Mathematics and Manufacturing: The Symbolic Approach

2014 ◽  
pp. 481-494
Author(s):  
Ryusuke Masuoka ◽  
Hirokazu Anai
Keyword(s):  
Symbolic Approach

The Reception of Ancient Egypt and Its Script in Renaissance Europe

2020 ◽  
pp. 192-204
Author(s):  
Lucie Jirásková
Keyword(s):  
Personal Experience ◽  
Late Antiquity ◽  
Ancient Egypt ◽  
Roman Period ◽  
Successful Attempt ◽  
Symbolic Approach

The chapter focuses on the perception of ancient Egypt and its culture through the eyes of Renaissance scholars and humanists. They could have known ancient Egypt from personal experience, including travels to Egypt or visits to Egyptian monuments that had been brought to Italy in the Roman period. The hieroglyphic script engraved into obelisks became a source of inspiration for the emblematics, but in fact never led to any successful attempt to decipher the ancient script. The symbolic approach to hieroglyphs was also supported by the philosophical trend of the time, Hermetism. It was a “construct” of Late Antiquity, resurrected and elaborated by Renaissance humanists, who were able to apply it to various branches of Renaissance science.

A numerical approach for structural system identification by observability techniques

2016 ◽  
Author(s):  
Jose Antonio Lozano Galant ◽  
Maria Nogal ◽  
Jun Lei ◽  
Dong Xu ◽  
José Turmo
Keyword(s):  
System Identification ◽  
Numerical Approach ◽  
Mathematical Foundation ◽  
Structural System ◽  
Numerical Errors ◽  
Definition Of ◽  
Structural System Identification ◽  
Symbolic Approach

Observability techniques enable the structural system identification of static structures from a symbolic approach. The main advantage of this method is its deep mathematical foundation that enables the definition of parametric equations for the estimates. Nevertheless, this symbolic approach is not enough for the application of this method on actual structures. To fill this gap, this article presents the introduction into the symbolic structural system identification by observability techniques of a new numerical approach. This application includes the development of an algorithm that reduces the unavoidable numerical errors produced by the lack of precision of computers. The comparison of the observability technique with other existing methods presented in the literature shows that the number of required measurements is significantly lower. Furthermore, contrary to other analysed methods, no information from the undamaged structure is required.

scholarly journals Do nations have navels'?: Gellner and Smith on the emergence of nations

2004 ◽  
pp. 177-210 ◽  
Author(s):  
Milan Subotic
Keyword(s):  
Research Priorities ◽  
The Common ◽  
Symbolic Approach ◽  
Theoretical Paradigms

This paper interprets and analyzes the debate having taken place in 1995 between E. Gellner and A. Smith concerning the problem of the emergence of nations. This discussion is used as an example to show the basic general features of two approaches in theories of nationalism - the modernist and the ethno symbolic ones. Pointing to the common assumptions shared by Gellner's and Smith's theories of nations (critique of primordialism and perennialism), the author interprets ethno-symbolism as a sort of internal self-criticism of the modernist standpoint. This polemic is therefore interpreted not as a debate between "creationist" and "evolutionist" solutions to the problem of the emergence of nations, but rather as a debate between two theoretical paradigms defining different research priorities in studying nations and nationalisms. From this perspective, the author concludes that the ethno symbolic approach to the genealogy of nations has broader heuristic capacities than the modernist paradigm, at least when the emergence of "peripheral nations" and the understanding of the dynamic of their nationalisms are concerned.

scholarly journals A Symbolic Approach to Explaining Bayesian Network Classifiers

2018 ◽  
Author(s):  
Andy Shih ◽  
Arthur Choi ◽  
Adnan Darwiche
Keyword(s):  
Bayesian Network ◽  
Case Studies ◽  
Decision Diagrams ◽  
Minimal Set ◽  
Symbolic Form ◽  
Bayesian Network Classifiers ◽  
Current State ◽  
Current Classification ◽  
Decision Functions ◽  
Symbolic Approach

We propose an approach for explaining Bayesian network classifiers, which is based on compiling such classifiers into decision functions that have a tractable and symbolic form. We introduce two types of explanations for why a classifier may have classified an instance positively or negatively and suggest algorithms for computing these explanations. The first type of explanation identifies a minimal set of the currently active features that is responsible for the current classification, while the second type of explanation identifies a minimal set of features whose current state (active or not) is sufficient for the classification. We consider in particular the compilation of Naive and Latent-Tree Bayesian network classifiers into Ordered Decision Diagrams (ODDs), providing a context for evaluating our proposal using case studies and experiments based on classifiers from the literature.

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