Jeng-Tzong Chen, Shyh-Rong Kuo, Yu-Lung Chang and Shing-Kai Kao
The purpose of this paper is to detect the degenerate scale of a 2D bending plate analytically and numerically.
Abstract
Purpose
The purpose of this paper is to detect the degenerate scale of a 2D bending plate analytically and numerically.
Design/methodology/approach
To avoid the time-consuming scheme, the influence matrix of the boundary element method (BEM) is reformulated to an eigenproblem of the 4 by 4 matrix by using the scaling transform instead of the direct-searching scheme to find degenerate scales. Analytical degenerate scales are derived from the boundary integral equation (BIE) by using the degenerate kernel only for the circular case. Numerical results of the direct-searching scheme and the eigen system for the arbitrary shape are also considered.
Findings
Results using three methods, namely, analytical derivation, the direct-searching scheme and the 4 by 4 eigen system, are also given for the circular case and arbitrary shapes. Finally, addition of a constant for the kernel function makes original eigenvalues (2 real roots and 2 complex roots) of the 4 by 4 matrix to be all real. This indicates that a degenerate scale depends on the kernel function.
Originality/value
The analytical derivation for the degenerate scale of a 2D bending plate in the BIE is first studied by using the degenerate kernel. Through the reformed eigenproblem of a 4 by 4 matrix, the numerical solution for the plate of an arbitrary shape can be used in the plate analysis using the BEM.
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Sakthivel Murugan R. and Vinodh S.
This paper aims to optimize the process parameters of the fused deposition modelling (FDM) process using the Grey-based Taguchi method and the results to be verified based on a…
Abstract
Purpose
This paper aims to optimize the process parameters of the fused deposition modelling (FDM) process using the Grey-based Taguchi method and the results to be verified based on a technique for order preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP) calculation.
Design/methodology/approach
The optimization of process parameters is gaining a potential role to develop robust products. In this context, this paper presents the parametric optimization of the FDM process using Grey-based Taguchi, TOPSIS and AHP method. The effect of slice height (SH), part fill style (PFS) and build orientation (BO) are investigated with the response parameters machining time, surface roughness and hardness (HD). Multiple objective optimizations were performed with weights of w1 = 60%, w2 = 20% and w3 = 20%. The significance of the process parameters over response parameters is identified through analysis of variance (ANOVA). Comparisons are made in terms of rank order with respect to grey relation grade (GRG), relative closeness and AHP index values. Response table, percentage contributions of process parameters for both GRG and TOPSIS evaluation are done.
Findings
The optimum factor levels are identified using GRG via the Grey Taguchi method and TOPSIS via relative closeness values. The optimized factor levels are SH (0.013 in), PFS (solid) and BO (45°) using GRG and SH (0.013 in), PFS (sparse-low density) and BO (45°) using TOPSIS relative closeness value. SH has higher significance in both Grey relational analysis and TOPSIS which were analysed using ANOVA.
Research limitations/implications
In this research, the multiple objective optimizations were done on an automotive component using GRG, TOPSIS and AHP which showed a 27% similarity in their ranking order among the experiments. In the future, other advanced optimization techniques will be applied to further improve the similarity in ranking order.
Practical implications
The study presents the case of an automotive component, which illustrates practical relevance.
Originality/value
In several research studies, optimization was done on the standard test specimens but not on a real-time component. Here, the multiple objective optimizations were applied to a case automotive component using Grey-based Taguchi and verified with TOPSIS. Hence, an effort has been taken to find optimum process parameters on FDM, for achieving smooth, hardened automotive components with enhanced printing time. The component can be explored as a replacement for the existing product.
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Ran Sun, Aidang Shan, Chengxi Zhang and Qingxian Jia
This paper aims to investigate the feasibility of using the combination of Lorentz force and aerodynamic force as a propellantless control method for spacecraft formation.
Abstract
Purpose
This paper aims to investigate the feasibility of using the combination of Lorentz force and aerodynamic force as a propellantless control method for spacecraft formation.
Design/methodology/approach
It is assumed that each spacecraft is equipped with several large flat plates, which can rotate to produce aerodynamic force. Lorentz force can be achieved by modulating spacecraft’s electrostatic charge. An adaptive output feedback controller is designed based on a sliding mode observer to account for unknown uncertainties and the absence of relative velocity measurements. Aiming at distributing the control input, an optimal control allocation method is proposed to calculate the electrostatic charge of the Lorentz spacecraft and control commands for the atmospheric-based actuators.
Findings
Numerical examples are provided to demonstrate the effectiveness of the proposed control strategy in the presence of J2 perturbations. Simulation results show that relative motion in a formation can be precisely controlled by the proposed propellantless control method under uncertainties and unavailability of velocity measurements.
Research limitations/implications
The controllability of the system is not theoretically investigated in the current work.
Practical implications
The proposed control method introduced in this paper can be applied for small satellites formation in low Earth orbit.
Originality/value
The main contribution of the paper is the proposal of the propellantless control approach for satellite formation using the combination of Lorentz force and aerodynamic force, which can eliminate the requirement of the propulsion system.
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This paper aims to propose an integration of the analytic hierarchy process (AHP) and data envelopment analysis (DEA) methods in a multiattribute grey relational analysis (GRA…
Abstract
Purpose
This paper aims to propose an integration of the analytic hierarchy process (AHP) and data envelopment analysis (DEA) methods in a multiattribute grey relational analysis (GRA) methodology in which the attribute weights are completely unknown and the attribute values take the form of fuzzy numbers.
Design/methodology/approach
This research has been organized to proceed along the following steps: computing the grey relational coefficients for alternatives with respect to each attribute using a fuzzy GRA methodology. Grey relational coefficients provide the required (output) data for additive DEA models; computing the priority weights of attributes using the AHP method to impose weight bounds on attribute weights in additive DEA models; computing grey relational grades using a pair of additive DEA models to assess the performance of each alternative from the optimistic and pessimistic perspectives; and combining the optimistic and pessimistic grey relational grades using a compromise grade to assess the overall performance of each alternative.
Findings
The proposed approach provides a more reasonable and encompassing measure of performance, based on which the overall ranking position of alternatives is obtained. An illustrated example of a nuclear waste dump site selection is used to highlight the usefulness of the proposed approach.
Originality/value
This research is a step forward to overcome the current shortcomings in the weighting schemes of attributes in a fuzzy multiattribute GRA methodology.
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Hannes Velt and Rudolf R. Sinkovics
This chapter offers a comprehensive review the literature on authentic leadership (AL). The authors employ a bibliometric approach to identify, classify, visualise and synthesise…
Abstract
This chapter offers a comprehensive review the literature on authentic leadership (AL). The authors employ a bibliometric approach to identify, classify, visualise and synthesise relevant scholarly publications and the work of a core group of interdisciplinary scholars who are key contributors to the research on AL. They review 264 journal articles, adopting a clustering technique to assess the central themes of AL scholarship. They identify five distinct thematic clusters: authenticity in the context of leadership; structure of AL; social perspectives on AL; dynamism of AL; and value perceptions of AL. Velt and Sinkovics assert that these clusters will help scholars of AL to understand the dominant streams in the literature and provide a foundation for future research.
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Data breaches in the US healthcare sector have more than tripled in the last decade across all states. However, to this day, no established framework ranks all states from most to…
Abstract
Purpose
Data breaches in the US healthcare sector have more than tripled in the last decade across all states. However, to this day, no established framework ranks all states from most to least at risk for healthcare data breaches. This gap has led to a lack of proper risk identification and understanding of cyber environments at state levels.
Design/methodology/approach
Based on the security action cycle, the National Institute of Standards and Technology (NIST) cybersecurity framework, the risk-planning model, and the multicriteria decision-making (MCDM) literature, the paper offers an integrated multicriteria framework for prioritization in cybersecurity to address this lack and other prioritization issues in risk management in the field. The study used historical breach data between 2015 and 2021.
Findings
The findings showed that California, Texas, New York, Florida, Indiana, Pennsylvania, Massachusetts, Minnesota, Ohio, and Georgia are the states most at risk for healthcare data breaches.
Practical implications
The findings highlight each US state faces a different level of healthcare risk. The findings are informative for patients, crucial for privacy officers in understanding the nuances of their risk environment, and important for policy-makers who must grasp the grave disconnect between existing issues and legislative practices. Furthermore, the study suggests an association between positioning state risk and such factors as population and wealth, both avenues for future research.
Originality/value
Theoretically, the paper offers an integrated framework, whose basis in established security models in both academia and industry practice enables utilizing it in various prioritization scenarios in the field of cybersecurity. It further emphasizes the importance of risk identification and brings attention to different healthcare cybersecurity environments among the different US states.
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In recent years, people have started to realize the importance of environmental protection, and in particular the problem of global warming. Consequently, many governments have…
Abstract
Purpose
In recent years, people have started to realize the importance of environmental protection, and in particular the problem of global warming. Consequently, many governments have started to view decreasing carbon emissions as a priority. Green transportation is one of the policies that is relevant to these efforts. This research aims to optimize the routing plan with minimizing fuel consumption.
Design/methodology/approach
In this research, a model is proposed for calculating the total fuel consumption when given a routing plan. Three factors which greatly affect fuel consumption of transportation – transportation distance, transportation speed and loading weight – are taken into consideration. Then a simple Tabu Search is used to optimize the routing plan and an experimental evaluation of the proposed method is performed.
Findings
It is shown that the proposed method provides substantial improvements over a method based on minimizing transportation distances.
Originality/value
The experimental results show that the routing plans found by the proposed method require less fuel consumption than that found by optimizing methods in which the distance travelled was minimized. That means that, if the distribution center can transport goods using vehicles with better fuel consumption, and the drivers can drive in the such a way as to reduce the discharge of carbon, then the proposed method can be a strategy for the continuous improvement of fuel consumption.
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H. K. Leng, T. Y. Kuo, Grain Baysa-Pee and Josephine Tay
Singapore hosted the inaugural Youth Olympic Games (YOG) in 2010. Prior studies have shown that a country hosting a major sports event can raise the level of national pride among…
Abstract
Purpose
Singapore hosted the inaugural Youth Olympic Games (YOG) in 2010. Prior studies have shown that a country hosting a major sports event can raise the level of national pride among its citizens. The purpose of this paper is to examine the change in national pride among spectators and non-spectators following the hosting of the YOG.
Design/methodology/approach
A longitudinal research design was employed in this study. Surveys using the General National Pride Scale to measure the level of national pride were conducted two months before and after the YOG.
Findings
Using paired t-tests, the results showed that there was a significant increase in the level of national pride among non-spectators.
Research limitations/implications
The research concurs with earlier research that hosting a major sports event can increase the level of national pride in the population.
Practical implications
From an application standpoint, this research suggests that in planning major sports events, the government should recognise that such events can increase the level of national pride even among those who have expressed no interest in the sports events.
Social implications
National pride can be fostered through the hosting of major sports events.
Originality/value
This study demonstrates that in hosting a major sports event, there is an increase in national pride even among non-spectators and those who have no interest in the event.
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Liang He, Haiyan Xu and Ginger Y. Ke
Despite better accessibility and flexibility, peer-to-peer (P2P) lending has suffered from excessive credit risks, which may cause significant losses to the lenders and even lead…
Abstract
Purpose
Despite better accessibility and flexibility, peer-to-peer (P2P) lending has suffered from excessive credit risks, which may cause significant losses to the lenders and even lead to the collapse of P2P platforms. The purpose of this research is to construct a hybrid predictive framework that integrates classification, feature selection, and data balance algorithms to cope with the high-dimensional and imbalanced nature of P2P credit data.
Design/methodology/approach
An improved synthetic minority over-sampling technique (IMSMOTE) is developed to incorporate the randomness and probability into the traditional synthetic minority over-sampling technique (SMOTE) to enhance the quality of synthetic samples and the controllability of synthetic processes. IMSMOTE is then implemented along with the grey relational clustering (GRC) and the support vector machine (SVM) to facilitate a comprehensive assessment of the P2P credit risks. To enhance the associativity and functionality of the algorithm, a dynamic selection approach is integrated with GRC and then fed in the SVM's process of parameter adaptive adjustment to select the optimal critical value. A quantitative model is constructed to recognize key criteria via multidimensional representativeness.
Findings
A series of experiments based on real-world P2P data from Prosper Funding LLC demonstrates that our proposed model outperforms other existing approaches. It is also confirmed that the grey-based GRC approach with dynamic selection succeeds in reducing data dimensions, selecting a critical value, identifying key criteria, and IMSMOTE can efficiently handle the imbalanced data.
Originality/value
The grey-based machine-learning framework proposed in this work can be practically implemented by P2P platforms in predicting the borrowers' credit risks. The dynamic selection approach makes the first attempt in the literature to select a critical value and indicate key criteria in a dynamic, visual and quantitative manner.