Search results

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

This study aims to modify the human factors analysis and classification system (HFACS) to make it suitable for collapse accident analysis in construction. Based upon the modified HFACS, distribution patterns of causal factors across multiple levels were discerned among causal factors of various stakeholders at construction sites. It explored the correlations between two causal factors from different levels and further determined causation paths from two perspectives of level and stakeholder.

The main research framework consisted of data collection, coding and analysis. Collapse accident reports were collected with adequate causation information. The modified HFACS was utilized for coding causal factors across all five levels in each case. A hybrid approach with two perspectives of level and stakeholder was proposed for frequency analysis, correlation analysis and path identification between causal factors.

Eight causal factors from external organizations at the fifth level were added to the original HFACS. Level-based correlation analyses and path identification provided safety managers with a holistic view of inter-connected causal factors across five levels. Stakeholder-based correlation analyses between causal factors from the fifth level and its non-adjacent levels were implemented based on client, government and third parties. These identified paths were useful for different stakeholders to develop specific safety plans for avoiding construction collapse accidents.

This paper fulfils an identified need to modify and utilize the HFACS model for correlation analysis and path identification of causal factors resulting in collapse accidents, which can provide opportunities for tailoring preventive and protective measures at construction sites.

This study is based on the regulatory focus theory and conservation of resources theory to examine how information confusion leads to users’ discontinuous usage intention of social networking sites (SNSs), with the mediating mechanisms of users’ motivation and affectivity.

Data were obtained from 270 users in different SNSs in Vietnam. Structural equation modeling was used to analyze the sample data and test the hypotheses.

Results show that information confusion has a positive influence on discontinuous usage intention, and prevention focus positively mediates this relationship. Furthermore, the negative affectivity positively mediates the link between information confusion and discontinuous usage intention and that between prevention focus and discontinuous usage intention. In addition, prevention focus and negative affectivity together play a serial mediating effect in the link between information confusion and discontinuous usage intention.

This study extends the regulatory focus theory and conservation of resources theory to validate a model that explains the transitional process of users’ motivation and affectivity in the link between information confusion and discontinuous usage intention of SNSs. The findings of this study provide implications for academic researchers and business managers of SNSs to understand and make better decisions to retain their users.

The purpose of this study is to contribute to the debate on the impact of organizational culture and national culture on green supply chain management (GSCM) adoption by empirically testing the developed framework, and ultimately pave the way toward potential areas for future research.

Using survey data from a sample of Moroccan manufacturing firms, 130 responses were collected and analyzed using SPSS 25 and Smart PLS v 3.3.3 software. The paper used a convenience sample, as it is required by the quantitative method, which legitimate making generalization under certain conditions.

The research results indicated that the national culture does not influence the GSCM implementation. The results contradict a number of prior works. As for the second direct effect measured postulated that organizational culture has a direct and significant impact on the GSCM. The results indicate that adhocracy culture, clan culture and hierarchical culture have a positive impact on the implementation of GSCM initiatives. To assess the impact of ownership type on GSCM, we underlined the difference between local and foreign firms. In fact, as argued, the foreign firms are more implementing GSCM initiatives than local firms do. Based on the arguments advanced on prior literature, the firm size does, as expected, exert significant control over the adoption of GSCM initiatives.

The paper here is a starting point to understand how environmental sustainability and culture are interlinked; further research might contribute to this topic by empirically testing the model in similar or different contexts, using different cultural frameworks.

The practical implications for the paper are related to the necessity of adopting adequate organizational culture to build responsible behaviors for GSCM adoption by Moroccan firms. Recognizing the powerful role of organizational culture as a crucial factor responsible for GSCM’s success beyond the well-defined corporate strategies, including market presence and technological advantages, etc.

This paper contributes to the establishment of codependent links between sociology and management fields as it helps to update the social theories present in the operations management area.

To the best of the author’s knowledge, few works have pursued to review and bridge cultural theories with the GSCM implementation.

This study aims to examine the mechanisms underlying social media commerce by investigating the interplay between platforms, people and information. Drawing upon trust transfer theory, the research model proposes that the platform’s information provision enhances the credibility of the information source, leading to increased information usefulness, adoption and sharing, ultimately influencing purchase intention.

The research design used in this study was a quantitative approach using a cross-sectional survey method. The study developed a research model based on trust transfer theory and hypothesized relationships between the platform’s information provision, information source credibility, information-related responses and purchase intention. Structural equation modeling was used to analyze the collected data and test the research hypotheses.

The findings supported most of the hypotheses and provided valuable insights into the role of information credibility in shaping consumers’ purchase intentions. Specifically, the study revealed that the platform’s information provision enhances the credibility of the information source, leading to increased information usefulness, adoption and sharing. Furthermore, information usefulness and adoption mediate the relationship between information source credibility and purchase intention.

The limitations of this research include the use of convenience sampling, which may not represent the broader population, and the cross-sectional design, which does not provide an in-depth understanding of the adoption process. The reliance on self-reported data and the limited scope of investigation with only six constructs are additional limitations. Future studies should consider national random sampling, longitudinal designs, multiple data sources and explore negative effects and other potential mediating variables. Despite these limitations, this research contributes to the understanding of social media commerce mechanisms and provides valuable insights for practitioners in the field.

The findings of this study provide valuable insights for platform providers and marketers in the social media commerce environment. First, the study emphasizes the importance of effective messaging in improving information credibility. Platform providers should focus on delivering accurate and trustworthy information to enhance consumers’ perceptions of product quality and increase purchase intentions. Second, marketers can leverage the information-related factors identified in this study, such as information usefulness and adoption, to optimize their marketing efforts. By understanding how consumers perceive and interact with information on social media platforms, marketers can tailor their strategies to effectively engage and influence potential customers. Overall, these practical implications can enhance success in the competitive social media commerce landscape.

The social implications of this study are significant for social media commerce practitioners. The findings highlight the importance of effective messaging and information provision on social media platforms in improving information credibility, thereby enhancing purchase intention. By understanding the mechanisms that drive consumer behavior in the context of social media commerce, platform providers and marketers can optimize their marketing efforts. This includes focusing on delivering trustworthy and useful information, fostering information adoption and sharing among users and ultimately increasing the likelihood of successful transactions. These insights provide valuable guidance for practitioners to navigate the competitive landscape of social media commerce and enhance their chances of success.

The originality of this research lies in its application of trust transfer theory to investigate the mechanisms driving social media commerce. By examining the interplay between platform, people and information, the study specifically focuses on the role of the platform’s information provision in enhancing information credibility and its impact on information-related responses and purchase intentions. This study extends the understanding of the trust transfer mechanism between customers and sellers/brands in customer-to-customer social commerce by emphasizing the importance of effective messaging and information credibility in shaping consumer behavior. The empirical findings contribute to the understanding of information trust transfer and provide a unique perspective on the underlying mechanisms that drive social media commerce.

In the context of Industry 4.0, intelligent construction technologies (ICT) represented by information technology and networking will undoubtedly provide new impetus to the development of the prefabricated building supply chain (PBSC), but they will also bring various potential risks. So far, there is a large lack of research on the comprehensive consideration of the risks associated with the intelligent transformation of PBSC based on the information sharing perspective, and the critical risks and interactions are still unclear, making it difficult to identify efficient risk mitigation strategies. Therefore, this paper aims to reveal the interactions between stakeholders and clarify the critical risk nodes and interactions in information sharing of PBSC (IS-PBSC), and propose targeted risk mitigation strategies.

Firstly, this paper creatively delineates the risks and critical stakeholders of IS-PBSC. Secondly, Data is collected through questionnaires to understand the degree of risks impact. Thirdly, with the help of NetMiner 4 software, social network analysis is conducted and IS-PBSC risk network is established to reveal critical risk nodes and interactions. Finally, further targeted discussion of critical risk nodes, the effectiveness and reasonableness of the risk mitigation strategies are proposed and verified through NetMiner 4 software simulation.

The results show that the critical risks cover the entire process of information sharing, with the lack of information management norms and other information assurance-related risks accounting for the largest proportion. In addition, the government dominates in risk control, followed by other stakeholders. The implementation of risk mitigation strategies is effective, with the overall network density reduced by 41.15% and network cohesion reduced by 24%.

In the context of Industry 4.0, ICT represented by information technology and networking will undoubtedly provide new impetus to the development of the PBSC, but they will also bring various potential risks. So far, there is a large lack of research on the comprehensive consideration of the risks associated with the intelligent transformation of PBSC based on the information sharing perspective, and the critical risks and interactions are still unclear, making it difficult to identify efficient risk mitigation strategies.

Based on the results of risk network visualization analysis, this paper proposes an ICT-based IS-PBSC mechanism that promotes the development of the integration of ICT and PBSC while safeguarding the benefits of various stakeholders.

The purpose of this study is to understand the psychological mechanism that affects consumer trust by focusing on the formation and influence process of psychological contracts, and taking this opportunity, explore the influence paths of food quality, food safety and service quality on consumer trust in the online food market, and provide theoretical suggestions for building trust in food businesses' consumers.

This study is based on an empirical investigation and uses partial least square structural equation modeling for analysis. Survey data were collected online from 359 APP users of online food transaction platforms in China.

Food quality, food safety and service quality influence consumer trust through the mediating effects of relational and transactional psychological contracts. However, the differences between these influencing paths are obvious and shift with changes in the marketing channels.

This study contributes to the body of consumer trust research by exploring online food transactions as an emerging trend in China. Some optimization strategies for food quality, food safety and service quality are provided for enterprises involved in online food transactions.

This is a pioneering study revealing psychological contracts as a missing but significant mediator between consumer trust and its antecedents.

The purpose of this study is to examine the moderating effect of two types of external funds in terms of loan and government subsidy on the relationship between R&D investment and firms' innovation performance in emerging markets, as well as the contingent role of firm leader's international experience associated with the effects of loan and government subsidy.

The authors tested the hypotheses using a longitudinal dataset of 716 high-tech firms of Zhongguancun Science Park (ZSP) in China during 2008–2014, covering detailed information on the operations, financial situation and R&D activities, patents, etc. The authors finally identified an unbalanced panel of 2,430 firm-year observations. Considering the dependent variable is the countable data and non-negative values, the negative binomial regression with fixed effects was adopted to test the hypotheses.

The results show that the more loans or government subsidies the firm receives, the weaker the positive effect of R&D investment on firms' innovation performance in emerging markets. Furthermore, the findings reveal that firm leaders' international experience can mitigate the negative moderating effect of government subsidies, but strengthen the negative moderating effect of loans.

The study provides new insights into how loans and government subsidies as external funds influence the effectiveness of R&D in enhancing innovation performance, and the findings highlight the fact that more external funds can reduce firm R&D efficiency. Moreover, the authors also enrich the resource orchestration theory by revealing the critical role of firm leaders' international experience in the decision-making of resource configuration to mitigate the inefficiency of high subsidies in emerging markets.

Polyaniline (PANI) has garnered attention for its potential applications in anticorrosion fields because of its unique properties. Satisfactory outcomes have been achieved when using PANI as a functional filler in organic coatings. More recently, research has extensively explored PANI-based organic coatings with self-healing properties. The purpose of this paper is to provide a summary of the active agents, methods and mechanisms involved in the self-healing of organic coatings.

This study uses specific doped acids and metal corrosion inhibitors as active and self-healing agents to modify PANI using the methods of oxidation polymerization, template synthesis, nanosheet carrier and nanocontainer loading methods. The anticorrosion performance of the coatings is evaluated using EIS, LEIS and salt spray tests.

Specific doped acids and metal corrosion inhibitors are used as active agents to modify PANI and confer self-healing properties to the coatings. The coatings’ active protection mechanism encompasses PANI’s own passivation ability, the adsorption of active agents and the creation of insoluble compounds or complexes.

This paper summarizes the active agents used to modify PANI, the procedures used for modification and the self-healing mechanism of the composite coatings. It also proposes future directions for developing PANI organic coatings with self-healing capabilities. The summaries and proposals presented may facilitate large-scale production of the PANI organic coatings, which exhibit outstanding anticorrosion competence and self-healing properties.

To provide high torques needed to move a robot’s links, electric actuators are followed by a transmission system with a high transmission rate. For instance, gear ratios of 100:1 are often used in the joints of a robotic manipulator. This results into an actuator with large mechanical impedance (also known as nonback-drivable actuator). This in turn generates high contact forces when collision of the robotic mechanism occur and can cause humans’ injury. Another disadvantage of electric actuators is that they can exhibit overheating when constant torques have to be provided. Comparing to electric actuators, pneumatic actuators have promising properties for robotic applications, due to their low weight, simple mechanical design, low cost and good power-to-weight ratio. Electropneumatically actuated robots usually have better friction properties. Moreover, because of low mechanical impedance, pneumatic robots can provide moderate interaction forces which is important for robotic surgery and rehabilitation tasks. Pneumatic actuators are also well suited for exoskeleton robots. Actuation in exoskeletons should have a fast and accurate response. While electric motors come against high mechanical impedance and the risk of causing injuries, pneumatic actuators exhibit forces and torques which stay within moderate variation ranges. Besides, unlike direct current electric motors, pneumatic actuators have an improved weight-to-power ratio and avoid overheating problems.

The aim of this paper is to analyze a nonlinear optimal control method for electropneumatically actuated robots. A two-link robotic exoskeleton with electropneumatic actuators is considered as a case study. The associated nonlinear and multivariable state-space model is formulated and its differential flatness properties are proven. The dynamic model of the electropneumatic robot is linearized at each sampling instance with the use of first-order Taylor series expansion and through the computation of the associated Jacobian matrices. Within each sampling period, the time-varying linearization point is defined by the present value of the robot’s state vector and by the last sampled value of the control inputs vector. An H-infinity controller is designed for the linearized model of the robot aiming at solving the related optimal control problem under model uncertainties and external perturbations. An algebraic Riccati equation is solved at each time-step of the control method to obtain the stabilizing feedback gains of the H-infinity controller. Through Lyapunov stability analysis, it is proven that the robot’s control scheme satisfies the H-infinity tracking performance conditions which indicate the robustness properties of the control method. Moreover, global asymptotic stability is proven for the control loop. The method achieves fast convergence of the robot’s state variables to the associated reference trajectories, and despite strong nonlinearities in the robot’s dynamics, it keeps moderate the variations of the control inputs.

In this paper, a novel solution has been proposed for the nonlinear optimal control problem of robotic exoskeletons with electropneumatic actuators. As a case study, the dynamic model of a two-link lower-limb robotic exoskeleton with electropneumatic actuators has been considered. The dynamic model of this robotic system undergoes first approximate linearization at each iteration of the control algorithm around a temporary operating point. Within each sampling period, this linearization point is defined by the present value of the robot’s state vector and by the last sampled value of the control inputs vector. The linearization process relies on first-order Taylor series expansion and on the computation of the associated Jacobian matrices. The modeling error which is due to the truncation of higher-order terms from the Taylor series is considered to be a perturbation which is asymptotically compensated by the robustness of the control algorithm. To stabilize the dynamics of the electropneumatically actuated robot and to achieve precise tracking of reference setpoints, an H-infinity (optimal) feedback controller is designed. Actually, the proposed H-infinity controller for the model of the two-link electropneumatically actuated exoskeleton achieves the solution of the associated optimal control problem under model uncertainty and external disturbances. This controller implements a min-max differential game taking place between: (i) the control inputs which try to minimize a cost function which comprises a quadratic term of the state vector’s tracking error and (ii) the model uncertainty and perturbation inputs which try to maximize this cost function. To select the stabilizing feedback gains of this H-infinity controller, an algebraic Riccati equation is being repetitively solved at each time-step of the control method. The global stability properties of the H-infinity control scheme are proven through Lyapunov analysis.

Pneumatic actuators are characterized by high nonlinearities which are due to air compressibility, thermodynamics and valves behavior and thus pneumatic robots require elaborated nonlinear control schemes to ensure their fast and precise positioning. Among the control methods which have been applied to pneumatic robots, one can distinguish differential geometric approaches (Lie algebra-based control, differential flatness theory-based control, nonlinear model predictive control [NMPC], sliding-mode control, backstepping control and multiple models-based fuzzy control). Treating nonlinearities and fault tolerance issues in the control problem of robotic manipulators with electropneumatic actuators has been a nontrivial task.

The novelty of the proposed control method is outlined as follows: preceding results on the use of H-infinity control to nonlinear dynamical systems were limited to the case of affine-in-the-input systems with drift-only dynamics. These results considered that the control inputs gain matrix is not dependent on the values of the system’s state vector. Moreover, in these approaches the linearization was performed around points of the desirable trajectory, whereas in the present paper’s control method the linearization points are related with the value of the state vector at each sampling instance as well as with the last sampled value of the control inputs vector. The Riccati equation which has been proposed for computing the feedback gains of the controller is novel, so is the presented global stability proof through Lyapunov analysis. This paper’s scientific contribution is summarized as follows: (i) the presented nonlinear optimal control method has improved or equally satisfactory performance when compared against other nonlinear control schemes that one can consider for the dynamic model of robots with electropneumatic actuators (such as Lie algebra-based control, differential flatness theory-based control, nonlinear model-based predictive control, sliding-mode control and backstepping control), (ii) it achieves fast and accurate tracking of all reference setpoints, (iii) despite strong nonlinearities in the dynamic model of the robot, it keeps moderate the variations of the control inputs and (iv) unlike the aforementioned alternative control approaches, this paper’s method is the only one that achieves solution of the optimal control problem for electropneumatic robots.

The use of electropneumatic actuation in robots exhibits certain advantages. These can be the improved weight-to-power ratio, the lower mechanical impedance and the avoidance of overheating. At the same time, precise positioning and accurate execution of tasks by electropneumatic robots requires the application of elaborated nonlinear control methods. In this paper, a new nonlinear optimal control method has been developed for electropneumatically actuated robots and has been specifically applied to the dynamic model of a two-link robotic exoskeleton. The benefit from using this paper’s results in industrial and biomedical applications is apparent.

A comparison of the proposed nonlinear optimal (H-infinity) control method against other linear and nonlinear control schemes for electropneumatically actuated robots shows the following: (1) Unlike global linearization-based control approaches, such as Lie algebra-based control and differential flatness theory-based control, the optimal control approach does not rely on complicated transformations (diffeomorphisms) of the system’s state variables. Besides, the computed control inputs are applied directly on the initial nonlinear model of the electropneumatic robot and not on its linearized equivalent. The inverse transformations which are met in global linearization-based control are avoided and consequently one does not come against the related singularity problems. (2) Unlike model predictive control (MPC) and NMPC, the proposed control method is of proven global stability. It is known that MPC is a linear control approach that if applied to the nonlinear dynamics of the electropneumatic robot, the stability of the control loop will be lost. Besides, in NMPC the convergence of its iterative search for an optimum depends on initialization and parameter values selection and consequently the global stability of this control method cannot be always assured. (3) Unlike sliding-mode control and backstepping control, the proposed optimal control method does not require the state-space description of the system to be found in a specific form. About sliding-mode control, it is known that when the controlled system is not found in the input-output linearized form the definition of the sliding surface can be an intuitive procedure. About backstepping control, it is known that it cannot be directly applied to a dynamical system if the related state-space model is not found in the triangular (backstepping integral) form. (4) Unlike PID control, the proposed nonlinear optimal control method is of proven global stability, the selection of the controller’s parameters does not rely on a heuristic tuning procedure, and the stability of the control loop is assured in the case of changes of operating points. (5) Unlike multiple local models-based control, the nonlinear optimal control method uses only one linearization point and needs the solution of only one Riccati equation so as to compute the stabilizing feedback gains of the controller. Consequently, in terms of computation load the proposed control method for the electropneumatic actuator’s dynamics is much more efficient.