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The electromagnetic excited audible noise of electrical machines can be mostly attributed to radial forces on stator tooth‐heads. The methodology proposed in this paper uses numerical field simulation to obtain the magnetic air gap field of electrical machines and an analytical‐based post‐processing approach to reveal the relationship between air gap field harmonics and the resulting force wave.

The simulated air gap field is sampled in space and time and a two‐dimensional Fourier transform is performed. The convolution of the Fourier transformed air gap field by itself represents a multiplication in space time domain. During the convolution process, all relevant combinations of field waves are stored and displayed using space vectors.

The effectiveness of the proposed approach is shown on an example machine. Particular examples of individual force waves demonstrate how the approach can be used for practical application in analysis of noise and vibration problems in electrical machines. The proposed method is compared to the result of a Maxwell stress tensor calculation. It shows that the deviation is small enough to justify the approach for analysis purposes.

The combination of analytically understood force waves and the use of numerical simulation by means of air gap field convolution has not been proposed before.

The purpose of this paper is to present a method for analyzing higher magnetic force harmonics in electrical machines based on electromagnetic finite element simulation.

Sampling of air gap field solution data allows for a Fourier decomposition of magnetic forces and flux densities. A two‐dimensional convolution gives insight into the spectral decomposition of forces responsible for acoustic noise, vibration and higher torque harmonics.

The proposed approach seems especially suitable for synchronous machine models. The influence of magnetic circuit design parameters that are difficult to calculate analytically on the harmonic air gap content can be analyzed and the spectral force decomposition illustrated by means of space vectors.

The approach is generalized to the convolution and analysis of arbitrarily sampled two‐dimensional data in this paper.

Conventional image super-resolution reconstruction by the conventional deep learning architectures suffers from the problems of hard training and gradient disappearing. In order to solve such problems, the purpose of this paper is to propose a novel image super-resolution algorithm based on improved generative adversarial networks (GANs) with Wasserstein distance and gradient penalty.

The proposed algorithm first introduces the conventional GANs architecture, the Wasserstein distance and the gradient penalty for the task of image super-resolution reconstruction (SRWGANs-GP). In addition, a novel perceptual loss function is designed for the SRWGANs-GP to meet the task of image super-resolution reconstruction. The content loss is extracted from the deep model’s feature maps, and such features are introduced to calculate mean square error (MSE) for the loss calculation of generators.

To validate the effectiveness and feasibility of the proposed algorithm, a lot of compared experiments are applied on three common data sets, i.e. Set5, Set14 and BSD100. Experimental results have shown that the proposed SRWGANs-GP architecture has a stable error gradient and iteratively convergence. Compared with the baseline deep models, the proposed GANs models have a significant improvement on performance and efficiency for image super-resolution reconstruction. The MSE calculated by the deep model’s feature maps gives more advantages for constructing contour and texture.

Compared with the state-of-the-art algorithms, the proposed algorithm obtains a better performance on image super-resolution and better reconstruction results on contour and texture.

There is an identified need in higher education research for methods which have the capacity to generate conceptual insights grounded in concrete local practice but with wider applicability in understanding and facilitating research-based change. This chapter outlines an intermediate approach to qualitative data analysis which can support theoretical knowledge advancement from practice-based research, which I call the difference-within-similarity approach. It involves a particular way of conducting dialogues with our data: of interanimating similarities and differences within our qualitative datasets. The approach outlined involves first identifying a similarity, then systematically examining differences within that similarity to generate theoretical explanations. Drawing on sociocultural theorising, particularly dialogic theory and cultural–historical activity theory, the approach is based on the idea that new meanings arise from a comparison of multiple perspectives on the ‘same’ phenomenon. The tensions between such perspectives are seen as a key driver for change in educational practice. Therefore, articulating and examining such tensions in our data gives an opportunity to simulate the possibility of change in our analysis and, hence, develop insights which can inform change beyond local settings. Important here is that the differences examined are bound together by an analytically productive similarity. Through multiple research examples, the chapter identifies and illustrates a range of ways of articulating productive analytical similarities for comparison in our data: through theory/literature, through forward and backwards processing of data itself and through a process termed ‘weaving’.

This chapter describes a case study of a multidisciplinary approach to the complex social issue of teaching English to multilingual tertiary students in a pluralistic context. It does this by advancing an innovative multilingual pedagogy combining specific aspects of Commedia dell’Arte (Di Niro) and translanguaging (Viljoen) to cross boundaries between languages and cultures for effectively teaching. This is achieved through an examination of Di Niro’s course structure, written reflections and observations of teaching students “English for Business Studies” at the University of South Australia (UniSA). Reflections are arranged and interpreted around three themes: multilingualism, game play, and physicality/embodied learning. Following O’Neill and Viljoen (2021, p. 1), the authors argue that “such reflection is not simply contemplative, but involves dynamic, transforming and reflexive processes of accessing” the lived-experience of language and culture of the teacher and students in an engaged and responsive learning dialogue. Commedia dell’Arte includes multilingualism, improvisation, gesture, role-play and extending students to develop socio-political dialogue. Translanguaging involves foregrounding and affirming the home language of multilingual students of English while also developing their English. Blending these methodologies and methods enables the authors to simultaneously address practical and theoretical aspects of teaching in a multilingual classroom.

Examines why the public are becoming increasingly concerned about marketing practices and corporate responsibility. States that present and future marketing executives in Norway have investigated these issues – but even so they were just as critical on issues where their personal experiences as consumers seemed to have been evoked. Reports that a self‐administered questionnaire was completed by members of three groups: a business executive group; a college students group; and a group of first and second‐year high school students. Gives the results and discusses them in detail. Concludes that the research gives reason for some hope that in the future more initiative may come from sources within the industry itself.

In the electromagnetic field simulation of modern servo drives, the computation of higher time and space harmonics is essential to consider appearing torque pulsations, radial forces and ripple torques. The purpose of this paper is to propose a method to cover the effect of saturation on the armature flux density within conformal mapping (CM) by an finite element (FE) re‐parameterization.

Field computation by CM techniques is a time‐effective method to compute the radial and tangential field components, but it generally neglects the effect of saturation.

This paper presents a method to re‐parameterize the CM approach by single FE computations so as to consider saturation in the model over a wide operation range of the electrical drive.

The proposed method is applied to a surface permanent magnet synchronous machine, and compared to numerical results obtained by finite element analysis (FEA).

The paper shows that an accuracy similar to that of FE simulations can be obtained with still the low‐computation time that is the characteristic of analytical models.

In this study the authors aim to outline new ways of information extraction for automated valuation models, which in turn would help to increase transparency in valuation procedures and thus contribute to more reliable statements about the value of real estate.

The authors hypothesize that empirical error in the interpretation and qualitative assessment of visual content can be minimized by collating the assessments of multiple individuals and through use of repeated trials. Motivated by this problem, the authors developed an experimental approach for semi-automatic extraction of qualitative real estate metadata based on Comparative Judgments and Deep Learning. The authors evaluate the feasibility of our approach with the help of Hedonic Models.

The results show that the collated assessments of qualitative features of interior images show a notable effect on the price models and thus over potential for further research within this paradigm.

To the best of the authors’ knowledge, this is the first approach that combines and collates the subjective ratings of visual features and deep learning for real estate use cases.

Examines consumerist developments in progressive Western economies. Studies present literature about consumerism, developing some propositions forming the basis for a theory of consumerism. Goes on to test the propositions, based on empirical data, to form the foundation for a framework to enable marketing to encompass consumerism. Examines in the first part the USA and the consumerist movement there, looking at various public interest groups active in the USA. Addresses the phenomenon in Europe in the second section stating that Sweden is the most consumer‐friendly, followed by the UK, France and Germany. Concludes that the consumer has a right to expect safety, quality, health; information, education and protection; and truth, authenticity and choice.

Meetings with colleagues are an essential activity in workplace collaboration. The iterative nature of collaborative work demands spaces that team members can access quickly and easily. Creating suitable meeting spaces will become more critical if the hybrid work model continues and the workplace environment becomes the hub for face-to-face collaborative time, learning and training. Workspace and fit-out is expensive so it is crucial that the investment in meeting spaces supports employees’ collaboration activities.

This paper presents a case study of a corporate organisation undertaken in New Zealand to investigate how employees from two business units use their workspace to collaborate within their own team and across other teams in their organisation. The study uses ethnographic techniques, including participant observation and in-depth face-to-face interviews.

The findings show that the frequency and nature of small group work in collaboration was underestimated in the initial planning of the new workspace. Although participants found the design and fit-out of the formal meeting rooms supportive of collaborative work, the meeting rooms were in high demand, and it was difficult to find a room at short notice. The breakout spaces were confusing because they lacked key design attributes identified by the participants as conducive to small group work. Design shortfalls together with fit-out features perceived as supportive of collaborative work are identified.

The research reports on employees’ perceptions and experiences across two functionally diverse business units, reflecting their different needs and concerns.