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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 aims to propose a precise turbulence model for automobile aerodynamics simulation, which can predict flow separation and reattachment phenomena more accurately.

As the results of wake flow simulation with commonly used turbulence models are unsatisfactory, by introducing a nonlinear Reynolds stress term and combining the detached Eddy simulation (DES) model, this paper proposes a nonlinear-low-Reynolds number (LRN)/DES turbulence model. The turbulence model is verified in a backward-facing step case and applied in the flow field analysis of the Ahmed model. Several widely applied turbulence models are compared with the nonlinear-LRN/DES model and the experimental data of the above cases.

Compared with the experimental data and several turbulence models, the nonlinear-LRN/DES model gives better agreement with the experiment and can predict the automobile wake flow structures and aerodynamic characteristics more accurately.

The nonlinear-LRN/DES model proposed in this paper suffers from separation delays when simulating the separation flows above the rear slant of the Ahmed body. Therefore, more factors need to be considered to further improve the accuracy of the model.

This paper proposes a turbulence model that can more accurately simulate the wake flow field structure of automobiles, which is valuable for improving the calculation accuracy of the aerodynamic characteristics of automobiles.

Based on the nonlinear eddy viscosity method and the scale resolved simulation, a nonlinear-LRN/DES turbulence model including the nonlinear Reynolds stress terms for separation and reattachment prediction, as well as the wake vortex structure prediction is first proposed.

The purpose of this paper is to review English-language publications about school principalship in China published between 1998 and 2013 and to present an overview of the authorship, topics, methodologies and key findings of these publications.

The methodology includes an exhaustive review of journal articles and book chapters about Chinese school principalship published in the English language. In total, 39 articles and 17 book chapters are identified for the 1998-2013 period. Qualitative analysis is conducted to determine the basic patterns of authorship, topics, methods and key findings. The changes or continuities in these patterns during the study period are also discerned.

The paper identifies several continuous and discontinuous patterns in each of the review categories and provides a better understanding of on-going research into the practice of school principalship in China. The results also suggest areas that require deeper exploration.

This paper explores the landscape of school principalship in China as reflected in the international literature and indicates the ways that this landscape has changed or remained the same over the years. As such, the paper contributes to the thin knowledge base concerning school principalship in China and sheds light on the enduring local-global tension in the evolution of education systems.

Looks at various forms of employee termination and the differing interpretations involved in law. Gives the steps in wrongful discharge, legal developments and organizational developments, plus the possible impacts on small business. Concludes that when employees complain about a problem on reasonable grounds, management should always try to rectify the problem – and not the complainant!

The aim of the study is to evaluate role of trade war between the United States and China on oil price. For this purpose, global oil price and US trade balance with China are selected as variables. In addition to this issue, monthly data of these variables for the periods between 1990 and 2019 are taken into consideration. In the evaluation process, both Engle–Granger cointegration and Toda–Yamamoto causality analysis are considered. The results of Engle–Granger cointegration analysis indicates that there is a ­relationship between trade war and oil prices. Nevertheless, according to the results of Toda–Yamamoto causality analysis, it is identified that trade war does not cause oil prices. While looking at these results, it is determined that trade war between the United States and China has an influence on the oil price changes. However, it is also understood that it is not the main factor of this volatility. Thus, it is recommended that in order to identify the main indicator of the oil price volatility, some different factors should also be taken into consideration.

Adequate, reliable, and efficient urban infrastructure systems (UIS) are fundamental to sustainable development, social mobility, and economic vitality. As communities continuously rely on basic infrastructure services to support their daily communal functions, major components of UIS are subject to heavy use, and thus rapidly deteriorate over time; hence, it is critical that efficient infrastructure management strategies practices are in place. As current strategies remain confronted with various limitations including adaptability to changing conditions, lack of public engagement, and cost-effectiveness, this study explores social media data mining as an approach to revitalise and support current urban infrastructure monitoring strategies by extracting valuable insights from public opinion. Twitter messages or ‘Tweets’ pertaining to public infrastructure in The Philippines were collected and analysed to identify recurring issues in public infrastructure, emerging topics in public discussions, and the overall perception of the public on infrastructure services. This study presents a topic model that extracts dominant topics from aggregated social media data and a sentiment analysis model that determines public opinion sentiment in relation to different urban infrastructure components. The findings of this study highlight the potential of social media data mining to surpass the limits of conventional data collection techniques and the importance of public opinion as a key driver for a more user-involved decision-making in infrastructure management and as an important social aspect that can be utilised to support planning and response strategies in routine maintenance, preservation, and improvement of UIS.

The choice of accounting policies by a company has implications for the market’s understanding of corporate performance. Whilst the critical areas of choice may change over time with new developments and changes in standards, the underlying issue remains relevant. This paper examines the effect of accounting techniques upon the relationship between accounting variables and UK share prices.

Reviews the latest management developments across the globe and pinpoints practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Expansion into international markets has become one of the main growth strategies for many organizations. The blueprint is straightforward enough. Identify untapped potential and exploit the opportunities provided. Build a strong market position and reap lucrative rewards. If only it was that simple. Entering any new territory in the home nation is invariably demanding enough. Factor in the additional challenges inherent in any oversea venture and the difficulty soars to even greater heights. In any market, companies are subject to both technical and institutional demands which increase the complexity of decisions firms have to make. Pressures differ in each environment, so reacting in an appropriate manner is a must. Negotiating these demands effectively can go a considerable way in determining whether organizations ultimately succeed or fail.

Provides strategic insights and practical thinking that have influenced some of the world's leading organizations.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to digest format.

The Journal of Intellectual Capital (JIC) celebrated its 20th anniversary in 2020. Therefore, the present study aims to provide a general overview of the history and key trends in this journal during 2000–2019.

Two types of citation and textual data during a 20-year journal period were retrieved from the Scopus database. The citation structures and contents were explored based on a combination of bibliometric analysis, altmetric analysis and text mining. The journal themes and trends of their changes were analyzed through citation bursts, mapping and topic modeling. To make a better comparison, the text mining process for the topic modeling of the IC field was performed in addition to the topic modeling of JIC.

Bibliometric analysis indicated that JIC has experienced a remarkable growth in terms of the number of publications and citations over the last 20 years. The results indicated that JIC plays a significant role among IC researchers. Additionally, a large number of researchers, institutes and countries have made contributions to this journal and cited its research papers. Altmetric analysis showed that JIC has been shared in different social media such as Twitter, Facebook, Wikipedia, Mendeley, Citeulike, news and blogs. Text mining abstract of JIC articles indicated that “measurement,” “financial performance” and “IC reporting” have the relative prevalence with increasing trends over the past 20 years. In addition, “research trends” and “national and international studies” had a stable trend with low thematic share.

The findings have important implications for the JIC editorial team in order to make informed decisions about the further development of JIC as well as for IC researchers and practitioners to make more valuable contributions to the journal.

Using bibliometric analysis, altmetric analysis and text mining, this study provided a systematic and comprehensive analysis of JIC. The simultaneous use of these methods provides an interesting, unique and suitable capacity to analyze the journals by considering their various aspects.