.org/10.1109/SYNASC.2015.52","url":null,"abstract":"We present a denotational semantics designed with metric spaces and continuations for a simple concurrent language LMB embodying a representative set of features encountered in membrane computing. LMB is a multiset rewriting language. In LMB multisets of objects are encapsulated in hierarchical structures of compartments, or regions, delimited by membranes. The behaviour of each membrane is specified by means of multiset rewriting rules. The semantics of parallel composition in LMB is based on the concept of maximal parallelism. Computations proceed according to the multiset rewriting rules, nondeterministically choosing the rules and the objects. Membranes can be grouped into classes based on the rewriting rules that they encapsulate, LMB also provides a primitive for membrane creation, or instantiation. In this sense, LMB is similar to anobject oriented language. We use continuations and a powerdomain constructionto represent nondeterministic behavior. An element of a powerdomain is a collection of sequences of observables representing dynamic membrane structures. Our continuation semantics describes in a compositional manner the behavior of an LMB program as a dynamic hierarchical system. As far as we know, this is the firstpaper that presents a metric denotational semanticsfor the combination of features embodied in LMB.","PeriodicalId":6488,"journal":{"name":"2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"16 1","pages":"281-288"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85336567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Automatic Language Identification for Romance Languages Using Stop Words and Diacritics 使用停止词和变音符符的罗曼语自动语言识别

2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2015-09-01 DOI: 10.1109/SYNASC.2015.45

Ciprian-Octavian Truică, Julien Velcin, A. Boicea

{"title":"Automatic Language Identification for Romance Languages Using Stop Words and Diacritics","authors":"Ciprian-Octavian Truică, Julien Velcin, A. Boicea","doi":"10.1109/SYNASC.2015.45","DOIUrl":"https://doi.org/10.1109/SYNASC.2015.45","url":null,"abstract":"Automatic language identification is a natural language processing problem that tries to determine the natural language of a given content. In this paper we present a statistical method for automatic language identification of written text using dictionaries containing stop words and diacritics. We propose different approaches that combine the two dictionaries to accurately determine the language of textual corpora. This method was chosen because stop words and diacritics are very specific to a language, although some languages have some similar words and special characters they are not all common. The languages taken into account were romance languages because they are very similar and usually it is hard to distinguish between them from a computational point of view. We have tested our method using a Twitter corpus and a news article corpus. Both corpora consists of UTF-8 encoded text, so the diacritics could be taken into account, in the case that the text has no diacritics only the stop words are used to determine the language of the text. The experimental results show that the proposed method has an accuracy of over 90% for small texts and over 99.8% for large texts.","PeriodicalId":6488,"journal":{"name":"2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"1 1","pages":"243-246"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86383362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Static Analysis in Finitely Supported Mathematics 有限支持数学中的静态分析

2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2015-09-01 DOI: 10.1109/SYNASC.2015.56

A. Alexandru, Gabriel Ciobanu

引用次数: 1

Computation of Stirling Numbers and Generalizations 斯特林数的计算及其推广

2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2015-09-01 DOI: 10.1109/SYNASC.2015.18

S. Ilie, D. J. Jeffrey, Robert M Corless, X. Zhang

引用次数: 4

Symbolic Derivation of Mean-Field PDEs from Lattice-Based Models 基于格子模型的平均场偏微分方程的符号推导

2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2015-06-29 DOI: 10.1109/SYNASC.2015.14

C. Koutschan, Helene Ranetbauer, G. Regensburger, Marie-Therese Wolfram

{"title":"Symbolic Derivation of Mean-Field PDEs from Lattice-Based Models","authors":"C. Koutschan, Helene Ranetbauer, G. Regensburger, Marie-Therese Wolfram","doi":"10.1109/SYNASC.2015.14","DOIUrl":"https://doi.org/10.1109/SYNASC.2015.14","url":null,"abstract":"Transportation processes, which play a prominent role in the life and social sciences, are typically described by discrete models on lattices. For studying their dynamics a continuous formulation of the problem via partial differential equations (PDE) is employed. In this paper we propose a symbolic computation approach to derive mean-field PDEs from a lattice-based model. We start with the microscopic equations, which state the probability to find a particle at a given lattice site. Then the PDEs are formally derived by Taylor expansions of the probability densities and by passing to an appropriate limit as the time steps and the distances between lattice sites tend to zero. We present an implementation in a computer algebra system that performs this transition for a general class of models. In order to rewrite the mean-field PDEs in a conservative formulation, we adapt and implement symbolic integration methods that can handle unspecified functions in several variables. To illustrate our approach, we consider an application in crowd motion analysis where the dynamics of bidirectional flows are studied. However, the presented approach can be applied to various transportation processes of multiple species with variable size in any dimension, for example, to confirm several proposed mean-field models for cell motility.","PeriodicalId":6488,"journal":{"name":"2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"10 1","pages":"27-33"},"PeriodicalIF":0.0,"publicationDate":"2015-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86993857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5