Widely, strongly and weakly defined measurement

Finkelstein, L.

doi:10.1016/s0263-2241(03)00018-6

Cited by 122 publications

(81 citation statements)

References 2 publications

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“…Sendo assim a medição é um processo de representação, relacionando o mundo real com este sistema simbólico. (MARLI, 1996;FINKELSTEIN, 2003FINKELSTEIN, , 2009 As escalas no grande universo das ciências comportamentais, que não diferem tanto de outras ciências, são fincadas em pressupostos particulares e desenvolvidas por modelos específicos (COSTA, 2011).…”

Section: Escala Likertunclassified

Regressão Não-Linear De Bleasdale: Revisitando Os Pressupostos Teóricos De Jakob Nielsen

Santos¹,

Silva²,

Walker³

et al. 2017

Blucher Design Proceedings

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RESUMO INTRODUÇÃOEm um mundo em que a informação tem grande importância e trafega globalmente de uma forma extremamente rápida, cada vez mais são demandadas ferramentas que facilitem essa comunicação. Desta forma, a tecnologia da informação teve sua parcela de contribuição para os processos e serviços empresariais, além das estratégias competitivas de empresas e pessoas. (TORRES, 2015) Com o tempo, não só as empresas viram a necessidade de uma comunicação dinâmica e globalizada, mas pessoas físicas começaram a utilizar o seu computador pessoal com enfoque de busca, compras, uso de mídia social entre outras. Isto acabou popularizando o uso e aumentando o número de pessoas com acesso à internet. (IBGE, 2015) O volume de vendas de aparelhos smartphones é muito grande no mundo. Em 2015, foram enviados para as lojas 1.5 bilhões de celulares. Esse total é 11,9% maior que no ano anterior (IDC, 2015). O IDC Brasil afirma que no mercado brasileiro em 2014 foram vendidos 104

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Section: Escala Likertunclassified

Regressão Não-Linear De Bleasdale: Revisitando Os Pressupostos Teóricos De Jakob Nielsen

Santos¹,

Silva²,

Walker³

et al. 2017

Blucher Design Proceedings

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show abstract

“…Among social scientists and philosophers of science this approach is widely thought to be the richest storehouse of information on the foundations of deterministic measurement. Unfortunately, because the underlying theory is largely disengaged from much of what is taken to be crucial to natural scientists and engineers in measurement practice, namely the articulation of causal interactions between measured systems and measuring instruments, and the relations between measurement information and measurement uncertainty, it has not received much support among most physicists and engineers, with the possible exception of Finkelstein [6] and those around him.…”

Section: Conceptual Issues In the Representationalist Founda-mentioning

confidence: 99%

“…Likewise, in general relativity and quantum mechanics, quantities are appropriately fitted to their specific theoretical contexts. 6 So a physical quantity is not just a Maxwellian product 6 The most fundamental difference between the classical and relativistic concepts of velicity is seen in their composition. In general relativity, the set factorization into its numerical value and unit, but factorization relative to the quantity's underlying theory or model.…”

Section: Introduction and Overviewmentioning

confidence: 99%

An Algebraic Approach to Unital Quantities and their Measurement

Domotor

Batitsky

2016

Measurement Science Review

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The goals of this paper fall into two closely related areas. First, we develop a formal framework for deterministic unital quantities in which measurement unitization is understood to be a built-in feature of quantities rather than a mere annotation of their numerical values with convenient units. We introduce this idea within the setting of certain ordered semigroups of physical-geometric states of classical physical systems. States are assumed to serve as truth makers of metrological statements about quantity values. A unital quantity is presented as an isomorphism from the target system's ordered semigroup of states to that of positive reals. This framework allows us to include various derived and variable quantities, encountered in engineering and the natural sciences. For illustration and ease of presentation, we use the classical notions of length, time, electric current and mean velocity as primordial examples. The most important application of the resulting unital quantity calculus is in dimensional analysis. Second, in evaluating measurement uncertainty due to the analog-to-digital conversion of the measured quantity's value into its measuring instrument's pointer quantity value, we employ an ordered semigroup framework of pointer states. Pointer states encode the measuring instrument's indiscernibility relation, manifested by not being able to distinguish the measured system's topologically proximal states. Once again, we focus mainly on the measurement of length and electric current quantities as our motivating examples. Our approach to quantities and their measurement is strictly state-based and algebraic in flavor, rather than that of a representationalist-style structure-preserving numerical assignment.

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“…It constitutes representation by symbols of properties of entities of the real world, based on an objective empirical process, but lacks some, or all, of the distinctive characteristics of strongly-defined measurement [23][24][25][26][27]. It lacks well-formed theories and involves predominantly non-physical sciences.…”

Section: Mathematical Modelling In Soft Measurement Systemsmentioning

confidence: 99%

“…An example could be measurement and natural language [23]. There is a strong relation between description by measurement, in the weakly defined sense, and description by natural language, which is in some of its functions a general form of symbolic representation.…”

Section: Mathematical Modelling In Soft Measurement Systemsmentioning

confidence: 99%

Mathematical modelling in the analysis and design of hard and soft measurement systems

Khan

Finkelstein

2013

Measurement

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Citation: Khan, S. and Finkelstein, L. (2013). Mathematical modelling in the analysis and design of hard and soft measurement systems. Measurement, 46(8), pp. 2936Measurement, 46(8), pp. -2941Measurement, 46(8), pp. . doi: 10.1016Measurement, 46(8), pp. /j.measurement.2013 This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent b s t r a c tThis paper briefly looks into the role and extent of mathematical modelling in the design and analysis of measurement systems, especially measurement sub-systems in the form of instruments and instrument elements. These fall within the classical domain of hard measurement (physical, strongly-defined measurement). It also examines the role and use of mathematical modelling in the area of soft measurement (non-physical, weakly defined measurement). These constitute two sub-sets of widely-defined measurement. Based on a number of examples it demonstrates the use of modern modelling techniques in the design and analysis of sub-systems in measurement technology. In doing so, it focuses on the scope and importance of physical modelling at a sub-system level, which ultimately contributes to modelling activities at a global systems level.

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Widely, strongly and weakly defined measurement

Cited by 122 publications

References 2 publications

Regressão Não-Linear De Bleasdale: Revisitando Os Pressupostos Teóricos De Jakob Nielsen

Regressão Não-Linear De Bleasdale: Revisitando Os Pressupostos Teóricos De Jakob Nielsen

An Algebraic Approach to Unital Quantities and their Measurement

Mathematical modelling in the analysis and design of hard and soft measurement systems

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