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The purpose of this paper is to present an automatic approach for mesh sizing field generation of complicated  computer-aided design (CAD) models.

In this paper, the authors present an automatic approach for mesh sizing field generation. First, a source point extraction algorithm is applied to capture curvature and proximity features of CAD models. Second, according to the distribution of feature source points, an octree background mesh is constructed for storing element size value. Third, mesh size value on each node of background mesh is calculated by interpolating the local feature size of the nearby source points, and then, an initial mesh sizing field is obtained. Finally, a theoretically guaranteed smoothing algorithm is developed to restrict the gradient of the mesh sizing field.

To achieve high performance, the proposed approach has been implemented in multithreaded parallel using OpenMP. Numerical results demonstrate that the proposed approach is remarkably efficient to construct reasonable mesh sizing field for complicated CAD models and applicable for generating geometrically adaptive triangle/tetrahedral meshes. Moreover, since the mesh sizing field is defined on an octree background mesh, high-efficiency query of local size value could be achieved in the following mesh generation procedure.

How to determine a reasonable mesh size for complicated CAD models is often a bottleneck of mesh generation. For the complicated models with thousands or even ten thousands of geometric entities, it is time-consuming to construct an appropriate mesh sizing field for generating high-quality mesh. A parallel algorithm of mesh sizing field generation with low computational complexity is presented in this paper, and its usability and efficiency have been verified.

Suspension is a significantly important component for automotive and railway vehicles. Regenerative hydraulic-electric shock absorbers (RHSA) have been proposed for the purpose of attenuating vibration of vehicle suspension, and also recover kinetic energy originated from vehicle vibration that is conventionally dissipated by hydraulic dampers. To advance the technology, the paper aims to present an RHSA system for heavy-duty and railway vehicles and create a dynamic modelling to discuss on the development process of RHSA model.

First, the development of RHSA dynamic model can be resolved into three stage models (an ideal one, a second one with an added accumulator and a third one that considers both accumulator and system losses) to comprehensively evaluate the RHSA's characterisation. Second, a prototype is fabricated for testing and the results meet desired agreements between simulation and measurement. Finally, the study of key parameters is carried out to investigate the influences of hydraulic-cylinder size, hydraulic-motor displacement and accumulator pre-charged pressure on the RHSA system.

The findings of sensitivity analysis indicate that the component design can satisfy the damping characteristics and power performance required for heavy-duty vehicle, freight wagon and typical passenger train. The results also show that reducing the losses is highly beneficial for saving suspension energy, improving system reliability and increasing power-conversion efficiency.

The paper presents a more detailed method for the development and analysis of a RHSA. Compared with the typical shock absorbers, RHSA can also recover the vibration energy dissipated by suspension.

This study aims to investigate the relationships between the perceived neighborhood walkable environment (PNWE), neighborhood interaction (NI) and residents’ mental health, with a focus on examining differences among residents of different age groups.

Using an electronic survey questionnaire, data on PNWE, NI and mental health were collected from 1,159 residents across 205 communities in Shanghai, China. Our study utilized a structural equation modeling (SEM), employing the maximum likelihood estimation method. The structural equation model was fitted using the MPLUS software.

The mental health of young and middle-aged adults is generally poor, and they are at higher risk of depression than children and older adults. The effects of PNWE and NI on the mental health of residents varied among different age groups. As residents get older, their mental health is more affected by the PNWE. In addition, the influence of the PNWE on children and older adults’ mental health is direct and not mediated by NI. For young and middle-aged adults, the influence of the PNWE on their mental health needs to be mediated by NI.

This study marks the first examination of the relationship between PNWE, NI and mental health among different age groups of residents in China. The findings of this research can assist policymakers in gaining a deeper understanding of the underlying mechanisms by which PNWE affects mental health. Furthermore, it can contribute to the development of more targeted walkable environment designs aimed at enhancing mental health among various age groups.

This paper aims to examine how a firm’s capability affects its political networking in emerging economies and how the institutional environment influences the relationship between a firm’s capability and its political networking.

The authors test the theoretical model by analyzing a database from a World Bank survey in China.

The results show a nonlinear (U-shaped) relationship between a firm’s capability and its efforts in political networking. The relationship between a firm’s capability and political networking is contingent on the institutional environment, as reflected in institutional development and industry regulation.

This study elucidates political networking in emerging economies and contributes to research on corporate political strategy.

Nowadays, WiFi indoor positioning based on received signal strength (RSS) becomes a research hotspot due to its low cost and ease of deployment characteristics. To further improve the performance of WiFi indoor positioning based on RSS, this paper aims to propose a novel position estimation strategy which is called radius-based domain clustering (RDC). This domain clustering technology aims to avoid the issue of access point (AP) selection.

The proposed positioning approach uses each individual AP of all available APs to estimate the position of target point. Then, according to circular error probable, the authors search the decision domain which has the 50 per cent of the intermediate position estimates and minimize the radius of a circle via a RDC algorithm. The final estimate of the position of target point is obtained by averaging intermediate position estimates in the decision domain.

Experiments are conducted, and comparison between the different position estimation strategies demonstrates that the new method has a better location estimation accuracy and reliability.

Weighted k nearest neighbor approach and Naive Bayes Classifier method are two classic position estimation strategies for location determination using WiFi fingerprinting. Both of the two strategies are affected by AP selection strategies and inappropriate selection of APs may degrade positioning performance considerably.

The RDC positioning approach can improve the performance of WiFi indoor positioning, and the issue of AP selection and related drawbacks is avoided.

The RSS-based effective WiFi indoor positioning system can makes up for the indoor positioning weaknesses of global navigation satellite system. Many indoor location-based services can be encouraged with the effective and low-cost positioning technology.

A novel position estimation strategy is introduced to avoid the AP selection problem in RSS-based WiFi indoor positioning technology, and the domain clustering technology is proposed to obtain a better accuracy and reliability.

The rapid growth of emerging market firms (EMFs) has been a topic of interest for the past two decades, especially in China. However, few studies have discussed how and why EMFs can impel the upgrading of their capabilities to quickly win competitive advantages in the global market. In this context, the purpose of this paper is to unravel the implausible upgrading phenomenon from the perspective of technological proximity.

This paper adopts a single case study, specifically that of a leading Chinese e-bike firm, with a special focus on the dynamic nature of the capability upgrading process and underlying mechanisms.

The results show that taking advantage of technological proximity is an important way for EMFs to climb the ladder of capability upgrading. The stage-based process reveals how capability upgrading is achieved through elaborate actions related to technological proximity. Furthermore, this study finds three learning mechanisms behind the technological proximity, which enable firms to successfully upgrade to higher levels of capabilities. In particular, the trigger role played by contextual conditions in guiding firms' capability upgrading is highlighted and characterized.

This study enriches traditional capability upgrading literature from a technological proximity perspective, especially the traditional static upgrading research related to EMFs. The authors also contribute to the conceptualization of technological proximity. However, the research setting is China's e-bike industry; therefore, the study's generalizability to other emerging markets and industries may be limited.

The results show that it is important to recognize the value of the transfer and sharing of technology between proximal industries for local governments. Also, appropriate policies should be developed to break down the technology barriers between these industries. Moreover, rather than catching up with the superior technologies of multinational corporations in advanced countries, focusing on products with high technological proximity in local or regional areas may be more helpful for EMFs' upgrading.

This paper investigates the capability upgrading process and mechanisms in EMFs, particularly with respect to the role played by technological proximity.

The purpose of this paper is to define new method (grey model (GM)) for predicting the value of gases in oil‐immersed power equipment, as well as change the traditional GM which requires equal interval data.

Trend forecasting is an important aspect in fault diagnosis and work state supervision, however, in practice, it is not practical that a number of data is necessary to build the forecast model. In transformer, the concentration of the gases dissolved in transformer oil is associated with gas type, oil quality, oil temperature, transformer load, etc. which some are known, others are unknown. So it can consider that transformer is grey system and the theory of grey system is chosen as a mathematical framework to solve the problem of forecasting the change of gases.

If possible, the results should be accompanied by significance.

Accessibility and availability of data are the main limitations which model will be applied.

A very useful advice for power transformer fault diagnosis method based on dissolved gas analysis data.

The paper presents a new approach of forecasting the value of gases in oil‐immersed power equipment and is aimed at unequal interval gases data which is used to GM.

The purpose of this study is to define and develop a new technological development path for latecomer firms in developing countries.

An analytical framework for development based on the technological capability (TC) dimensions is developed and examined in the drilling sector. Since the process of TC accumulation is dynamic, the case study approach is the best method for an exploratory theory-building study. Through a comparative case study of two Iranian drilling contractors, a new path for the technological development of latecomer oil service companies is proposed.

The study of two cases indicates that despite having similar scope and levels of TC, one of them demonstrated superior technical performance. To address this difference, the concept of operational efficiency is introduced which is considered the outcome of increasing the depth of TC.

Although upgrading the level of technological and innovation capability is an important path for technological development, latecomers that suffer from various disadvantages can perform their routine activities with superior performance and develop through their basic operational/production capabilities. Also, specialized indicators designed for assessing the level and depth of TC in the drilling industry have important insights for evaluating the technological and competitive position of oil service companies.

To the best of the author’s knowledge, this study takes the first step in defining and elaborating on the concept of depth of TC as a development path for latecomers. It also introduced a novel approach to the global operational/production efficiency frontier as a target for their catch-up.

Wireless mesh networks (WMNs) have evolved quickly during the last several years. They are widely used in a lot of fields. Channel allocation provides basic means to guarantee mesh networks’ good performance such as efficient routing. The purpose of this paper is to study channel allocation in mesh networks.

First, the papers in channel allocation fields are surveyed, and then the limitations in existing methods noted. Graph theory is used to find a better model to represent the problem and algorithms are proposed based on this model. Simulation proved that algorithms are better than the previous conflict graph‐based approaches.

The paper analyzes the conflict graph‐based model and finds its limitations, then proposes a bipartite graph‐based model. Algorithms were devised based on this model. Simulation results illustrate that the algorithms can reduce the starvation ratio and improve the bandwidth utilization, compared with previous conflict graph‐based algorithms.

The research of this paper is based on an ideal network environment without interference or noises. It will be better if the noises are considered in future work.

To study the routing strategies of WMNs, it is not sufficient to only consider path length as routing metric since the nodes are heterogeneous. The routing metrics should include the channel bandwidths which are the results of channel allocation.

This paper presents a new bipartite graph‐based model to represent the channel allocation problem in mesh networks. This model is more efficient and includes more information compared with conflict graph model, and it also proposes channel allocation algorithms based on bipartite graph‐based model. The algorithms can reduce starvation ratio and improve the bandwidth utilization.

Emerging Market Multinationals (EMNCs) are often seen as firms with singular identity. While they may share certain characteristics, EMNCs are seldom orchestrated and managed in the same manner. Through a cluster analysis of outward foreign direct investment data of EMNCs from India, we propose taxonomy of EMNCs based on their mode of operation, industry in which they operate, region where they invest and the amount invested. We use a dataset spread over 2007–2013, constituting investment data of 4,824 Indian firms into 7,238 foreign entities. Based on a two-step clustering approach, we propose three strategic archetypes of EMNCs: Global Service Providers, Integrated Manufacturers, and Established Internationalizers. The Global Service Providers mainly consists of firms operating in developed markets with an intention to serve their client needs through wholly owned subsidiaries. Integrated Manufacturers are firms that are primarily operating in other developing markets to sell their products through joint ventures and also present in developed markets through wholly owned subsidiaries – to acquire technology and other resources. The Established Internationalizers are large EMNCs with highest levels of investments, and relatively similar to the Western multinationals. We analyze the characteristics of these three groups of EMNCs based on their strategy and investment behavior, to derive insights into the heterogeneity across EMNCs. We discuss our findings and lay out future directions for research in the area.