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Inverse problems in electromagnetism, namely, the recovery of sources (currents or charges) or system data from measured effects, are usually ill-posed or, in the numerical formulation, ill-conditioned and require suitable regularization to provide meaningful results. To test new regularization methods, there is the need of benchmark problems, which numerical properties and solutions should be well known. Hence, this study aims to define a benchmark problem, suitable to test new regularization approaches and solves with different methods.

To assess reliability and performance of different solving strategies for inverse source problems, a benchmark problem of current synthesis is defined and solved by means of several regularization methods in a comparative way; subsequently, an approach in terms of an artificial neural network (ANN) is considered as a viable alternative to classical regularization schemes. The solution of the underlying forward problem is based on a finite element analysis.

The paper provides a very detailed analysis of the proposed inverse problem in terms of numerical properties of the lead field matrix. The solutions found by different regularization approaches and an ANN method are provided, showing the performance of the applied methods and the numerical issues of the benchmark problem.

The value of the paper is to provide the numerical characteristics and issues of the proposed benchmark problem in a comprehensive way, by means of a wide variety of regularization methods and an ANN approach.

This study aims to measure and further compare the countries in terms of the achievement in the degree of financial inclusion over the study period and between income groups considering 26 nations from Asia for the period 2013-2017.

While measuring the degree of financial inclusion, the study prepares an index using weighted arithmetic mean and the inverse of the Euclidean distance method. Further, comparison between the study period and between the income groups has been made using the dependent samples t-test as well as the Wilcoxon signed-rank test and independent samples t-test, respectively.

The study extends empirical insights by laying out the ranks for the countries considered for each of the study periods individually as well as in terms of mean financial inclusion scores for the study period. Further, comparison in terms of mean financial inclusion scores shows significant differences between the income groups, whereas the differences between the study periods turn out to be non-significant.

Less availability of intended variables over time restricts the predictive capability of sketching the phenomena in a true sense and claims further an exhaustive research to pursue in the future.

With the declining trend except for 2016-2017 in the achievement of financial inclusion scores over time, the study suggests emphasizing the initiatives targeted to include the excluded within the ambit of the formal financial system, which somehow seems unstable.

The novelty of the study lies in the portrayal of a measure that seems representative of the scale for development with deeper insight.

The purpose of this paper is to apply the conjugate gradient (CG) method, together with the adjoint operator (AO) to the pulsating heat pipe problem, including some quite interesting experimental results. The CG method, together with the AO, was able to estimate the unknown functions more efficiently than the other techniques presented in this paper. The estimation of local heat transfer coefficients, rather than the global ones, in pulsating heat pipes is a relatively new subject and presenting a robust, efficient and self-regularized inverse tool to estimate it, supported also by some experimental results, is the main purpose of this paper. To also increase the visibility and the general use of the paper to the heat transfer community, the authors include, as supplemental material, all numerical and experimental data used in this paper.

The approach was established on the solution of the inverse heat conduction problem in the wall by using as starting data the temperature measurements on the outer surface. The procedure is based on the CG method with AO. The here proposed approach was first verified adopting synthetic data and then it was validated with real cases regarding pulsating heat pipes.

An original fast methodology to estimate local convective heat flux is proposed. The procedure has been validated both numerically and experimentally. The procedure has been compared to other classical methods presenting some peculiar benefits.

The approach is suitable for pulsating heat pipes performance evaluation because these devices present a local heat flux distribution characterized by an important variation both in time and in space as a result of the complex flow patterns that are generated in this type of devices.

The procedure here proposed shows these benefits: it affords a general model of the heat conduction problem that is effortlessly customized for the particular case, it can be applied also to large datasets and it presents reduced computational expense.

This paper aims to present an iterative path-following method with joint limits to solve the problem of large computation cost, movement exceeding joint limits and poor path-following accuracy for the path planning of hyper-redundant snake-like manipulator.

When a desired path is given, new configuration of the snake-like manipulator is obtained through a geometrical approach, then the joints are repositioned through iterations until all the rotation angles satisfy the imposed joint limits. Finally, a new arrangement is obtained through the analytic solution of the inverse kinematics of hyper-redundant manipulator. Finally, simulations and experiments are carried out to analyze the performance of the proposed path-following method.

Simulation results show that the average computation time is 0.1 ms per step for a hyper-redundant manipulator with 12 degrees of freedom, and the deviation in tip position can be kept below 0.02 mm. Experiments show that all the rotation angles are within joint limits.

Currently , the manipulator is working in open-loop, the elasticity of the driving cable will cause positioning error. In future, close-loop control based on real-time attitude detection will be used in in combination with the path-following method to achieve high-precision trajectory tracking.

Through a series of iterative processes, the proposed method can make the manipulator approach the desired path as much as possible within the joint constraints with high precision and less computation time.

Japan's decision to release nuclear wastewater into the Pacific Ocean in 2023 has sparked strong opposition at home and abroad. In this study, Graph Model for Conflict Resolution (GMCR) method is adopted to analyze the conflict problem, and reasonable equilibrium solutions are given to solve the conflict event.

In this study, GMCR is adopted to solve the conflict problem. First, identify the key decision-makers (DMs) on the issue of nuclear effluent and the relevant options they might adopt. Second, the options of each DM are arranged and combined to form a set of feasible states. Thirdly, the graph model is constructed according to the change of DM's options, and the relative preference of each DM is determined. Finally, the conflict problem is solved according to the definition of GMCR equilibrium.

Discharging nuclear wastewater into the ocean is not the right choice to solve the problem. Developing more space to store nuclear wastewater is more conducive to the protection of the ocean environment.

It is undesirable for the Japanese government to unilaterally discharge nuclear wastewater into the ocean. Objectively assessing the radioactivity of nuclear wastewater and the cooperation of relevant stakeholders can better solve this conflict.

The problem arising from Japan's releasing plan is complicated because of a lack of information and the existence of multiple stakeholders, while GMCR can help us with a better view of the current circumstance in the conflict.