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Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.

Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.

Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.

Other optimization techniques can be applied for WSN to analyze the performance.

Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.

Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.

Literature survey is carried out to find the methods which give better performance.

Purpose: Blockchain technology has exploded in popularity in the social economy over the years. Because blockchain technology offers so many advantages, it was first employed for Bitcoin transactions. The interaction between blockchain technology and financial industries will grow more personal and interwoven with the introduction of Bitcoin. As the value of blockchain technology became evident, more financial companies began to test its use in monetary operations. Numerous financial companies have been experimenting with blockchain technology to reduce the transactional costs and to improve the efficiency of operations, specifically in the domain of financial notes, cross-border payments, and asset-backed securitisation. Blockchain will have a broad range of applications in the financial industry shortly.

Methodology: Through financial tools and methods, trust may result in successful businesses. In the long term, blockchain technology is generally a significant source of the finance industry revolution. It allows you to create immutable transaction histories available to everyone on the network. A blockchain system consists of a sequence of blocks connected by a connection to the block before each block. Each block comprises more than one transaction representing changes in the ownership of assets on the ledger. A consensus procedure is employed to add new blocks to the existing chain, in which members of the public blockchain confirm that transactions are accurate.

Findings: Blockchain technology is still in its infancy. The challenges of sustainability, privacy, secrecy, and latency, among others, have surfaced. Financial markets must get a deeper grasp of Blockchain to provide trustworthy alternatives.

Significance: The book chapter highlights the architecture, protocols, and applications of Blockchain Technology. The chapter will also enlighten the readers about the challenges and solutions of Blockchain Technology in the Financial Market. Moreover, the chapter also discusses the future research scope of Blockchain Technology in the Financial Market.

This new paper aims to combine the recent new contributions about direct data driven control and other safety property to form an innovative direct data driven safety control for aircraft flight system. More specifically, within the framework of direct data driven strategy, the collected data are dealt with to get the identified plant and designed controller. After reviewing some priori information about aircraft flight system, a closed loop system with the unknown plant and controller simultaneously is considered. Data driven estimation is proposed to identify the plant and controller only through the ratios of two correlation functions, computed from the collected data. To achieve the dual missions about perfect tracking and safety property, a new notion about safety controller is introduced. To design this safety controller, direct data driven safety controller is proposed to solve one constrain optimization problem. Then the authors apply the Karush–Kuhn–Tucker (KKT) optimality conditions to derive the explicit safety controller.

First, consider one closed loop system corresponding to aircraft flight system with the unknown plant and feed forward controller, data driven estimation is used to identify the plant and feed forward controller. This identification process means nonparametric estimation. Second, to achieve the perfect tracking one given transfer function and guarantee the closed loop output response within one limited range simultaneously, safety property is introduced. Then direct data driven safety control is proposed to design the safety controller, while satisfying the dual goals. Third, as the data driven estimation and direct data driven safety control are all formulated as one constrain optimization problem, the KKT optimality conditions are applied to obtain the explicit safety controller.

Some aircraft system identification and aircraft flight controller design can be reformulated as their corresponding constrain optimization problems. Then through solving these constrain optimization problems, the optimal estimation and controller are yielded, while satisfying our own priori goals. First, data driven estimation is proposed to get the rough estimation about the plant and controller. Second, data driven safety control is proposed to get one safety controller before our mentioned safety concept.

To the best of the authors’ knowledge, some existing theories about nonparametric estimation and tube model predictive control are very mature, but few contributions are applied in practice, such as aircraft system identification and aircraft flight controller design. This new paper shows the new theories about data driven estimation and data driven safety control on aircraft, being corresponded to the classical nonparametric estimation and tube model predictive control. Specifically, data driven estimation gives the rough estimations for the aircraft and its feed forward controller. Furthermore, after introducing the safety concept, data driven safety control is introduced to achieve the desired dual missions with the combination of KKT optimality conditions.

Dual-thrust hybrid unmanned aerial vehicle (UAV) technology offers a highly robust and efficient system that incorporates the take-off and landing capabilities of rotary-wing aircraft with the endurance capacities of fixed-wing aircraft. The purpose of this study is to model and control a hybrid UAV in three distinct flight modes: rotary-wing, fixed-wing and over-actuated model.

Model predictive control (MPC) along with linear models are applied to design controllers for the rotary-wing or vertical take-off and transition to the fixed-wing flight. The MPC algorithm is implemented with two approaches, first in its usual form and then in a new form with the help of tracking error variables as state variables.

Because the tracking error variables are more compatible with the cost function used in MPC, the results improve significantly. This is especially important for a safe and stable transition from rotary-wing to fixed-wing flight, which should be done quickly. The authors also propose a control allocation strategy with MPC algorithm to exploit the thrust and control inputs of both rotary-wing and fixed-wing systems for the transition phase. As the control system is over-actuated, the proposed algorithm distributes the control signal among the actuators better than the MPC alone. The numerical results show that the flight trajectory is also improved.

The research background is reviewed in the introduction section. The other sections are originally developed in this paper to the best of the authors’ knowledge.

This study aims to give a glimpse of the existing blockchain applications across industries and add to a complete knowledge of the blockchain’s properties.

Systematic literature review is used as the research strategy for this investigation and other aspects of the preferred reporting items for systematic reviews and meta-analyses framework have been incorporated to create a scholarly publications evaluation of the blockchain-based application in the financial arena and its future. The research looks at 86 studies published between 2018 and 2022.

There has been a steady but noticeable increase in the study of blockchain’s potential in many application domains over the past few of years. This rising tendency illustrates the newness and potential of blockchain technology, as well as the increasing attention from academics. According to the findings, blockchain is an appropriate solution for processing transactions using cryptocurrencies; nevertheless, it still has significant technical issues and limits that require to be exploring and solving before it can be considered a viable option. It is therefore, necessary to have a high level of reliability for payments and confidentiality, in addition to maintaining the anonymity of nodes, to stop assaults and efforts to disrupt transactions in the blockchain.

This study has several important theoretical and practical implications. First, it adds to the body of knowledge on blockchain and Fintech, focusing on the transaction side. While much blockchain research has focused on how the technology may affect strategic choices, this study has shed light on its potential from the perspective of financial reporting. Second, by highlighting the importance of the demand for the prompt identification of losses, this work adds to the body of knowledge on the factors that influence transaction frauds involving paper money. Additionally, by establishing the link between transparency and virtual transactions, the author backs up the asymmetric responses of investors to different investment possibilities. It looks at the evolution of financial technology (Fintech) and shows how it can be used to take the advantage of unique opportunities.

The study is different and novel from the previously published literature on this topic mainly because of its comprehensiveness, as it revolves around all industrial and commercial areas. The three main lines of research have been outlined, namely, classifying the many blockchain-based innovations that will alter the financial landscape in many industries; identifying whether these industries are a good fit for blockchain’s wealth creation potential; and directing researchers by outlining prospective study pathways.

Every company or manufacturing system is vulnerable to breakdowns. This research aims to analyze the role of Multi-Agent Technology (MAT) in minimizing breakdown probabilities in Manufacturing Industries.

This study formulated a framework of six factors and twenty-eight variables (explored in the literature). A hybrid approach of Multi-Criteria Decision-Making Technique (MCDM) was employed in the framework to prioritize, rank and establish interrelationships between factors and variables grouped under them.

The research findings reveal that the “Manufacturing Process” is the most essential factor, while “Integration Manufacturing with Maintenance” is highly impactful on the other factors to eliminate the flaws that may cause system breakdown. The findings of this study also provide a ranking order for variables to increase the performance of factors that will assist manufacturers in reducing maintenance efforts and enhancing process efficiency.

The ranking order developed in this study may assist manufacturers in reducing maintenance efforts and enhancing process efficiency. From the manufacturer’s perspective, this research presented MAT as a key aspect in dealing with the complexity of manufacturing operations in manufacturing organizations. This research may assist industrial management with insights into how they can lower the probability of breakdown, which will decrease expenditures, boost productivity and enhance overall efficiency.

This study is an original contribution to advancing MAT’s theory and empirical applications in manufacturing organizations to decrease breakdown probability.

This research aims to present a novel cooperative control architecture designed specifically for roads with variations in height and curvature. The primary objective is to enhance the longitudinal and lateral tracking accuracy of the vehicle.

In addressing the challenges posed by time-varying road information and vehicle dynamics parameters, a combination of model predictive control (MPC) and active disturbance rejection control (ADRC) is employed in this study. A coupled controller based on the authors’ model was developed by utilizing the capabilities of MPC and ADRC. Emphasis is placed on the ramifications of road undulations and changes in curvature concerning control effectiveness. Recognizing these factors as disturbances, measures are taken to offset their influences within the system. Load transfer due to variations in road parameters has been considered and integrated into the design of the authors’ synergistic architecture.

The framework's efficacy is validated through hardware-in-the-loop simulation. Experimental results show that the integrated controller is more robust than conventional MPC and PID controllers. Consequently, the integrated controller improves the vehicle's driving stability and safety.

The proposed coupled control strategy notably enhances vehicle stability and reduces slip concerns. A tailored model is introduced integrating a control strategy based on MPC and ADRC which takes into account vertical and longitudinal force variations and allowing it to effectively cope with complex scenarios and multifaceted constraints problems.

The purpose of this paper is to propose a novel event-triggered aperiodic intermittent sliding-mode control (ETAI-SMC) algorithm for master–slave bilateral teleoperation robotic systems to further save communication resources while maintaining synchronization precision.

By using the Lyapunov theory, a new event-triggered aperiodic intermittent sliding-mode controller is designed to synchronize master–slave robots in a discontinuous method. Unlike traditional periodic time-triggered continuous control strategy, a new ETAI condition is discussed for less communication pressure. Then, the exponential reaching law is adopted to accelerate sliding-mode variables convergence, which has a significant effect on synchronization performance. In addition, the authors use quantizers to make their algorithm have obvious progress in saving communication resources.

The proposed control algorithm performance is validated by an experiment developed on a practical bilateral teleoperation system with two PHANToM Omni robotic devices. As a result, the synchronization error is limited within a small range and the control frequency is evidently reduced. Compared with a conventional control algorithm, the experimental results illustrate that the proposed control algorithm is more sensitive to system states changes and it can further save communication resources while guaranteeing the system synchronization accuracy, which is more practical for real bilateral teleoperation robotic systems.

A novel ETAI-SMC for bilateral teleoperation robotic systems is proposed to find a balance between reducing the control frequency and synchronization control precision. Combining the traditional sliding-mode control algorithm with the periodic intermittent control strategy and the event-triggered control strategy has produced obvious effect on our control performance. The proposed ETAI-SMC algorithm helps the controller be more sensitive to system states changes, which makes it possible to achieve precise control with lower control frequency. Moreover, we design an environment contact force feedback algorithm for operators to improve the perception of the slave robot working environment. In addition, quantizers and the exponential convergence law are adopted to help the proposed algorithm perform better in saving communication resources and improving synchronization precision.

Reasonable risk sharing is the key to the smooth implementation of infrastructure public-private partnership (PPP) projects and the optimization of benefit distribution among the participants. This study aims to explore the risk redistribution ratio between the government and the private sector under different degree of fairness concern.

Renegotiation is a mechanism to provide flexibility and make up for incompleteness of PPP contracts. However, the threshold value of risk redistribution ratio and negotiation cost are not explicitly considered in previous studies. In addition, these studies do not consider the influence of the fairness concern psychology on the negotiation process. To address these gaps, based on risk-income equilibrium analysis, this paper established the bargaining optimization model of PPP projects renegotiation considering the fairness concerns of the negotiating parties. Furthermore, this study analyzed the influence of fairness concern degree on negotiation thresholds, negotiation results, and negotiation incomes under three scenarios.

The results showed that excessive focus on the fairness of incomes may exclude the risk redistribution ratio that is most beneficial to project incomes from the negotiation threshold. Moreover, the increase in the fairness concerns of negotiating parties can reduce the negotiation success period, but the net income may not necessarily be improved.

The main contribution of this paper is to propose a new risk renegotiation methodology based on the risk-income equilibrium analysis, which is helpful to develop risk management strategies in the construction field. The research results can provide government with reference about renegotiation in decision making and provide theoretical support for the practice of PPP renegotiation.

Smart Heritage is a recently established discourse that entwines smartness and the heritage discipline. Studies have shown that place identity is at the core of value-based frameworks of built heritage. This study aims to unveil the role of identity in existing Smart Heritage frameworks, which is currently a gap in existing research.

To better understand place identity in the Smart Heritage context and facilitate future framework establishments, this study uses a cross-case analysis method to scrutinise common trends in the identity development of seven current best practices.

The results show that current best practices involve smart technologies in sustaining or rebuilding heritage identities, mostly mapped on the local scale. Catered solutions are essential in this context due to historic cities’ variegated pursuits of identity. Most current Smart Heritage projects are at the transitioning stage from digital to smart, as the autonomous ability of smart innovations is yet to be fully realised on the city or the global scale. Researchers are encouraged to draw essence from existing heritage frameworks considering the built heritage’s place identity, which is at the core of culturally sustainable Smart Heritage transitions.

This study concludes with five recommendations for addressing heritage identity in Smart Heritage frameworks, targeting future research avenues. Also, this study furthers the discussion on the linkage of Smart Heritage, place identity and marketing strategy, contributing to the city branding and tourism management field. Future research should extend the case-study selection beyond Europe, which is a recognised limitation of this study.