Realisation of an effective dual-parameter sensor employing a single fibre Bragg grating structure

A novel technology for simultaneous and independent measurement of dual parameters is proposed and experimented. The length of a single fibre Bragg grating (FBG) is divided into two parts. The temperature variation and another measurand can be measured independently and simultaneously, and the thermal effect can be erased with great ease. © 2005 Elsevier Ltd. All rights reserved.

Microfiber-based inline Mach-Zehnder interferometer for dual-parameter measurement

An approach to realizing simultaneous measurement of refractive index (RI) and temperature based on a microfiber-based dual inline Mach-Zehnder interferometer (MZI) is proposed and demonstrated. Due to different interference mechanisms, as one interference between the core mode and the lower order cladding mode in the sensing single-mode fiber and the other interference between the fundamental mode and the high-order mode in the multimode microfiber, the former interferometer achieves RI sensitivity of -23.67 nm/RIU and temperature sensitivity of 81.2 pm/oC, whereas those of the latter are 3820.23 nm/RIU, and -465.7 pm/oC, respectively. The large sensitivity differences can provide a more accurate demodulation of RI and temperature. The sensor is featured with multiparameters measurement, compact structure, high sensitivity, low cost, and easy fabrication.

Nonlinear Variational Inequalities Depending on a Parameter

This paper develops the results announced in the Note [14]. Using an eigenvalue problem governed by a variational inequality, we try to unify the theory concerning the post-critical equilibrium state of a thin elastic plate subjected to unilateral conditions.

Parameter Identification of a Fed-Batch Cultivation of S. Cerevisiae using Genetic Algorithms

Fermentation processes as objects of modelling and high-quality control are characterized with interdependence and time-varying of process variables that lead to non-linear models with a very complex structure. This is why the conventional optimization methods cannot lead to a satisfied solution. As an alternative, genetic algorithms, like the stochastic global optimization method, can be applied to overcome these limitations. The application of genetic algorithms is a precondition for robustness and reaching of a global minimum that makes them eligible and more workable for parameter identification of fermentation models. Different types of genetic algorithms, namely simple, modified and multi-population ones, have been applied and compared for estimation of nonlinear dynamic model parameters of fed-batch cultivation of S. cerevisiae.

One-Parameter Bifurcation Analysis of Dynamical Systems using Maple

This paper presents two algorithms for one-parameter local bifurcations of equilibrium points of dynamical systems. The algorithms are implemented in the computer algebra system Maple 13 © and designed as a package. Some examples are reported to demonstrate the package’s facilities.

A lumped parameter model for the analysis of the motion of the muscles of the lower limbs under whole-body vibration

Through a lumped parameter modelling approach, a dynamical model, which can reproduce the motion of the muscles of a human body standing in different postures during Whole Body Vibrations (WBVs) treatment, has been developed. The key parameters, associated to the dynamics of the motion of the muscles of the lower limbs, have been identified starting from accelerometer measurements. The developed model can be usefully applied to the optimization of WBVs treatments which can effectively enhance muscle activation. © 2013 IEEE.

Theorem for Series in Three-Parameter Mittag-Leffler Function

Mathematics Subject Classification 2010: 26A33, 33E12.

Conditional Confidence Interval for the Scale Parameter of a Weibull Distribution

2000 Mathematics Subject Classification: 62F25, 62F03.

Microfiber Fabry-Perot interferometer for dual-parameter sensing

We propose and demonstrate a microfiber Fabry-Perot interferometer (MFPI) fabricated by taper-drawing microfiber at the center of a uniform fiber Bragg grating (FBG). The MFPI employing the two separated sections of FBG as reflectors and a length of microfiber as its cavity is derived. Theoretic study shows that the reflection spectrum of such MFPI is consisted of two parts-interference fringes induced by multi-beam interference and reflection spectrum envelope induced by FBGs. Temperature affects both interference fringes and reflection wavelength of FBGs while ambient refractive index (RI) only influences the interference fringes, i.e., MFPI has different response to temperature and RI. Therefore, MFPI for simultaneous sensing of RI and temperature is experimentally demonstrated by tracking a reflection peak of interference fringes and the Bragg wavelength of the FBGs, which are respectively assisted by frequency domain processing and Gaussian fitting of the optical spectrum. Consequently, wavelength measurement resolution of 0.5 pm is realized. © 1983-2012 IEEE.

Type space on a purely measurable parameter space

Several game theoretical topics require the analysis of hierarchical beliefs, particularly in incomplete information situations. For the problem of incomplete information, Hars´anyi suggested the concept of the type space. Later Mertens & Zamir gave a construction of such a type space under topological assumptions imposed on the parameter space. The topological assumptions were weakened by Heifetz, and by Brandenburger & Dekel. In this paper we show that at very natural assumptions upon the structure of the beliefs, the universal type space does exist. We construct a universal type space, which employs purely a measurable parameter space structure.

A diszkrét kiválasztási modell becslése Cox-regresszióval (Parameter estimation for multinomial discrete choice model using Cox-regression)

Considering the so-called "multinomial discrete choice" model the focus of this paper is on the estimation problem of the parameters. Especially, the basic question arises how to carry out the point and interval estimation of the parameters when the model is mixed i.e. includes both individual and choice-specific explanatory variables while a standard MDC computer program is not available for use. The basic idea behind the solution is the use of the Cox-proportional hazards method of survival analysis which is available in any standard statistical package and provided a data structure satisfying certain special requirements it yields the MDC solutions desired. The paper describes the features of the data set to be analysed.

Környezeti kockázatok felmérése. Paraméterek bizonytalanságának hatása a kockázatkezelési döntéshozatalra = Assessment of environmental risks – effects of parameter uncertainty to the risk management decisions

A környezeti kockázatok megfelelő felmérése és kezelése napjaink egyik legfontosabb kérdése, nemcsak a szakmai, hanem a széles értelemben vett közvélemény számára. A szerző cikkében azt vizsgálja, hogy a környezeti kockázatok felmérésének milyen megközelítései vannak. Kulcskérdésként pedig arra koncentrál, hogy a kockázatkezelési döntéseket hogyan befolyásolja a becslések bizonytalansága. Először a környezeti kockázat definícióját adja meg, majd azt mutatja be, hogy a környezeti kockázatok kezelésére vonatkozó megközelítések milyen párhuzamban állnak a pénzügyi rendszerrel, mint komplex rendszerre vonatkozó megközelítésekkel. Végül a jelenleg legnagyobb kockázatoknak tartott környezeti kockázatokat ismerteti röviden. A cikk második részében kockázatkezelési alternatívákat mutat be, és azt, hogy a kockázatkezelési lépések kiválasztását befolyásolja a bizonytalanság. Ezt illusztrálandó Brouwer-Blois (2008) modelljét használva a soklépéses szimulációt és alternatív döntési kritériumot – a kritikus (extrém) költség-hatás mutatót – alkalmazza. _____________ Adequate assessment and management of environmental risks is a key question nowadays also for professional experts and also for the overall public. In this article the author examines the different approaches concerning environmental risks. He concentrates as a key question the influence on risk management decisions of uncertainties raised by our estimations. First he analyses the definition of environmental risks, and he shows the similarities and differences between approaches concerning environmental risks and risks threatening financial system, and finally he gives short overview on the most current environmental risks. In the second part of the paper he presents risk management alternatives and analyses the influential power of uncertainty on risk management decisions. In order to illustrate this phenomenon the author applies the model of Brouwer-Blois (2008) with multistep simulation and an alternative decisive criterion, the ranking based on critical (extreme) cost to effect measure.

Magyarország hét régiójának új gazdaságföldrajzi modellje – paraméterbecslés (The new economic-geography model of Hungary's seven regions - a parameter estimate)

Az új gazdaságföldrajz – amely napjaink egy igen népszerű közgazdaságtani tudományága – modelljének majdnem minden paramétere előállítható közvetlenül külső adatok segítségével. A helyettesítési rugalmassághoz azonban más módszerre van szükség. Puga [1999] által felvázolt új gazdaságföldrajzi modellt követve, egy regressziós egyenlettel megbecsülhetővé válik a kívánt paraméter, amit Magyarország hét régiójára vonatkozó béregyenlet becsléséből nyertünk. A helyettesítési rugalmasság értéke eltér a szakirodalomhoz képest, aminek magyarázata Magyarország fejlettségi szintjével állhat összefüggésben. ____ The model of the new economic geography - very popular material for economic study these days - allows almost every parameter to be presented directly with the aid of outside data. However, another method is required for substitution flexibility. With the new economic-geography model devised by Puga [1999], a regression equation allows an estimate to be made for the desired parameter, which yielded the wage equation for the six regions of Hungary. The value for substitution flexibility differs from that of the literature, the explanation for which may lie in Hungary's level of development.

Parameter design considerations in precision engineering

Parameter design is an experimental design and analysis methodology for developing robust processes and products. Robustness implies insensitivity to noise disturbances. Subtle experimental realities, such as the joint effect of process knowledge and analysis methodology, may affect the effectiveness of parameter design in precision engineering; where the objective is to detect minute variation in product and process performance. In this thesis, approaches to statistical forced-noise design and analysis methodologies were investigated with respect to detecting performance variations. Given a low degree of process knowledge, Taguchi's methodology of signal-to-noise ratio analysis was found to be more suitable in detecting minute performance variations than the classical approach based on polynomial decomposition. Comparison of inner-array noise (IAN) and outer-array noise (OAN) structuring approaches showed that OAN is a more efficient design for precision engineering. ^

Improving the predictability of time series by chaotic parameter estimation

Limited literature regarding parameter estimation of dynamic systems has been identified as the central-most reason for not having parametric bounds in chaotic time series. However, literature suggests that a chaotic system displays a sensitive dependence on initial conditions, and our study reveals that the behavior of chaotic system: is also sensitive to changes in parameter values. Therefore, parameter estimation technique could make it possible to establish parametric bounds on a nonlinear dynamic system underlying a given time series, which in turn can improve predictability. By extracting the relationship between parametric bounds and predictability, we implemented chaos-based models for improving prediction in time series. ^ This study describes work done to establish bounds on a set of unknown parameters. Our research results reveal that by establishing parametric bounds, it is possible to improve the predictability of any time series, although the dynamics or the mathematical model of that series is not known apriori. In our attempt to improve the predictability of various time series, we have established the bounds for a set of unknown parameters. These are: (i) the embedding dimension to unfold a set of observation in the phase space, (ii) the time delay to use for a series, (iii) the number of neighborhood points to use for avoiding detection of false neighborhood and, (iv) the local polynomial to build numerical interpolation functions from one region to another. Using these bounds, we are able to get better predictability in chaotic time series than previously reported. In addition, the developments of this dissertation can establish a theoretical framework to investigate predictability in time series from the system-dynamics point of view. ^ In closing, our procedure significantly reduces the computer resource usage, as the search method is refined and efficient. Finally, the uniqueness of our method lies in its ability to extract chaotic dynamics inherent in non-linear time series by observing its values. ^