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As main mode of modern service industry and future economy society, the research on crowd network can greatly facilitate governances of economy society and make it more efficient, humane, sustainable and at the same time avoid disorders. However, because most results cannot be observed in real world, the research of crowd network cannot follow a traditional way. Simulation is the main means to put forward related research studies. Compared with other large-scale interactive simulations, simulation for crowd network has challenges of dynamic, diversification and massive participants. Fortunately, known as the most famous and widely accepted standard, high level architecture (HLA) has been widely used in large-scale simulations. But when it comes to crowd network, HLA has shortcomings like fixed federation, limited scale and agreement outside the software system.

This paper proposes a novel reflective memory-based framework for crowd network simulations. The proposed framework adopts a two-level federation-based architecture, which separates simulation-related environments into physical and logical aspect to enhance the flexibility of simulations. Simulation definition is introduced in this architecture to resolve the problem of outside agreements and share resources pool (constructed by reflective memory) is used to address the systemic emergence and scale problem.

With reference to HLA, this paper proposes a novel reflective memory-based framework toward crowd network simulations. The proposed framework adopts a two-level federation-based architecture, system-level simulation (system federation) and application-level simulation (application federations), which separates simulation-related environments into physical and logical aspect to enhance the flexibility of simulations. Simulation definition is introduced in this architecture to resolve the problem of outside agreements and share resources pool (constructed by reflective memory) is used to address the systemic emergence and scale problem.

Simulation syntax and semantic are all settled under this framework by templates, especially interface templates, as simulations are separated by two-level federations, physical and logical simulation environment are considered separately; the definition of simulation execution is flexible. When developing new simulations, recompile is not necessary, which can acquire much more reusability, because reflective memory is adopted as share memory within given simulation execution in this framework; population can be perceived by all federates, which greatly enhances the scalability of this kind of simulations; communication efficiency and capability has greatly improved by this share memory-based framework.

As the tourism industry continues to evolve and adapt to changing consumer demands, automated systems and artificial intelligence have gained significant attention. However, concerns related to ethical, social and environmental aspects have arisen alongside the benefits offered by these technologies. This chapter explores the emerging challenges surrounding the integration of robots and self-service technology in responsible and creative tourism.

The purpose of this paper is to show how the EStra-Many method works on optimization problems characterized by high-dimensionality of the objective space. Moreover, a comparison with a more classical approach (a constrained bi-objective problem solved by means of NSGA-II) is done.

The six reactances of a compensation network (CN) for a wireless power transfer system (WPTS) are synthesized by means of an automated optimal design. In particular, an evolutionary algorithm EStra-Many coupled with a sorting strategy has been applied to an optimization problem with four objective functions (OFs). To assess the obtained results, a classical genetic algorithm NSGA-II has been run on a bi-objective problem, constrained by two functions, and the solutions have been analyzed and compared with the ones obtained by EStra-Many.

The proposed EStra-Many method identified a solution (CN synthesis) that enhances the WPTS, considering all the four OFs. In particular, to assess the synthesized CN, the Bode diagram of the frequency response and a circuital simulation were evaluated a posteriori; they showed good performance of the CN, with smooth response and without unwanted oscillations when fed by a square wave signal with offset. The EStra-Many method has been able to find a good solution among all the feasible solutions, showing potentiality also for other fields of research, in fact, a solution nondominated with respect to the starting point has been identified. From the methodological viewpoint, the main finding is a new formulation of the many-objective optimization problem based on the concept of degree of conflict, which gives rise to an implementation free from hierarchical weights.

The new approach EStra-Many used in this paper showed to properly find an optimal solution, trading-off multiple objectives. The compensation network so synthesized by the proposed method showed good properties in terms of frequency response and robustness. The proposed method, able to deal effectively with four OFs, could be applied to solve problems with a higher number of OFs in a variety of applications because of its generality.

The purpose of the study is to design the compensation network of a dynamic wireless power transfer system, considering the movement of the receiving coil along an electrified track with a large number of inductors buried on the road.

A finite element model has been developed to calculate the self-inductances of transmitting and receiving coils as well as the mutual inductances between the receiving coil and the transmitting ones in the nearby and for various relative positions. The calculated lumped parameters, self-inductances and mutual inductances depending on the relative positions between the coils, have been considered to design the compensation network of the active coils, which is composed of three capacitive or inductive reactances connected in the T form. The optimal values of the six reactances, three for the transmitting coils and three for the receiving one, have been calculated by resorting to the Genetic Algorithm NSGA-II.

In this paper, the results obtained by means of the optimizations have broadly discussed. The optimal values of the reactances of the compensation networks show a clear trend in the receiving part of the circuit. On the other hand, the problem seems very sensitive to the values of the reactances in the transmitting circuit.

Dynamic wireless power transfer system is one of the newest ways of recharging electric vehicles. Hence, the design of compensation networks for this kind of systems is a new topic, and there is the need to investigate possible solutions to obtain a good performance of the recharging system.

The paper aims to propose a a field-circuit method for investigating the magnetic behavior of a wireless power transfer system (WPTS) for the charge of batteries of electric vehicles. In particular, a 3D model for finite element analysis (FEA) for the field simulation of a WPTS is developed. Specifically, the effects of aluminum shield and steel layer, representing the car frame, on the self and mutual inductances are investigated. An equivalent electric circuit is then built, and the relevant lumped parameters are identified by means of the FEAs.

The finite element model is used to evaluate self and mutual inductances in several transmitting-receiving coil configurations and relative positions. In particular, the FEA simulates the aluminum and steel layers as shell elements in a 3D domain. The self and mutual inductance values in the aligned coil case are also used as input parameters in a circuit model to evaluate the onload current.

The use of shell elements in FEA substantially reduces the number of mesh elements needed to simulate the eddy currents in the steel and aluminum layer, so putting the ground for low-cost field analysis. Moreover, the FEA gives an accurate computation of the self and mutual inductance to be used in a circuit model, which, in turn, provides a fast update of the onload induced current.

To save computational time, the use of 2D shell elements to model thin conductive regions introduces a simplified FEA that could be used in the WPTS simulation. Moreover, the dynamic behavior of WPTS, i.e. the operation when the receiving coil is moving with respect to the transmitting one, is considered. Because of the lumped parameters’ dependence upon the relative positions of the two coils, the proposed method allows identifying the circuit parameters for several configurations so substantially reducing the computational burden.

Based on the text mining tools, this paper aims to propose a new method to evaluate the subjectivity and objectivity of corporate social responsibility information disclosure.

The authors build up a text subjectivity evaluation model of corporate social responsibility reports through meta-analysis; a text mining is conducted to all sample CSR reports released by Chinese listed companies untill March 2016[1]. Furthermore, the authors made an overall and quantitative analysis of the situation which contained changing state, characteristics and abnormal value on the subjectivity and objectivity of information disclosure.

The results show that the subjectivity scores of social responsibility reports of Chinese listed companies are generally in a normal distribution. The diagram turns out to be a rising trend over the years and increases linearly from 2011 to 2013. Also, the industry heterogeneity and policy control are the main reasons for the formation of the differences, which are significant between different industries and different years.

This paper provides not only an important empirical basis for the research of corporate social responsibility but also a new idea for the non-financial information disclosure as well as objective evaluation of normative text.

The purpose of this paper is to attempt to realize a distribution network optimization in supply chain using grey systems theory for uncertain information.

There is much uncertain information in the distribution network optimization of supply chain, including fuzzy information, stochastic information and grey information, etc. Fuzzy information and stochastic information have been studied in supply chain, however grey information of the supply chain has not been covered. In the distribution problem of supply chain, grey demands are taken into account. Then, a mathematics model with grey demands has been constructed, and it can be transformed into a grey chance‐constrained programming model, grey simulation and a proposed hybrid particle swarm optimization are combined to resolve it. An example is also computed in the last part of the paper.

The results are convincing: not only that grey system theory can be used to deal with grey uncertain information about distribution of supply chain, but grey chance‐constrained programming, grey simulation and particle swarm optimization can be combined to resolve the grey model.

The method exposed in the paper can be used to deal with distribution problems with grey information in the supply chain, and network optimization results with a grey uncertain factor could be helpful for supply chain efficiency and practicability.

The paper succeeds in realising both a constructed model of the distribution of supply chain with grey demands and a solution algorithm of the grey mathematics model by using one of the newest developed theories: grey systems theory.

There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.

Design is a time-consuming process for mechanical production. Some design structures frequently occur in different products and can be shared by multiple assembly models. Thus, identifying these structures and adding them to a design knowledge library significantly speed up the design process. Most studies addressing this issue have traditionally focused on part models and have not extended to assembly models. This paper aims to find a method for common design structure discovery in assembly models.

Computer-aided design models have a great deal of valuable information defined by different designers in the design stages, especially the assembly models, which are actually carriers of information from multiple sources. In this paper, an approach for discovering a common design structure in assembly models is proposed by comparing information from multiple sources. Assembly models are first represented as attribute connection graphs (ACGs), in which we mainly consider topological information and various attributes of parts and connections. Then, we apply a K-means clustering method based on a similarity analysis of different attributes to classify the parts and connections and transform ACGs of assemblies into type code graphs (TCGs). After this, a discovery algorithm that improves upon fast frequent subgraph mining is used to identify common design structures in assemblies.

A new method was developed for discovering common design structures in assembly models, considering the similarity of information from multiple sources and allowing some differences in the details to keep both commonalities and individualities of common design structures.

Experiments show that the proposed method is efficient and can produce a reasonable result.

This discovery method helps designers find common design structures from different assembly models and shorten the design cycle. It is an effective approach to build a knowledge library for product design that can shorten the design cycle.

This paper attempts to put forward a convincing and flexible grey cluster method that can be used in confirming credibility level of trustworthy software development process.

Determination on credibility level in the software development process is dynamic, as credibility of the results may be different at different times and under different project requirements. Qualitative methods are not entirely convincing, and most quantitative methods are not flexible enough. Grey cluster based on nonlinear grey whitening weight function put forward in this paper is both convincing and flexible. Finally eight projects from the ISBSG database are used for empirical analysis, which confirm that the method put forward in this paper is available and credible.

The results are convincing: not only that grey cluster based on nonlinear grey whitening weight function put forward in this paper is both convincing and flexible, but it can be used in confirming credibility level of trustworthy software development process.

Eight projects from the ISBSG database are used for empirical analysis, which confirms that the method put forward in this paper is available and credible.

Nonlinear grey whitening weight function is derivable except endpoint. Grey cluster based on nonlinear grey whitening weight function put forward in this paper is both convincing and flexible.