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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.

This paper explores optimal service resource management strategy, a continuous challenge for health information service to enhance service performance, optimise service resource utilisation and deliver interactive health information service.

An adaptive optimal service resource management strategy was developed considering a value co-creation model in health information service with a focus on collaborative and interactive with users. The deep reinforcement learning algorithm was embedded in the Internet of Things (IoT)-based health information service system (I-HISS) to allocate service resources by controlling service provision and service adaptation based on user engagement behaviour. The simulation experiments were conducted to evaluate the significance of the proposed algorithm under different user reactions to the health information service.

The results indicate that the proposed service resource management strategy, considering user co-creation in the service delivery, process improved both the service provider’s business revenue and users' individual benefits.

The findings may facilitate the design and implementation of health information services that can achieve a high user service experience with low service operation costs.

This study is amongst the first to propose a service resource management model in I-HISS, considering the value co-creation of the user in the service-dominant logic. The novel artificial intelligence algorithm is developed using the deep reinforcement learning method to learn the adaptive service resource management strategy. The results emphasise user engagement in the health information service process.

The purpose of this study is to designed a robot odometry based on three dimensional (3D) laser point cloud data, inertial measurement unit (IMU) data and real-time kinematic (RTK) data in underground spatial features and gravity fluctuations environment. This method improves the mapping accuracy in two types of underground space: multi-layer space and large-scale scenarios.

An IMU–Laser–RTK fusion mapping algorithm based on Iterative Kalman Filter was proposed, and the observation equation and Jacobian matrix were derived. Aiming at the problem of inaccurate gravity estimation, the optimization of gravity is transformed into the optimization of SO(3), which avoids the problem of gravity over-parameterization.

Compared with the optimization method, the computational cost is reduced. Without relying on the wheel speed odometer, the robot synchronization localization and 3D environment modeling for multi-layer space are realized. The performance of the proposed algorithm is tested and compared in two types of underground space, and the robustness and accuracy in multi-layer space and large-scale scenarios are verified. The results show that the root mean square error of the proposed algorithm is 0.061 m, which achieves higher accuracy than other algorithms.

Based on the problem of large loop and low feature scale, this algorithm can better complete the map loop and self-positioning, and its root mean square error is more than double compared with other methods. The method proposed in this paper can better complete the autonomous positioning of the robot in the underground space with hierarchical feature degradation, and at the same time, an accurate 3D map can be constructed for subsequent research.

This study employs Stein Rokkan's methodological approach to analyse state formation in the Greater Middle East. It develops a conceptual framework distinguishing colonial, populist and democratic pacts, suitable for analysis of state formation and nation-building through to the present period. The framework relies on historical institutionalism. The methodology, however, is Rokkan's. The initial conceptual analysis also specifies differences between European and the Middle Eastern state formation processes. It is followed by a brief and selective discussion of historical preconditions. Next, the method of plotting singular cases into conceptual-typological maps is applied to 20 cases in the Greater Middle East (including Afghanistan, Iran and Turkey). For reasons of space, the empirical analysis is limited to the colonial period (1870s to the end of World War 1). Three typologies are combined into one conceptual-typological map of this period. The vertical left-hand axis provides a composite typology that clarifies cultural-territorial preconditions. The horizontal axis specifies transformations of the region's agrarian class structures since the mid-19th century reforms. The right-hand vertical axis provides a four-layered typology of processes of external intervention. A final section presents selected comparative case reconstructions. To the authors' knowledge, this is the first time such a Rokkan-style conceptual-typological map has been constructed for a non-European region.

This study defines and critically analyzes Korean high modernism using the Sewoon Sangga project as a case study, as it has significant value in Korea's urban and architectural history.

The methodology applied for this study was a theory-interpretive analysis. This study examines the modernization process of Seoul based on the concept of “high modernism,” in that the theory-interpretive analysis method analyzes historical phenomena centered on a specific concept.

As a form of national belief, the various ideas that give birth to modern cities are defined as “high modernism.” As a Korean megastructure, the Sewoon Sangga project is significant in the history of Korean urbanism and architecture because it is the archetype of Korean high modernism and is representative of South Korea's compressed economic growth. However, soon-to-be-demolished Sewoon Sangga signifies the failure of Korean high modernism. This study identified the critical characteristics of Korean high modernism through the Sewoon Sangga project.

This study analyzed a representative Asian city through the specific concept of high modernism. It transpired that high modernism, which played an important role in the birth and development of modern cities, should be transformed for future cities and architectural development. This study has significance in that it expands the study of the history of urbanism and architecture centered on the West to the same in Asia.

This study aims to illustrate the potential of coworking spaces as one way to achieve optimal workplace arrangements and corporate real estate (CRE) agility, especially for large organizations. The authors suggest understanding coworking spaces from the boundary organization theory and organizational growth model.

This study takes a threefold theoretical approach: conducting a literature review and identifying the gaps in coworking studies for large organizations, applying the organizational boundary theory in tandem with organizational growth models in the context of coworking spaces as a part of the workplace ecology and identifying future research agendas for coworking studies.

This study proposes a conceptual framework of how coworking spaces can be viewed and used as a boundary object throughout the organizational growth phases. Besides, four major future research areas are proposed: case studies and/or empirical evidence of coworking spaces as CRE buffer zones and boundary objects for organizations, coworking space design and different formats of boundary object-infused collaboration, coworking space design and management for its own agility and flexibility and how coworking affects employees’ performance, health and well-being and professional training/mentoring.

For large organizations, there is a clear pressure to rethink CRE to increase workplace agility, flexibility and resilience, much accelerated with the recent COVID-19 pandemic. Understanding the effective use of coworking spaces as a part of CRE portfolios will help enhance corporates’ state and ability to reassess, realign and replan their CRE portfolios.

Many existing studies about coworking spaces are based on observations and self-reported justification at an individual level. Whether and how coworking can benefit companies at an organizational level is largely unstudied and worth more attention. This study illustrates a new theoretical understanding of how coworking spaces can be a part of CRE portfolios and bring potential benefits of inter and intraorganizational collaboration throughout the phases of organizational growth.

The most important need after natural disasters is the sheltering. However, most of the existing temporary shelters do not meet all requirements for long-term use and not provide adequate flexibility within the space. This paper aims to develop a transitional postdisaster shelter transforming from a closed shape to an expanded form in response to changing functional and spatial needs of disaster victims. The study also proposes alternative unit combinations for various functions, and settlement layouts to create a comfortable living environment for occupants.

The research methodology is based on theoretical and design frameworks which requires inductive and deductive approaches. Forming the background of the study, the theoretical framework consists of four parts which are literature review on temporary shelters presenting state-of-the-art; determination of design guidelines and strategies based on shelter standards; identification of technical requirements; and analysis of existing temporary shelters. Having three parts, the design framework includes design of transformable transitional shelter based on three-dimensional modeling, creation of different unit combinations to be used for various purposes and development of settlement layouts as case studies.

The analysis conducted in this study demonstrates that most of the existing temporary shelters have limited geometric configurations and major problems in terms of their performance, transportation and storage. On the other hand, the transformable shelter proposed by the authors can provide form and spatial flexibilities thanks to its expansion properties, occupy less space for transportation, easily be transported to any desired location in its compact state and be customized according to user needs. Several units can be combined either to serve larger families or to be used for different functions.

This paper contributes to the literature as presenting not only a theoretical framework on temporary shelters but also a design framework on transformable shelter design for the ones who are willing to develop similar transformable shelters based on the determined guidelines, strategies and requirements.

This exploratory paper aims to examine attitudes and practices with regard to the COVID-19 pandemic, as well as the effects of mandatory teleworking from home in the wake of the first state of emergency orders in Japan in 2020.

An online survey of married employees retrospectively assessed changes in work style, subjective well-being, work–family conflict and job performance before and during forced teleworking from home in Tokyo and three of the surrounding prefectures.

Regular employees reported high levels of anxiety and to have thoroughly implemented government-recommended hygiene and safety practices. A majority of respondents were satisfied with mandatory telework from home and desired to continue partial telework after the end of the pandemic. The strongest predictor of satisfaction with mandatory telework from home turned out to be adequate workspace at home for both men and women. However, the antecedents of the desire to continue working from home differed by gender.

These findings can help individuals, firms and governments better understand the effects of mandatory teleworking from home and devise countermeasures to maximize employee well-being and job performance. This is all the more crucial, as Japan has had successive waves of the virus and has declared numerous states of emergency since the beginning of the pandemic, forcing office workers to continue social distancing and remote working for the time being.

To the best of the authors’ knowledge, this research is one of the first to provide insights on how imposed teleworking from home in the context of COVID-19 in Japan affected regular employees’ personal and professional lives and to identify predictors of satisfaction with teleworking and the desire to continue doing so.