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Article
Publication date: 23 November 2021

Feifei Sun and Guohong Shi

This paper aims to effectively explore the application effect of big data techniques based on an α-support vector machine-stochastic gradient descent (SVMSGD) algorithm in…

372

Abstract

Purpose

This paper aims to effectively explore the application effect of big data techniques based on an α-support vector machine-stochastic gradient descent (SVMSGD) algorithm in third-party logistics, obtain the valuable information hidden in the logistics big data and promote the logistics enterprises to make more reasonable planning schemes.

Design/methodology/approach

In this paper, the forgetting factor is introduced without changing the algorithm's complexity and proposed an algorithm based on the forgetting factor called the α-SVMSGD algorithm. The algorithm selectively deletes or retains the historical data, which improves the adaptability of the classifier to the real-time new logistics data. The simulation results verify the application effect of the algorithm.

Findings

With the increase of training times, the test error percentages of gradient descent (GD) algorithm, gradient descent support (SGD) algorithm and the α-SVMSGD algorithm decrease gradually; in the process of logistics big data processing, the α-SVMSGD algorithm has the efficiency of SGD algorithm while ensuring that the GD direction approaches the optimal solution direction and can use a small amount of data to obtain more accurate results and enhance the convergence accuracy.

Research limitations/implications

The threshold setting of the forgetting factor still needs to be improved. Setting thresholds for different data types in self-learning has become a research direction. The number of forgotten data can be effectively controlled through big data processing technology to improve data support for the normal operation of third-party logistics.

Practical implications

It can effectively reduce the time-consuming of data mining, realize the rapid and accurate convergence of sample data without increasing the complexity of samples, improve the efficiency of logistics big data mining, reduce the redundancy of historical data, and has a certain reference value in promoting the development of logistics industry.

Originality/value

The classification algorithm proposed in this paper has feasibility and high convergence in third-party logistics big data mining. The α-SVMSGD algorithm proposed in this paper has a certain application value in real-time logistics data mining, but the design of the forgetting factor threshold needs to be improved. In the future, the authors will continue to study how to set different data type thresholds in self-learning.

Details

Journal of Enterprise Information Management, vol. 35 no. 4/5
Type: Research Article
ISSN: 1741-0398

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Article
Publication date: 6 December 2019

Jingyi Wang, Run Yuan and Hongwei Shi

The purpose of this paper is to evaluate the service quality of university library more accurately and dynamically and improve the service efficiency of library. The paper…

635

Abstract

Purpose

The purpose of this paper is to evaluate the service quality of university library more accurately and dynamically and improve the service efficiency of library. The paper realizes quantified representation of library service quality and overcomes the shortcoming of the traditional library evaluation system, which does not consider reader’s identity and cannot be evaluated separately. In addition, according to the function configuration of each department of library, a relation between library evaluation parameter and its organization structure is built. According to the evaluation results and the chain of relations, some suggestions for improving library service can be put forward; thus, it can improve the quality of library service and management efficiency.

Design/methodology/approach

In this paper, a four-dimensional (4-D) representation method is put forward to express four kinds of parameters, namely, the category of participants, the number of people evaluated, the rating level and the weight of parameters, which is expressed by chromaticity and a three-dimensional column coordinate space. Considering the existing evaluation methods such as LibQUAL+TM, the content of evaluation parameters, the grade of evaluation parameters and the weight of evaluation parameters are modified. Using the volume and the equivalent number of people under this evaluation system, the evaluation grade can be quantified and the total results can be evaluated quantitatively.

Findings

The evaluation model proposed in this paper is a 4-D system that is based on content parameters to evaluate the number of participants, score segments, evaluation content weights and reader information. It gives full consideration to the good advice of many scholars and combines the actual operation of domestic libraries. The situation effectively integrates successful experience abroad. Both the undergraduate and teacher sampling evaluation results and their analysis in this paper show the accuracy and credibility of the method.

Originality/value

Although the satisfaction index model has a good effect in foreign countries, taking into account that readers of university libraries in China are different from those in foreign countries in the evaluation methods of the tutorial, professional multi-level evaluation will produce greater errors in practical applications. The traditional four-level method based on Chinese education evaluation (excellent, good, pass and fail) has reached consensus among teachers and students in practical application, and it is easy to achieve consistency. Therefore, this paper also adopts four-level evaluation, that is, very satisfied, satisfied, generally satisfied and very dissatisfied. The embedded application will be able to perform dynamic evaluation and thus can be used in China. The evaluation of service quality in university libraries provides an effective new method.

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Article
Publication date: 23 February 2024

Guizhi Lyu, Peng Wang, Guohong Li, Feng Lu and Shenglong Dai

The purpose of this paper is to present a wall-climbing robot platform for heavy-load with negative pressure adsorption, which could be equipped with a six-degree of freedom (DOF…

379

Abstract

Purpose

The purpose of this paper is to present a wall-climbing robot platform for heavy-load with negative pressure adsorption, which could be equipped with a six-degree of freedom (DOF) collaborative robot (Cobot) and detection device for inspecting the overwater part of concrete bridge towers/piers for large bridges.

Design/methodology/approach

By analyzing the shortcomings of existing wall-climbing robots in detecting concrete structures, a wall-climbing mobile manipulator (WCMM), which could be compatible with various detection devices, is proposed for detecting the concrete towers/piers of the Hong Kong-Zhuhai-Macao Bridge. The factors affecting the load capacity are obtained by analyzing the antislip and antioverturning conditions of the wall-climbing robot platform on the wall surface. Design strategies for each part of the structure of the wall-climbing robot are provided based on the influencing factors. By deriving the equivalent adsorption force equation, analyzed the influencing factors of equivalent adsorption force and provided schemes that could enhance the load capacity of the wall-climbing robot.

Findings

The adsorption test verifies the maximum negative pressure that the fan module could provide to the adsorption chamber. The load capacity test verifies it is feasible to achieve the expected bearing requirements of the wall-climbing robot. The motion tests prove that the developed climbing robot vehicle could move freely on the surface of the concrete structure after being equipped with a six-DOF Cobot.

Practical implications

The development of the heavy-load wall-climbing robot enables the Cobot to be installed and equipped on the wall-climbing robot, forming the WCMM, making them compatible with carrying various devices and expanding the application of the wall-climbing robot.

Originality/value

A heavy-load wall-climbing robot using negative pressure adsorption has been developed. The wall-climbing robot platform could carry a six-DOF Cobot, making it compatible with various detection devices for the inspection of concrete structures of large bridges. The WCMM could be expanded to detect the concretes with similar structures. The research and development process of the heavy-load wall-climbing robot could inspire the design of other negative-pressure wall-climbing robots.

Details

Industrial Robot: the international journal of robotics research and application, vol. 51 no. 3
Type: Research Article
ISSN: 0143-991X

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Article
Publication date: 1 January 2018

Ying Han and Guohong Chen

The purpose of this paper is to clarify the influence of knowledge sharing on innovation performance from the knowledge-based dynamic capabilities perspective within industrial…

990

Abstract

Purpose

The purpose of this paper is to clarify the influence of knowledge sharing on innovation performance from the knowledge-based dynamic capabilities perspective within industrial clusters.

Design/methodology/approach

This paper designed a five-point Likert questionnaire measuring knowledge sharing, dynamic capabilities, trust and innovation performance, and a sample was collected from the industrial clusters within Fujian province in China. Empirical analysis was applied to test the hypotheses.

Findings

Significant relationships were found between knowledge sharing and innovation performance. Three key characteristics of dynamic capabilities were distinguished, namely, knowledge acquisition capability, knowledge integration capability and knowledge creative capabilities. On this basis, further analysis found that dynamic capabilities played a mediating role in this relationship, and trust was a significant moderator.

Practical implications

This paper helps to understand the mechanism between knowledge sharing, knowledge-based dynamic capabilities, trust and innovation. Managers should focus on contributing to knowledge sharing activities, dynamic capabilities and trustful environment to improve innovation effectively.

Originality/value

This paper contributes to the burgeoning literature on the relationship between knowledge sharing and innovation performance in China. Further, it highlights the crucial role of cluster knowledge management in contributing to innovation and management practices.

Details

Journal of Chinese Economic and Foreign Trade Studies, vol. 11 no. 1
Type: Research Article
ISSN: 1754-4408

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Article
Publication date: 1 February 2008

Xiaorui Tian, Weidong Geo, Hongbo Wang and Bingyao Deng

In this paper, microbial transglutaminase (MTG) was applied to process silk fabric for improving its crease resistance under the prerequisite of maintaining other performances…

85

Abstract

In this paper, microbial transglutaminase (MTG) was applied to process silk fabric for improving its crease resistance under the prerequisite of maintaining other performances. Not only was the effect of MTG on silk fabric investigated through the Fourier transform infrared spectroscopy (FR), but analysis was also undertaken in the microcosmic structure of fibroin through the scanning electron microscope (SEM). Solo MTG treatment as well as compound treatments of MTG followed by hydrogen peroxide, protease and ultrasonic, all showed that MTG can improve the crease resistance of silk fabric. It also enhanced its tensile breaking strength or amended damage in the tensile breaking strength caused by pretreatments.

Simultaneously, comparison with other treatments showed that compound treatment of MTG followed by ultrasonic exerted a better coordinated effect and conferred better performances, which made the wrinkle recovery angle (WRA) increase by 17.4% and tensile breaking strength improve by 11.2% respectively. At the same time, other performances were still maintained well.

Details

Research Journal of Textile and Apparel, vol. 12 no. 1
Type: Research Article
ISSN: 1560-6074

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Article
Publication date: 26 July 2011

Khairy A.H. Kobbacy and Sunil Vadera

The use of AI for operations management, with its ability to evolve solutions, handle uncertainty and perform optimisation continues to be a major field of research. The growing…

2686

Abstract

Purpose

The use of AI for operations management, with its ability to evolve solutions, handle uncertainty and perform optimisation continues to be a major field of research. The growing body of publications over the last two decades means that it can be difficult to keep track of what has been done previously, what has worked, and what really needs to be addressed. Hence, the purpose of this paper is to present a survey of the use of AI in operations management aimed at presenting the key research themes, trends and directions of research.

Design/methodology/approach

The paper builds upon our previous survey of this field which was carried out for the ten‐year period 1995‐2004. Like the previous survey, it uses Elsevier's Science Direct database as a source. The framework and methodology adopted for the survey is kept as similar as possible to enable continuity and comparison of trends. Thus, the application categories adopted are: design; scheduling; process planning and control; and quality, maintenance and fault diagnosis. Research on utilising neural networks, case‐based reasoning (CBR), fuzzy logic (FL), knowledge‐Based systems (KBS), data mining, and hybrid AI in the four application areas are identified.

Findings

The survey categorises over 1,400 papers, identifying the uses of AI in the four categories of operations management and concludes with an analysis of the trends, gaps and directions for future research. The findings include: the trends for design and scheduling show a dramatic increase in the use of genetic algorithms since 2003 that reflect recognition of their success in these areas; there is a significant decline in research on use of KBS, reflecting their transition into practice; there is an increasing trend in the use of FL in quality, maintenance and fault diagnosis; and there are surprising gaps in the use of CBR and hybrid methods in operations management that offer opportunities for future research.

Originality/value

This is the largest and most comprehensive study to classify research on the use of AI in operations management to date. The survey and trends identified provide a useful reference point and directions for future research.

Details

Journal of Manufacturing Technology Management, vol. 22 no. 6
Type: Research Article
ISSN: 1741-038X

Keywords

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Article
Publication date: 1 June 2021

Ayodeji Emmanuel Oke and Victor Adetunji Arowoiya

This purpose of the study is to evaluate areas of application of internet of things (IoT) in the construction industry, with the view of increasing the level of usage of…

1599

Abstract

Purpose

This purpose of the study is to evaluate areas of application of internet of things (IoT) in the construction industry, with the view of increasing the level of usage of technology. This will help in understanding the areas where IoT can be applied in the construction industry for better improvement.

Design/methodology/approach

A quantitative approach was adopted for this study, and the adopted questionnaire was structured on a five-point Likert scale to elicit the opinion of respondents in the areas of application of IoT in the construction industry. The respondents included are quantity surveyors, land surveyors, builders, architects and engineers. Bar chart, mean item score, one sample t-test and Kruskal–Wallis H test were used in analyzing the retrieved data.

Findings

The results showed that building information modeling, construction management, remote usage monitoring, equipment services and repair, construction tools and equipment tracking are areas where IoT is mostly applied in the industry. Site monitoring is the only factor that has significant difference in the opinions of professionals, while others do not have. One sample t-test revealed that three factors out of 12 do not have significance attached by professionals.

Originality/value

The study gives insight into different areas where IoT can be applied in the construction industry. It also highlights how its application can be improved through workshops, training, seminar and conference for construction professionals to keep themselves abreast of information and communication technology trends, especially in the aspect of IoT. The IoT adoption helps in accomplishing sustainable infrastructural projects with more convenience.

Details

Smart and Sustainable Built Environment, vol. 10 no. 3
Type: Research Article
ISSN: 2046-6099

Keywords

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Article
Publication date: 26 December 2023

Li Zhang and Xican Li

Aim to the limitations of grey relational analysis of interval grey number, based on the generalized greyness of interval grey number, this paper tries to construct a grey angle…

190

Abstract

Purpose

Aim to the limitations of grey relational analysis of interval grey number, based on the generalized greyness of interval grey number, this paper tries to construct a grey angle cosine relational degree model from the perspective of proximity and similarity.

Design/methodology/approach

Firstly, the algorithms of the generalized greyness of interval grey number and interval grey number vector are given, and its properties are analyzed. Then, based on the grey relational theory, the grey angle cosine relational model is proposed based on the generalized greyness of interval grey number, and the relationship between the classical cosine similarity model and the grey angle cosine relational model is analyzed. Finally, the validity of the model in this paper is illustrated by the calculation examples and an application example of related factor analysis of maize yield.

Findings

The results show that the grey angle cosine relational degree model has strict theoretical basis, convenient calculation and is easy to program, which can not only fully utilize the information of interval grey numbers but also overcome the shortcomings of greyness relational degree model. The grey angle cosine relational degree is an extended form of cosine similarity degree of real numbers. The calculation examples and the related factor analysis of maize yield show that the model proposed in this paper is feasible and valid.

Practical implications

The research results not only further enrich the grey system theory and method but also provide a basis for the grey relational analysis of the sequences in which the interval grey numbers coexist with the real numbers.

Originality/value

The paper succeeds in realizing the algorithms of the generalized greyness of interval grey number and interval grey number vector, and the grey angle cosine relational degree, which provide a new method for grey relational analysis.

Details

Grey Systems: Theory and Application, vol. 14 no. 2
Type: Research Article
ISSN: 2043-9377

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