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Article
Publication date: 14 February 2019

Xiaobo Wang, Zhipeng Li, Wen Zhan, Jesong Tu, Xiaohua Zuo, Xiangyi Deng and Boyi Gui

This study aims to expand the reliability and special functions of lightweight materials for high-end equipment and green manufacturing, so that it is the first such…

Abstract

Purpose

This study aims to expand the reliability and special functions of lightweight materials for high-end equipment and green manufacturing, so that it is the first such research to carry out nano-composite technology of nickel-coated carbon nanotubes (Ni-CNTs)-based titanium-zirconium chemical conversion on aluminum alloy substrate.

Design/methodology/approach

Corrosion behavior of various coatings was investigated using dropping corrosion test, linear polarization and electrochemical impedance spectroscopy. The results showed that the corrosion resistance of the nano-composite conversion coatings was significantly improved to compare with the conventional titanium-zirconium conversion coating. The morphology and microdomain characteristics of the nano-composite conversion coatings were characterized by SEM/eds/EPMA, which indicated that the CNT or Ni-CNTs addition promoting the integrity coverage of coatings in a short time.

Findings

Surface morphology of titanium-zirconium (Ti-Zr)/Ni-CNT specimens exhibited smooth, compact and little pores. The nano-composite conversion coatings are mainly composed of Al, O, C and Ti elements and contain a small amount of F and Zr elements, which illuminated that CNT or Ni-CNT addition could co-deposit with aluminum and titanium metal oxides.

Originality/value

The study of corrosion resistance of nano-composite conversion coatings and the micro-zone film-formation characteristics would be provided theoretical support for the development of basic research on surface treatment of aluminum alloys.

Details

Anti-Corrosion Methods and Materials, vol. 66 no. 3
Type: Research Article
ISSN: 0003-5599

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Article
Publication date: 16 March 2020

Chunlei Li, Chaodie Liu, Zhoufeng Liu, Ruimin Yang and Yun Huang

The purpose of this paper is to focus on the design of automated fabric defect detection based on cascaded low-rank decomposition and to maintain high quality control in…

Abstract

Purpose

The purpose of this paper is to focus on the design of automated fabric defect detection based on cascaded low-rank decomposition and to maintain high quality control in textile manufacturing.

Design/methodology/approach

This paper proposed a fabric defect detection algorithm based on cascaded low-rank decomposition. First, the constructed Gabor feature matrix is divided into a low-rank matrix and sparse matrix using low-rank decomposition technique, and the sparse matrix is used as priori matrix where higher values indicate a higher probability of abnormality. Second, we conducted the second low-rank decomposition for the constructed texton feature matrix under the guidance of the priori matrix. Finally, an improved adaptive threshold segmentation algorithm was adopted to segment the saliency map generated by the final sparse matrix to locate the defect regions.

Findings

The proposed method was evaluated on the public fabric image databases. By comparing with the ground-truth, the average detection rate of 98.26% was obtained and is superior to the state-of-the-art.

Originality/value

The cascaded low-rank decomposition was first proposed and applied into the fabric defect detection. The quantitative value shows the effectiveness of the detection method. Hence, the proposed method can be used for accurate defect detection and automated analysis system.

Details

International Journal of Clothing Science and Technology, vol. 32 no. 4
Type: Research Article
ISSN: 0955-6222

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Article
Publication date: 1 September 2004

Yantao Shen, Ning Xi, King W.C. Lai and Wen J. Li

This paper presents our development of a novel Internet‐based E‐manufacturing system to advance applications in micromanipulation and microassembly using an in situ

Abstract

This paper presents our development of a novel Internet‐based E‐manufacturing system to advance applications in micromanipulation and microassembly using an in situ polyvinylidene fluoride (PVDF) piezoelectric sensor. In this system, to allow close monitoring of magnitude and direction of microforces (adhesion, surface tension, friction, and assembly forces) acting on microdevices during assembly, the PVDF polymer films are used to fabricate the highly sensitive 1D and 2D sensors, which can detect the real‐time microforce and force rate information during assembly processes. This technology has been successfully used to perform a tele‐assembly of the surface MEMS structures with force/visual feedback via Internet between USA and Hong Kong. Ultimately, this E‐manufacture system will provide a critical and major step towards the development of automated micromanufacturing processes for batch assembly of microdevices.

Details

Assembly Automation, vol. 24 no. 3
Type: Research Article
ISSN: 0144-5154

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Article
Publication date: 1 September 2004

Yantao Shen, Ning Xi, King W.C. Lai and Wen J. Li

This paper presents our development of a novel force and force rate sensory system to advance applications in micromanipulation using an in situ polyvinylidene fluoride…

Abstract

This paper presents our development of a novel force and force rate sensory system to advance applications in micromanipulation using an in situ polyvinylidene fluoride (PVDF) piezoelectric sensor. To allow close monitoring of magnitude and direction of microforces acting on microdevices during manipulation, PVDF ploymer films are used to fabricate highly sensitive 1D and 2D sensors to detect real‐time microforce and force rate information during the manipulation process. The sensory system with a resolution in the range of sub‐micronewtons can be applied effectively to develop a technology on the force‐reflection microassembly of surface MEMS structures. In addition, a tele‐micromanipulation platform, which can be used to perform tele‐microassembly of the MEMS structures and tele‐cell‐manipulation with force/haptic feedback via Internet was also built successfully.

Details

Sensor Review, vol. 24 no. 3
Type: Research Article
ISSN: 0260-2288

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Article
Publication date: 7 January 2021

Saba Gharehdash, Bre-Anne Louise Sainsbury, Milad Barzegar, Igor B. Palymskiy and Pavel A. Fomin

This research study aims to develop regular cylindrical pore network models (RCPNMs) to calculate topology and geometry properties of explosively created fractures along…

Abstract

Purpose

This research study aims to develop regular cylindrical pore network models (RCPNMs) to calculate topology and geometry properties of explosively created fractures along with their resulting hydraulic permeability. The focus of the investigation is to define a method that generates a valid geometric and topologic representation from a computational modelling point of view for explosion-generated fractures in rocks. In particular, extraction of geometries from experimentally validated Eulerian smoothed particle hydrodynamics (ESPH) approach, to avoid restrictions for image-based computational methods.

Design/methodology/approach

Three-dimensional stabilized ESPH solution is required to model explosively created fracture networks, and the accuracy of developed ESPH is qualitatively and quantitatively examined against experimental observations for both peak detonation pressures and crack density estimations. SPH simulation domain is segmented to void and solid spaces using a graphical user interface, and the void space of blasted rocks is represented by a regular lattice of spherical pores connected by cylindrical throats. Results produced by the RCPNMs are compared to three pore network extraction algorithms. Thereby, once the accuracy of RCPNMs is confirmed, the absolute permeability of fracture networks is calculated.

Findings

The results obtained with RCPNMs method were compared with three pore network extraction algorithms and computational fluid dynamics method, achieving a more computational efficiency regarding to CPU cost and a better geometry and topology relationship identification, in all the cases studied. Furthermore, a reliable topology data that does not have image-based pore network limitations, and the effect of topological disorder on the computed absolute permeability is minor. However, further research is necessary to improve the interpretation of real pore systems for explosively created fracture networks.

Practical implications

Although only laboratory cylindrical rock specimens were tested in the computational examples, the developed approaches are applicable for field scale and complex pore network grids with arbitrary shapes.

Originality/value

It is often desirable to develop an integrated computational method for hydraulic conductivity of explosively created fracture networks which segmentation of fracture networks is not restricted to X-ray images, particularly when topologic and geometric modellings are the crucial parts. This research study provides insight to the reliable computational methods and pore network extraction algorithm selection processes, as well as defining a practical framework for generating reliable topological and geometrical data in a Eulerian SPH setting.

Details

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

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Article
Publication date: 14 October 2019

Riccardo Mangiaracina, Alessandro Perego, Arianna Seghezzi and Angela Tumino

The purpose of this paper is twofold: first, to review and classify scientific publications dealing with those innovative solutions aimed at increasing the efficiency of…

Abstract

Purpose

The purpose of this paper is twofold: first, to review and classify scientific publications dealing with those innovative solutions aimed at increasing the efficiency of last-mile delivery in business to consumer (B2C) e-commerce; and, second, to outline directions for future research in this field.

Design/methodology/approach

The review is based on 75 papers published between 2001 and 2019 in international peer-reviewed journals or proceedings of conferences, retrieved from bibliographic databases and science search engines.

Findings

Due to its importance in affecting the overall logistics costs and, as a consequence, the economic sustainability of a B2C e-commerce initiative, last-mile delivery process deserves particular attention in order to be optimised. The review highlights that, among the main factors affecting its cost, there are the probability to have failed deliveries, the customer density in the delivery areas and the degree of automation of the process. Innovative and viable last-mile delivery solutions – which may impact the mentioned drivers – include parcel lockers, crowdsourcing logistics, mapping the consumer presence at home and dynamic pricing policies. Eventually, some gaps and areas for further research activities have been identified (e.g. mapping customer behaviour, crowdsourcing logistics).

Originality/value

This review offers interesting insights to both academics and practitioners. On the academic side, it analyses and classifies relevant literature about innovative and efficiency-oriented last-mile delivery solutions, proposing directions for future research efforts. On the managerial side, it presents a holistic framework of the main factors affecting last-mile delivery cost and of viable innovative solutions that may be implemented to increase efficiency.

Details

International Journal of Physical Distribution & Logistics Management, vol. 49 no. 9
Type: Research Article
ISSN: 0960-0035

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Article
Publication date: 13 August 2020

Mayur Pratap Singh, Dinesh Kumar Shukla, Rajneesh Kumar and Kanwer Singh Arora

The key purpose of conducting this review is to identify the issues that affect the structural integrity of pipeline structures. Heat affected zone (HAZ) has been…

Abstract

Purpose

The key purpose of conducting this review is to identify the issues that affect the structural integrity of pipeline structures. Heat affected zone (HAZ) has been identified as the weak zone in pipeline welds which is prone to have immature failures

Design/methodology/approach

In the present work, literature review is conducted on key issues related to the structural integrity of pipeline steel welds. Mechanical and microstructural transformations that take place during welding have been systematically reviewed in the present review paper.

Findings

Key findings of the present review underline the role of brittle microstructure phases, and hard secondary particles present in the matrix are responsible for intergranular and intragranular cracks.

Research limitations/implications

The research limitations of the present review are new material characterization techniques that are not available in developing countries.

Practical implications

The practical limitations are new test methodologies and associated cost.

Social implications

The fracture of pipelines significantly affects the surrounding ecology. The continuous spillage of oil pollutes the land and water of the surroundings.

Originality/value

The present review contains recent and past studies conducted on welded pipeline steel structures. The systematic analysis of studies conducted so far highlights various bottlenecks of the welding methods.

Details

International Journal of Structural Integrity, vol. 12 no. 3
Type: Research Article
ISSN: 1757-9864

Keywords

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Article
Publication date: 25 February 2014

Guoli Ji, Yong Zeng, Zijiang Yang, Congting Ye and Jingci Yao

The time complexity of most multiple sequence alignment algorithm is O(N2) or O(N3) (N is the number of sequences). In addition, with the development of biotechnology, the…

Abstract

Purpose

The time complexity of most multiple sequence alignment algorithm is O(N2) or O(N3) (N is the number of sequences). In addition, with the development of biotechnology, the amount of biological sequences grows significantly. The traditional methods have some difficulties in handling large-scale sequence. The proposed Lemk_MSA method aims to reduce the time complexity, especially for large-scale sequences. At the same time, it can keep similar accuracy level compared to the traditional methods.

Design/methodology/approach

LemK_MSA converts multiple sequence alignment into corresponding 10D vector alignment by ten types of copy modes based on Lempel-Ziv. Then, it uses k-means algorithm and NJ algorithm to divide the sequences into several groups and calculate guide tree of each group. A complete guide tree for multiple sequence alignment could be constructed by merging guide tree of every group. Moreover, for large-scale multiple sequence, Lemk_MSA proposes a GPU-based parallel way for distance matrix calculation.

Findings

Under this approach, the time efficiency to process multiple sequence alignment can be improved. The high-throughput mouse antibody sequences are used to validate the proposed method. Compared to ClustalW, MAFFT and Mbed, LemK_MSA is more than ten times efficient while ensuring the alignment accuracy at the same time.

Originality/value

This paper proposes a novel method with sequence vectorization for multiple sequence alignment based on Lempel-Ziv. A GPU-based parallel method has been designed for large-scale distance matrix calculation. It provides a new way for multiple sequence alignment research.

Details

Engineering Computations, vol. 31 no. 2
Type: Research Article
ISSN: 0264-4401

Keywords

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Article
Publication date: 8 June 2021

Jia Luo, Yongqiang Li and Yu Che

Regarding the interpersonal influence of customer anger on frontline employees (FLEs) in service encounters, existing findings remain mixed. Building on emotion as a…

Abstract

Purpose

Regarding the interpersonal influence of customer anger on frontline employees (FLEs) in service encounters, existing findings remain mixed. Building on emotion as a social information model and appraisal theory, this study aims to focus on two dimensions of customer anger – intensity and relevance with FLEs and examined their divergent effects on FLEs’ immediate recovery performance.

Design/methodology/approach

This study conducted a questionnaire survey of 366 Chinese FLEs in the hospitality and tourism industries. Hierarchical regressions and bootstrap analysis for nonlinear mediated relationships were used to test the hypotheses.

Findings

The results suggested a U-shaped curvilinear relationship between the intensity of customer anger and FLEs’ recovery performance and a positive linear relationship between relevance with FLEs of customer anger and FLEs’ recovery performance. Moreover, the mediating effects of FLEs’ emotional anger and cognitive perceived threat were confirmed.

Practical implications

Service managers should improve FLEs’ awareness of unconscious emotional contagion and encourage them to shoulder responsibility actively even if customer anger is not related to them. In addition, complaining customers can learn how to strategically express anger to get good remedies.

Originality/value

This paper examines the divergent effects of two dimensions of customer anger on FLEs, advancing the understanding of customer anger in the service interaction. It is also the first to suggest the U-shaped nonlinear effect of customer anger intensity on employees’ service outcomes and its underlying mechanisms, reconciling mixed findings.

Details

Nankai Business Review International, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-8749

Keywords

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Article
Publication date: 7 August 2017

Wei-Chao Lin, Shih-Wen Ke and Chih-Fong Tsai

Data mining is widely considered necessary in many business applications for effective decision-making. The importance of business data mining is reflected by the…

Abstract

Purpose

Data mining is widely considered necessary in many business applications for effective decision-making. The importance of business data mining is reflected by the existence of numerous surveys in the literature focusing on the investigation of related works using data mining techniques for solving specific business problems. The purpose of this paper is to answer the following question: What are the widely used data mining techniques in business applications?

Design/methodology/approach

The aim of this paper is to examine related surveys in the literature and thus to identify the frequently applied data mining techniques. To ensure the recent relevance and quality of the conclusions, the criterion for selecting related studies are that the works be published in reputed journals within the past 10 years.

Findings

There are 33 different data mining techniques employed in eight different application areas. Most of them are supervised learning techniques and the application area where such techniques are most often seen is bankruptcy prediction, followed by the areas of customer relationship management, fraud detection, intrusion detection and recommender systems. Furthermore, the widely used ten data mining techniques for business applications are the decision tree (including C4.5 decision tree and classification and regression tree), genetic algorithm, k-nearest neighbor, multilayer perceptron neural network, naïve Bayes and support vector machine as the supervised learning techniques and association rule, expectation maximization and k-means as the unsupervised learning techniques.

Originality/value

The originality of this paper is to survey the recent 10 years of related survey and review articles about data mining in business applications to identify the most popular techniques.

Details

Kybernetes, vol. 46 no. 7
Type: Research Article
ISSN: 0368-492X

Keywords

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