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The paper presents a novel method of utilising neural networks for optimisation systems. First, a conventional magnetic circuit model of the device is developed to create a set of sensitivity rules which guide the optimisation. The rules are coded in a knowledge‐based neural network. Second, an error network is developed to correct the approximations inherent in the magnetic circuit approach and this combines with the first network to generate realistic outputs. Finally, the error network can be trained on‐line with a finite element system. Over time, the network replaces the finite element analysis, thus speeding up the optimisation process.

COVID-19 has generated unprecedented circumstances with a tremendous impact on the global community. The academic community has also been affected by the current pandemic, with strategy and management researchers now required to adapt elements of their research process from study design through to data collection and analysis. This chapter makes a contribution to the research methods literature by documenting the process of adapting research in light of rapidly changing circumstances, using vignettes of doctoral students from around the world. In sharing their experience of shifting from the initially proposed methodologies to their modified or completely new methodologies, they demonstrate the critical importance of adaptability in research. In doing so, this chapter draws on core literature of adaptation and conducting research in times of crises, aiming to provide key learnings, methodological tips and a “story of hope” for scholars who may be faced with similar challenges in the future.

Design and optimisation of many practical electromechanical devices involve intensive field simulation studies and repetitive usage of time‐consuming software such as finite elements (FEs), finite differences of boundary elements. This is a costly, but unavoidable process and thus a lot of research is currently directed towards finding ways by which the number of necessary function calls could be reduced. New algorithms are being proposed based either on stochastic or deterministic techniques where a compromise is achieved between accuracy and speed of computation. Four different approaches appear to be particularly promising and are summarised in this review paper. The first uses a deterministic algorithm, known as minimal function calls approach, introduces online learning and dynamic weighting. The second technique introduced as ES/DE/MQ – as it combines evolution strategy, differential evolution and multiquadrics interpolation – offers all the advantages of a stochastic method, but with much reduced number of function calls. The third recent method uses neuro‐fuzzy modelling and leads to even further economy of computation, although with slightly reduced accuracy of computation. Finally, a combined FE/neural network approach offers a novel approach to optimisation if a conventional magnetic circuit model could also be used.

The power transformer is one of the most important pieces of equipment in a power system. The necessity for the optimum design of a power transformer arises because the design chosen should satisfy all the limitations and restrictions placed on it. This paper presents an improved fast evolutionary programming (IFEP) technique for the optimal design of a three‐phase power transformer.

The optimization of the transformer design problem is formulated as an NLP problem, expressing the objective and constraint functions in terms of the selected independent variables. Here the cost of the transformer is considered as the objective function and is the sum of material cost of stampings and copper windings, cost of cooling tube arrangements, cost of cooling medium, insulation cost and labour cost. A computer program is written from which the optimal design parameters are obtained. For optimization, the classical evolutionary programming (CEP) technique and its variant the IFEP technique are used and the results are compared.

The application of CEP and IFEP for transformer design has been demonstrated on two test cases. It has been observed that this IFEP outperforms the CEP in obtaining the optimum design of transformers of smaller as well as larger ratings in terms of execution time, convergence rate, quality and success rate.

The proposed method results in the economical design of a three‐phase power transformer which can significantly reduce the cost of manufacturing transformers.

The process of identifying unknown hidden objects by taking advantage of electromagnetic effects becomes more and more important. Clearing of mines or finding electrical conductors in concrete should be mentioned here. Magnetisation and eddy currents are the phenomena which are used in general. In this case, the layout and arrangement of the excitation coils and receiving coils influences the effectiveness and accuracy crucially. This design optimization process can be done by simulating the electromagnetic field with a 3D finite element method. Once a satisfying configuration has been found, the question arises, which quantities of the measured (and hence simulated) signals contain the most reliable information? Since the 3D finite element calculations are very time consuming, the inverse problem (detecting the ferrous object from some measured signals) is performed by approximating the corresponding electromagnetic signal by a neural network. Investigations on a ferrous conductive rod will be described in the paper.

Mothers – The Silent supporters focus on the potential role of the mother in the restorative justice (RJ) process. This chapter provides a contextual framework for the research highlighting debates pertaining to RJ and parents, especially mothers. This was made possible with a grant from the BA/Leverhulme Small Research Grants. The research provided a holistic understanding of social backgrounds and links between theory and the practice of RJ. The workshop provided a multi-perspective analysis of the interactions within significant relationships between mothers and sons. The author’s focus was on the role of the mother prior to the RJ process. The workshops were held in a safe space in a northern region. The mothers were from different economic and social backgrounds.

Over 2 million individuals are incarcerated in the US criminal justice system. More than half of incarcerated Americans are also parents of minors. Parental incarceration can lead to a higher risk of mental illness and enduring trauma in children, as well as other problematic cognitive, developmental, and educational outcomes. Examining parental incarceration through a racial equity lens is critical, as people of color make up 67% of the incarcerated population despite making up only 37% of the US population. Further, gender-related equity issues pose important challenges for families with incarcerated parents. Here, we discuss prison-based psychosocial interventions designed both to build parenting skills and to improve parent well-being within a racial and gender equity lens. We hypothesize that effective services in these areas are essential components in a broad strategy designed to mitigate the potential negative effects suffered by families and children of incarcerated parents of color as a result of their imprisonment.

Cyber management of organizations includes eliminating security gaps, ensuring information confidentiality, and protecting customers' data. In addition, production and planning, protecting cyber and digital infrastructure are included in the chapter. The chapter deals with these issues in the context of strategy and management. In addition, the conflicts arising from competitors to access the tacit knowledge (confidential information, commercial secrets, commercial relations, customers, and tenders) of the businesses are discussed in the chapter. Cyber conflicts have now turned into a business-to-business war. Businesses have become targets in cyberwars. This chapter, therefore, examines these issues in depth.

This paper aims to examine whether from a factual standpoint, it is sufficiently reasonable to address the suppression of terrorist financing by analogy with money laundering.

The process of terrorist financing will be examined in regard to the funding requirements of terrorists and the methods and tools that terrorists use to raise, move and store their funds. The process of money laundering will be compared with terrorist financing. The role of money laundering in terrorist financing will be discussed. In the core part of this paper, the assumptions justifying the inclusion of anti-money laundering measures to terrorist financing will be challenged.

What terrorist financing and money laundering share in common is money. However, there are fundamental differences between them with regard to the sources of funds and the direction of financial flows. None of the elements –“accumulation” and “legitimization”– involved in money laundering are necessarily engaged in the process of terrorist financing. This questions the authenticity of the assumptions which underlie the adopted approach. It also requires further investigation on the effectiveness of the integrated counter-terrorist regime, which will not be covered by this paper.

This paper provides a comprehensive introduction for those dealing with the greater question of whether the terrorist financing can and should be tackled by anti-money laundering measures.

Investigates the effects of the most influential cutting parameters (cutting speed, feed rate, depth of cut, tool nose radius, tool length and work piece length) on surface roughness quality and on the formation of built‐up edge in a lathe dry turning process of mild carbon steel samples. A full factorial design (384 experiments), taking into account the three‐level interactions between the independent variables has been conducted. The results show that the following three‐level interactions: feed rate × cutting speed × depth of cut, feed rate × cutting speed × tool nose radius and tool nose radius × depth of cut × tool length have significant effects on surface roughness in this type of machining operation. Shows that the analysis of main effects alone and even two‐level interactions could lead to a false interpretation of the results. The analysis of variance revealed that the best surface roughness is achieved with a low feed rate, a large tool nose radius and a high cutting speed. The results also show that the depth of cut has no significant effect on surface roughness when operating at cutting speeds higher than 160m/min. Furthermore, it is shown that built‐up edge formation deteriorates surface roughness when machining mild carbon steel at specific feed rate, tool nose radius and cutting speed levels. Proposes a new model for evaluating the limiting cutting speed to avoid the built‐up edge formation. Finally, shows through experimentation that an increase in depth of cut would lead to improved surface roughness when tool vibration is increased.