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Article
Publication date: 14 June 2022

Rie Isshiki, Ryota Kawamata, Shinji Wakao and Noboru Murata

The density method is one of the powerful topology optimization methods of magnetic devices. The density method has the advantage that it has a high degree of freedom of…

Abstract

Purpose

The density method is one of the powerful topology optimization methods of magnetic devices. The density method has the advantage that it has a high degree of freedom of shape expression which results in a high-performance design. On the other hand, it has also the drawback that unsuitable shapes for actually manufacturing are likely to be generated, e.g. checkerboards or grayscale. The purpose of this paper is to develop a method that enables topology optimization suitable for fabrication while taking advantage of the density method.

Design/methodology/approach

This study proposes a novel topology optimization method that combines convolutional neural network (CNN) as an effective smoothing filter with the density method and apply the method to the shield design with magnetic nonlinearity.

Findings

This study demonstrated some numerical examples verifying that the proposed method enables to efficiently obtain a smooth and easy-to-manufacture shield shape with high shielding ability. A network architecture suitable as smoothing filter was also exemplified.

Originality/value

In the field of magnetic field analysis, very few studies have verified the usefulness of smoothing by using CNN in the topology optimization of magnetic devices. This paper develops a novel topology optimization method that skillfully combines CNN with the nonlinear magnetic field analysis and also clarifies a suitable network architecture that makes it possible to obtain a target device shape that is easy to manufacture while minimizing the objective function value.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0332-1649

Keywords

Book part
Publication date: 16 August 2011

Avinash Arya

This note presents a method of teaching accounting problems involving the use of the effective interest method such as bonds, notes, capital leases, and installment sales…

Abstract

This note presents a method of teaching accounting problems involving the use of the effective interest method such as bonds, notes, capital leases, and installment sales. The method is conceptually sound and simpler than the traditional method found in current textbooks and stimulates student interest by focusing on the economics of the transaction and relating it to real-life examples.

To assess its pedagogical efficacy, the method was tested in the introductory and intermediate accounting classes. In both courses, the results indicate that students' test scores are significantly higher under the new method than the traditional method. It is hoped that this evidence of the superiority of the new method in a classroom environment will spur its adoption by instructors and textbook writers.

Details

Advances in Accounting Education: Teaching and Curriculum Innovations
Type: Book
ISBN: 978-1-78052-223-4

Open Access
Article
Publication date: 11 August 2022

Krishna Chauhan, Antti Peltokorpi, Rita Lavikka and Olli Seppänen

Prefabricated products are continually entering the building construction market; yet, the decision to use prefabricated products in a construction project is based mostly…

Abstract

Purpose

Prefabricated products are continually entering the building construction market; yet, the decision to use prefabricated products in a construction project is based mostly on personal preferences and the evaluation of direct costs. Researchers and practitioners have debated appropriate measurement systems for evaluating the impacts of prefabricated products and for comparing them with conventional on-site construction practices. The more advanced, cost–benefit approach to evaluating prefabricated products often inspires controversy because it may generate inaccurate results when converting non-monetary effects into costs. As prefabrication may affect multiple organisations and product subsystems, the method used to decide on production methods should consider multiple direct and indirect impacts, including nonmonetary ones. Thus, this study aims to develop a multi-criteria method to evaluate both the monetary and non-monetary impacts of prefabrication solutions to facilitate decision-making on whether to use prefabricated products.

Design/methodology/approach

Drawing upon a literature review, this research suggests a multi-criteria method that combines the choosing-by-advantage approach with a cost–benefit analysis. The method was presented for validation in focus group discussions and tested in a case involving a prefabricated bathroom.

Findings

The analysis indicates that the method helps a project’s stakeholders communicate about the relative merits of prefabrication and conventional construction while facilitating the final decision of whether to use prefabrication.

Originality/value

This research contributes a method of evaluating the monetary and non-monetary impacts of prefabricated products. The research underlines the need to evaluate the diverse benefits and sacrifices that stakeholder face when considering production methods in construction.

Details

Construction Innovation , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1471-4175

Keywords

Article
Publication date: 19 August 2022

Kadir Dönmez

This study aims to evaluate the performance of the most popular multi-objective programming scalarization methods in the literature for the aircraft sequencing and…

Abstract

Purpose

This study aims to evaluate the performance of the most popular multi-objective programming scalarization methods in the literature for the aircraft sequencing and scheduling problem (ASSP). These methods are the weighted sum method, weighted goal programming, the ε-constraint method, the elastic constraint method, weighted Tchebycheff and augmented weighted Tchebycheff.

Design/methodology/approach

First, the ASSP for a single runway case was modeled using mixed-integer programming considering the safety and operational constraints and the objectives of the minimization of total delay and total flight time for a sample airport. The objectives were then combined by using the multi-objective programming scalarization methods and various expected times of arrival–departure samples were run for the mathematical models. Finally, the methods were evaluated in terms of the number of nondominated solutions, superior nondominated solution and the average solution time using the Measurement of Alternatives and Ranking according to Compromise Solution method, which is a popular multi-criteria decision-making method.

Findings

Augmented Weighted Tchebycheff was found to be the most effective approach to ASSP in terms of the evaluation criteria followed by Weighted Tchebycheff and then weighted sum method.

Practical implications

The methodology presented in this study could provide more efficient air traffic management in terminal maneuvering areas when multiple objectives need to be optimized.

Originality/value

Although there are studies including the comparison of several scalarization methods for other problems, the comparison of the methods for ASSP has not yet been handled in the literature. As there are several stakeholders in the air traffic system, ASSP includes several objectives, and as a result, this problem can benefit from analyses using this comparison.

Details

Aircraft Engineering and Aerospace Technology, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 11 August 2022

Xiaoqi Wang, Jianfu Cao and Ye Cao

Adaptive slicing is a key step in 3D printing as it is closely related to the building time and the surface quality. This study aims to develop an adaptive layering…

Abstract

Purpose

Adaptive slicing is a key step in 3D printing as it is closely related to the building time and the surface quality. This study aims to develop an adaptive layering algorithm that can coordinate the optimization of printing quality and efficiency to meet different printing needs.

Design/methodology/approach

A multiobjective optimization model is established for printing quality, printing time and layer height based on the variation of surface features, profile slope and curvature of the model. The optimal solution is found by an improved method combining Newton's method and gradient method and adapts to different printing requirements by adjusting the parameter thresholds.

Findings

Several benchmarks are applied to verify this new method. The proposed method has also been compared with the uniform layering method, it reduces the volume error by 46.4% and shortens the printing time by 28.1% and is compared with five existing adaptive layering methods to demonstrate its superior performance.

Originality/value

Compared with other methods with only one layered result, this method is a demand-oriented algorithm that can obtain different results according to different needs and it can reach a trade-off between the building time and the surface quality.

Details

Rapid Prototyping Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 9 August 2022

Vinay Singh, Iuliia Konovalova and Arpan Kumar Kar

Explainable artificial intelligence (XAI) has importance in several industrial applications. The study aims to provide a comparison of two important methods used for…

Abstract

Purpose

Explainable artificial intelligence (XAI) has importance in several industrial applications. The study aims to provide a comparison of two important methods used for explainable AI algorithms.

Design/methodology/approach

In this study multiple criteria has been used to compare between explainable Ranked Area Integrals (xRAI) and integrated gradient (IG) methods for the explainability of AI algorithms, based on a multimethod phase-wise analysis research design.

Findings

The theoretical part includes the comparison of frameworks of two methods. In contrast, the methods have been compared across five dimensions like functional, operational, usability, safety and validation, from a practical point of view.

Research limitations/implications

A comparison has been made by combining criteria from theoretical and practical points of view, which demonstrates tradeoffs in terms of choices for the user.

Originality/value

Our results show that the xRAI method performs better from a theoretical point of view. However, the IG method shows a good result with both model accuracy and prediction quality.

Details

Benchmarking: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 16 August 2022

Zibo Li, Zhengxiang Yan, Shicheng Li, Guangmin Sun, Xin Wang, Dequn Zhao, Yu Li and Xiucheng Liu

The purpose of this paper is to overcome the application limitations of other multi-variable regression based on polynomials due to the huge computation room and time cost.

Abstract

Purpose

The purpose of this paper is to overcome the application limitations of other multi-variable regression based on polynomials due to the huge computation room and time cost.

Design/methodology/approach

In this paper, based on the idea of feature selection and cascaded regression, two strategies including Laguerre polynomials and manifolds optimization are proposed to enhance the accuracy of multi-variable regression. Laguerre polynomials were combined with the genetic algorithm to enhance the capacity of polynomials approximation and the manifolds optimization method was introduced to solve the co-related optimization problem.

Findings

Two multi-variable Laguerre polynomials regression methods are designed. Firstly, Laguerre polynomials are combined with feature selection method. Secondly, manifolds component analysis is adopted in cascaded Laguerre polynomials regression method. Two methods are brought to enhance the accuracy of multi-variable regression method.

Research limitations/implications

With the increasing number of variables in regression problem, the stable accuracy performance might not be kept by using manifold-based optimization method. Moreover, the methods mentioned in this paper are not suitable for the classification problem.

Originality/value

Experiments are conducted on three types of datasets to evaluate the performance of the proposed regression methods. The best accuracy was achieved by the combination of cascade, manifold optimization and Chebyshev polynomials, which implies that the manifolds optimization has stronger contribution than the genetic algorithm and Laguerre polynomials.

Details

Engineering Computations, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 9 August 2022

Xiangnan Liu and Kuanfang He

The purpose of this paper is to propose a new fault feature extraction scheme for the rolling element bearing.

Abstract

Purpose

The purpose of this paper is to propose a new fault feature extraction scheme for the rolling element bearing.

Design/methodology/approach

The generalized Stockwell transform (GST) and the singular value ratio spectrum (SVRS) methods are combined. A time-frequency distribution measurement criterion named the energy concentration measurement (ECM) is initially used to determine the parameter of the optimal GST method. Then, the optimal GST is applied to conduct a time-frequency transformation for a raw signal. Subsequently, the two-dimensional time-frequency matrix is obtained. Finally, the improved singular value decomposition (SVD) analysis is used to conduct a noise reduction of the time-frequency matrix. The SVRS is proposed to select the effective singular values. Furthermore, the time-domain feature of the impact signal is obtained by taking the inverse GST transform.

Findings

The simulated and experimental signals are used to verify the superiority of the proposed method over conventional methods. The obtained results show that the proposed method can effectively extract fault features of the rolling element bearing.

Research limitations/implications

This paper mainly discusses the application of GST and SVRS methods to analyze the weak fault feature extraction problem. The next research direction is to explore the application of the Hilbert Huang transform (HHT) and variational modal decomposition (VMD) in the impact feature extraction of rolling bearing.

Originality/value

In the present study, a new SVRS method is proposed to select the number of effective singular values. This paper proposed an effective way to obtain the fault feature in monitoring of rotating machinery.

Details

Engineering Computations, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0264-4401

Keywords

Open Access
Article
Publication date: 12 August 2022

Bolin Gao, Kaiyuan Zheng, Fan Zhang, Ruiqi Su, Junying Zhang and Yimin Wu

Intelligent and connected vehicle technology is in the ascendant. High-level autonomous driving places more stringent requirements on the accuracy and reliability of…

Abstract

Purpose

Intelligent and connected vehicle technology is in the ascendant. High-level autonomous driving places more stringent requirements on the accuracy and reliability of environmental perception. Existing research works on multitarget tracking based on multisensor fusion mostly focuses on the vehicle perspective, but limited by the principal defects of the vehicle sensor platform, it is difficult to comprehensively and accurately describe the surrounding environment information.

Design/methodology/approach

In this paper, a multitarget tracking method based on roadside multisensor fusion is proposed, including a multisensor fusion method based on measurement noise adaptive Kalman filtering, a global nearest neighbor data association method based on adaptive tracking gate, and a Track life cycle management method based on M/N logic rules.

Findings

Compared with fixed-size tracking gates, the adaptive tracking gates proposed in this paper can comprehensively improve the data association performance in the multitarget tracking process. Compared with single sensor measurement, the proposed method improves the position estimation accuracy by 13.5% and the velocity estimation accuracy by 22.2%. Compared with the control method, the proposed method improves the position estimation accuracy by 23.8% and the velocity estimation accuracy by 8.9%.

Originality/value

A multisensor fusion method with adaptive Kalman filtering of measurement noise is proposed to realize the adaptive adjustment of measurement noise. A global nearest neighbor data association method based on adaptive tracking gate is proposed to realize the adaptive adjustment of the tracking gate.

Details

Smart and Resilient Transportation, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2632-0487

Keywords

Article
Publication date: 4 August 2022

Daniel Amos

Despite the increasing discourse on mixed methods (MM) in academic literature, less attention has been focused on its methodological development in the built environment…

Abstract

Purpose

Despite the increasing discourse on mixed methods (MM) in academic literature, less attention has been focused on its methodological development in the built environment in developing countries. This paper aims to examine the basis and challenges of the application of MM for health-care facilities management (FM) research in Ghana.

Design/methodology/approach

This paper adopts autoethnography as its research method, coupled with a scholarly review of methodological literature to position a technical view on the application of mixed methods for health-care FM research in a developing country.

Findings

This paper contributes and lends support to the methodological strength of MM as epistemologically coherent and useful for understanding the intricacies of health-care FM. This paper advances the proposition that the nascent stage of FM development in Ghana, paucity of literature, epistemological and axiological considerations underscore the choice of a sequential MM. The attitude of research participants, ethical challenges and time-lapse for data analysis were observed as practical challenges.

Research limitations/implications

Discussion of data integration is excluded.

Practical implications

This paper provides a nuanced understanding of the concept of MM in health-care FM and set forth practical recommendations worthy to enhance the application of MM research.

Originality/value

This paper is among the few focusing on methodological discussion of health-care FM. This paper proposes a framework to guide researchers in the application of mixed methods.

Details

Facilities , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0263-2772

Keywords

1 – 10 of over 283000