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The purpose of this paper is to obtain a fully analytical model of an eddy current coupler and to use it in a multi‐objective optimisation algorithm.

Analytical expressions of device performances are adopted in the objective function and are obtained from a closed solution of the field problem. The optimisation has been carried out by considering both the torque and the momentum of inertia of the object. Two different structures have been considered.

A fully analytical expression of the torque has been obtained for two different geometrical configurations. The optimisation procedure has been used to compare these structures and it is possible to observe that the DSPM performances are better than the SSPM ones.

To obtain a closed form of the torque function, the non‐linearities of the iron have been neglected. Nevertheless, in the optimisation procedure has been limited the magnetic flux density in the iron core to a feasible value in the linear part of the ferromagnetic characteristic. The thermal effects have been neglected.

In the industry, eddy current couplers can be used as transmission, dampers and brakes. The use of objective functions (OFs) in a closed formulation allows to perform a light optimisation from the point of view of the time computation and to drastically increase the development efficiency.

In this paper, a model for computing the electromagnetic behaviour of eddy current couplers is presented. The optimisation of both the torque and the inertia momentum allows to obtain good static and dynamic performances.

Recently, star variables and the post-crisis nature of cyclical fluctuations have attracted a great deal of interest. In this chapter, the authors investigate different methods of assessing business cycles (BCs) for the European Union in general and the euro area in particular. First, the authors conduct a Monte Carlo (MC) experiment using a broad spectrum of univariate trend-cycle decomposition methods. The simulation aims to examine the ability of the analysed methods to find the observed simulated cycle with structural properties similar to actual macroeconomic data. For the simulation, the authors used the structural model’s parameters calibrated to the euro area’s real gross domestic product (GDP) and unemployment rate. The simulation outcomes indicate the sufficient composition of the suite of models (SoM) consisting of popular Hodrick–Prescott, Christiano–Fitzgerald and structural trend-cycle-seasonal filters, then used for the real application. The authors find that: (i) there is a high level of model uncertainty in comparing the estimates; (ii) growth rate (acceleration) cycles have often the worst performances, but they could be useful as early-warning predictors of turning points in growth and BCs; and (iii) the best-performing MC approaches provide a reasonable combination as the SoM. When swings last less time and/or are smaller, it is easier to pick a good alternative method to the suite to capture the BC for real GDP. Second, the authors estimate the BCs for real GDP and unemployment data varying from 1995Q1 to 2020Q4 (GDP) or 2020Q3 (unemployment), ending up with 28 cycles per country. This analysis also confirms that the BCs of euro area members are quite synchronized with the aggregate euro area. Some major differences can be found, however, especially in the case of periphery and new member states, with the latter improving in terms of coherency after the global financial crisis. The German cycles are among the cyclical movements least synchronized with the aggregate euro area.

This work aims to present a multilevel optimization strategy based on manifold‐mapping combined with multiquadric interpolation for the coarse model construction.

In the proposed approach the coarse model is obtained by interpolating the fine model using multiquadrics in a small number of points. As the algorithm iterates the response surface model is improved by enriching the set of interpolation points.

This approach allows to accurately solve the TEAM Workshop Problem 25 using as little as 33 finite element simulations. Furthermore, it allows a robust sizing optimization of a cylindrical voice‐coil actuator with seven design variables.

Further analysis is required to gain a better understanding of the role that the initial coarse model accuracy plays in the convergence of the algorithm. The proposed model allows to carry out such analysis by varying the number of points included in the initial response surface model. The effect of the trust‐region stabilization in the presence of manifolds of equivalent solutions is also a topic of further investigations.

Unlike the closely related space‐mapping algorithm, the manifold‐mapping algorithm is guaranteed to converge to a fine model optimal solution. By combining it with multiquadric response surface models, its applicability is extended to problems for which other kinds of coarse model such as lumped parameter approximations for instance are tedious or impossible to construct.

The purpose of this paper is to present a new concept of passive loop technique called “high magnetic coupling passive loop” (HMCPL) (suitable for buried power lines) along with optimised design parameters.

The optimal design (geometrical displacement and shielding current intensity and phase) for the mitigation of magnetic field produced by flat and trefoil configuration of the power line is carried out by means of genetic algorithm.

Different layouts for the source (flat and trefoil configuration) and the shield (introduction of the phase splitting technique) are designed. The optimization parameters are the coordinates of the shield conductors and the transformer ratio of the magnetic core that couple the source and the shield. Moreover, physical constraints as maximum depth of excavation and geometric interference between cables were introduced in the optimization procedure.

The paper deals with a very new technology for field mitigation called HMCPL. Actually, the base layout of the HMCPL does not need an optimal design. On the other hand, in some applications the base layout cannot be used, therefore, the introduction of an optimal design cannot be avoided. In this paper, the optimal design of several configurations is performed showing that the performances of the HMCPL are very interesting even if the base layout cannot be used.

The definition of a simple model of low frequency magnetic field created by power industrial installations can be approached by using an equivalent source system (ESS). Given a set of measured magnetic field points, the ESS, made by a limited set of current carrying wires or turns, must be placed and supplied in order to fit the measured magnetic field values. An optimisation procedure can be used to define the current values and the location of the ESS which minimize the error between the measured and computed magnetic field values.

A two‐step optimal procedure is defined: in the outer step a stochastic optimisation routine is used to drive the geometric control parameters of the ESS while, in the inner step, the current values flowing through the sources are computed to find the minimization of the error with respect to a set of measured magnetic field values. The optimisation procedure is based on an artificial immune system algorithm which focuses on a deep exploration of the search space and gave interesting results both in terms of accuracy and computational efficiency.

The results show that the proposed approach is able to reconstruct the magnetic field created by complex source system and give some accuracy measure on the reconstruction error. The optimisation process carried out also on conductor positions has allowed to find out the location of the real sources in an accurate way, also in presence of measurement errors.

The approach proposed uses optimisation procedures to solve the inverse problem of source reconstruction starting by a set of measured magnetic field values. The definition of a simple equivalent source structure, together with an optimisation procedure to set its control parameters, allows to simulate complex magnetic field sources, like power substations or cable systems, in a very efficient and compact way.

The paper presents an hybrid optimization technique which couples the artificial immune system (AIS) algorithm with a zeroth order deterministic method.

AIS has been developed to tackle multi‐modal optimization problems and it has shown a great ability to explore the objective function space. The algorithm is subdivided into two phases: an outer and an inner cycle. The outer cycle is devoted to the exploration of the space while the inner is a local exploration of the objective function. The new hybrid method proposes to replace the local search by a zeroth order deterministic search to speed up the overall convergence.

Results on two multi‐modal analytical objective functions show an increase of speed of the new procedure with respect to the standard AIS. The method is also tested on the TEAM 22 numerical problem and some a posteriori techniques for the analysis of multimodal blind objective functions are discussed.

The new Multimodal optimization algorithm has allowed to explore thoroughly feasibility space giving rise to a partition of the whole space, the use of hybrid technique increases the performances of standard AIS increasing the convergence to the optimal points.

The optimisation of a tubular linear motor with interior permanent magnets is described. For a rapid design the whole process is divided in three parts: an analytical approach for the a preliminary investigation, a parametric analysis by means of a finite element method and an optimisation. The obtained results show that the adopted optimisation process is efficient for rapid and effective optimisation of the tubular linear motor.

The scope of the work is to provide an hybrid numerical technique for the solution of electric field.

In this paper an integral approach for the solution of static electric field based on a dual discretization (DD) and on a surface method of moment (MoM) is presented. The proposed technique is applied to the solution of 3D electric field problems where different perfectly conducting bodies are placed in a homogeneous and isotropic medium. The approach is also extended to the analysis of static current field. In the presented formulation MoM is applied on a surface domain which is discretized according to a baricentrical dual scheme.

The procedure has been applied to several practical cases and it represents an efficient tool for the evaluation of lumped circuit parameters as capacitances of 3D conducting bodies and ground resistance of grounding systems.

The formulation presented in the paper is limited to the calculus of electric field in homogeneous media. For future development the authors are working in order to include non‐homogeneous media.

The proposed approach aids the designer of electrical systems as large scale grounding systems or integrated circuit connections in the calculations of lumped electrical parameters.

The originality of the paper lies in the coupling of MoM with finite formulation and DD.

This study aims to examine the transmission mechanism of factors on the characteristic fluctuation of Vietnamese coffee bean export price (PVN).

Applying Markov switching–vector autoregressive model.

Significantly, the empirical results showed that the transmission of independent variables on PVN is non-linear, and the fluctuation of PVN is affected by many factors, especially PVN in the previous period. In addition, the effect of Robusta coffee price was the greatest with coefficient is 0.28785, and the correlation between PVN and it was also the highest in both regimes with coefficients are 0.5317 and 0.3959, respectively.

These obtained results are in accordance with reality, as Vietnam is the largest exporter of Robusta coffee in the world.

Following behavioral finance and monetary wisdom, the authors theorize: Decision-makers (investors) adopt deep-rooted personal values (the love-of-money attitudes/avaricious financial aspirations) as a lens to frame critical concerns (short-term and long-term investment decisions) in the immediate-proximal (current income) and distal-omnibus (future inheritance) contexts to maximize expected utility and ultimate serenity across context, people and time.

The authors collected data from 277 active equity traders (professional money managers and individual investors) in Pakistan’s two most robust investment hubs—Karachi and Lahore. The authors measured their love-of-money attitude (avaricious monetary aspirations), short-term and long-term investment decisions and demographic variables and collected data during Pakistan's bear markets (Pakistan Stock Exchange, PSX-100).

Investors’ love of money relates to short-term and long-term decisions. However, these relationships are significant for money managers but non-significant for individual investors. Further, investors’ current income moderates this relationship for short-term investment decisions but not long-term decisions. The intensity of the aspirations-to-short-term investment relationship is much higher for investors with low-income levels than those with average and high-income levels. Future inheritance moderates the relationships between aspirations and short-term and long-term decisions. Regardless of their love-of-money orientations, investors with future inheritance have higher magnitudes of short-term and long-term investments than those without future inheritance. The intensity of the aspirations-to-investments relationship is more potent for investors without future inheritance than those with inheritance. Investors with low avaricious monetary aspirations and without inheritance expectations show the lowest short-term and long-term investment decisions. Investors' current income and future inheritance moderate the relationships between their love of money attitude and short-term and long-term decisions differently in Pakistan's bear markets.

The authors help investors make financial decisions and help financial institutions, asset management companies, brokerage houses and investment banks identify marketing strategies and investor segmentation and provide individualized services.

Professional money managers have a stronger short-term orientation than individual investors. Lack of wealth (current income and future inheritance) motivates greedy investors to take more risks and become more vulnerable than non-greedy ones—investors’ financial resources and wealth matter. The Matthew Effect in investment decisions exists in Pakistan’s emerging economy.