Measuring is more than assigning numbers

'Measurement is fundamental to research-related activities in social science (hence this Handbook). In my own field of education research, perhaps the most discussed element of education lies in test scores. Examination results are measurements, the number of students attaining a particular standard in a test is a measurement; indeed the standard of a test is a measurement. The allocation of places at school, college or university, student:teacher ratios, funding plans, school timetables, staff workloads, adult participation rates, and the stratification of educational outcomes by sex, social class, ethnicity or geography for example, are all based on measurements. Good and careful work has been done in all of these areas (Nuttall 1987). However, the concept of measurement itself remains under-examined, and is often treated in an uncritical way. In saying this I mean more than the usual lament about qualitative:quantitative schism or the supposed reluctance of social scientists to engage with numeric analysis (Gorard et al. 2004a). I mean that even where numeric analysis is being conducted, the emphasis is on collecting, collating, analysing, and reporting the kinds of data generated by measurement, with the process of measurement and the rigor of the measurement instrument being somewhat taken for granted by many commentators. Issues that are traditionally considered by social scientists include levels of measurement, reliability, validity, and the creation of complex indices (as illustrated in some of the chapters contained in this volume). But these matters are too often dealt with primarily as technical matters – such as how to assess reliability or which statistical test to use with which combination of levels of measurement. The process of quantification itself is just assumed'

Models of computation: A numeric analysis and performance evaluation

This research seeks to better understand what drives performance in computation. To develop this understanding the researcher investigates the literature on computational performance within the classical and quantum paradigm for both binary and multi-value logic. Based on the findings of the literature the researcher evaluates through an experiment of addition what drives performance and how performance can be improved. For the evaluation of this research, a realist research paradigm employs two research methods. The first is an automaton model of computation to model each of the computing paradigms and computational logic. The second is computational complexity theory for measuring the performance of addition. Through this evaluation the researcher seeks to gain a better understanding of what drives computational performance and how addition can be performed more efficiently. The results of the research lead the researcher to conclude that modernisation of machinery caused the birth start of automated computing and the binary number system in computers. As this research indicated that computation through increasing the radix can improve performance of computation for addition. Based on reported findings in the science of quantum mechanics research, it would be possible to implement a model of computation with increased radix. Through embracing state discrimination/ distinguishability this research calls to review the current quantum computing paradigm based on state duality

Control System Simulation of Technical Equipment

AbstractSubmission is concerned to complete information system about quality, operation, automatic testing using mechatronic system and new evaluating method of vehicle subsystem. Presentation of statistic significant group of tracing commercial cars is used. Data about operational parameters were taken from this group. Numeric analysis is realized on the base of automatic collection and systematic recording of commercial car operation. Proposed new information system about operation and trial process allows verification according to proposed method. Critical components verified in laboratory conditions are detected by numeric analysis of reliability. Trial method is described and also numerically compared in three levels. Quality level increasing not only for final product, but also related automatic test laboratory for cars is the result of these principles respecting. The model of technical system operation is proposed by estimating the level of its elements’ reliability. Application of the repair cycle adaptive structure creates the basis of organizing the preventive maintenance and repair and increasing the operational efficiency of technical systems

Object oriented studies into artificial space debris

A prototype simulation is being developed under contract to the Royal Aerospace Establishment (RAE), Farnborough, England, to assist in the discrimination of artificial space objects/debris. The methodology undertaken has been to link Object Oriented programming, intelligent knowledge based system (IKBS) techniques and advanced computer technology with numeric analysis to provide a graphical, symbolic simulation. The objective is to provide an additional layer of understanding on top of conventional classification methods. Use is being made of object and rule based knowledge representation, multiple reasoning, truth maintenance and uncertainty. Software tools being used include Knowledge Engineering Environment (KEE) and SymTactics for knowledge representation. Hooks are being developed within the SymTactics framework to incorporate mathematical models describing orbital motion and fragmentation. Penetration and structural analysis can also be incorporated. SymTactics is an Object Oriented discrete event simulation tool built as a domain specific extension to the KEE environment. The tool provides facilities for building, debugging and monitoring dynamic (military) simulations

Symbolic numeric analysis of attractors in randomly generated piecewise affine models of gene networks

International audienceThe goal of this paper is to present and experiment the computer aided analysis of phase portraits of some ordinary differential equations. The latter are piecewise affine, and have been primitively introduced as coarse-grained models of gene regulatory networks. Their simple formulation allows for numerical investigation, but their typical phase portrait is still largely unknown. They have been shown to present all the main aspects of nonlinear dynamics, including chaos. But it is still of interest to simulate random versions of these models, and to count and classify their attractors. This paper presents algorithms that allow for an automatic treatment of this kind, and apply it to four-dimensional sample systems. Contrary to previous studies, the latter have several thresholds in each direction, a fact whose consequences on the number and nature of attractors is discussed