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The purpose of this study was to provide an outline of the process of developing an on-road driving test route and rating form. Comprehensive evaluation of medical fitness to drive should comprise of an off-road and an on-road assessment. Much research attention has focussed on the off-road phase of assessment, while there is less standardisation evident in the completion and measurement of the on-road phase of fitness-to-drive assessment.

A scholarship of practice approach was used to inform the development of an on-road test route and an associated generic on-road assessment tool that was guided by research evidence and best practice recommendations.

A step-by-step guide, outlining seven recommended phases in the development of an on-road route for the assessment of fitness to drive that aligns with best practice recommendations, was developed. A preliminary generic on-road assessment tool (the Maynooth–Trinity Driving Test) that includes higher-order cognition alongside element of strategic, tactical and operational driving ability was developed and piloted alongside the newly developed on-road test route.

This paper offers an overview of an approach to developing evidence-based on-road test routes and an associated generic assessment tool that may assist occupational therapists and on-road driving assessors establish a standard practice for testing on-road behaviour as part of a comprehensive approach to evaluate fitness to drive.

The purpose of this study is to formulate an algorithm designed to discern the optimal routes for efficient municipal solid waste (MSW) collection.

The research method is simulation. The proposed algorithm combines heuristics derived from the constructive genetic algorithm (CGA) and tabu search (TS). The algorithm is applied in a municipality located at Southern Brazil, with 40,000 inhabitants, circa.

The implementation achieved a remarkable 25.44% reduction in daily mileage of the vehicles, resulting in savings of 150.80 km/month and 1,809.60 km/year. Additionally, it reduced greenhouse gas emissions (including fossil CO₂, CH₄, N₂O, total CO₂e and biogenic CO₂) by an average of 26.15%. Moreover, it saved 39 min of daily working time.

Further research should thoroughly analyze the feasibility of decision-making regarding planning, scheduling and scaling municipal services using digital technology.

The municipality now has a tool to improve public management, mainly related with municipal solid waste. The municipality reduced the cost of public management of municipal solid waste, redirecting funds to other priorities, such as public health and education.

The study integrates MSW collection service with an online platform based on Google MapsTM. The advantages of employing geographical information systems are agility, low cost, adaptation to changes and accuracy.

The internet of vehicles (IoV) communication has recently become a popular research topic in the automotive industry. The growth in the automotive sector has resulted in significant standards and guidelines that have engaged various researchers and companies. In IoV, routing protocols play a significant role in enhancing communication safety for the transportation system. The high mobility of nodes in IoV and inconsistent network coverage in different areas make routing challenging. This paper aims to provide a lane-based advanced forwarding protocol for internet of vehicles (LAFP-IoV) for efficient data distribution in IoV. The proposed protocol’s main feature is that it can identify the destination zone by using position coordinates and broadcasting the packets toward the direction of destination. The novel suppression technique is used in the broadcast method to reduce the network routing overhead.

The proposed protocol considers the interferences between different road segments, and a novel lane-based forwarding model is presented. The greedy forwarding notion, the broadcasting mechanism, and the suppression approach are used in this protocol to reduce the overhead generated by standard beacon forwarding procedures. The SUMO tool and NS-2 simulator are used for the vehicle's movement pattern and to simulate LAFP-IoV.

The simulation results show that the proposed LAFP-IoV protocol performs better than its peer protocols. It uses a greedy method for forwarding data packets and a carry-and-forward strategy to recover from the local maximum stage. This protocol's low latency and good PDR make it ideal for congested networks.

The proposed paper provides a unique lane-based forwarding for IoV. The proposed work achieves a higher delivery ratio than its peer protocols. The proposed protocol considers the lanes while forwarding the data packets applicable to the highly dense scenarios.

This study aims to analyzed the development of open innovation research knowledge and its application in the tourism sector during the past 17 years, with the aim of understanding the scientific activity and impact of existing research. In addition, this research identifies trending thematic lines and provides recommendations for future research on this topic.

A bibliometric analysis was carried out from the Scopus database, in which 110 studies related to open innovation in tourism were identified. The analysis of the papers was done with the Bibliometrix and Vosviewer tools.

The results show that there is a recent and growing interest among academics, especially since 2017. Moreover, four main lines of work were identified: overtourism and sustainability, value cocreation, open innovation and competitive advantage and its impact on organizations belonging to the hotel sector and the relationship between external knowledge and internal sources in innovation management and open innovation performance.

The relationship with other stakeholders involved in the customer experience value creation in the tourism sector depends to a large extent on the joint offer that hotels, restaurants, tour operators and tourist offices, can provide in a tourist destination. Therefore, having external sources to innovate from will improve their innovative and organizational performance. However, there are no bibliometric analyses on the application of the open innovation paradigm in this sector. Thus, this research contributes to fill this gap, as well as to identify the most recurrent themes that show how open innovation is developing in tourism, providing academics and researchers with guidelines for future research.

A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.

First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real time. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time.

Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first (OSPF) routing methods.

Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds, coupled with the shortcomings of traditional interdomain routing methods, such as cumbersome configuration and inflexible acquisition of network state information. These drawbacks make it difficult to obtain global state information about the network, and the optimal routing decision cannot be made in real time, affecting network performance. This paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL method. First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to realize the real-time acquisition of global network state information. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a prediction mechanism for the network traffic state is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time. Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and OSPF routing methods.

Recently, electric vehicles have been widely used in the cold chain logistics sector to reduce the effects of excessive energy consumption and to support environmental friendliness. Considering the limited battery capacity of electric vehicles, it is vital to optimize battery charging during the distribution process.

This study establishes an electric vehicle routing model for cold chain logistics with charging stations, which will integrate multiple distribution centers to achieve sustainable logistics. The suggested optimization model aimed at minimizing the overall cost of cold chain logistics, which incorporates fixed, damage, refrigeration, penalty, queuing, energy and carbon emission costs. In addition, the proposed model takes into accounts factors such as time-varying speed, time-varying electricity price, energy consumption and queuing at the charging station. In the proposed model, a hybrid crow search algorithm (CSA), which combines opposition-based learning (OBL) and taboo search (TS), is developed for optimization purposes. To evaluate the model, algorithms and model experiments are conducted based on a real case in Chongqing, China.

The result of algorithm experiments illustrate that hybrid CSA is effective in terms of both solution quality and speed compared to genetic algorithm (GA) and particle swarm optimization (PSO). In addition, the model experiments highlight the benefits of joint distribution over individual distribution in reducing costs and carbon emissions.

The optimization model of cold chain logistics routes based on electric vehicles provides a reference for managers to develop distribution plans, which contributes to the development of sustainable logistics.

In prior studies, many scholars have conducted related research on the subject of cold chain logistics vehicle routing problems and electric vehicle routing problems separately, but few have merged the above two subjects. In response, this study innovatively designs an electric vehicle routing model for cold chain logistics with consideration of time-varying speeds, time-varying electricity prices, energy consumption and queues at charging stations to make it consistent with the real world.

In a wireless sensor network (WSN), the sensor nodes are distributed in the network, and in general, they are linked through wireless intermediate to assemble physical data. The nodes drop their energy after a specific duration because they are battery-powered, which also reduces network lifetime. In addition, the routing process and cluster head (CH) selection process is the most significant one in WSN. Enhancing network lifetime through balancing path reliability is more challenging in WSN. This paper aims to devise a multihop routing technique with developed IIWEHO technique.

In this method, WSN nodes are simulated originally, and it is fed to the clustering process. Meanwhile, the CH is selected with low energy-based adaptive clustering model with hierarchy (LEACH) model. After CH selection, multipath routing is performed by developed improved invasive weed-based elephant herd optimization (IIWEHO) algorithm. In addition, the multipath routing is selected based on certain fitness functions like delay, energy, link quality and distance. However, the developed IIWEHO technique is the combination of IIWO method and EHO algorithm.

The performance of developed optimization method is estimated with different metrics, like distance, energy, delay and throughput and achieved improved performance for the proposed method.

This paper presents an effectual multihop routing method, named IIWEHO technique in WSN. The developed IIWEHO algorithm is newly devised by incorporating EHO and IIWO approaches. The fitness measures, which include intra- and inter-distance, delay, link quality, delay and consumption of energy, are considered in this model. The proposed model simulates the WSN nodes, and CH selection is done by the LEACH protocol. The suitable CH is chosen for transmitting data through base station from the source to destination. Here, the routing system is devised by a developed optimization technique. The selection of multipath routing is carried out using the developed IIWEHO technique. The developed optimization approach selects the multipath depending on various multi-objective functions.

Heritage landmarks and historical values often coexist with places and regions of remarkable environmental and landscape wealth. This article studies their capacity to generate global understanding of their territory through the creation of cultural routes. The proposed methodology is verified through the study of the defensive features of the ancient Nasrid Kingdom, the last Islamic territory in the Iberian Peninsula from the thirteenth to the fifteenth century, which shaped the Spanish region known as the Kingdom of Granada until the nineteenth century.

To assist in the proposal of new routes, a precise collection of physical data (topography, landmarks, resources, population centres …), existing public paths and protected natural sites was carried out. Those cultural routes relevant to the area of study were also selected and mapped through GIS. A set of indicators prioritised through an analytic hierarchy process (AHP) have evaluated the proposed itineraries.

The methodology enables the integral evaluation of parameters such as natural heritage, existing paths networks, defensive architectural heritage (watchtowers), existing cultural routes or proximity to basic services. The methodology's application allows an index to be obtained that quantifies the global implications of these parameters in the design of new itineraries. This leads to the development of a network with its own narrative that provides a historical, environmental and cultural meaning.

Watchtowers in this region have previously been studied as isolated and locally relevant architectural features. This work studies them from an overall perspective, considering each tower as a piece of a complex defensive and territorial system. Cultural routes arise from this joint interpretation as tools to restore and highlight the interrelationship between architectural heritage and territory and people.

The purpose of this paper is to conduct a comprehensive study on building, fire and evacuation, so as to effectively improve the efficiency of building fire evacuation and the management level of fire evacuation site. Make up for the difficulties of BIM technology in effectively connecting building information and fire data.

First, this paper establishes a fire model and an evacuation model based on BIM information. Then, the safety index (SI) is introduced as a comprehensive index, and the IRI is established by integrating the SI function to evaluate the safety of evacuation routes. Based on these two indices, the IRI-based fire evacuation model is established.

This study offers an Improved Risk Index (IRI)-based fire evacuation model, which may achieve effective evacuation in fire scenes. And the model is verified by taking the fire evacuation of a shopping center building as an example.

This paper proposes a fire evacuation principle based on IRI, so that the relevant personnel can comprehensively consider the fire factors and evacuation factors to achieve the optimization of building design, thereby improving the fire safety of buildings.

The study aims to understand how cultural route heritage is conceptualized and managed in China by systematically reviewing the research literature on Chinese cultural route heritage (CRH). The study intends to inspire further discussion on the theoretical and practical development of cultural routes since the development is still at a liminal stage in China.

A total of 253 research articles related to Chinese cultural rote heritage from major Chinese and English research databases China National Knowledge Infrastructure (CNKI), Web of Science (WOS) and Scopus have been comprehensively identified and reviewed for the purpose of the study.

Four major themes of research on Chinese CRH have been identified: conceptual evaluation, list of the routes and characteristics of the routes, conservation and utilization. The results revealed that China has very rich resources in CRH, many of which were formed a long time ago, which exist across vast geographic regions and have assumed multiple functions and undergone dynamic reciprocal exchanges among diverse cultures and ethnicities.

The paper summarizes some major obstacles faced by CRH in China and proposes a strategic model to address the need for a more sustainable development of CRH in the Chinese context.

The paper offers a comprehensive overview of CRH in China and discusses practical issues in management and development of heritage great in size, number and complexity.