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The duration of an urban search and rescue (USAR) operation directly depends on the number of rescue teams involved. The purpose of this paper is to simplify the earthquake environment and determine the initial number of rescuers in earthquake emergencies in USAR operation.

In the proposed methodology, four primary steps were considered: evaluation of buildings damage and the number of injured people by exerting geospatial information system (GIS) analyses; determining service time by means of task allocation; designing the simulation model (queuing theory); and calculation of survival rate and comparison with the time of rescue operations.

The calculation of buildings damage for an earthquake with 6.6 Richter in Tehran’s District One indicated that 18% of buildings are subjected to the high damage risk. The number of injured people calculated was 28,856. According to the calculated survival rate, rescue operations in the region must be completed within 22.33 h to save 75% of the casualties. Finally, the design of the queue model indicated that at least 2,300 rescue teams were required to provide the calculated survival rate.

The originality of this paper is an innovative approach for determining an appropriate number of rescue teams by considering the queuing theory. The results showed that the integration of GIS and the simulation of queuing theory could be a helpful tool in natural disaster management, especially in terms of rapid vulnerability assessment in urban districts, the adequacy and appropriateness of the emergency services.

The purpose of this paper is to give an account for preparative collaboration between the police and municipal eldercare in Sweden concerning missing persons with dementia.

Design/methodology/approach used was a qualitative case study design, consisting of one focus group with representatives for the participating organisations, followed by directed content analysis.

The findings showed a lack of current collaboration and reluctance to new collaborative initiatives. However, when focussing on preparative collaboration of coordinated responses to missing incidents, possibilities for improvement could be identified. The improvements concerned updated personnel response checklists, along with suggestions for an elaborate life story document in eldercare, with police access. Finally, better coordination of the return of the found person and a follow up were proposed.

It is suggested that collaboration must be given different meanings and use different approaches adapted to the different phases in a rescue operation. In the preparation and the response phase, the focus should be on coordination of the resources available. In the pre-planning and prevention phases, as well as in evaluation and learning, horizontal collaboration is more suitable. The amount of data in this study is a research limitation which calls for further research.

It is suggested that collaboration must be given different meanings and use different approaches adapted to the different phases in a rescue operation. In the preparation and the response phase, the focus should be on coordination of the resources available. In the pre-planning and prevention phases, as well as in evaluation and learning, horizontal co-operation is more suitable.

The originality/value of this paper can be found in the novelty of missing person research in Sweden, and in practical suggestions for preparative collaboration concerning persons with dementia who go missing. Finally, it can be found in the suggested need for a more dynamic and process-sensitive view of collaboration in SAR or rescue operations.

Drones have become an important element within hospitality and tourism. The purpose of this study is to identify the corpus of knowledge and create a research agenda that establishes appropriate guidelines for future study of drone application in hospitality and tourism.

This work has been undertaken using a mixed-methods approach that combines quantitative and qualitative research and includes a review of the literature related to the study of drone use in hospitality and tourism.

The mixed-methods review identified gaps in the research, potential areas of study to enhance the scientific literature and potential uses of drones in tourism and hospitality for researchers, consumers and industry professionals.

This study makes an original contribution by establishing an integrated framework, which led to a synthesis of the research corpus and provided a holistic conceptualisation of the relationship between tourism and drones. In addition, the research agenda proposed will help boost and consolidate this emerging field of research.

无人机已经成为接待和旅游中的一个重要元素。本研究的主要目的是确定知识库, 并建立一个研究议程, 为未来无人机在酒店和旅游业的应用研究建立适当的指导方针。

这项工作采用了混合方法, 将定量和定性研究结合起来, 包括对与酒店和旅游业中无人机使用研究有关的文献进行回顾。

混合方法审查确定了研究中的差距、加强科学文献的潜在研究领域, 以及研究人员、消费者和行业专业人士在旅游和酒店业的无人机应用潜力。

这项研究通过建立一个综合框架做出了原创性的贡献, 它综合合成了研究语料库, 并对旅游和无人机之间的关系提供了一个整体的概念化。此外, 提出的研究议程将有助于促进和巩固这一新兴的研究领域。

Los drones se han convertido en un elemento importante dentro de la hostelería y el turismo. El objetivo principal de este estudio es identificar el corpus de conocimiento y crear una agenda de investigación que establezca las directrices adecuadas para el estudio futuro de la aplicación de los drones en la hostelería y el turismo.

Este trabajo se ha realizado utilizando un enfoque de métodos mixtos que combina la investigación cuantitativa y cualitativa e incluye una revisión de la literatura relacionada con el estudio del uso de drones en hostelería y turismo.

La revisión de métodos mixtos identificó lagunas en la investigación, áreas potenciales de estudio para mejorar la literatura científica y potencial de las aplicaciones de los drones en el turismo y la hostelería para investigadores, consumidores y profesionales del sector.

Este estudio aporta una contribución original al establecer un marco integrado, que conduce a una síntesis del corpus de investigación y proporciona una conceptualización holística de la relación entre el turismo y los drones. Además, la agenda de investigación propuesta contribuirá a impulsar y consolidar este campo de investigación emergente.

This paper investigates how agile capabilities in humanitarian settings work in combination, and its effects on performance outcome. The study was conducted in the frame of reference of response operations during cyclones and floods, which is considered most complex and with the most widespread impact.

A survey-based method was used to collect empirical data on response operations from 131 field officers who were involved in disaster response during cyclones or floods. A partial least square based structural equation model was used to study the path model of interaction of agile capabilities, and their effect on performance outcomes.

The results show that integration of agile capabilities is important for enhancing effectiveness of humanitarian response. The results indicated a serial mediation effect involving visibility, responsiveness and flexibility capability on the effectiveness of emergency response.

This research has implications for response units of humanitarian organisations. This includes capacity building for key agile capabilities, integration, supply chain re-configuration and differential positioning of response phase as against preparedness and recovery phases.

This study is unique for the chosen humanitarian setting, which is considered most difficult. The authors demonstrate from empirical evidence the interaction effects of agile capabilities during response phase for cyclones and floods, and their impact. The research insights will help practitioners to configure and position supply chains for better effectiveness during response operations, which have markedly different objectives vis-à-vis other phases or types of humanitarian settings.

This paper aims to focus on solving the path optimization problem by modifying the probabilistic roadmap (PRM) technique as it suffers from the selection of the optimal number of nodes and deploy in free space for reliable trajectory planning.

Traditional PRM is modified by developing a decision-making strategy for the selection of optimal nodes w.r.t. the complexity of the environment and deploying the optimal number of nodes outside the closed segment. Subsequently, the generated trajectory is made smoother by implementing the modified Bezier curve technique, which selects an optimal number of control points near the sharp turns for the reliable convergence of the trajectory that reduces the sum of the robot’s turning angles.

The proposed technique is compared with state-of-the-art techniques that show the reduction of computational load by 12.46%, the number of sharp turns by 100%, the number of collisions by 100% and increase the velocity parameter by 19.91%.

The proposed adaptive technique provides a better solution for autonomous navigation of unmanned ground vehicles, transportation, warehouse applications, etc.

To generate electricity, solar photovoltaic (PV) systems are among the best, most eco-friendly and most cost-effective solutions available. Extraction of maximum possible electricity from the solar PV system is complicated by a number of factors brought on by the ever-changing weather conditions under which it must operate. Many conventional and evolutionary algorithm-based maximum power point tracking (MPPT) techniques have the limitation of not being able to extract maximum power under partial shade and rapidly varying irradiance. Hence, the purpose of this paper is to propose a novel hybrid slime mould assisted with perturb and observe (P&O) global MPPT technique (HSMO) for the hybrid bridge link-honey comb (BL-HC) configured PV system to enhance the better maximum power during dynamic and steady state operations within less time.

In this method, a hybridization of two algorithms is proposed to track the true with faster convergence under PSCs. Initially, the slime mould optimization (SMO) algorithm is initiated for exploration of optimum duty cycles and later P&O algorithm is initiated for exploitation of global duty cycle for the DC–DC converter to operate at GMPP and for fast convergence.

The effectiveness of the proposed HSMO MPPT is compared with adaptive coefficient particle swarm optimization (ACPSO), flower pollination algorithm and SMO MPPT techniques in terms of tracked GMPP, convergence time/tracking speed and efficacy under six complex partial shading conditions. From the results, it is noticed that the proposed algorithm tracks the true GMPP under most of the shading conditions with less tracking time when compared to other MPPT techniques.

This paper proposes a novel hybrid slime mould assisted with perturb and observe (P&O) global MPPT technique (HSMO) for the hybrid BL-HC configured PV system enhance the better maximum power under partial shading conditions (PSCs). This method operated in two stages as SMO for exploration and P&O for exploitation for faster convergence and to track true GMPP under PSCs. The proposed approach largely improves the performance of the MPP tracking of the PV systems. Initially, the proposed MPPT technique is simulated in MATLAB/Simulink environment. Furthermore, an experimental setup has been designed and implemented. Simulation results obtained are validated through experimental results which prove the viability of the proposed technique for an efficient green energy solution.

The purpose of this study is to identify LGBTQ+ perceptions of and experiences with hazards, vulnerabilities and disasters in the San Francisco Bay Area in the USA and to co-develop applied projects to “queer” disaster knowledge production and risk reduction activities in the region.

This is a community science project in which we collaborate with community members to enhance both community and scientific knowledge with the goal of utilizing it to produce a positive change to pressing social issues and their underlying causes. We do this through a series of four focus group workshops to identify community priorities, hazards, vulnerabilities and local action. We follow this with further ethnographic research and projects to apply findings from phase one.

The authors have found that: LGBTQ+ people in the Bay Area have unique experiences with hazards, vulnerabilities and disasters; there are significant gaps in the representation of LGBTQ+ hazard exposure in local scientific models that we can address through alternative methodologies; and tabletop exercises, learning modules and podcasts help orient and train disaster response agencies and personnel on LGBTQ+ inclusive operations.

This initiative entails novel approaches to community science for disaster risk reduction and creative collaboration with community-based organizations to foster the development of LGBTQ+ inclusive disaster risk reduction and response.

The purpose of this paper is to provide a detailed insight into the global military robot industry with an emphasis on products and their applications.

Following an introduction which includes a brief historical account, this provides an industry overview, including various market dimensions and a discussion of the geopolitical and technological factors driving market development. The three following sections provide details of land, airborne and marine robots, their capabilities and deployments in recent conflicts. Finally, brief conclusions are drawn.

Military robots which operate on land, in the air and at sea constitute a multi-billion dollar industry which is growing rapidly. It is being driven by geopolitical tensions, notably the military-technology arms race between China and the USA and the conflict in Ukraine, together with technological progress, particularly in AI. Many robots possess multi-functional capabilities, and the leading application is presently intelligence, surveillance and reconnaissance. An increasing number of heavily armed robots are being developed, and AI has the potential to impart these with the capacity to deliver lethal force without human intervention. Although heavily criticised in some quarters, this capability has probably already been deployed on the battlefield. With ever-growing military budgets, escalating political tensions and technological innovations, robots will play an increasingly significant role in future conflicts.

This provides a detail account of military robots and their role in modern warfare.

This study aims to present a type of metamorphic mechanism-based quadruped crawling robot. The trunk design of the robot has a metamorphic mechanism, which endows it with excellent crawling capability and adaptability in challenging environments.

The robot consists of a metamorphic trunk and four series-connected three-joint legs. First, the walking and steering strategy is planned through the stability and mechanics analysis. Then, the walking and steering performance is examined using virtual prototype technology, as well as the efficacy of the walking and turning strategy.

The metamorphic quadruped crawling robot has wider application due to its variable trunk configuration and excellent leg motion space. The robot can move in two modes (constant trunk and trunk configuration transformation, respectively, while walking and rotating), which exhibits outstanding stability and adaptability in the examination and verification of prototypes.

The design can enhance the capacity of the quadruped crawling robot to move across a complex environment. The virtual prototype technology verifies that the proposed walking and steering strategy has good maneuverability and stability, which considerably expands the application opportunity in the fields of complicated scene identification and investigation.

To solve the obstacle detection problem in robot autonomous obstacle negotiation, this paper aims to propose an obstacle detection system based on elevation maps for three types of obstacles: positive obstacles, negative obstacles and trench obstacles.

The system framework includes mapping, ground segmentation, obstacle clustering and obstacle recognition. The positive obstacle detection is realized by calculating its minimum rectangle bounding boxes, which includes convex hull calculation, minimum area rectangle calculation and bounding box generation. The detection of negative obstacles and trench obstacles is implemented on the basis of information absence in the map, including obstacles discovery method and type confirmation method.

The obstacle detection system has been thoroughly tested in various environments. In the outdoor experiment, with an average speed of 22.2 ms, the system successfully detected obstacles with a 95% success rate, indicating the effectiveness of the detection algorithm. Moreover, the system’s error range for obstacle detection falls between 4% and 6.6%, meeting the necessary requirements for obstacle negotiation in the next stage.

This paper studies how to solve the obstacle detection problem when the robot obstacle negotiation.