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Article
Publication date: 13 May 2014

Tianmiao Wang, Chaolei Wang, Jianhong Liang and Yicheng Zhang

The purpose of this paper is to present a Rao–Blackwellized particle filter (RBPF) approach for the visual simultaneous localization and mapping (SLAM) of small unmanned aerial…

312

Abstract

Purpose

The purpose of this paper is to present a Rao–Blackwellized particle filter (RBPF) approach for the visual simultaneous localization and mapping (SLAM) of small unmanned aerial vehicles (UAVs).

Design/methodology/approach

Measurements from inertial measurement unit, barometric altimeter and monocular camera are fused to estimate the state of the vehicle while building a feature map. In this SLAM framework, an extra factorization method is proposed to partition the vehicle model into subspaces as the internal and external states. The internal state is estimated by an extended Kalman filter (EKF). A particle filter is employed for the external state estimation and parallel EKFs are for the map management.

Findings

Simulation results indicate that the proposed approach is more stable and accurate than other existing marginalized particle filter-based SLAM algorithms. Experiments are also carried out to verify the effectiveness of this SLAM method by comparing with a referential global positioning system/inertial navigation system.

Originality/value

The main contribution of this paper is the theoretical derivation and experimental application of the Rao–Blackwellized visual SLAM algorithm with vehicle model partition for small UAVs.

Details

Industrial Robot: An International Journal, vol. 41 no. 3
Type: Research Article
ISSN: 0143-991X

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Article
Publication date: 26 October 2018

Lingcheng Kong, Ling Liang, Jianhong Xu, Weisi Zhang and Weijun Zhu

Although the wind power industry has been booming in China during the last decade, the development of wind turbine aftermarket service is still lagging behind, which seriously…

590

Abstract

Purpose

Although the wind power industry has been booming in China during the last decade, the development of wind turbine aftermarket service is still lagging behind, which seriously affects the operational efficiency of wind farms. If wind turbine manufacturers get involved in the aftermarket, the service pricing policy will impact the profits of both the manufacturer and the wind farm. Therefore, it is necessary to discuss an optimal service pricing strategy in the wind turbine aftermarket and design a method to improve electricity generation efficiency through service contract design. The paper aims to discuss these issues.

Design/methodology/approach

In order to decide the maintenance quantity and channel effort level, the authors design a normal Stackelberg game and an efficiency value-added revenue-sharing contract and discuss two kinds of revenue increment sharing models under situations, in which the supply chain’s leaders are the wind farm and the wind turbine manufacturer, respectively.

Findings

The results show that in either case, there exist optimal power generation revenue-sharing ratios that can maximize profit. At the same time, the authors outline an optimal service pricing policy, maintenance demand policy and channel service effort-level policy. The results summarize the influences of wind aftermarket services on wind farms’ and wind turbine manufacturers’ profit, which provides managerial insights into the process of manufacturing servitization.

Practical implications

The manufacturer’s channel effort level will influence the power generation increments very much, so the authors have developed a mechanism to stimulate the manufacturer improving the efficiency of aftermarket services.

Originality/value

Taking the power generation increment revenue as the profit increment function, the authors discuss the influence of service price on the profit increment of the wind farm and the wind turbine manufacturer and also consider the influence of service price on the wind farms maintenance quantity and wind turbine manufacturers channel effort level.

Details

Industrial Management & Data Systems, vol. 119 no. 3
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 1 February 2021

Ling Liang, Lin Tian, Jiaping Xie, Jianhong Xu and Weisi Zhang

The car-sharing market has entered the mature stage, and consumers' demand shows a diversified increasing trend. This paper considers two modes of operation and two pricing…

1739

Abstract

Purpose

The car-sharing market has entered the mature stage, and consumers' demand shows a diversified increasing trend. This paper considers two modes of operation and two pricing strategies, which are business-to-consumer and consumer-to-consumer modes, market pricing and platform pricing. Under these conditions, the platform's revenue-sharing ratio will be different. The purpose of this paper is to explore this research question, and seeks an optimal pricing mechanism that can achieve a win–win situation between platform and automobile manufacturer in the two market modes.

Design/methodology/approach

The authors design different profit functions for platform under the two contexts. Of course, the platform's function is constrained to the manufacturer's function. By introducing a revenue-sharing contract a Stackelberg game model dominated by the platform is established and the equilibrium solutions under the two pricing models are derived.

Findings

The study found that even if only market pricing is executed, the scale of the car-sharing market will continue to expand. As the car-sharing market becomes more saturated, platform pricing is better for the automobile manufacturer; in most cases, the platform prefers platform pricing, but when the number of private cars is relatively small, if the cost of car operation and maintenance for the automobile manufacturer is lower or the revenue-sharing ratio of private cars is high, then market pricing will be more favorable to the platform.

Practical implications

With the cross-border integration of car service platforms and the automobile manufacturing industry, the key to achieving win–win cooperation and sustainable development in the car-sharing market will converge on the question of how to design a suitable pricing mechanism and revenue-sharing method.

Originality/value

Authors have determined how a car-sharing platform achieves a win–win order pricing strategy with the manufacturer and private car owners, respectively. And authors combined the supply chain revenue-sharing contract with the car-sharing market to explore the application of the revenue-sharing contract in the sharing economy.

Details

Industrial Management & Data Systems, vol. 121 no. 3
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 14 August 2024

Lizhi Zhou, Chuan Wang, Pei Niu, Hanming Zhang, Ning Zhang, Quanyi Xie, Jianhong Wang, Xiao Zhang and Jian Liu

Laser point clouds are a 3D reconstruction method with wide range, high accuracy and strong adaptability. Therefore, the purpose is to discover a construction point cloud…

47

Abstract

Purpose

Laser point clouds are a 3D reconstruction method with wide range, high accuracy and strong adaptability. Therefore, the purpose is to discover a construction point cloud extraction method that can obtain complete information about the construction of rebar, facilitating construction quality inspection and tunnel data archiving, to reduce the cost and complexity of construction management.

Design/methodology/approach

Firstly, this paper analyzes the point cloud data of the tunnel during the construction phase, extracts the main features of the rebar data and proposes an M-E-L recognition method. Secondly, based on the actual conditions of the tunnel and the specifications of Chinese tunnel engineering, a rebar model experiment is designed to obtain experimental data. Finally, the feasibility and accuracy of the M-E-L recognition method are analyzed and tested based on the experimental data from the model.

Findings

Based on tunnel morphology characteristics, data preprocessing, Euclidean clustering and PCA shape extraction methods, a M-E-L identification algorithm is proposed for identifying secondary lining rebars in highway tunnel construction stages. The algorithm achieves 100% extraction of the first-layer rebars, allowing for the three-dimensional visualization of the on-site rebar situation. Subsequently, through data processing, rebar dimensions and spacings can be obtained. For the second-layer rebars, 55% extraction is achieved, providing information on the rebar skeleton and partial rebar details at the construction site. These extracted data can be further processed to verify compliance with construction requirements.

Originality/value

This paper introduces a laser point cloud method for double-layer rebar identification in tunnels. Current methods rely heavily on manual detection, lacking objectivity. Objective approaches for automatic rebar identification include image-based and LiDAR-based methods. Image-based methods are constrained by tunnel lighting conditions, while LiDAR focuses on straight rebar skeletons. Our research proposes a 3D point cloud recognition algorithm for tunnel lining rebar. This method can extract double-layer rebars and obtain construction rebar dimensions, enhancing management efficiency.

Details

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

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Article
Publication date: 24 May 2024

Shupeng Liu, Jianhong Shen and Jing Zhang

Learning from past construction accident reports is critical to reducing their occurrence. Digital technology provides feasibility for extracting risk factors from unstructured…

107

Abstract

Purpose

Learning from past construction accident reports is critical to reducing their occurrence. Digital technology provides feasibility for extracting risk factors from unstructured reports, but there are few related studies, and there is a limitation that textual contextual information cannot be considered during extraction, which tends to miss some important factors. Meanwhile, further analysis, assessment and control for the extracted factors are lacking. This paper aims to explore an integrated model that combines the advantages of multiple digital technologies to effectively solve the above problems.

Design/methodology/approach

A total of 1000 construction accident reports from Chinese government websites were used as the dataset of this paper. After text pre-processing, the risk factors related to accident causes were extracted using KeyBERT, and the accident texts were encoded into structured data. Tree-augmented naive (TAN) Bayes was used to learn the data and construct a visualized risk analysis network for construction accidents.

Findings

The use of KeyBERT successfully considered the textual contextual information, prompting the extracted risk factors to be more complete. The integrated TAN successfully further explored construction risk factors from multiple perspectives, including the identification of key risk factors, the coupling analysis of risk factors and the troubleshooting method of accident risk source. The area under curve (AUC) value of the model reaches up to 0.938 after 10-fold cross-validation, indicating good performance.

Originality/value

This paper presents a new machine-assisted integrated model for accident report mining and risk factor analysis, and the research findings can provide theoretical and practical support for accident safety management.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 21 March 2016

Ivan Y. Sun, Jianhong Liu and Ashley K. Farmer

– The purpose of this paper is to assess factors that influence Chinese police supervisors’ attitudes toward police roles, community policing, and job satisfaction.

673

Abstract

Purpose

The purpose of this paper is to assess factors that influence Chinese police supervisors’ attitudes toward police roles, community policing, and job satisfaction.

Design/methodology/approach

Survey data were collected from police supervisors in a major Chinese city. Multivariate regression was used to assess the effects of officers’ background characteristics and assignments on their occupational attitudes.

Findings

Ethnic minority supervisors were more likely to have a broader order maintenance orientation, a narrower crime fighting orientation, and supportive attitudes toward quality of life activities. Less experienced supervisors were more inclined to favor the order maintenance role. Supervisors with a stronger order maintenance orientation tended to support problem solving activities and have a greater level of job satisfaction. Officers with military service experience also expressed a higher degree of job satisfaction.

Research limitations/implications

Survey data collected from a single Chinese city may not be generalizable to officers in other regions and departments.

Practical implications

Police administrators should screen all applicants on attitudes that reflect departmental work priorities and styles of policing during the initial selection process. Desirable attitudes can be further molded into officers during their academic training, field officer training, and in-service training. Police administrators should continue their recruiting efforts targeting former military personnel. With adequate training in fulfilling civilian tasks and displaying proper outlooks, these individuals could become effective members of the forces.

Originality/value

Despite a growing number of studies on crime and justice in China, empirical research on policing in general and on officers’ occupational attitudes in particular remains very limited. This study represents one of the first attempts to assess factors related to police occupational outlooks in China.

Details

Policing: An International Journal of Police Strategies & Management, vol. 39 no. 1
Type: Research Article
ISSN: 1363-951X

Keywords

Available. Open Access. Open Access
Article
Publication date: 3 February 2025

Jianhong Zhang, Suzana B. Rodrigues, Jiangang Jiang and Chaohong Zhou

The purpose of this paper is to investigate the impact of political instability at the local level on foreign firms in China. Building on the literature on political embeddedness…

66

Abstract

Purpose

The purpose of this paper is to investigate the impact of political instability at the local level on foreign firms in China. Building on the literature on political embeddedness and business power, the authors propose a theoretical framework to explain how political turnover can affect foreign firms’ performance and how they respond to such challenges by leveraging their power bases.

Design/methodology/approach

To test the hypotheses, the authors apply fixed effects regression to an unbalanced panel data set comprising 13,360 foreign firms from 1998 to 2013 and the political replacement that involved changes in provincial governors.

Findings

The findings confirm that political turnover incidents have a negative impact on the performance of foreign firms in China. However, the authors also found that this negative relationship is weaker for firms that can choose various types of power sources. Specifically, the study reveals that foreign firms with large firm size, government ownership and a strong foreign direct investment community are better qualified to mitigate the negative effects of political instability.

Originality/value

This study contributes to the literature by developing the understanding of how political uncertainties and risks affect the performance of foreign firms in China and the importance of firms’ power in counterbalancing these effects. The research provides valuable insights into how multinational corporations can exploit their power to manage the effects of local political turnover, which has practical implications for the strategy and management of foreign firms operating in China.

Details

Multinational Business Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1525-383X

Keywords

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Article
Publication date: 5 September 2023

Xuwei Pan, Jihu Li, Jianhong Luo and Wenbang Zhan

It is widely known that fast-fashion retailers are struggling to keep up with consumer attention for quick responses within the fashion industry. With the advance of Internet and…

681

Abstract

Purpose

It is widely known that fast-fashion retailers are struggling to keep up with consumer attention for quick responses within the fashion industry. With the advance of Internet and e-commerce, consumers prefer to purchase online. Online platform information has become an essential source for exploring consumer attention. However, there is often a mismatch between the information provided by retailers and the feedback received from consumers, leading to an imbalance between the supply side and demand side of online information. The purpose of this study is therefore to provide a unified approach to discover consumer attention from the design topic aspect by revealing the information imbalance between supply side and demand side.

Design/methodology/approach

To address the issue of online information imbalance and discover consumer attention, this study proposed an approach that focuses on the design topic perspective. The design topic is a collection of design elements that represent a clothing-design feature more comprehensively and accurately compared to a single design element. The proposed approach begins with generating design topics through topic modeling based on online information provided by retailers on e-commerce platforms. Two indicators, influence degree and attention degree, are then used to quantify the intensity of supply information and consumer attention related to design topics. Finally, design topic strategy diagrams are constructed to reveal information imbalance and discover consumer attention.

Findings

The experimental case demonstrates the existence of information imbalance, indicating that the intensity of supply information and consumer attention from the perspective of design topics is not uniform, although both follow the Pareto principle. The results of consumer attention distribution with heavy power-law tails are consistent with current research findings. This further demonstrates that the proposed approach is capable of discovering consumer attention in the design topic strategy diagrams.

Practical implications

The issue of information imbalance between retailers and consumers poses a challenge in keeping up with customer attention. The proposed approach offers a practical solution by visually identifying the symptoms of information imbalance and discovering consumer attention through design topic strategy diagrams. This approach provides fast-fashion retailers with a valuable reference to seize market opportunities, improve product design and adjust marketing or management strategies.

Originality/value

This study proposes a novel approach to disclose the issue of information imbalance between supply side and demand side and therefore to discover consumer attention from the perspective of design topics. In addition, guidelines for applying the proposed approach for fast-fashion marketing and management are presented.

Details

Journal of Fashion Marketing and Management: An International Journal, vol. 28 no. 2
Type: Research Article
ISSN: 1361-2026

Keywords

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Book part
Publication date: 31 October 2022

Abstract

Details

International Environments and Practices of Higher Education
Type: Book
ISBN: 978-1-80117-590-6

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Article
Publication date: 30 August 2011

Qazi Muhammad Adnan Hye and Irina Dolgopolova

The purpose of this paper is to construct a financial development index for China and to analyze the relationship between the financial sector development index and economic…

1522

Abstract

Purpose

The purpose of this paper is to construct a financial development index for China and to analyze the relationship between the financial sector development index and economic growth.

Design/methodology/approach

This study uses Johansen‐Juselius cointegration approach to determine long run relationship between variables. To determine the strength of causal relationship variance decomposition is used. The stability of coefficient is evaluated through rolling window regression method.

Findings

The results of Johansen‐Juselius cointegration approach confirm long run relationship between financial development index and economic growth. Normalized cointegrating vector indicates that financial development index, real interest rate, capital and labor force positively determine economic growth in China. The yearly coefficient is provided by the rolling regression and indicates that financial development index negatively link to economic growth in 1991, 1992, 1994, 1995, 1999, 2000, 2003‐2005. Interest rate is negatively linked to economic growth in 1991‐1996, 2007 and 2008. The variance decomposition method validates that shocks in financial development index and real interest rate are explained by economic growth.

Originality/value

A financial development index for China is constructed and the relationship between economic growth and financial development is indicated.

Details

Chinese Management Studies, vol. 5 no. 3
Type: Research Article
ISSN: 1750-614X

Keywords

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