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George Herbert Mead developed a sophisticated social and pragmatist model of science, which has escaped the attention of most modern-day scholars and symbolic interactionists. While Mead’s insights have much to offer to contemporary interactionist studies of science and technology, they are not without their shortcomings. In his analyses, Mead tends to put most of his emphasis on the concrete micro-foundations of knowledge production and the functional necessity of science as a problem-solving institution par excellence, yet he fails to seriously question the role of power and domination within the competitive terrain of scientific fields. Lonnie Athens has attempted to reconstitute the basic assumptions of symbolic interactionism by insisting that domination, rather than mere sociality, is the foundation of human existence, since the root of all social acts are comprised of super- and subordinate relations. Changing our fundamental assumptions about social action thus forces us to ask new questions about the micro- and macro-processes we explore in our research. By applying this radicalized lens to Mead’s view of science, I attempt to forge a new interactionist approach, which would better connect with and contribute to the critical wing of the science studies tradition.

This chapter seeks to evaluate the charges made by a number of Herbert Blumer's critics who claim that he has in various ways misconstrued or misapplied the social psychological ideas of George Herbert Mead. My examination of these charges leads me to conclude that numerous passages in which Blumer discusses Mead's thought are in fact open to several legitimate objections: Blumer seldom documents or supports his discussions of Mead's ideas by means of specific references to relevant passages in Mead's lectures or writings; he fails to note that his own theoretical project typically begins where Mead's project ends; he often uses the concepts of meaning, interpretation, and “taking the role of the other” in ways that differ somewhat from the uses Mead makes of these notions in his theorizing. Nevertheless, these shortcomings and differences by no means support the arguments of those critics who exaggerate the significance of Mead's so-called behaviorism or of Blumer's alleged subjectivism; nor do they justify the claims of those who fail to see how Blumer's theory of experiential objects, despite its inadequate formulation and development, is a legitimate attempt to extend the account of such objects one finds in Mead's later writings. Blumer, in short, may not always have been a completely accurate interpreter of Mead, but he was in most important respects a faithful, creative, and effective champion of Mead’s social psychological ideas.

The purpose of this paper is to propose hybrid revised weighted fuzzy c-means (RWFCM) clustering and Nelder–Mead (NM) simplex algorithm, called as RWFCM-NM, for generalized multisource Weber problem (MWP).

Although the RWFCM claims that there is no obligation to sequentially use different methods together, NM’s local search advantage is investigated and performance of the proposed hybrid algorithm for generalized MWP is tested on well-known research data sets.

Test results state the outstanding performance of new hybrid RWFCM and NM simplex algorithm in terms of cost minimization and CPU times.

Proposed approach achieves better results in continuous facility location problems.

ALTHOUGH the University of Southampton has had an independent existence for ten years it has roots going back almost a century in the Hartley Institute. An early pioneer in aeronautics, F. W. Lanchester received his technical training in Southampton and the first of the new engineering buildings at the university has been called after him.

THE mechanical properties of 112 nominally identical glass reinforced laminates prepared by four different organisations have been determined. A statistical analysis of the results investigated the effect of variability in the raw materials and laminating techniques. It was concluded that the total variability was approximately 7 per cent.

This paper aims to propose a simple, derivative-free novel method named as Nelder–Mead optimization algorithm to estimate the unknown parameters of the photovoltaic (PV) module considering the environmental conditions.

At a particular temperature and irradiation, experimental current-voltage (I-V) and power-voltage (P-V) characteristics are drawn and considered as a reference model. The PV system model with unknown model parameters is considered as the adaptive model whose unknown model parameters are to be adapted so that the simulated characteristics closely matches with the experimental characteristics. A single diode (Rsh) model with five unknown model parameters is considered here for the parameter estimation.

The key advantages of this method are that parameters are estimated considering environmental conditions. Experimental characteristics are considered for parameter estimation which gives accurate results. Parameters are estimated considering both I-V and P-V curves as most of the applications demand extraction of the actual power from the PV module.

The proposed model is compared with other three well-known models available in the literature considering various statistical errors. The results show the superiority of the proposed model with a minimum error for both I-V and P-V characteristics.

The awareness for protecting the environment has resulted in remanufacturing and recycling policies in manufacturing industries. Carbon emission is one of the most important elements affecting the environment. Carbon emission due to production and transportation creates complicated situations for the manufacturing firms by affecting the manufacturer's carbon quota. The ecological consequences posed in a reverse logistic model are the subject of this study.

The present study explores the fuzzy model of economic production for both remanufacturing and recycling with uncertain cost parameters under the cap-and-trade rule to control the carbon emission due to different modes of transportation. Due to imprecise cost parameters, the hexagonal fuzzy numbers are set to fuzzify the overall cost, which leads to correct decisions in a more confident way. The result is defuzzified by using graded mean integration.

This study offers an explicit condition to control the carbon emission of the manufacturer and reduce the optimum cost. The findings indicate that the collection of used goods that can be remanufactured must be increased. The model is validated numerically. Sensitivity analysis explores the various aspects of different parameters on net cost to accomplish the fuzzy production model.

Under fuzzy inference, the research offers a relevant contribution in the field of recycling with controlling carbon emission by using the cap-and-trade policy. This study provides a trading strategy for a manufacturer's decision to avoid losses.

The purpose of this paper is to present an adaptive numerical algorithm for forward kinematics analysis of general Stewart platform.

Unlike the convention of developing a set of kinematic equations and then solving them, an alternative numerical algorithm is proposed in which the principal components of link lengths are used as a bridge to analyze the forward kinematics of a Stewart platform. The values of link lengths are firstly transformed to the values of principal components through principal component analysis. Then, the computation of the values of positional variables is transformed to a two‐dimensional nonlinear minimization problem by using the relationships between principal components and positional variables. A hybrid Nelder Mead‐particle swarm optimizer (NM‐PSO) algorithm and a modified NM algorithm are used to solve the two‐dimensional nonlinear minimization problem.

Simulation experiments have been conducted to validate the numerical algorithm and experimental results show that the numerical algorithm is valid and can achieve good accuracy and high efficiency.

This paper proposes an adaptive numerical algorithm for forward kinematics analysis of general Stewart platform.

The effects of rotor blade design variables and their mutual interactions on aerodynamic efficiency of helicopters are investigated. The aerodynamic efficiency is defined based on figure of merit (FM) and lift-to-drag responses developed for hover and forward flight, respectively.

The approach is to couple a general flight dynamic simulation code, previously validated in the time domain, with design of experiment (DOE) required for the response surface development. DOE includes I-optimality criteria to preselect the data and improve data acquisition process. Desirability approach is also implemented for a better understanding of the optimum rotor blade planform in both hover and forward flight.

The resulting system provides a systematic manner to examine the rotor blade design variables and their interactions, thus reducing the time and cost of designing rotor blades. The obtained results show that the blade taper ratio of 0.3, the point of taper initiation of about 0.64 R within a SC1095R8 airfoil satisfy the maximum FM of 0.73 and the maximum lift-to-drag ratio of about 5.5 in hover and forward flight.

The work shows the practical possibility to implement the proposed optimization process that can be used for the advanced rotor blade design.

The work presents the rapid and reliable optimization process efficiently used for designing advanced rotor blades in hover and forward flight.

Improperly fitted parameters for the Jiles–Atherton (JA) hysteresis model can lead to non-physical hysteresis loops when ferromagnetic materials are simulated. This can be remedied by including a proper physical constraint in the parameter-fitting optimization algorithm. This paper aims to implement the constraint in the meta-heuristic simulated annealing (SA) optimization and Nelder–Mead simplex (NMS) algorithms to find JA model parameters that yield a physical hysteresis loop. The quasi-static B(H)-characteristics of a non-oriented (NO) silicon steel sheet are simulated, using existing measurements from a single sheet tester. Hysteresis loops received from the JA model under modified logistic function and piecewise cubic spline fitted to the average M(H) curve are compared against the measured minor and major hysteresis loops.

A physical constraint takes into account the anhysteretic susceptibility at the origin. This helps in the optimization decision-making, whether to accept or reject randomly generated parameters at a given iteration step. A combination of global and local heuristic optimization methods is used to determine the parameters of the JA hysteresis model. First, the SA method is applied and after that the NMS method is used in the process.

The implementation of a physical constraint improves the robustness of the parameter fitting and leads to more physical hysteresis loops. Modeling the anhysteretic magnetization by a spline fitted to the average of a measured major hysteresis loop provides a significantly better fit with the data than using analytical functions for the purpose. The results show that a modified logistic function can be considered a suitable anhysteretic (analytical) function for the NO silicon steel used in this paper. At high magnitude excitations, the average M(H) curve yields the proper fitting with the measured hysteresis loop. However, the parameters valid for the major hysteresis loop do not produce proper fitting for minor hysteresis loops.

The physical constraint is added in the SA and NMS optimization algorithms. The optimization algorithms are taken from the GNU Scientific Library, which is available from the GNU project. The methods described in this paper can be applied to estimate the physical parameters of the JA hysteresis model, particularly for the unidirectional alternating B(H) characteristics of NO silicon steel.