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Happiness is an important mental emotion and yet becoming a major health concern nowadays. For this reason, better recognizing the objective understanding of how humans respond to event-related observations in their daily lives is especially important.

This paper uses non-intrusive technology (hyperspectral imaging [HSI]) for happiness recognition. Experimental setup is conducted for data collection in real-life environments where observers are showing spontaneous expressions of emotions (calm, happy, unhappy: angry) during the experimental process. Based on facial imaging captured from HSI, this work collects our emotional database defined as SWU Happiness DB and studies whether the physiological signal (i.e. tissue oxygen saturation [StO2], obtained by an optical absorption model) can be used to recognize observer happiness automatically. It proposes a novel method to capture local dynamic patterns (LDP) in facial regions, introducing local variations in facial StO₂ to fully use physiological characteristics with regard to hyperspectral patterns. Further, it applies a linear discriminant analysis-based support vector machine to recognize happiness patterns.

The results show that the best classification accuracy is 97.89 per cent, objectively demonstrating a feasible application of LDP features on happiness recognition.

This paper proposes a novel feature (i.e. LDP) to represent the local variations in facial StO₂ for modeling the active happiness. It provides a possible extension to the promising practical application.

One hundred and seventy‐eight heroin addicts in reformatory school were sent to one of two rehabilitation treatments: reform through education and labour and therapeutic community (TC)‐based rehabilitation programme. After six months of being discharged, pre‐ and post‐treatment scores on the Addiction Severity Index were compared, and relapse related factors were investigated. Results indicated improvements in both treatments, with the TC‐based rehabilitation programme showing superior improvement overall. Results support the efficacy of the TC‐based rehabilitation programme proving it to be better than reform through labour and education. It is suggested that psychosocial intervention and relapse prevention should be emphasised in the treatment of drug dependence.

Wireless mesh networks (WMNs) are regarded as a milestone in developing next‐generation wireless networks. The multi‐hop architecture of WMN makes it very attractive. However, interoperability is an inherent problem for deploying a large‐scale WMN, which may consist of various types of wireless networks. There are two intuitive approaches to solving the interoperability problem: the dual‐stack/multi‐stack approach and the naive layer‐2 broadcast approach. While the former incurs high cost in all devices, the latter creates broadcast storm in the whole network. This paper aims to propose a cross‐layer heterogeneous routing protocol for solving this problem without the adverse effects of the intuitive approaches.

A conceptual discussion and approach are employed.

The simulation results validate the efficiency of the proposed protocol.

The paper provides details of a method for routing selection in WMNs.

Despite the availability of several published reviews on the adoption of blockchain (BC) in supply chain (SC), at present, the literature lacks a comprehensive review incorporating the antecedents and consequences of BC adoption. Moreover, the complex adoption of BC in SC, explained with the mediating and moderating relationships, is not fully consolidated. Thus, the aim of this study was to conduct a systematic literature review (SLR) on BC technology adoption (BCTA) in SC by integrating its antecedents and consequences.

Keyword searches were performed in multiple databases resulting 382 articles for evaluation and verification. After careful screening with respect to the purpose of the study and systematic processing of the retrieved articles, a total of 211 peer-reviewed articles were included in this study for review.

Various technological, organisational, individual, social, environmental, operational and economic factors were found as the antecedents of BCTA in SC. In addition, numerous applications of BC Technology (BCT) were identified, including asset management, identity management, transaction management, data management and operations management. Finally, the consequences of BCTA were categorised as operational, risk management, economic and sustainability outcomes.

This study can assist relevant decision-makers in managing the factors influencing BCTA and the potential uses of the technology to enhance SC performance.

By integrating the antecedents, applications and consequences of BCTA in SC, including the mediators and moderators, an integrated framework was developed that can potentially assist researchers to develop theoretical models. Further, the results of this SLR provide future directions for studying BCTA in supply chain management (SCM).

Social network group decision-making (SNGDM) has rapidly developed because of the impact of social relationships on decision-making behavior. However, not only do social relationships affect decision-making behavior, but decision-making behavior also affects social relationships. Such complicated interactions are rarely considered in current research. To bridge this gap, this study proposes an SNGDM model that considers the interaction between social trust relationships and opinion evolution.

First, the trust propagation and aggregation operators are improved to obtain a complete social trust relationship among decision-makers (DMs). Second, the evolution of preference information under the influence of trust relationships is measured, and the development of trust relationships during consensus interactions is predicted. Finally, the iteration of consensus interactions is simulated using an opinion dynamics model. A case study is used to verify the feasibility of the proposed model.

The proposed model can predict consensus achievement based on a group’s initial trust relationship and preference information and effectively captures the dynamic characteristics of opinion evolution in social networks.

This study proposes an SNGDM model that considers the interaction of trust and opinion. The proposed model improves trust propagation and aggregation operators, determines improved preference information based on the existing trust relationships and predicts the evolution of trust relationships in the consensus process. The dynamic interaction between the two accelerates DMs to reach a consensus.

Economic turbulence brings a significant impact in the mental health of workforce on both developed and developing countries. The purpose of this paper is to explore the impact of equity sensitivity on employee mental health. Innovation is considered to be among the critical drivers for the success and future of organizational existence, therefore this paper also investigates how the equity sensitivity impacts innovation orientation and turnover intentions across two geographies India and Hungary.

An online survey was carried out among Hungarian and Indian students. Students were selected only on the basis of having two to three years of work experience and also from good business and economics colleges from India and Hungary.

The results were analyzed using partial least square–structural equation modelling method to test the hypotheses and it showed that equity sensitivity has a positive effect on employee mental health. The findings of the study highlight that even with significant cultural differences equity sensitivity perception does not differ between Hungary and India.

The relationship between equity sensitivity and employee mental health is an important area to understand in a volatile economy. Innovation orientation and turnover intention both are important to understand the productivity of any organization; this paper is an effort to understand the impact of both variables bringing in the positive or negative impact on the growth of an organization. Limitations of this study include the sample size, cross-sectional data. Future studies can be based on a larger sample size from wider cross-sections and cultures.

Managers need to give importance to understand the equity sensitivity of employee and how it impacts their mental health and well-being. Knowing the volatile nature of economy this becomes very relevant and important for managers and organizations.

This study is important to understand that how two countries that are significantly different in cultural values still have no difference in equity sensitivity perception. Therefore, equity sensitivity is an important determinant to bring innovation and productivity in organizations across cultures.

These findings contribute to literature of equity sensitivity by exploring the impact of equity sensitivity on employee mental health in the context of two countries. Mental health is a concern not only in India but also in Hungarian context as well.

This paper aims to report on a study that used the practice theory lens to understand how Chinese ethnic culture influences restaurant workers' learning through engagement in everyday work practices.

A multiple case study approach was used. Data were collected from semi-structured interviews and site observations. Thematic analysis was conducted to identify how workers learnt the sayings, doings and relatings in their workplaces.

The findings show that the ethnic culture of the participants influences and enriches their learning in practice settings such as small Chinese restaurants.

The understandings presented here need to be verified through more research in different regions and nations. In addition, cross-cultural studies on other ethnic restaurants may contribute to deeper understandings of the influences of ethnic culture on practice-based learning.

The research contributes to understanding the influence of ethnic culture on practice-based learning.

The understandings gained from the findings of this study form a useful basis for curriculum development and instructional design of training programmes for practice-based as well as work-integrated-learning components of vocational curriculum. Furthermore, awareness of the strengths of the ethnic culture is of interest to owner/managers of small Chinese restaurants to afford supportive learning environments for workers.

This study introduces a comprehensive bibliometric analysis of the foreign direct investment (FDI) literature by multinational corporations (MNCs) focusing on emerging economies to identify the most influential authors, journals and articles in FDI research and reveals the fields' conceptual and intellectual structures. The purpose of this paper is to address these issues.

The study analyzed 533 articles published between 1974 and 2020 in 226 academic journals indexed in the Web of Science (WoS) and Scopus databases. We used the R language for statistical computing to map author collaboration, co-word and develop a conceptual and intellectual map of the field.

The results show that, although the FDI literature has many authors, few dominate the field. The International Business Review (IBR) and International Journal of Emerging Markets (IJoEM) are the main sources of the publications. Moreover, bibliometric laws show that our dataset follows the Lotka law of scientific productivity and Bradford law of scattering, identifying the core journals. Finally, FDI by MNCs in emerging economies research is divided into four sub-research themes related to (1) FDI determinants, (2) entry mode, (3) MNCs and FDI performance and (4) the internationalization process.

The current article provides several starting points for practitioners and researchers investigating FDI. It contributes to broadening the vision of the field and offers recommendations for future studies.

The purpose of this paper is to present a dual manipulator system for aloft hot-line assembly tasks of connection fittings in 110-kv intelligent substation, which is significant to the research on hot-line working robots.

This paper addresses the challenges of the task and presents a dual manipulator system which can overcome these challenges to realize the robotic assembly of connection fittings in narrow space without impacting the safe distance of both phase to phase and phase to ground. Two manipulators share a same global reference coordinate. The mission of Manipulator 1 is to position the fixed part of connection fittings and screw the bolts on it. Visual computing provides the approximately position for the end-effector of Manipulator 2, after which The Manipulator 2 carries the removable part of connection fittings to this position. Then, the assembly task could be completed with the posture of the Manipulator 2 adjusted following the guidance by force-position control.

The dual manipulator system can position the target under different illumination conditions and complete fast assembly of connect fittings in 110-kV substation. No strong arc discharge or surface erosion phenomenon has been observed.

This dual manipulator system will be particularly useful for the hot-line assembly of connection fittings in 110-kv intelligent substation, as well as some assembly tasks where uncertain target position and complex contact surface such as cylindrical hole is involved.

This study presents a dual manipulator system used by a field robot working in 110-kv intelligent substation. The system is able to achieve the connection fittings assembly task under energized simulation experimental system. Unlike other peg-in-hole assembly strategy, it does not require high stability of manipulator or plane contact surface around the hole.

The supply chain (SC) of the fast-moving consumer goods (FMCG) sector in India witnessed a significant change soon after introducing the Goods and Services Tax (GST). With the initiation of this tax, companies started moving from individual state-wise warehouses to consolidation warehouses model to save costs. This paper proposes a model that frames a mathematical formulation to optimize the distribution network in the downstream SC by considering the complexities of multi-product lines, multi-transport modes and consolidated warehouses.

The model is designed as mixed-integer linear programming (MILP), and an algorithm is developed that works on the feedback loop mechanism. It optimizes the transportation and warehouses rental costs simultaneously with impact analysis.

Total cost is primarily influenced by the critical factor transportation price rather than the warehouse rent. The choice of warehouses at prime locations was a trade-off between a lower distribution cost and higher rent tariffs.

The study enables FMCG firms to plan their downstream SC efficiently and to be in line with the recent trend of consolidation of warehouses. The study will help SC managers solve complexities such as multi-product categories, truck selection and consolidation warehouse selection problems and find the optimum value for each.

The issues addressed in the proposed work are transporting products with different sizes and weights, selecting consolidated warehouses, selecting suitable vehicles for transportation and optimizing distance in the distribution network by considering consolidated warehouses.