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Article
Publication date: 1 April 2019

Peide Liu, Xiaoxiao Liu and Hongyu Yang

Accurately judging the quality of marine economic development is the premise of grasping the level and status of marine economic development. In order to scientifically…

Abstract

Purpose

Accurately judging the quality of marine economic development is the premise of grasping the level and status of marine economic development. In order to scientifically evaluate the development quality of regional marine economy, the purpose of this paper is to select the marine area of Qingdao as the research object, and construct a marine economic development quality evaluation index system with 16 indicators.

Design/methodology/approach

The raw data is normalized by the range conversion method, and the weight of the index is determined by the information entropy model. Further, the grey relational analysis (GRA) method is used to evaluate the quality of marine economic development of Qingdao from 2012 to 2017.

Findings

The results show that the marine economic development capacity of Qingdao is with the generally increasing trend, the total marine economy is with on the rising trend, the marine storage and transportation capacity, and marine ecological environment are first decreased, and then increased. The utilization of marine resources is generally decreasing, and the comprehensive management of oceans varies with the changes of environment and economy. Therefore, in view of the development capacity of marine economy, the coordinated development of economy and environment should be carried out.

Originality/value

This paper uses the GRA to evaluate the quality of marine economic development and provides a reference for the development of marine economy in Qingdao.

Details

Marine Economics and Management, vol. 2 no. 1
Type: Research Article
ISSN: 2516-158X

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Article
Publication date: 5 November 2018

Hui Zhao, Shengnan Li, Hongyu Yang and Quan Zhou

Variable fractional delay filtering is an important technology in signal processing; the research shows that all-pass variable fractional delay (VFD) filters achieve…

Abstract

Purpose

Variable fractional delay filtering is an important technology in signal processing; the research shows that all-pass variable fractional delay (VFD) filters achieve higher design accuracy than FIR VFD filters; therefore, the design, analysis and implementation of all-pass VFD filters are of great importance.

Design/methodology/approach

In this paper, a two-stage approach for the design of general 1-D stable VFD all-pass filters is proposed. The method takes the desired group delay range [N−1, N], where N is the filter order.

Findings

The design algorithm is decomposed into two design stages: first, a set of fixed delay all-pass filters are designed by minimizing a set of objective functions defined in terms of approximating error criterion and filter stability constraint. Then, the design result is determined by fitting each of the fixed delay all-pass filter coefficients as 1-D polynomials. A design example together with its comparisons with those of the recent literature studies is given to justify the effectiveness of the proposed design method.

Originality/value

An illustrating design example shows that the method proposed can achieve better filter performances than the existing ones.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 37 no. 6
Type: Research Article
ISSN: 0332-1649

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Article
Publication date: 5 June 2007

Hongyu Yang, Joseph Mathew and Lin Ma

The purpose of this article is to present a new application of pursuit‐based analysis for diagnosing rolling element bearing faults.

Abstract

Purpose

The purpose of this article is to present a new application of pursuit‐based analysis for diagnosing rolling element bearing faults.

Design/methodology/approach

Intelligent diagnosis of rolling element bearing faults in rotating machinery involves the procedure of feature extraction using modern signal processing techniques and artificial intelligence technique‐based fault detection and identification. This paper presents a comparative study of both the basis and matching pursuits when applied to fault diagnosis of rolling element bearings using vibration analysis.

Findings

Fault features were extracted from vibration acceleration signals and subsequently fed to a feed forward neural network (FFNN) for classification. The classification rate and mean square error (MSE) were calculated to evaluate the performance of the intelligent diagnostic procedure. Results from the basis pursuit fault diagnosis procedure were compared with the classification result of a matching pursuit feature‐based diagnostic procedure. The comparison clearly illustrates that basis pursuit feature‐based fault diagnosis is significantly more accurate than matching pursuit feature‐based fault diagnosis in detecting these faults.

Practical implications

Intelligent diagnosis can reduce the reliance on experienced personnel to make expert judgements on the state of the integrity of machines. The proposed method has the potential to be extensively applied in various industrial scenarios, although this application concerned rolling element bearings only. The principles of the application are directly translatable to other parts of complex machinery.

Originality/value

This work presents a novel intelligent diagnosis strategy using pursuit features and feed forward neural networks. The value of the work is to ease the burden of making decisions on the integrity of plant through a manual program in condition monitoring and diagnostics particularly of complex pieces of plant.

Details

Journal of Quality in Maintenance Engineering, vol. 13 no. 2
Type: Research Article
ISSN: 1355-2511

Keywords

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Article
Publication date: 17 September 2020

Ning Yang, Zhelong Wang, Hongyu Zhao, Jie Li and Sen Qiu

Dyadic interactions are significant for human life. Most body sensor networks-based research studies focus on daily actions, but few works have been done to recognize…

Abstract

Purpose

Dyadic interactions are significant for human life. Most body sensor networks-based research studies focus on daily actions, but few works have been done to recognize affective actions during interactions. The purpose of this paper is to analyze and recognize affective actions collected from dyadic interactions.

Design/methodology/approach

A framework that combines hidden Markov models (HMMs) and k-nearest neighbor (kNN) using Fisher kernel learning is presented in this paper. Furthermore, different features are considered according to the interaction situations (positive situation and negative situation).

Findings

Three experiments are conducted in this paper. Experimental results demonstrate that the proposed Fisher kernel learning-based framework outperforms methods using Fisher kernel-based approach, using only HMMs and kNN.

Practical implications

The research may help to facilitate nonverbal communication. Moreover, it is important to equip social robots and animated agents with affective communication abilities.

Originality/value

The presented framework may gain strengths from both generative and discriminative models. Further, different features are considered based on the interaction situations.

Details

Sensor Review, vol. 40 no. 5
Type: Research Article
ISSN: 0260-2288

Keywords

Content available
Article
Publication date: 23 July 2020

Rami Mustafa A. Mohammad

Spam emails classification using data mining and machine learning approaches has enticed the researchers' attention duo to its obvious positive impact in protecting…

Abstract

Spam emails classification using data mining and machine learning approaches has enticed the researchers' attention duo to its obvious positive impact in protecting internet users. Several features can be used for creating data mining and machine learning based spam classification models. Yet, spammers know that the longer they will use the same set of features for tricking email users the more probably the anti-spam parties might develop tools for combating this kind of annoying email messages. Spammers, so, adapt by continuously reforming the group of features utilized for composing spam emails. For that reason, even though traditional classification methods possess sound classification results, they were ineffective for lifelong classification of spam emails duo to the fact that they might be prone to the so-called “Concept Drift”. In the current study, an enhanced model is proposed for ensuring lifelong spam classification model. For the evaluation purposes, the overall performance of the suggested model is contrasted against various other stream mining classification techniques. The results proved the success of the suggested model as a lifelong spam emails classification method.

Details

Applied Computing and Informatics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2634-1964

Keywords

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Article
Publication date: 24 November 2020

Qi Xiao, Rui Wang, Hongyu Sun and Limin Wang

The paper aims to build a new objective evaluation method of fabric pilling by combining an integrated image analysis technology with a deep learning algorithm.

Abstract

Purpose

The paper aims to build a new objective evaluation method of fabric pilling by combining an integrated image analysis technology with a deep learning algorithm.

Design/methodology/approach

Series of image analysis techniques were adopted. First, a Fourier transform transformed images into the frequency domain. The optimal resolution matrix of an exponential high-pass filter was determined by combining the energy algorithm. Second, the multidimensional discrete wavelet transform determined the optimal division level. Third, the iterative threshold method was used to enhance images to obtain a complete and clear pilling ball images. Finally, the deep learning algorithm was adopted to train data from pilling ball images, and the pilling levels were classified according to the learning features.

Findings

The paper provides a new insight about how to objectively evaluate fabric pilling grades. Results of the experiment indicate that the proposed objective evaluation method can obtain clear and complete pilling information and the classification accuracy rate of the deep learning algorithm is 94.2%, whose structures are rectified linear unit (ReLU) activation function, four hidden layers, cross-entropy learning rules and the regularization method.

Research limitations/implications

Because the methodology of the paper is based on woven fabric, the research study’s results may lack generalizability. Therefore, researchers are encouraged to test other kinds of fabric further, such as knitted and unwoven fabrics.

Originality/value

Combined with a series of image analysis technology, the integrated method can effectively extract clear and complete pilling information from pilled fabrics. Pilling grades can be classified by the deep learning algorithm with learning pilling information.

Details

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

Keywords

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Article
Publication date: 24 September 2020

Qin Kang, Yicheng Fan, Kun Zhang, Xiaolang Chen, Hongyu San, Yiqing Chen and Heming Zhao

With excellent mechanic properties and hydrogen embrittlement (HE) resistance, 12Cr2Mo1R(H) steel is suitable to make hot-wall hydrogenation reactors. However, longtime…

Abstract

Purpose

With excellent mechanic properties and hydrogen embrittlement (HE) resistance, 12Cr2Mo1R(H) steel is suitable to make hot-wall hydrogenation reactors. However, longtime exposure to a harsh environment of high-pressure hydrogen at medium temperature in practical application would still induce severe hydrogen uptake and eventually damage the mechanical properties of the steel. The study aims to evaluate the HE resistance of the steel under different tensile strain rates after hydrogen charging and analyze the hydrogen effect from atomic level.

Design/methodology/approach

This research studied the HE properties of 12Cr2Mo1R(H) steel by slow strain rate tests. Meanwhile, the effect of hydrogen on the structures and the mechanical properties of the simplified models of the steel was also investigated by first-principle calculations.

Findings

Experimental results showed that after hydrogen pre-charging in this work, hydrogen had little effect on the microstructure of the steel. The elongations and reduction of cross-sectional area of the samples reduced a lot, by contrast, the yield and tensile strengths changed slightly. The 12Cr2Mo1R(H) steel was not very susceptible to HE with a maximum embrittlement index of about 20.00%. First principles calculation results showed that after H dissolution, lattice distortion occurred and interstitial H atoms would preferentially occupy the tetrahedral interstitial site in bcc-Fe crystal and increase the stability of the supercells. With the increase of H atoms added into the simplified model, the steel still possessed a good ductility and toughness at a low hydrogen concentration, while the material would become brittle as the concentration of hydrogen continued to increase.

Originality/value

These finds can provide valuable information for subsequent HE studies on this steel.

Details

Anti-Corrosion Methods and Materials, vol. 67 no. 6
Type: Research Article
ISSN: 0003-5599

Keywords

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Article
Publication date: 3 June 2019

Ying Huang, Nu-nu Wang, Hongyu Zhang and Jianqiang Wang

The purpose of this paper is to propose a model for product recommendation to improve the accuracy of recommendation based on the current search engines used in e-commerce…

Abstract

Purpose

The purpose of this paper is to propose a model for product recommendation to improve the accuracy of recommendation based on the current search engines used in e-commerce platforms like Tmall.com.

Design/methodology/approach

First, the proposed model comprehensively considers price, trust and online reviews, which all represent critical factors in consumers’ purchasing decisions. Second, the model introduces the quantization methods for these criteria incorporating fuzzy theory. Third, the model uses a distance measure between two single valued neutrosophic sets based on the prioritized average operator to consolidate the influences of positive, neutral and negative comments. Finally, the model uses multi-criteria decision-making methods to integrate the influences of price, trust and online reviews on purchasing decisions to generate recommendations.

Findings

To demonstrate the feasibility and efficiency of the proposed model, a case study is conducted based on Tmall.com. The results of case study indicate that the recommendations of our model perform better than those of current search engines of Tmall.com. The proposed model can significantly improve the accuracy of product recommendations based on search engines.

Originality/value

The product recommendation method can meet the critical challenge from the search engines on e-commerce platforms. In addition, the proposed method could be used in practice to develop a new application for e-commerce platforms.

Details

Kybernetes, vol. 48 no. 6
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 28 November 2019

Shijing Liu, Hongyu Jin, Chunlu Liu, Benzheng Xie and Anthony Mills

The purpose of this paper is to examine public–private partnership (PPP) approaches for the construction of rental retirement villages in Australia and to allocate the…

Abstract

Purpose

The purpose of this paper is to examine public–private partnership (PPP) approaches for the construction of rental retirement villages in Australia and to allocate the investment proportions under a certain project return rate among three investors which are the government, private sectors and pension funds. The apportionment will achieve a minimum overall investment risk for the project.

Design/methodology/approach

Capital structure, particularly determination of investment apportionment proportions, is one of the key factors affecting the success of PPP rental retirement villages. Markowitz mean-variance model was applied to examine the investment allocations with minimum project investment risks under a certain projected return rate among the PPP partners for the construction of rental retirement villages.

Findings

The research findings validate the feasibility of the inclusion of pension funds in the construction of PPP rental retirement villages and demonstrate the existence of relationships between the project return rate and the investment allocation proportions.

Originality/value

This paper provides a quantitative approach for determination of the investment proportions among PPP partners to enrich the theory of PPP in relation to the construction of rental retirement villages. This has implications for PPP partners and can help these stakeholders make vital contributions in developing intellectual wealth in the PPP investment area while providing them with a detailed guide to decision making and negotiation in relation to investment in PPP rental retirement villages.

Details

Built Environment Project and Asset Management, vol. 10 no. 1
Type: Research Article
ISSN: 2044-124X

Keywords

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Article
Publication date: 21 February 2019

Lin Liu, Hongyu Su, Xue Li, Yanan Wang, Qiang Zhang and Jianhua Qian

This paper aims to evaluate the inhibitive effect and adsorption behavior of the 2-amino-5-thiol-1,3,4-thiadiazole vanillin (A) on copper in 3 per cent NaCl solution.

Abstract

Purpose

This paper aims to evaluate the inhibitive effect and adsorption behavior of the 2-amino-5-thiol-1,3,4-thiadiazole vanillin (A) on copper in 3 per cent NaCl solution.

Design/methodology/approach

A thiazole Schiff bases were synthesized, named, 2-amino-5-thiol-1,3,4-thiadiazole vanillin (A), which was fabricated respectively on copper surface by the molecular self-assembled. Evaluation was carried out by electrochemical measurement and surface analysis techniques. Measurement of static friction coefficient scanning electron microscopy and Contact angle analysis were applied, and it is finally confirmed the existence of the adsorbed film. The inhibitive mechanism of A was evaluated by means of quantitative calculation and molecular dynamics simulation.

Findings

The electrochemical measurement indicated that the self-assembled molecular film can effectively inhibit the corrosion of copper sheet, when the concentration was 15 mmol⋅L−1 and the assembly time was 6 h, the corrosion inhibition effect was the best, reaching as high as 97.5 per cent. Scanning electron microscopy results showed that the Schiff base compound forms a protective film on the surface of the copper, which effectively blocks the transfer of corrosion particles to the metal substrate, thereby inhibiting the occurrence of corrosion. Adsorption behavior of A followed the Langmuir’s adsorption isotherm and attributed to mixed-type adsorption. The results of Quantitative calculation and molecular dynamics simulation showed that A was adsorbed on Cu (111) surface in parallel.

Research limitations/implications

In this study, the corrosion inhibition properties of Schiff base film were investigated by combining theory with experiment. Theoretical calculation is helpful to guide the synthesis of efficient and environmentally friendly corrosion inhibitors.

Practical implications

The damage caused by metal corrosion is great. The self-assembled Schiff base membrane synthesized in this paper is simple and compact, and the corrosion inhibition efficiency of copper in 3 per cent NaCl solution is 97.5 per cent.

Social implications

Inhibition of metal corrosion can better save energy and reduce economic losses.

Originality/value

The synthesized Schiff base was prepared on the copper surface by the molecular self-assembled. The Schiff base membrane has a good corrosion inhibition effect on copper in 3 per cent NaCl solution, and the corrosion inhibition efficiency is up to 97.5 per cent.

Details

Anti-Corrosion Methods and Materials, vol. 66 no. 2
Type: Research Article
ISSN: 0003-5599

Keywords

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