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Numerical magnetic field analysis is used for predicting the performance of an induction motor and a slip‐ring generator having different faults implemented in their structure. Virtual measurement data provided by the numerical magnetic field analysis are analysed using modern signal processing techniques to get a reliable indication of the fault. Support vector machine based classification is applied to fault diagnostics. The stator line current, circulating currents between parallel stator branches and forces between the stator and rotor are compared as media of fault detection.

Studies aspects of Heinz von Foerster's work that are of particular importance for cognitive science and artificial intelligence.

Kohonen's self‐organizing map is presented as one method that may be useful in implementing some of Von Foerster's ideas. The main foci are the distinction between trivial and non‐trivial machines and the concept of constructive learning. The self‐organizing map is also presented as a potential tool for alleviating the participatory crisis discussed by von Foerster.

The participatory crisis in society is discussed and the concept of change is handled within the framework of information systems development.

Considers the importance of considering change in information systems development.

The purpose of this paper is to establish a paint deposition pattern model applied to robotic air spray painting in order to achieve the accuracy and uniformity of paint film thickness on free‐form surface.

The paper opts for an exploratory study using the curvature circle method for air spray painting on free‐form surface to construct a spray gun model. First, a paint deposition pattern model of ellipse dual‐β distribution is fitted on the basic of experimental data from robotic air spray painting. Second, a spray gun model is proposed using the curvature circle method for air spray painting on free‐form surface. The theoretical result is coincident with the film thickness in verification experiment spraying a cylinder surface. The biggest error of the sample points between the theoretical and experimental results is less than 4 μm, thereby the correctness and effectiveness of the proposed model is validated.

The paper provides a specific theoretical and methodological support for the realization of process planning and simulation system in surface spray manufacturing. It will make the future developed system meet the actual processing requirement. At the same time, it is more representative.

The paper finds an approach to solve paint deposition pattern model suitable to free‐form surface. The present method can be applied to the complex reality of topological relation for actual workpiece surface to be painted.

Some personality schemas are seen to compete with others, but are they really complementary? The purpose of this paper is to show that two trait approaches, Myers‐Briggs Type Indicator (MBTI) and Mindscape theory, which are normally considered to be competitive, shall be migrated into a more complex modeling space using knowledge cybernetics, when they are shown to have a complementary potential.

The paper uses the meta‐framework of knowledge cybernetics (KC) part of the relevantial universe identified by Maruyama, to migrate different theoretical approaches and relate them. A consequence is the possible development of a more sophisticated trait theory that is capable of providing more complex information about personality.

The findings indicate that current type theories are not necessarily stand‐alone, but may be seen as complementary within a broader conceptual framework.

This paper is limited to the investigation of MBTI. However, it offers a generic approach that can be applied to other solitary theories like MBTI.

The paper leads to the possibility of improved explanatory power for a type theory than is currently possible.

Very little comparative work has been done relating representations of MBTI and Mindscape theory. This also appears to be the first serious extensive direct comparison between any form of MBTI and Mindscapes. KC uses Habermas's three world theory and shows that it is possible to consider MBTI and Mindscape theory as conceptually distinct and complementary, and together contributing to a new way of exploring the field of personality theory.

This two-part paper is concerned with the creation of a generalised cybernetic agency-based ecosystem. The purpose of the first part is to explore the basis for the creation of an agentic ecology theory to provide a generalised multidisciplinary context-free manifold that can be applied to specific domains and contexts. As an element of this, it will explore the relationship between agency and its agents (at various foci) and the nature of agency ecologies and their evolution. It will also explore the relationship between viability and sustainability. In the second part of the paper, the purpose will be to formulate a general basis for agency ecology, followed by an agency model that recognises the analytical and decision-making attributes of the viability–sustainability relationship by centering on the modelling a socioeconomic ecosystem and a social disciplinary species model.

Agency theory will be used to model a generic agency ecology and its environment of subordinate elements – especially those subordinates that can be used as amenities to satisfy the needs to agency development. Part 1 of the paper will take a tour of concepts relevant to the representation of neo-ecosystem structures and their application. Part 2 will centre on delivering a schema capable of embracing agency neo-ecology from which applications may derive.

It is shown that agency theory as a modelling schema can be used as a methodology through which to provide diagnosis to examine the condition of, or for locating problems within, an agency in its ecosystem environment. This is illustrated within a socioeconomic context.

The paper is conceptual in nature, and there has been no intention to diagnose any substantive issues within the socioeconomic context.

A generalised agency ecology approach is proposed over this two-part paper that is novel through the use of third-order cybernetics.

Tourism systems have been considered more and more in the light of complexity and chaos theories. Most of the work done in this area has highlighted the reasons for and the issues regarding this approach. A steadily growing strand of the recent literature uses the theories to overcome the problems of a reductionist and mechanistic view that is considered unable to provide a full understanding of the structural and dynamic characteristics of tourism systems, and specifically of tourism destinations. This paper seeks to continue this approach and to provide a series of quantitative methods to assess the dynamics of non‐linear complex tourism systems.

The time series used in the paper contains data collected from a sample of 23 large (four‐star) hotels located in Milan, Italy. For each structure daily data of occupancy, average room rate and RevPAR (revenue per available room) were recorded for the period 2006‐2009. The daily distributions of these observations are highly skewed, and therefore the median of the daily values were considered. This results in three series of 1,461 points per type (occupancy, room rate and RevPAR).

The data confirm the complex nature of the destination system and its tendency towards a chaotic state. Additionally, high stability and long memory effects are detected. The outcomes and the implications of this analysis are examined.

A comparison of the values obtained leads to the conclusion that the series under study has a detectable level of non‐linearity, even if it does not reach the pure chaoticity of the Lorenz attractor. A first conclusion is that, as qualitatively assessed in many similar studies, the tourism destination is a complex system with a tendency to become chaotic.

The picture obtained with the analyses conducted can be summarised by saying that the system under study exhibits an unequivocally complex nature. It tends towards a chaotic stage but does so at a slow pace. The stability of the system is quite high: it might be able to resist transient shocks well but, once led in one direction, its long memory characteristics tend to keep it on the resulting path.

The purpose of this paper is to present a study and analysis of insulation failure inter‐turn fault in induction machines (IMs).

A time stepping finite element method (FEM) analysis is performed for the study of IM with inter‐turn fault and determining the machine parameters (self and mutual inductances) after occurring fault. A simple dynamic model for IM with inter‐turn fault is presented. The model parameters are obtained by FEM analysis. An experimental test is also carried out to verify the results.

The behavior of IM is studied under various insulation failure inter‐turn fault conditions and severity using FEM. The paper's results help the machine designers to improve the fault tolerance as well the overall design of the machine drive system. It can also be useful for predict and detection of fault in IM.

Predicting and detection of turn faults in IM are in industry very helpful because it avoids the fully damage of IM and it is more easy to repair the machine. Designing a fault tolerant IM is required in some applications for increasing the reliability.

By using FEM for studying the fault, the machine parameters which are calculated with FEM and the study's results are very precise and accurate because the flux fluctuation after occurring fault has been taken into account. On the other hand, the fault model is very fast, global and accurate. It can be used in model‐based health monitoring systems.

Pluralities of personality schemas reside across different Maruyama universes suggesting incommensurability and isolation. Schemas may migrate across Maruyama universes given appropriate means. As illustration, the Myers Briggs Type Indicator (MBTI) schema for personality temperament is migrated into a sociocognitive schema through the intermediary of knowledge cybernetics (KC). MBTI is a type approach that operates with polar opposites; however, conceptually there is no reason for it not to be associated with a trait space. Supposing that MBTI has traits at some horizon of meaning, then since traits are responsible for the creation of enduring states, sociocognitive explanations should be able to explain the stable states consistent with a variation of the McCrae and Costa proposition. As a result this paper aims to formulate for the first time a link between the MBTI type schema, a trait space, and a capacity for sociocultural descriptions.

The paper uses the meta‐framework of KC, part of the relevantial universe identified by Maruyama, to formulate a representation of MBTI. This also appears to be the first serious use of the Maruyama universe concept, and the first time that MBTI has been explored from a relevantial perspective. A consequence is the possible development of a more sophisticated trait theory that is capable of providing more complex information about personality.

The findings indicate that a more complex form of type theory is possible than has been provided by MBTI.

This paper is limited to the investigation of MBTI. However, it offers a generic approach that can be applied to other solitary theories like MBTI. It also postulates a trait basis for the MBTI type approach.

The paper leads to the possibility of improved explanatory power for a type theory than is currently possible.

The paper adopts for the first time a relevantial meta‐framework approach to explore a development of MBTI. It has value to those researchers who may wish to explore the potential of more complex forms of type personality theory than are currently available.

This chapter discusses the emerging network science approach to the study of complex adaptive systems and applies tools derived from statistical physics to the analysis of tourism destinations. The authors provide a brief history of network science and the characteristics of a network as well as different models such as small world and scale free networks, and dynamic properties such as resilience and information diffusion. The Italian resort island of Elba is used as a case study allowing comparison of the communication network of tourist organizations and the virtual network formed by the websites of these organizations. The study compares the parameters of these networks to networks from the literature and to randomly created networks. The analyses include computer simulations to assess the dynamic properties of these networks. The results indicate that the Elba tourism network has a low degree of collaboration between members. These findings provide a quantitative measure of network performance. In general, the application of network science to the study of social systems offers opportunities for better management of tourism destinations and complex social systems.