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This paper aims to propose an energetic model parameter calculation method for predicting the materials’ symmetrical static hysteresis loop and asymmetrical minor loop to improve the accuracy of electromagnetic analysis of equipment.

For predicting the symmetrical static hysteresis loop, this paper deduces the functional relationship between magnetic flux density and energetic model parameters based on the materials’ magnetization mechanism. It realizes the efficient and accurate symmetrical static hysteresis loop prediction under different magnetizations. For predicting the asymmetrical minor loop, a new algorithm is proposed that updates the energetic model parameters of the asymmetrical minor loop to consider the return-point memory effect.

The comparison of simulation and experimental results verifies that the proposed parameters calculation method has high accuracy and strong universality.

The proposed parameter calculation method improves the existing parameter calculation method’s problem of relying on too much experimental data and inaccuracy. Consequently, the presented work facilitates the application of the finite element electromagnetic field analysis method coupling the hysteresis model.

Pulse width modulated (PWM) inverters are widely used to feed induction motors for variable speed applications. The use of PWM power supplies induces additional magnetic losses in the magnetic circuit of the electrical machine. The aim of this paper is to present a novel analytical approach to account for these losses.

The methodology proposed here consists in identifying the analytical method with a static Preisach hysteresis model. The Preisach model was validated by comparing it with measurements obtained from an Epstein frame. Then, the results obtained with this approach were compared with a basic analytical method that is widely used.

The authors' model provides a fast way for estimating the minor loop iron losses introduced by static convertors. They compared the proposed model with another analytical model (J. Lavers model) for different wave forms. One can observe that the J. Lavers model overestimates the iron losses introduced by the non‐centred minor loops.

In this paper, an improved analytical model is presented which estimates the non‐centred minor loop iron losses. In order to do a precise estimation of the iron loss introduced by the minor loops, the authors' model takes into account the position and the size of the minor loop. The proposed model is identified from a static Preisach model.

Introduces diversity management as managing the increased diversity of issues that confront humankind in contemporary organizational and societal affairs. Defines triple loop learning as being about the increase in the fullness and deepness of learning about the diversity of issues and dilemmas faced. Presents the contours of diversity management and triple loop learning. Sees the latter as the dénouement of single loop learning and of double loop learning. Provides a “quickmap” of the contours of diversity management and triple loop learning.

The purpose of this paper is to find effective methods of loop analysis of multi‐branch and multi‐node non‐linear circuits using a singular formulation.

The classical loop analysis and the loop analysis using a singular formulation have been compared. The non‐linear systems of equations have been considered and iterative procedures of solving non‐linear equations have been applied. Special attention has been paid to the Newton‐Raphson method combined with successive over relaxation and incomplete Cholesky conjugate gradient methods. The convergence of the methods has been discussed.

It has been shown that in the case of the loop analysis of non‐linear circuits it is not necessary to form fundamental loops. The system of loop equations with a singular coefficient matrix can be successfully solved iteratively. Using a singular formulation one of the infinitely many solutions can be found quicker than the only one resulting from a classical method with a non‐singular coefficient matrix. Therefore, in the case of the analysis of multi‐branch and multi‐node non‐linear circuits using iterative methods, it is beneficial to introduce superfluous loops. This results in more economical computation and faster convergence.

The presented methods of solving multi‐branch and multi‐node non‐linear circuits using a singular formulation are universal and may be successfully applied both in circuit analysis and the FE analysis using edge elements for non‐linear problems with a large number of unknowns.

Although the original Jiles‐Atherton (J‐A) hysteresis model is able to represent a wide range of major hysteresis loops, in particular those of soft magnetic materials, it can produces non‐physical minor loops with its classical equations. The purpose of this paper is to show a modification in the J‐A hysteresis model in order to improve the minor and inner loops representation. The proposed technique allows the J‐A model representing non‐centred minor loops with accuracy as well as improving the symmetric inner loops representation.

Only the irreversible magnetization component is slightly modified keeping unchanged the other model equations and the model simplicity. The high‐variation rate of the irreversible magnetization, which causes the non‐physical behaviour of minor loops, is limited by introducing a new physical parameter linked to the losses. Contrarily to other modifications of the original model found in the literature, the previously knowledge of the magnetic field waveform is not needed in this case.

The modified hysteresis model is validated by comparison with experimental results. A good agreement is observed between calculations and measurements. The modified model retains the low‐computational effort and numerical simplicity of the original one.

This paper shows that a classical scalar hysteresis model can be suitably used to take into account the minor loops behaviour and be included in a finite element code. The methodology is useful for the design and analysis of electromagnetic devices under distorted flux patterns.

Contemporary literature reveals that, to date, the poultry livestock sector has not received sufficient research attention. This particular industry suffers from unstructured supply chain practices, lack of awareness of the implications of the sustainability concept and failure to recycle poultry wastes. The current research thus attempts to develop an integrated supply chain model in the context of poultry industry in Bangladesh. The study considers both sustainability and supply chain issues in order to incorporate them in the poultry supply chain. By placing the forward and reverse supply chains in a single framework, existing problems can be resolved to gain economic, social and environmental benefits, which will be more sustainable than the present practices.

The theoretical underpinning of this research is ‘sustainability’ and the ‘supply chain processes’ in order to examine possible improvements in the poultry production process along with waste management. The research adopts the positivist paradigm and ‘design science’ methods with the support of system dynamics (SD) and the case study methods. Initially, a mental model is developed followed by the causal loop diagram based on in-depth interviews, focus group discussions and observation techniques. The causal model helps to understand the linkages between the associated variables for each issue. Finally, the causal loop diagram is transformed into a stock and flow (quantitative) model, which is a prerequisite for SD-based simulation modelling. A decision support system (DSS) is then developed to analyse the complex decision-making process along the supply chains.

The findings reveal that integration of the supply chain can bring economic, social and environmental sustainability along with a structured production process. It is also observed that the poultry industry can apply the model outcomes in the real-life practices with minor adjustments. This present research has both theoretical and practical implications. The proposed model’s unique characteristics in mitigating the existing problems are supported by the sustainability and supply chain theories. As for practical implications, the poultry industry in Bangladesh can follow the proposed supply chain structure (as par the research model) and test various policies via simulation prior to its application. Positive outcomes of the simulation study may provide enough confidence to implement the desired changes within the industry and their supply chain networks.

Accounting for quality and improved organizational performance has recently received attention in management control research. However, the extent to which process innovation changes have been integrated into management control research is limited. This paper contributes to that integration by drawing from institutional adaptive theory of organizational change and process innovation strategies. The paper utilizes a 2 by 2 contingency table that uses two factors: environmental conditions and organizational change/learning strategies, to build a process innovation framework. A combination of these two factors yields four process innovation strategies: mechanistic, organic, organizational development (OD) and organizational transformation (OT).

The four process innovation typologies are applied to characterize innovations in accounting such as activity based costing (ABC). ABC has been discussed as a multi-phased innovation process that provides an environment where both the initiation and the implementation of accounting change can occur. Technical innovation can be successfully initiated as organic innovation that unfolds in a decentralized organization and requires radical change and double loop learning. Implementation occurs best as a mechanistic innovation in a hierarchical organization and involving incremental change and single loop learning. The paper concludes that if ABC is integrated into an OD or OT intervention strategy, the technical and administrative innovation aspects of ABC can be utilized to manage the organization’s operating activities.

The paper extends the organizational learning framework: Structural-Functional (SF)-single-loop or Conflictual-Radical (CR)-double-loop learning to the management accounting literature. The sociological approach of organizational learning is utilized to understand those contingent factors that can explain why management accounting innovations succeed or fail in organizations.

We view learning as enhancing an organization’s strategic competitive advantage by making it better able to adopt and diffuse innovation in respond to changes in its environment in order to manage improved performance. The success of management accounting innovations is contingent upon whether its learning process involves SF-single-loop or CR-double-loop learning to adopt and diffuse process innovation.

The paper suggests that the learning strategy that the organization chooses is the reason why some management accounting innovations are more successfully adopted than others and why some innovations are easily diffused in some organizations but not in others. We propose that the sociological approaches to learning provide an alternative framework with which to better understand the adoption and diffusion of process innovations in management accounting systems.

It has become evident that management accounting researchers need to pay particular attention to an organization’s approach to adoption and diffusion of innovation strategies, particularly when they are designing and implementing process innovation programs for an organization. According to Schulz (2001), there are two interrelated stages of the learning that can shape the outcome of the innovation process in an organization. The first stage is related to the acquisition/production (adoption) of knowledge that results in gathering information, codification, and exploration. This is followed by the second stage which is the distribution or dissemination (diffusion) processes. When these two stages – adoption and diffusion – are applied within an accounting context, they address issues that are commonly associated with the successes and/or failures of management accounting innovations.

Although innovation involves learning, the nature of the learning process does not completely describe the manner in which an innovation affects the organization. Accordingly, we suggest that the two interrelated organizational sociological dimensions of innovations processes, namely, (1) the adoption and diffusion theories of Rogers (1971 and 1995), to approach organizational learning, and (2) the SF (single loop) and CR (double loop) approaches to learning be used simultaneously to describe management accounting innovations.

When an innovation is implemented, it initially can be introduced as an incremental change, one that can be limited in both in its scope and its breadth of administrative changes. This means that situations which are most likely to benefit from its initiation can serve as the prototype for its adoption by the organization. If successful, this can be followed by systemic accounting innovations to instituting broader administrative changes within the existing accounting reporting and control systems.

The accurate modeling of magnetic hysteresis in electrical steels is important in several electrical and electronic applications. Numerical models have long been known that can correctly reproduce some typical behaviours of these magnetic materials. Among these, the model proposed by Jiles and Atherton must certainly be mentioned. This model is intuitive and fairly easy to implement and identify with relatively few experimental data. Also, for this reason, it has been extensively studied in different formulations. The developments and numerical tests made on this hysteresis model have indicated that it is able to accurately reproduce symmetrical cycles, especially the major loop, but often it fails to reproduce non-symmetrical cycles. This paper aims to show the positive aspects and highlight the defects of the different formulations in predicting the minor loops of electrical steels excited by non-sinusoidal currents.

The different formulations are applied to different electrical steels, and the data coming from the simulations are compared with those measured experimentally. The direct and inverse Jiles–Atherton models, including the introduction of the dissipative factor approach, are presented, and their limitations are proposed and validated using the measurements of three non-grain-oriented materials. Only the measured major loop is used to identify the parameters of the Jiles–Atherton model. Furthermore, the direct and inverse Jiles–Atherton models were used to simulate the minor loops as well as the hysteresis cycles with direct component (DC) bias excitation. Finally, the simulation results are discussed and compared to measurements for each study case.

The paper indicates that both the direct and the inverse Jiles–Atherton model formulations provide a good agreement with the experimental data for the major loop representation; nevertheless, both models can not accurately predict the minor loops even when the modification approaches proposed in the literature were implemented.

The Jiles–Atherton model and its modifications are widely discussed in the literature; however, some limitations of the model and its modification in the case of the distorted current waveform are not completely highlighted. Furthermore, this paper contains an original discussion on the accuracy of the prediction of minor loops from distorted current waveforms, including DC bias.

The light detection and ranging sensor has been widely deployed in the area of simultaneous localization and mapping (SLAM) for its remarkable accuracy, but obvious drift phenomenon and large accumulated error are inevitable when using SLAM. The purpose of this study is to alleviate the accumulated error and drift phenomenon in the process of mapping.

A novel light detection and ranging SLAM system is introduced based on Normal Distributions Transform and dynamic Scan Context with switch. The pose-graph optimization is used as back-end optimization module. The loop closure detection is only operated in the scenario, while the path satisfies conditions of loop-closed.

The proposed algorithm exhibits competitiveness compared with current approaches in terms of the accumulated error and drift distance. Further, supplementary to the place recognition process that is usually performed for loop detection, the authors introduce a novel dynamic constraint that takes into account the change in the direction of the robot throughout the total path trajectory between corresponding frames, which contributes to avoiding potential misidentifications and improving the efficiency.

The proposed system is based on Normal Distributions Transform and dynamic Scan Context with switch. The pose-graph optimization is used as back-end optimization module. The loop closure detection is only operated in the scenario, while the path satisfies condition of loop-closed.