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Article
Publication date: 20 December 2019

Guolei Wang, Xiaotong Hua, Jing Xu, Libin Song and Ken Chen

This paper aims to achieve automatically surface segmentation for painting different kinds of aircraft efficiently considering the demands of painting robot.

386

Abstract

Purpose

This paper aims to achieve automatically surface segmentation for painting different kinds of aircraft efficiently considering the demands of painting robot.

Design/methodology/approach

This project creatively proposed one method that accepts point cloud, outputs several blocks, each of which can be handled by ABB IRB 5500 in one station. Parallel PointNet (PPN) is proposed in this paper for better handling six dimensional aircraft data including every point normal. Through semantic segmentation of PPN, each surface has its own identity information indicating which part this surface belongs to. Then clustering considering constraints is applied to complete surface segmentation with identity information. To guarantee segmentation paintable and improve painting efficiency, different dexterous workspaces of IRB 5500 corresponding to different postures have been analyzed carefully.

Findings

The experiments confirm the effectiveness of the proposed surface segmentation method for painting different types of aircraft by IRB 5500. For semantic segmentation on aircraft data with point normal, PPN has higher precision than PointNet. In addition, the whole algorithm can efficiently segment one complex aircraft into qualified blocks, each of which has its own identity information, can be painted by IRB 5500 in one station and has fewer edges with other blocks.

Research limitations/implications

As the provided experiments indicate, the proposed method can segment one aircraft into qualified blocks automatically, which highly improves the efficiency in aircraft painting compared with traditional approaches. Moreover, the proposed method is able to provide identity information of each block, which is necessary for application of different paint parameters and different paint materials. In addition, final segmentation results by the proposed method behaves better than k-means cluster on variance of normal vector distance.

Originality/value

Inspired by semantic segmentation of 3 D point cloud, some improvements based on PointNet have been proposed for better handling segmentation of 6 D point cloud. By introducing normal vectors, semantic segmentation could be accomplished precisely for close points with opposite normal, such as wing upper and lower surfaces. Combining deep learning skills with traditional methods, the proposed method is proved to behave much better for surface segmentation task in aircraft painting.

Details

Assembly Automation, vol. 40 no. 2
Type: Research Article
ISSN: 0144-5154

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Article
Publication date: 20 December 2019

Chicheng Liu, Libin Song, Ken Chen and Jing Xu

This paper aims to present an image-based visual servoing algorithm for a multiple pin-in-hole assembly. This paper also aims to avoid the matching and tracking of image features…

1433

Abstract

Purpose

This paper aims to present an image-based visual servoing algorithm for a multiple pin-in-hole assembly. This paper also aims to avoid the matching and tracking of image features and the remaining robust against image defects.

Design/methodology/approach

The authors derive a novel model in the set space and design three image errors to control the 3 degrees of freedom (DOF) of a single-lug workpiece in the alignment task. Analytic computations of the interaction matrix that link the time variations of the image errors to the single-lug workpiece motions are performed. The authors introduce two approximate hypotheses so that the interaction matrix has a decoupled form, and an auto-adaptive algorithm is designed to estimate the interaction matrix.

Findings

Image-based visual servoing in the set space avoids the matching and tracking of image features, and these methods are not sensitive to image effects. The control law using the auto-adaptive algorithm is more efficient than that using a static interaction matrix. Simulations and real-world experiments are performed to demonstrate the effectiveness of the proposed algorithm.

Originality/value

This paper proposes a new visual servoing method to achieve pin-in-hole assembly tasks. The main advantage of this new approach is that it does not require tracking or matching of the image features, and its supplementary advantage is that it is not sensitive to image defects.

Details

Assembly Automation, vol. 40 no. 6
Type: Research Article
ISSN: 0144-5154

Keywords

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Article
Publication date: 22 April 2020

Libin Yang, Dong Wang, Hong Gao, Hui Cao, Yuzhen Zhao, Zongcheng Miao, Zhou Yang and Wanli He

This study aims to develop a new kind of functional low molecular weight organic dyes, which is highly efficient, meanwhile inexpensive and easily prepared and modified and can be…

100

Abstract

Purpose

This study aims to develop a new kind of functional low molecular weight organic dyes, which is highly efficient, meanwhile inexpensive and easily prepared and modified and can be used in photoacoustic (PA) imaging and photothermal therapy (PTT). To further realize the release of molecules under the biomedical condition, the releasing efficiency of micellar nanoparticles under different stimuli were represented.

Design/methodology/approach

A class of azo and Schiff base derivatives with different click reagents were characterized by PA imaging and photothermal (PT) experiments. The molecule with best PT effect was loaded into a temperature-stimuli-sensitive amphiphilic block copolymer which demonstrated the capability of releasing the polymers under the near-infrared (NIR) light of 650 nm.

Findings

The PA and PT effects of a series of azo and Schiff base derivatives with different click reagents were characterized. Introducing the click reagent F4-TCNQ can result in red shift of peaks of PA intensity. Stimulated with 650 nm laser irradiation, the polymer processed higher release rate than being stimulated by temperature stimuli.

Practical implications

This paper not only guides the design of NIR dyes with good PA intensity but also provides a method which has great potential for the application of NIR photothermal dyes in the field of biotechnology for controlled release.

Originality/value

This paper uses click reagents to modify azo and Schiff derivatives and an amphiphilic block copolymer under NIR light to realize controlled release.

Details

Pigment & Resin Technology, vol. 49 no. 4
Type: Research Article
ISSN: 0369-9420

Keywords

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Expert briefing
Publication date: 21 October 2016

Modest progress is underway in rebalancing towards more consumption and less reliance on exports and investment. GDP growth is on target, helped by buoyant housing and automobile…

Details

DOI: 10.1108/OXAN-DB214444

ISSN: 2633-304X

Keywords

Geographic
Topical
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Article
Publication date: 24 August 2023

Ramona Paloș

Although many studies emphasize the need to design programs to help students manage post-pandemic burnout, few address personal resources' mediating role in the relationship…

217

Abstract

Purpose

Although many studies emphasize the need to design programs to help students manage post-pandemic burnout, few address personal resources' mediating role in the relationship between positive self-evaluation and experienced academic burnout. The present study aims to investigate the mediating role of two personal resources (i.e. psychological capital and proactive coping) on the relationship between core self-evaluations and academic burnout.

Design/methodology/approach

The research was carried out in the first part of 2022, at the end of two years of online teaching. The sample consisted of 183 Romanian university students who voluntarily filled in four questionnaires that measured core self-evaluations, academic burnout, psychological capital and proactive coping. To verify the hypotheses, a mediation analysis using the PROCESS 4.0 macro in SPSS 23.0, Model 6 was conducted. The indirect effect was tested based on a bias-corrected bootstrapping procedure with 5,000 samples, and a bootstrap confidence interval (95% CI).

Findings

Results showed that students with a high level of core self-evaluations report a low level of burnout. Also, students with positive core self-evaluations are more likely to use their psychological resources (i.e. psychological capital) and act proactively (i.e. proactive coping) in dealing with challenging situations, which can increase their burnout. However, the overall effect of the core self-evaluations on burnout was lower in the case of mediation by students' personal resources.

Originality/value

These research findings highlight the role of personal resources in coping with a challenging context, being among the few studies that have focused on student burnout in the immediate post-pandemic period. Furthermore, by working with malleable personal resources that can be enhanced through instruction, this research underlines how students can be taught to assess and develop these resources to cope with a highly demanding educational context.

Details

Journal of Applied Research in Higher Education, vol. 16 no. 3
Type: Research Article
ISSN: 2050-7003

Keywords

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Article
Publication date: 30 September 2024

Ed Cottam and Pushkar.P. Jha

Decision-makers often struggle to combine advice with their own intuition. This study examines how advice-giver traits and decision-makers’ intuition influence advice uptake. We…

56

Abstract

Purpose

Decision-makers often struggle to combine advice with their own intuition. This study examines how advice-giver traits and decision-makers’ intuition influence advice uptake. We present a novel typology based on decision-makers’ trust in advice-givers and their perceived expertise.

Design/methodology/approach

This qualitative study uses a sample of publicly available interview data with 51 elite performers. Using inductive and content analysis, we explore the mediation between decision-makers’ intuitive competence (ability to effectively deploy intuition in interface with advice) and their autonomy (self-endorsement from past performance).

Findings

We identify four sources of advice: mentor advice, specialist advice, confidant advice and commentator advice. Drawing on instances of different sources of advice along varying degrees of trust and expertise, we propose a framework for interaction between intuitional competence and advice characteristics.

Originality/value

We offer a novel way of contextualising nuanced forms of advice and provide a structured typology of sources, characterised by trust and expertise. This typology and our findings help reconcile contradictions in decision-making research. Finally, we offer practical guidance for the uptake of advice.

Details

Management Decision, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0025-1747

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Article
Publication date: 22 August 2019

Jeremy Yee Li Yap, Chiung Chiung Ho and Choo-Yee Ting

The purpose of this paper is to perform a systematic review on the application of different multi-criteria decision-making (MCDM) methods in solving the site selection problem…

1678

Abstract

Purpose

The purpose of this paper is to perform a systematic review on the application of different multi-criteria decision-making (MCDM) methods in solving the site selection problem across multiple problem domains. The domains are energy generation, logistics, public services and retail facilities. This study aims to answer the following research questions: Which evaluating criteria were used for each site selection problem domain? Which MCDM methods were frequently applied in a particular site selection problem domain?

Design/methodology/approach

The goals of the systematic review were to identify the evaluating criteria as well as the MCDM method used for each problem domain. A total of 81 recent papers (2014–2018) including 32 papers published in conference proceedings and 49 journal articles from various databases including IEEE Xplore, PubMed, Springer, Taylor and Francis as well as ScienceDirect were evaluated.

Findings

This study has shown that site selection for energy generation facilities is the most active site selection problem domain, and that the analytic hierarchy process (AHP) method is the most commonly used MCDM method for site selection. For energy generation, the criteria which were most used were geographical elements, land use, cost and environmental impact. For logistics, frequently used criteria were geographical elements and distance, while for public services population density, supply and demand, geographical layout and cost were the criteria most used. Criteria useful for retail facilities were the size (space) of the store, demographics of the site, the site characteristics and rental of the site (cost).

Research limitations/implications

This study is limited to reviewing papers which were published in the years 2014–2018 only, and only covers the domains of energy generation, logistics, public services and retail facilities.

Practical implications

MCDM is a viable tool to be used for solving the site selection problem across the domains of energy generation, logistics, public services and retail facilities. The usage of MCDM continues to be relevant as a complement to machine learning, even as data originating from embedded IoT devices in built environments becomes increasingly Big Data like.

Originality/value

Previous systematic review studies for MDCM and built environments have either focused on studying the MCDM techniques itself, or have focused on the application of MCDM for site selection in a single problem domain. In this study, a critical review of MCDM techniques used for site selection as well as the critical criteria used during the MCDM process of site selection was performed on four different built environment domains.

Details

Built Environment Project and Asset Management, vol. 9 no. 4
Type: Research Article
ISSN: 2044-124X

Keywords

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Article
Publication date: 16 April 2020

Mohammad Mahdi Ershadi and Abbas Seifi

This study aims to differential diagnosis of some diseases using classification methods to support effective medical treatment. For this purpose, different classification methods…

244

Abstract

Purpose

This study aims to differential diagnosis of some diseases using classification methods to support effective medical treatment. For this purpose, different classification methods based on data, experts’ knowledge and both are considered in some cases. Besides, feature reduction and some clustering methods are used to improve their performance.

Design/methodology/approach

First, the performances of classification methods are evaluated for differential diagnosis of different diseases. Then, experts' knowledge is utilized to modify the Bayesian networks' structures. Analyses of the results show that using experts' knowledge is more effective than other algorithms for increasing the accuracy of Bayesian network classification. A total of ten different diseases are used for testing, taken from the Machine Learning Repository datasets of the University of California at Irvine (UCI).

Findings

The proposed method improves both the computation time and accuracy of the classification methods used in this paper. Bayesian networks based on experts' knowledge achieve a maximum average accuracy of 87 percent, with a minimum standard deviation average of 0.04 over the sample datasets among all classification methods.

Practical implications

The proposed methodology can be applied to perform disease differential diagnosis analysis.

Originality/value

This study presents the usefulness of experts' knowledge in the diagnosis while proposing an adopted improvement method for classifications. Besides, the Bayesian network based on experts' knowledge is useful for different diseases neglected by previous papers.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 13 no. 1
Type: Research Article
ISSN: 1756-378X

Keywords

Available. Open Access. Open Access

Abstract

Details

Journal of Intelligent Manufacturing and Special Equipment, vol. 4 no. 1
Type: Research Article
ISSN: 2633-6596

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