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Article
Publication date: 18 January 2013

Chen Guodong, Zeyang Xia, Rongchuan Sun, Zhenhua Wang and Lining Sun

Detecting objects in images and videos is a difficult task that has challenged the field of computer vision. Most of the algorithms for object detection are sensitive to…

Abstract

Purpose

Detecting objects in images and videos is a difficult task that has challenged the field of computer vision. Most of the algorithms for object detection are sensitive to background clutter and occlusion, and cannot localize the edge of the object. An object's shape is typically the most discriminative cue for its recognition by humans. The purpose of this paper is to introduce a model‐based object detection method which uses only shape‐fragment features.

Design/methodology/approach

The object shape model is learned from a small set of training images and all object models are composed of shape fragments. The model of the object is in multi‐scales.

Findings

The major contributions of this paper are the application of learned shape fragments‐based model for object detection in complex environment and a novel two‐stage object detection framework.

Originality/value

The results presented in this paper are competitive with other state‐of‐the‐art object detection methods.

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Article
Publication date: 12 August 2014

Wang Zhenhua, Xu Hui, Chen Guodong, Sun Rongchuan and Lining Sun

The purpose of this paper is to present a distance accuracy-based industrial robot kinematic calibration model. Nowadays, the repeatability of the industrial robot is…

Abstract

Purpose

The purpose of this paper is to present a distance accuracy-based industrial robot kinematic calibration model. Nowadays, the repeatability of the industrial robot is high, while the absolute positioning accuracy and distance accuracy are low. Many factors affect the absolute positioning accuracy and distance accuracy, and the calibration method of the industrial robot is an important factor. When the traditional calibration methods are applied on the industrial robot, the accumulative error will be involved according to the transformation between the measurement coordinate and the robot base coordinate.

Design/methodology/approach

In this manuscript, a distance accuracy-based industrial robot kinematic calibration model is proposed. First, a simplified kinematic model of the robot by using the modified Denavit–Hartenberg (MDH) method is introduced, then the proposed distance error-based calibration model is presented; the experiment is set up in the next section.

Findings

The experimental results show that the proposed calibration model based on MDH and distance error can improve the distance accuracy and absolute position accuracy dramatically.

Originality/value

The proposed calibration model based on MDH and distance error can improve the distance accuracy and absolute position accuracy dramatically.

Details

Industrial Robot: An International Journal, vol. 41 no. 5
Type: Research Article
ISSN: 0143-991X

Keywords

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Article
Publication date: 20 December 2017

Kaigang Yi, Tinggui Chen and Guodong Cong

Nowadays, database management system has been applied in library management, and a great number of data about readers’ visiting history to resources have been accumulated…

Abstract

Purpose

Nowadays, database management system has been applied in library management, and a great number of data about readers’ visiting history to resources have been accumulated by libraries. A lot of important information is concealed behind such data. The purpose of this paper is to use a typical data mining (DM) technology named an association rule mining model to find out borrowing rules of readers according to their borrowing records, and to recommend other booklists for them in a personalized way, so as to increase utilization rate of data resources at library.

Design/methodology/approach

Association rule mining algorithm is applied to find out borrowing rules of readers according to their borrowing records, and to recommend other booklists for them in a personalized way, so as to increase utilization rate of data resources at library.

Findings

Through an analysis on record of book borrowing by readers, library manager can recommend books that may be interested by a reader based on historical borrowing records or current book-borrowing records of the reader.

Research limitations/implications

If many different categories of book-borrowing problems are involved, it will result in large length of encoding as well as giant searching space. Therefore, future research work may be considered in the following aspects: introduce clustering method; and apply association rule mining method to procurement of book resources and layout of books.

Practical implications

The paper provides a helpful inspiration for Big Data mining and software development, which will improve their efficiency and insight on users’ behavior and psychology.

Social implications

The paper proposes a framework to help users understand others’ behavior, which will aid them better take part in group and community with more contribution and delightedness.

Originality/value

DM technology has been used to discover information concealed behind Big Data in library; the library personalized recommendation problem has been analyzed and formulated deeply; and a method of improved association rules combined with artificial bee colony algorithm has been presented.

Details

Library Hi Tech, vol. 36 no. 3
Type: Research Article
ISSN: 0737-8831

Keywords

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Article
Publication date: 27 April 2020

Roger (Rongxin) Chen, Liang Wang, Eric Ping Hung Li and Guodong Hu

As entrepreneurial top management teams in multidivisional forms are typically treated in pertinent literature as the default organizational solutions for developing…

Abstract

Purpose

As entrepreneurial top management teams in multidivisional forms are typically treated in pertinent literature as the default organizational solutions for developing dynamic capabilities, the emerging innovative organizational forms tend to be overlooked, even though they could be a viable means of transforming established enterprises. The present case study examines how Haier's microenterprise and platforms influenced the firm's dynamic capabilities development.

Design/methodology/approach

The paper presents a qualitative case study of Haier Group Corporation in China.

Findings

The findings indicate that Haier employed a loosely coupled relationship between its headquarters and the microenterprises, developed quasi market-based exchange relationships and established peer-to-peer learning opportunities and coordination among its microenterprises. Data analyses further revealed that Haier has adopted three-step routines to capture market opportunities and enhance operational efficiency. This research extends the sensing-seizing-reconfiguration model typically recommended in the existing literature. It also demonstrates that organizational configuration is an important aspect of dynamic innovation. In summary, the study results showcase microdivisionalization as a new way for developing dynamic capabilities to better adapt to the ever-changing market environments.

Originality/value

In summary, our study showcased microdivisionalization as a new way for firms to change the organization structure and business strategies to better adapt to the ever-changing market environments.

Details

Management Decision, vol. 59 no. 3
Type: Research Article
ISSN: 0025-1747

Keywords

Content available
Article
Publication date: 5 October 2018

Liwei Xu, Guodong Yin, Guangmin Li, Athar Hanif and Chentong Bian

The purpose of this paper is to investigate problems in performing stable lane changes and to find a solution to reduce energy consumption of autonomous electric vehicles.

Abstract

Purpose

The purpose of this paper is to investigate problems in performing stable lane changes and to find a solution to reduce energy consumption of autonomous electric vehicles.

Design/methodology/approach

An optimization algorithm, model predictive control (MPC) and Karush–Kuhn–Tucker (KKT) conditions are adopted to resolve the problems of obtaining optimal lane time, tracking dynamic reference and energy-efficient allocation. In this paper, the dynamic constraints of vehicles during lane change are first established based on the longitudinal and lateral force coupling characteristics and the nominal reference trajectory. Then, by optimizing the lane change time, the yaw rate and lateral acceleration that connect with the lane change time are limed. Furthermore, to assure the dynamic properties of autonomous vehicles, the real system inputs under the restraints are obtained by using the MPC method. Based on the gained inputs and the efficient map of brushless direct-current in-wheel motors (BLDC IWMs), the nonlinear cost function which combines vehicle dynamic and energy consumption is given and the KKT-based method is adopted.

Findings

The effectiveness of the proposed control system is verified by numerical simulations. Consequently, the proposed control system can successfully achieve stable trajectory planning, which means that the yaw rate and longitudinal and lateral acceleration of vehicle are within stability boundaries, which accomplishes accurate tracking control and decreases obvious energy consumption.

Originality/value

This paper proposes a solution to simultaneously satisfy stable lane change maneuvering and reduction of energy consumption for autonomous electric vehicles. Different from previous path planning researches in which only the geometric constraints are involved, this paper considers vehicle dynamics, and stability boundaries are established in path planning to ensure the feasibility of the generated reference path.

Details

Journal of Intelligent and Connected Vehicles, vol. 1 no. 2
Type: Research Article
ISSN: 2399-9802

Keywords

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Article
Publication date: 7 March 2016

Bei Wang, Jituo Li, Jiping Zeng, Guang Chen and Guodong Lu

Skeleton plays an important role in representing the essential feature of garment in image. General skeleton extraction methods often yield many short skeletal branches…

Abstract

Purpose

Skeleton plays an important role in representing the essential feature of garment in image. General skeleton extraction methods often yield many short skeletal branches. Though short branches reflect the geometric details of the garment, they are obstacles in extracting the essential features. The purpose of this paper is to provide an approach to hierarchically remove them to reveal the level of details (LOD) of the skeleton, thus both the essential skeleton and the geometric skeletal branches can be definitely extracted and separated.

Design/methodology/approach

First, the initial garment image skeleton is extracted and smoothed. Then, the hierarchically removing mechanism is established on scoring the importance of each skeletal branch by an altered PageRank method and computing the symmetry among skeletal branches.

Findings

Experimental examples show that this method can extract and separate garment essential skeleton as well as geometric skeletal branches hierarchically. Garments in same class have a similar essential skeleton with detailed differences, so this approach can be potentially applied in garment recognition and style specification.

Originality/value

Traditionally, there is almost no work attempts to build LOD in skeleton of planar shapes. This paper provide an automatic device for building LOD skeleton for garment image. In another word, hierarchic skeletons with details in different prominence level are gradually established. And pairs of symmetric skeletal parts are found by taking advantage of symmetry characteristic of garment. This method is efficient in garment image skeleton extraction.

Details

International Journal of Clothing Science and Technology, vol. 28 no. 1
Type: Research Article
ISSN: 0955-6222

Keywords

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Article
Publication date: 27 May 2014

Zheng Liu, Jituo Li, Guang Chen and Guodong Lu

Detailed body sizes are prerequisite for made to measure or customized manufacture. Nowadays, detailed body sizes can be precisely obtained by using 3D scanners, however…

Abstract

Purpose

Detailed body sizes are prerequisite for made to measure or customized manufacture. Nowadays, detailed body sizes can be precisely obtained by using 3D scanners, however, the high prices of the scanners block the population for such approaches. The purpose of this paper is to provide an economical and accurate data-driven method which can predict detailed body sizes with a small number of feature sizes.

Design/methodology/approach

First, the representative body sizes are extracted from dozens of detail body sizes by using factor analysis and garment knowledge. Among the representative body sizes, those that are easy to be measured are selected as the feature parameters (FPs). Second, by mining the database of the body sizes, mapping from the FPs to the detailed body sizes is expressed by a combination of radial basis function and multiply linear regression. Thus, for an individual human body, his/her detailed body sizes can be predicted by a small number of FPs.

Findings

First, FPs which are easily measured and represent the main shape information of a human body are extracted. Second, detailed body sizes can be functionally predicted by the FPs.

Originality/value

Traditionally, measuring dozens of body sizes for each human body is tiresome and the accuracy of the sizes depends on the experience of the gaugers. In this paper, a small number of body sizes are selected as the FPs which are easy to be measured and can functionally express the other body sizes. Thus, by only measuring the FPs, the detailed body sizes can be intelligently and automatically predicted. This approach is meaningful to improve the intelligence and accuracy of the measurement, so that even an inexperienced gauger is competent to obtain accurate detailed body sizes.

Details

International Journal of Clothing Science and Technology, vol. 26 no. 2
Type: Research Article
ISSN: 0955-6222

Keywords

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Article
Publication date: 3 August 2015

Jun Zhang, Mengfei Ran, Guodong Han and Guiping Yao

The purpose of this paper is to utilize the proposed function transformation to make the original data series meet the properties of smooth ratio being lessen and stepwise…

Abstract

Purpose

The purpose of this paper is to utilize the proposed function transformation to make the original data series meet the properties of smooth ratio being lessen and stepwise ratio deviation being reduced, so that to improve the accuracy of grey forecasting model.

Design/methodology/approach

According to the characteristics of anti-cotangent functional graph variation, the theory of functional transformation and grey system modeling, the authors proposed a grey model based on the transformation of Aarc cot x+B function.

Findings

The calculated result of practical example shows that the proposed method is both valid on improving fitting effectiveness and forecasting accuracy.

Practical implications

The proposed method in this paper can effectively improve the accuracy of forecasting of high-growth original data series (derivative of data series is not only greater than 1 but also increasing).

Originality/value

The paper succeeds in providing an effective function transformation to make the smooth ratio and stepwise ratio deviation reduced significantly.

Details

Grey Systems: Theory and Application, vol. 5 no. 2
Type: Research Article
ISSN: 2043-9377

Keywords

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Article
Publication date: 13 April 2021

Guodong Ni, Ziyao Zhang, Zhenmin Yuan, Haitao Huang, Na Xu and Yongliang Deng

The purpose of this paper is to figure out the paths about transformation of tacit knowledge into explicit knowledge, i.e. tacit knowledge explicating (TKE) in real estate…

Abstract

Purpose

The purpose of this paper is to figure out the paths about transformation of tacit knowledge into explicit knowledge, i.e. tacit knowledge explicating (TKE) in real estate companies, and determine the influencing factors of TKE in Chinese real estate companies to enable enterprises make better use of their knowledge resources.

Design/methodology/approach

The study adopted an exploratory design method using thematic analysis and grounded theory, and semi-structured interviews were conducted to collect data. The interviewees consisted of employees in different positions, who come from Chinese real estate companies with different ranking ranges and different knowledge management levels. Data collection was divided into two rounds for the identification of transformation paths and influencing factors.

Findings

This study has shown that 11 paths about TKE divided into solidified organization process and construction of organizational infrastructure go into effect within the real estate companies. Factors influencing TKE in real estate companies concern three main categories: organizational distal factors, contextual proximal factors and individual factors, including 21 subordinates in total. Furthermore, correlation between TKE paths and influencing factors is established.

Research limitations/implications

Research results may lack generalizability due to the method adopted. Therefore, researchers are encouraged to verify the outcomes of this research.

Practical implications

This research provides a new idea and solutions for the tacit knowledge management in real estate companies.

Originality/value

To the best of the authors’ knowledge, this study is the first to systematically identify paths and the influencing factors of TKE in real estate companies, contribute to the incipient but growing understanding of achievement of “tacit to explicit” and enrich the corporate tacit knowledge management literature.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

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Article
Publication date: 31 July 2019

Linhua Sang, Dongchun Xia, Guodong Ni, Qingbin Cui, Jianping Wang and Wenshun Wang

The purpose of this paper is to explore the influence mechanism of job satisfaction and positive affect on knowledge sharing among project members in Chinese construction…

Abstract

Purpose

The purpose of this paper is to explore the influence mechanism of job satisfaction and positive affect on knowledge sharing among project members in Chinese construction industry, and test the moderating role of organizational commitment between them in order to find a new approach from the perspective of psychology to improve the knowledge sharing performance within project management organizations in China constantly.

Design/methodology/approach

An empirical study was used based on confirmatory factor analysis and hierarchical regression analysis with a sample of 540 project members from 80 project management organizations in China.

Findings

Research results showed that job satisfaction and positive affect of project members both have a significant positive impact on knowledge sharing; organizational commitment could moderate the influence of job satisfaction and positive affect on knowledge sharing among project members partially within the Chinese context.

Research limitations/implications

A questionnaire study from China only represents the relationship and regular pattern within a shorter time interval in the Chinese context. It is necessary to continue to implement a longitudinal study in a relatively long period in future research.

Practical implications

Knowledge sharing among project members can be enhanced through improving job satisfaction and positive affect, and strengthening project members’ organizational commitment can amplify the influence effect of job satisfaction and positive affect on knowledge sharing.

Originality/value

This paper clarifies the direct influence mechanism of project members’ job satisfaction and positive affect on explicit knowledge sharing (EKS) and tacit knowledge sharing (TKS), and further tests the partial moderating effect of organizational commitment on the influence relationship of job satisfaction and positive affect on EKS and TKS.

Details

Engineering, Construction and Architectural Management, vol. 27 no. 1
Type: Research Article
ISSN: 0969-9988

Keywords

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