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Maintaining the safety of the human is a major concern in factories where humans co-exist with robots and other physical tools. Typically, the area around the robots is monitored using lasers. However, lasers cannot distinguish between human and non-human objects in the robot’s path. Stopping or slowing down the robot when non-human objects approach is unproductive. This research contribution addresses that inefficiency by showing how computer-vision techniques can be used instead of lasers which improve up-time of the robot.

A computer-vision safety system is presented. Image segmentation, 3D point clouds, face recognition, hand gesture recognition, speed and trajectory tracking and a digital twin are used. Using speed and separation, the robot’s speed is controlled based on the nearest location of humans accurate to their body shape. The computer-vision safety system is compared to a traditional laser measure. The system is evaluated in a controlled test, and in the field.

Computer-vision and lasers are shown to be equivalent by a measure of relationship and measure of agreement. R² is given as 0.999983. The two methods are systematically producing similar results, as the bias is close to zero, at 0.060 mm. Using Bland–Altman analysis, 95% of the differences lie within the limits of maximum acceptable differences.

In this paper an original model for future computer-vision safety systems is described which is equivalent to existing laser systems, identifies and adapts to particular humans and reduces the need to slow and stop systems thereby improving efficiency. The implication is that computer-vision can be used to substitute lasers and permit adaptive robotic control in human–robot collaboration systems.

In line with the stimulus overload theory, this study seeks a comprehensive understanding of tourism crowding by examining residents’ perceived tourism crowding and their corresponding avoidance and approach reactions through sustainable tourism. In addition, the study aims to investigate whether residents’ proenvironmental behavior moderates’ tourism’s negative impacts on the local ecosystem, delving into its potential mitigating role.

Using purposive sampling, the authors engaged residents associated with government and nongovernment organizations, universities, colleges and schools, as well as individuals from the business sector encompassing hotels, restaurants and cafeterias, markets and dedicated social activists actively involved in community affairs.

The analysis, conducted on 920 questionnaires using structural equation modeling, demonstrates that tourism crowding exhibits a negative correlation with sustainable tourism and approach reactions but a positive correlation with avoidance reactions. Furthermore, the moderation analysis suggests that as residents’ proenvironmental behavior improves, the detrimental effect of tourism crowding on sustainable tourism diminishes.

The study presents numerous implications for policymakers and the tourism industry, emphasizing the need to comprehend residents’ perceptions of tourism crowding and sustainable tourism. It underscores the importance of engaging residents in the tourism process to achieve sustainability goals.

The novel theoretical contribution lies in applying the stimulus overload theory to examine tourism crowding and sustainable tourism, specifically from the residents’ perspectives.

本研究根据刺激超负荷理论, 通过考察旅游地居民在整个可持续旅游过程中对旅游拥挤的感知以及他们的相应回避和接近反应, 寻求对旅游拥挤的全面了解。此外, 本研究旨在调查旅游地居民的环保行为是否可以缓和旅游对当地生态系统造成的负面影响, 并深入探讨潜在缓解作用。

我们采用目的性抽样方法, 邀请了与政府和非政府组织、大学、学院和学校有关联的旅游地居民, 来自商业领域（包括HORECA“酒店、餐馆和自助餐厅”和市场）的个人, 以及积极参与社区事务的专职社会活动家。

本研究采用结构方程模型（SEM）对920份调查问卷进行分析, 结果表明旅游拥挤与可持续旅游和接近反应呈负相关, 而与回避反应呈正相关。此外, 缓和分析表明, 随着旅游地居民环保行为的改善, 旅游拥挤对可持续旅游的不利影响呈现减弱。

本研究为决策者和旅游业提供了许多启示, 强调需要了解旅游地居民对旅游拥挤和可持续旅游的感知, 亦强调了让旅游地居民参与旅游过程的重要性, 以确保实现可持续发展目标。

本研究贡献了新颖的理论, 应用刺激超负荷理论考察旅游拥挤和可持续旅游, 特别是从旅游地居民角度进行考察。

Este estudio busca una comprensión global de la masificación turística mediante el examen de la masificación turística percibida por los residentes y sus correspondientes reacciones de aproximación y evitación a través del turismo sostenible, en el marco de la teoría de la sobrecarga de estímulos. Además, el estudio investiga si el comportamiento proambiental de los residentes modera los impactos negativos del turismo en el ecosistema local, profundizando en su potencial papel mitigador.

Utilizando un muestreo intencional o por juicio, se recogieron datos de residentes vinculados a organizaciones gubernamentales y no gubernamentales, universidades, institutos y escuelas, así como a personas del sector empresarial que engloba hoteles, restaurantes y cafeterías, mercados y activistas sociales que participan activamente en asuntos comunitarios.

El análisis de 920 cuestionarios mediante un modelo de ecuaciones estructurales demuestra que la masificación turística presenta una correlación negativa con el turismo sostenible y las reacciones de aproximación, pero una correlación positiva con las reacciones de evitación. Además, el análisis de moderación sugiere que a medida que mejora el comportamiento proambiental de los residentes, disminuye el impacto negativo de la masificación turística sobre el turismo sostenible.

El estudio presenta numerosas implicaciones para los responsables políticos y la industria turística, destacando la necesidad de comprender las percepciones de los residentes sobre la masificación turística y el turismo sostenible. Se subraya la importancia de implicar a los residentes en el proceso turístico para alcanzar objetivos de sostenibilidad.

La novedosa aportación teórica radica en la aplicación de la teoría de la sobrecarga de estímulos para examinar la masificación turística y el turismo sostenible, específicamente desde la perspectiva de los residentes.

The purpose of this paper is to explore issues relating to imposing a ban on the importation of asbestos-contaminated building materials (ACBMs) in the Australian context to better understand the multiple accountabilities and consequences.

This study undertakes a qualitative content analysis of the multiple accountabilities and stakeholder expectations using the lens of actor–network theory. This study further explores the weaknesses and complexities associated with implementing a complete ban on asbestos, ensuring that only asbestos-free building materials are imported to Australia. This study uses data collected from 15 semi-structured interviews with stakeholders, responses from the Australian Border Force to a questionnaire and 215 counter accounts from the media, the Australian Government, industry organizations, non-governmental organizations and social group websites during the period from 2003 to 2021.

This study reveals that stakeholders' expectations of zero tolerance for asbestos have not been met. This assertion has been backed by evidence of asbestos contamination in imported building materials throughout recent years. Stakeholders say that the complete prevention of the importation of ACBMs has been delayed because of issues in policy implementations, opaque supply chain activities, lack of transparency and non-adherence to mandatory and self-regulated guidelines.

Stakeholders expect public and private sector organizations to meet their accountabilities through mandatory adoption of the given policy framework.

This research provides a road map to identify the multiple accountabilities, their related weaknesses and the lack of implementation of the necessary protocol, which prevents a critical aspect of legislation from being effectively implemented.

This study aims to investigate whether frugality increases customer complaints via the mediating role of the zone of tolerance (ZOT) of quality for Shanzhai products. Additionally, the study seeks to explore how customer empathy as a boundary condition affects the relationship between the ZOT of quality and customer complaints.

Based on the purchasing data of 241 low-income customers from business-to-consumer (B2C) e-commerce and social platforms in China, hierarchical analysis was conducted in the study. Moreover, “PROCESS SPSS Macro” was used to test the mediation effect of the ZOT of quality and the moderated mediation effect with customer empathy as a moderator.

The results indicate a positive impact of frugality on customer complaints, which is mediated by the ZOT of quality. Moreover, with an increase in customer empathy, the negative effect of the ZOT of quality on customer complaints increases, and the positive influence of frugality on customer complaints, through the mediation of the ZOT of quality, also becomes stronger.

Drawing upon the principle of cognitive consistency, this study not only extends the stream of research on frugality by exploring how frugality influences customer complaints via the mediation of the ZOT of quality but also sheds new light on the research on customer empathy by exploring its moderating role in the relationship between the ZOT of quality and customer complaints.

This paper contributes insights into how different firm types in the emerging market (EM) of Turkey respond to upgrading pressures in terms of internationalization and the usage of domestic political support. It seeks to highlight how the usage of and the responses to different strategies, connections and policy instruments vary with firm types.

Binary logistic regression analysis is used to differentiate and identify characteristics of firms regarding market-seeking strategies and their usage of institutional and financial support. The analysis is based on survey data from firms located in the metro-region of Istanbul: advanced market multinational enterprises (AMNEs), Turkish MNEs (TMNEs) and domestic Turkish firms (DTFs).

Different types of firms within the population of innovative firms in the EM setting of Turkey show significant variety regarding the usage of and the responses to key factors affecting internationalization. AMNEs particularly benefit from investment and export incentives as well as from establishing political connections in Turkey. DTFs significantly use tax incentives and primarily seek advanced markets. TMNEs particularly benefit from investment and export incentives and prefer to target advanced markets.

Using Turkey as a single-country setting is a limitation to the generalizability of the results. Future studies could use more cases of AMNEs to compare different countries of origin. In addition, the intended focus on R&D-related firms produces specific outcomes for such companies.

National and regional policies need to pursue different strategies for the surveyed groups of firms to attract and maintain foreign direct investments (FDIs) of AMNEs as well as to support outward FDIs of domestic firms and EM MNEs. In particular, policies for market entries and knowledge sourcing in advanced markets are becoming a crucial factor for EM firms in overcoming a shortage of resources at home.

This paper’s findings challenge existing theories such as the concept of psychic distance or liabilities of foreignness, which do not always provide an adequate explanation for internationalization activities of EM firms. In addition, it is highly relevant to apply an eclectic or multidimensional concept when conducting research in EMs in order to capture the interrelated constructs of upgrading, internationalization and political support.

The electromechanical brake system is leading the latest development trend in railway braking technology. The tolerance stack-up generated during the assembly and production process catalyzes the slight geometric dimensioning and tolerancing between the motor stator and rotor inside the electromechanical cylinder. The tolerance leads to imprecise brake control, so it is necessary to diagnose the fault of the motor in the fully assembled electromechanical brake system. This paper aims to present improved variational mode decomposition (VMD) algorithm, which endeavors to elucidate and push the boundaries of mechanical synchronicity problems within the realm of the electromechanical brake system.

The VMD algorithm plays a pivotal role in the preliminary phase, employing mode decomposition techniques to decompose the motor speed signals. Afterward, the error energy algorithm precision is utilized to extract abnormal features, leveraging the practical intrinsic mode functions, eliminating extraneous noise and enhancing the signal’s fidelity. This refined signal then becomes the basis for fault analysis. In the analytical step, the cepstrum is employed to calculate the formant and envelope of the reconstructed signal. By scrutinizing the formant and envelope, the fault point within the electromechanical brake system is precisely identified, contributing to a sophisticated and accurate fault diagnosis.

This paper innovatively uses the VMD algorithm for the modal decomposition of electromechanical brake (EMB) motor speed signals and combines it with the error energy algorithm to achieve abnormal feature extraction. The signal is reconstructed according to the effective intrinsic mode functions (IMFS) component of removing noise, and the formant and envelope are calculated by cepstrum to locate the fault point. Experiments show that the empirical mode decomposition (EMD) algorithm can effectively decompose the original speed signal. After feature extraction, signal enhancement and fault identification, the motor mechanical fault point can be accurately located. This fault diagnosis method is an effective fault diagnosis algorithm suitable for EMB systems.

By using this improved VMD algorithm, the electromechanical brake system can precisely identify the rotational anomaly of the motor. This method can offer an online diagnosis analysis function during operation and contribute to an automated factory inspection strategy while parts are assembled. Compared with the conventional motor diagnosis method, this improved VMD algorithm can eliminate the need for additional acceleration sensors and save hardware costs. Moreover, the accumulation of online detection functions helps improve the reliability of train electromechanical braking systems.

This research is aimed at preparing landslide susceptibility using spatial analysis and soft computing machine learning techniques based on convolutional neural networks (CNNs), artificial neural networks (ANNs) and logistic regression (LR) models.

Using the Geographical Information System (GIS), a spatial database including topographic, hydrologic, geological and landuse data is created for the study area. The data are randomly divided between a training set (70%), a validation (10%) and a test set (20%).

The validation findings demonstrate that the CNN model (has an 89% success rate and an 84% prediction rate). The ANN model (with an 84% success rate and an 81% prediction rate) predicts landslides better than the LR model (with a success rate of 82% and a prediction rate of 79%). In comparison, the CNN proves to be more accurate than the logistic regression and is utilized for final susceptibility.

Land cover data and geological data are limited in largescale, making it challenging to develop accurate and comprehensive susceptibility maps.

It helps to identify areas with a higher likelihood of experiencing landslides. This information is crucial for assessing the risk posed to human lives, infrastructure and properties in these areas. It allows authorities and stakeholders to prioritize risk management efforts and allocate resources more effectively.

The social implications of a landslide susceptibility map are profound, as it provides vital information for disaster preparedness, risk mitigation and landuse planning. Communities can utilize these maps to identify vulnerable areas, implement zoning regulations and develop evacuation plans, ultimately safeguarding lives and property. Additionally, access to such information promotes public awareness and education about landslide risks, fostering a proactive approach to disaster management. However, reliance solely on these maps may also create a false sense of security, necessitating continuous updates and integration with other risk assessment measures to ensure effective disaster resilience strategies are in place.

Landslide susceptibility mapping provides a proactive approach to identifying areas at higher risk of landslides before any significant events occur. Researchers continually explore new data sources, modeling techniques and validation approaches, leading to a better understanding of landslide dynamics and susceptibility factors.

The purpose of this paper is to construct an event-triggered finite-time fault-tolerant formation tracking controller, which can achieve a time-varying formation control for multiple unmanned aerial vehicles (UAVs) during actuator failures and external perturbations.

First, this study developed the formation tracking protocol for each follower using UAV formation members, defining the tracking inaccuracy of the UAV followers’ location. Subsequently, this study designed the multilayer event-triggered controller based on the backstepping method framework within finite time. Then, considering the actuator failures, and added self-adaptive thought for fault-tolerant control within finite time, the event-triggered closed-loop system is subsequently shown to be a finite-time stable system. Furthermore, the Zeno behavior is analyzed to prevent infinite triggering instances within a finite time. Finally, simulations are conducted with external disturbances and actuator failure conditions to demonstrate formation tracking controller performance.

It achieves improved performance in the presence of external disturbances and system failures. Combining limited-time adaptive control and event triggering improves system stability, increase robustness to disturbances and calculation efficiency. In addition, the designed formation tracking controller can effectively control the time-varying formation of the leader and followers to complete the task, and by adding a fixed-time observer, it can effectively compensate for external disturbances and improve formation control accuracy.

A formation-following controller is designed, which can handle both external disturbances and internal actuator failures during formation flight, and the proposed method can be applied to a variety of formation control scenarios and does not rely on a specific type of UAV or communication network.

Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.

Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.

Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.

Other optimization techniques can be applied for WSN to analyze the performance.

Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.

Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.

Literature survey is carried out to find the methods which give better performance.