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Due to its high leverage nature, a bank suffers vitally from the credit risk it inherently bears. As a result, managing credit is the ultimate responsibility of a bank. In this chapter, we examine how efficiently banks manage their credit risk via a powerful tool used widely in the decision/management science area called data envelopment analysis (DEA). Among various existing versions, our DEA is a two-stage, dynamic model that captures how each bank performs relative to its peer banks in terms of value creation and credit risk control. Using data from the largest 22 banks in the United States over the period of 1996 till 2013, we have identified leading banks such as First Bank systems and Bank of New York Mellon before and after mergers and acquisitions, respectively. With the goal of preventing financial crises such as the one that occurred in 2008, a conceptual model of credit risk reduction and management (CRR&M) is proposed in the final section of this study. Discussions on strategy formulations at both the individual bank level and the national level are provided. With the help of our two-stage DEA-based decision support systems and CRR&M-driven strategies, policy/decision-makers in a banking sector can identify improvement opportunities regarding value creation and risk mitigation. The effective tool and procedures presented in this work will help banks worldwide manage the unknown and become more resilient to potential credit crises in the 21st century.

This chapter analyses the efficiency of African airlines using a two-stage network DEA (Data Envelopment Analysis) model. Network DEA models usually take into account the production process with intermediate inputs derived from the first stage and a second stage that departs from it. This fundamental feature enables one to view the airline production process as a carry-over activity. The analysis covers the 2010–2013 period. The relative efficiency ranks are presented and policy implications are derived.

This study aims to obtain the minimum torque ripple at the maximum average torque for Flux-switching permanent magnet (FSPM) machines.

This paper is about torque performance optimization of the FSPM machines. To achieve that, finite element analysis and genetic algorithm (GA) are used. Five different designs are simulated, optimized and compared on their air gap flux density, back electromotive force, cogging torque, average torque, torque density and torque ripple.

After the thousands of iterations, its proved that all proposed shaping techniques have potential for reducing torque ripple and cogging torque, with slightly reduced average torque. The best design is the joint stator and rotor shaping, Design V, which results in the lowest torque ripple and cogging torque. The techniques should be applicable to FSPMs with other stator slot/rotor pole number combinations.

In this paper, rotor pole shaping by notching, chamfering and generic shaping, stator tooth shaping and joint shaping techniques are investigated for 12 s/10p FSPM machines. Rotor and stator flanks are optimized separately and jointly, by using finite element analysis and GA for optimization to achieve maximum average torque and minimum torque ripple. Five different design is implemented and compared, respectively.

The purpose of this paper is to propose a novel type of switched flux PM machines with two separate stators.

2D-FEA is employed to analyze the electromagnetic performance of the proposed machines. Moreover, the results are validated by experiments.

The proposed machine has higher torque density, less unbalanced magnetic force on the modulating steel piece and uses less PM volume.

The proposed machine is a low-cost novel topology with different rotor pole combinations.

The purpose of this paper is to investigate the influence of end‐effect and cross‐coupling on the torque‐speed characteristics of switched flux permanent magnet (SFPM) machines.

The torque‐speed characteristics are predicted using two different methods. These are direct and indirect finite element methods, at different cross‐coupling levels, namely, full cross‐coupling on both PM flux linkage and dq‐axis inductances, partial cross‐coupling on the PM flux linkage only and without cross‐coupling.

The influence of the cross‐coupling on dq‐axis inductances of the studied machine is relatively small. However, it is more significant on the PM flux linkage. Therefore, the partial cross‐coupling model, which is much easier and faster, exhibits almost the same accuracy as the full cross‐coupling model. Furthermore, the end‐effect causes a large reduction in torque‐speed characteristics. However, such a reduction is more significant in the flux weakening operation region.

This is the first time that the influence of end‐effect of SFPM machines on the torque‐speed characteristics, especially in flux weakening region, and on the dq‐axis inductances has been investigated.

Fractional slot permanent magnet (PM) brushless machines having concentrated non‐overlapping windings have been the subject of research over last few years. They have already been employed in the commercial hybrid electric vehicles (HEVs) due to high‐torque density, high efficiency, low‐torque ripple, good flux‐weakening and fault‐tolerance performance. The purpose of this paper is to overview recent development and research challenges in such machines in terms of various structural and design features for electric vehicle (EV)/HEV applications.

In the paper, fractional slot PM brushless machines are overviewed according to the following main and sub‐topics: first, machine topologies: slot and pole number combinations, all and alternate teeth wound (double‐ and single‐layer windings), unequal tooth structure, modular stator, interior magnet rotor; second, machine parameters and control performance: winding inductances, flux‐weakening capability, fault‐tolerant performance; and third, parasitic effects: cogging torque, iron loss, rotor eddy current loss, unbalanced magnetic force, acoustic noise and vibration.

Many fractional slot PM machine topologies exist. Owing to rich mmf harmonics, fractional slot PM brushless machines exhibit relatively high rotor eddy current loss, potentially high unbalanced magnetic force and acoustic noise and vibration, while the reluctance torque component is relatively low or even negligible when an interior PM rotor is employed.

This is the first overview paper which systematically reviews the recent development and research challenges in fractional‐slot PM machines. It summarizes their various structural and design features for EV/HEV applications.

Purpose: In this chapter of this book, the role and contributions of blockchain in Industry 5.0 are examined. Especially, the advantages offered by blockchain in mass customization, hyper-personalization, human–robot collaboration and cognitive systems, which constitute the main theme of Industry 5.0, are mentioned.

Need for the study: With developing technology, revolutions are taking place in the industry. While these revolutions are occurring, various technologies serve as enablers. In this chapter, one of these technologies, blockchain, is examined.

Methodology: Industrial revolutions represent important technological developments for societies. In this chapter, Industry 5.0, one of these revolutions, is discussed. In the first section, the main themes of Industry 5.0 were examined. Afterward, the transition from Industry 4.0 to Industry 5.0 was analyzed. Then, the opportunities offered by Industry 5.0 were reviewed. Subsequently, the contributions of blockchain to Industry 5.0 were examined. Finally, the role of blockchain in Industry 5.0 is summarized.

Findings: The main themes of Industry 5.0 enable customized processes and smart production approaches. Blockchain makes significant contributions to these processes with its security and traceability features. In addition, smart contracts can increase transparency, traceability and security among stakeholders in the production process with their distributed ledger structure and immutability features. In blockchain networks, each transaction is carried out and approved by consensus. This consensus, provided by smart contracts, also secures transactions by reducing administrative costs. With these contributions, blockchain meets the security and smart management requirements of Industry 5.0.

While the adverse health consequences of obesity are well-documented, the causal effect between obesity and economic outcomes, particularly individual income in the labor market, has yielded inconsistent findings. At the same time, China has the highest number of obese or overweight people around the world in recent years. However, limited research has examined the causal effect of obesity on Chinese rural residents’ income. To answer this question, our study aims to identify the causal impact of obesity on Chinese rural residents.

First, we conduct ordinary least squares, instrumental variable and Mendelian randomization methods to evaluate the impact of obesity on Chinese rural residents’ income. Then, we employ quantile regression and instrumental variable quantile regression to investigate the potential distributional impacts of obesity across various income segments. For the generality of our results, we also use 485,849 samples from the UK Biobank and the two-sample Mendelian randomization method to analyze.

Our one-sample Mendelian randomization analysis, based on a sample of 441 people collected from rural China in 2019 and 2021, revealed that obesity reduced residents’ annual income by 647.87 China Yuan. Results from the UK further support our findings. We also find that the adverse causal impact of obesity on income is significant in individuals within the above 50th percentile of the income distribution. Additionally, childhood obesity has a long-term adverse effect on income in adulthood.

These results contribute to a more nuanced understanding of the economic costs of obesity. Weight penalties may lead to a deviation from the efficiency that should be pursued in the labor market and widen income disparity.

We provide novel and robust instrumental variables and utilize the Mendelian randomization method to analyze the effect of obesity on Chinese rural residents.