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As the strategy of 5G new infrastructure is deployed and advanced, 5G-R becomes the primary technical system for future mobile communication of China’s railway. V2V communication is also an important application scenario of 5G communication systems on high-speed railways, so time synchronization between vehicles is critical for train control systems to be real-time and safe. How to improve the time synchronization performance in V2V communication is crucial to ensure the operational safety and efficiency of high-speed railways.

This paper proposed a time synchronization method based on model predictive control (MPC) for V2V communication. Firstly, a synchronous clock for V2V communication was modeled based on the fifth generation mobile communication-railway (5G-R) system. Secondly, an observation equation was introduced according to the phase and frequency offsets between synchronous clocks of two adjacent vehicles to construct an MPC-based space model of clock states of the adjacent vehicles. Finally, the optimal clock offset was solved through multistep prediction, rolling optimization and other control methods, and time synchronization in different V2V communication scenarios based on the 5G-R system was realized through negative feedback correction.

The results of simulation tests conducted with and without a repeater, respectively, show that the proposed method can realize time synchronization of V2V communication in both scenarios. Compared with other methods, the proposed method has faster convergence speed and higher synchronization precision regardless of whether there is a repeater or not.

This paper proposed an MPC-based time synchronization method for V2V communication under 5G-R. Through the construction of MPC controllers for clocks of adjacent vehicles, time synchronization was realized for V2V communication under 5G-R by using control means such as multistep prediction, rolling optimization, and feedback correction. In view of the problems of low synchronization precision and slow convergence speed caused by packet loss with existing synchronization methods, the observer equation was introduced to estimate the clock state of the adjacent vehicles in case of packet loss, which reduces the impact of clock error caused by packet loss in the synchronization process and improves the synchronization precision of V2V communication. The research results provide some theoretical references for V2V synchronous wireless communication under 5G-R technology.

The purpose of this paper is to build possible future scenarios for indoor connectivity in a venue such as a university campus and build alternative value network configurations (VNCs) defining different local network deployment options, focused on the Finnish telecom market.

In this paper, Schoemaker’s scenario planning method (Schoemaker, 1995) is used to construct future scenarios and the VNC method of Casey et al. (2010) is used to build alternative VNCs. The paper studies the Aalto University campus network for current end-user data usage demand and the existing technology used in meeting the end-user needs and forecasts the demand for the next five years to understand the need for 5G.

This research concludes that with the provision of local spectrum licenses, there is an opportunity for venue owners to take the role of 5G local operator on the venue premises. Furthermore, it enables venue owners to collaborate with the incumbent mobile network operators (MNOs) in a neutral host model and provide venue-specific connectivity services.

A detailed economic assessment for the network deployment in the campus is considered for future study.

Considering the provision for local spectrum licenses, this paper has taken a unique attempt in identifying the future scenarios for local 5G network operations. It provides a strategic direction for the venue owners in adopting 5G technology and whether to make 5G or buy 5G from MNOs.

The purpose of this paper is to develop Delphi methodology toward a holistic method for forecasting market change. Delphi methodology experienced its culmination in marketing research during the 1970s–1980s, but still has much to offer to both marketing scholars and practitioners in contexts where future market changes are associated with ambiguity and uncertainty.

This study revives the Delphi methodology by exemplifying how a recently developed framework on market change can be combined with the Delphi technique for data collection to support forecasting activities and research. The authors demonstrate the benefits of the improved methodology in an empirical study on the impact of the fifth generation of wireless communications technologies (5G) on the Finnish media market.

The developed methodological approach aids marketing scholars in categorizing and analyzing the data collected for capturing market change; and better guiding experts/respondents to provide holistic projections of future market change. The authors show that using a predefined theoretical framework in combination with the Delphi method for data collection and analysis is beneficial for studying future market change.

This paper develops Delphi methodology and contributes with a novel methodological approach to assessing market change.

This paper is premised upon an analysis of 26 cities within the UK regarding their smart city projects. Each city was analyzed through news articles, reports and policy documents to ascertain the level of each city's development as a smart city. Each was coded by separating the projects into five types, which were ranked on a scale from 0 (no plans for use) to 5 (project type in use). The most common types are the provision of open data and the creation of business ecosystems as the primary driver of the smart city. However, many councils and enterprises proclaim smartness before the technology is actually in use, making it difficult to separate what is utilised and what is under development. Therefore, this paper further carried out an analysis of 20 cities and their intended plans to usher in the smart city, to observe the expected emergence of smart city technology. This was achieved by interrogating various roadmaps and policy documents produced by the respective cities. It was found that the most prevalent form of emergent smart city technology is the rollout of 5G and increased educational programmes alongside a proliferation of internet of things and electric vehicle usage.

The purpose of this study is to examine the role of artificial intelligence (AI) in transforming the healthcare sector, with a focus on how AI contributes to entrepreneurship and value creation. This study also aims to explore the potential of combining AI with other technologies, such as cloud computing, blockchain, IoMT, additive manufacturing and 5G, in the healthcare industry.

Exploratory qualitative methodology was chosen to analyze 22 case studies from the USA, EU, Asia and South America. The data source was public and specialized podcast platforms.

The findings show that combining technologies can create a competitive advantage for technology entrepreneurs and bring about transitions from simple consumer devices to actionable healthcare applications. The results of this research identified three main entrepreneurship areas: 1. Analytics, including staff reduction, patient prediction and decision support; 2. Security, including protection against cyberattacks and detection of atypical cases; 3. Performance optimization, which, in addition to reducing the time and costs of medical procedures, includes staff training, reducing capital costs and working with new markets.

This study demonstrates how AI can be used with other technologies to cocreate value in the healthcare industry. This study provides a conceptual framework, “AI facilitators – AI achievers,” based on the findings and offer several theoretical contributions to academic literature in technology entrepreneurship and technology management and industry recommendations for practical implication.

Among the proposed radio access strategies for improving system execution in 5G networks, the non-orthogonal multiple access (NOMA) scheme is the prominent one.

Among the most fundamental NOMA methods, power-domain NOMA is the one where at the transmitter, superposition coding is used, and at the receiver, successive interference cancellation (SIC) is used. The importance of power allocation (PA) in achieving appreciable SIC and high system throughput cannot be overstated.

This research focuses on an outage probability analysis of NOMA downlink system under various channel conditions like Rayleigh, Rician and Nakagami-m fading channel. The system design's objectives, techniques and constraints for NOMA-based 5G networks' PA strategies are comprehensively studied.

From the results of this study, it is found that the outage probability performance of downlink ordered NOMA under Rayleigh, Rician and Nakagami-m fading channel was good.

Outage probability analysis of downlink ordered NOMA under various channel conditions like Rayleigh, Rician and Nakagami-m fading channels were employed. Though the performance of Nakagami-m fading channel is lesser compared to Rayleigh channel, the performance for user 1 and user 2 are good.

The impact of potassium permanganate (KMnO₄) treatment on the tensile strength of an alkali-treated pineapple leaf fiber (PALF) reinforced with tapioca-based bio resin (cassava starch) was studied.

The PALF was exposed to sodium hydroxide (NaOH) treatment in varying concentrations of 2.0, 3.7, 4.5 and 5.5g prior to the fiber treatment with KMnO₄. The treated and untreated PALFs were reinforced with tapioca-based bio resin. Subsequently, they were subjected to Fourier transform infrared (FTIR) and tensile test analysis.

The FTIR analysis of untreated PALF revealed the presence of O-H stretch, N-H stretch, C=O stretch, C=O stretch and H-C-H bond. The tensile test result confirmed the highest tensile strength of 35N from fiber that was reinforced with 32.5g of cassava starch and treated with 1.1g of KMnO₄. In comparison, the lowest tensile strength of 15N was recorded for fiber reinforced with 32.5g of cassava starch without KMnO₄ treatment.

Based on the results, it could be deduced that despite the enhancement of bioresin (cassava starch) towards strength-impacting on the fibers, KMnO₄ treatment on PALF is very vital for improved tensile strength of the fiber when compared to untreated fibers. Hence, KMnO₄ treatment on alkali-treated natural fibers preceding reinforcement is imperative for bio-based fibers.

Cloud computing originated in central data centers that are connected to the backbone of the Internet. The network transport to and from a distant data center incurs long latencies that hinder modern low-latency applications. In order to flexibly support the computing demands of users, cloud computing is evolving toward a continuum of cloud computing resources that are distributed between the end users and a distant data center. The purpose of this review paper is to concisely summarize the state-of-the-art in the evolving cloud computing field and to outline research imperatives.

The authors identify two main dimensions (or axes) of development of cloud computing: the trend toward flexibility of scaling computing resources, which the authors denote as Flex-Cloud, and the trend toward ubiquitous cloud computing, which the authors denote as Ubi-Cloud. Along these two axes of Flex-Cloud and Ubi-Cloud, the authors review the existing research and development and identify pressing open problems.

The authors find that extensive research and development efforts have addressed some Ubi-Cloud and Flex-Cloud challenges resulting in exciting advances to date. However, a wide array of research challenges remains open, thus providing a fertile field for future research and development.

This review paper is the first to define the concept of the Ubi-Flex-Cloud as the two-dimensional research and design space for cloud computing research and development. The Ubi-Flex-Cloud concept can serve as a foundation and reference framework for planning and positioning future cloud computing research and development efforts.

The purpose of this study is to analyze the robot trends of the next generation.

This paper is divided into two sections: the key modern technology on which Europe's robotics industry has built its foundation is described. Then, the next key megatrends were analyzed.

Artificial intelligence (AI) and robotics are technologies of major importance for the development of humanity. This time is mature for the evolution of industrial and service robots. The perception of robot use has changed from threading to aiding. The cost of mass production of technological devices is decreasing, while a rich set of enabling technologies is under development. Soft mechanisms, 5G and AI have enabled us to address a wide range of new problems. Ethics should guide human behavior in addressing this newly available powerful technology in the right direction.

The paper describes the impact of new technology, such as AI and soft robotics. The world of work must react quickly to these epochal changes to enjoy their full benefits.

This case study aims to analyse the different factors that cause a decline in an organisation's performance. It projects data for the prospective case readers to explore the possible approaches for the Chairman-cum-Managing Director (CMD) of Mahanagar Telephone Nigam Limited (MTNL) and Bharat Sanchar Nigam Limited (BSNL) to turnaround both the organisations. Furthermore, the case compels the readers to study the Indian Telecom industry to analyse the competitive behaviour and the consequent actions necessary to survive and thrive amongst their peers. From the theoretical perspective, the case emphasises the recent change observed in the Telecom industry regarding the transition from value-chain to value-network.

The authors collected the case facts and data for the case study from secondary sources like the latest news articles, the CRISIL database, company annual statements, company press releases and government regulatory body web portals.

The case study has identified the issues pertinent in the public sector companies in India, especially in the telecom sector, concerning leadership, pending government financial commitments and a slow-moving attitude towards taking action.

The case study highlights the management problems faced by the CMD of the two public sector telecom companies i.e. BSNL and MTNL.