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Article
Publication date: 20 April 2018

Xuefeng Zhang and Jiafu Su

Task recommendation is an important way for workers and requesters to get better outcomes in shorter time in crowdsourcing. This paper aims to propose an approach based on…

Abstract

Purpose

Task recommendation is an important way for workers and requesters to get better outcomes in shorter time in crowdsourcing. This paper aims to propose an approach based on 2-tuple fuzzy linguistic method to recommend tasks to the workers who would be capable of completing and accept them.

Design/methodology/approach

In this paper, worker’s capability-to-complete (CTC) and possibility-to-accept (PTA) for a task needs to be recommended are proposed, measured and aggregated to determine worker’s priority for task recommendation. Therein, the similarity between the recommended task and its similar tasks and worker’s performance on these similar tasks are computed and aggregated to determine worker’s CTC quantitatively. In addition, two factors of worker’s active degree and worker’s preferences to a task category are presented to reflect and determine worker’s PTA. In the process of measuring them, 2-tuple fuzzy linguistic method is used to represent, process and aggregate vague and imprecise information.

Findings

To demonstrate the implementation process and performance of the proposed approach, an illustrative example is conducted on Taskcn, a widely used Chinese online crowdsourcing market. The experimental results show that the proposed approach outperformed the self-selection approach, especially for complex or creative tasks. Moreover, comparing with task recommendation considering worker’s CTC solely, the proposed approach would be better in terms of workers’ response rate. Additionally, the use of linguistic terms and fuzzy linguistic method facilitates the expression of vague and subjective information and makes recommendation process more practical.

Research limitations/implications

In the study, the authors capture alternative workers, collect workers’ behaviors and compute workers’ CTC and PTA manually. However, as the number of tasks and alternative workers grow, the issue, i.e. how to conveniently collect workers’ behaviors and determine their CTC and PTA, becomes conspicuous and needs to be studied further.

Practical implications

The proposed approach provides an alternative way to perform tasks posted in crowdsourcing platforms. It can assist workers to contribute to right tasks, and requesters to get outcomes with high quality more efficiently.

Originality/value

This study proposes an approach to task recommendation in crowdsourcing that integrates workers’ CTC and PTA for the recommended tasks and can deal with vague and imprecise information.

Details

Kybernetes, vol. 47 no. 8
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 17 March 2019

Jiafu Su, Qun Bai, Stavros Sindakis, Xuefeng Zhang and Tao Yang

The vulnerability of multinational corporation (MNC) knowledge network is one of the major causes for the failure and even the death of MNCs in the fierce global market…

Abstract

Purpose

The vulnerability of multinational corporation (MNC) knowledge network is one of the major causes for the failure and even the death of MNCs in the fierce global market competition. Employee turnover and knowledge loss are the triggers for the MNC knowledge network vulnerability and a matter of serious concern in the evolution and development of MNC knowledge network. The purpose of this work is to propose a valid and quantitative measurement method to investigate the influence of employee loss and knowledge loss on the vulnerability of MNC knowledge network.

Design/methodology/approach

MNC knowledge network is inherently a heterogeneous network where there are mainly two types of units: employees and their knowledge. Therefore, this paper establishes a weighted super-network model for MNC knowledge network to depict its heterogeneous composition. On the basis of the weighted MNC knowledge super-network, the static and dynamic vulnerability measurement methods are further proposed to investigate and evaluate MNC knowledge network vulnerability.

Findings

A real case is given to illustrate the applicability of the proposed weighted MNC knowledge super-network model and the network vulnerability measurement methods. The results show the super-network model proposed in this paper can effectively embody the complex features of MNC knowledge network, and the vulnerability measurement methods can effectively investigate the influence of employee loss and knowledge loss on network vulnerability.

Originality/value

From the perspective of super-network, researchers and practitioners can get a more systematic and deeper understanding of the MNC knowledge network and its human and knowledge resource constitute which are vital for the evolution and development of MNC. Moreover, the MNC knowledge network vulnerability measurement methods can effectively measure and analyze the influence of resource loss on network vulnerability, which can provide a helpful decision support for monitoring and managing of MNC knowledge network vulnerability to reduce its adverse effects.

Details

Management Decision, vol. 59 no. 1
Type: Research Article
ISSN: 0025-1747

Keywords

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Article
Publication date: 7 September 2012

Xuefeng Zhang, Yulong Zhao and Xuelei Zhang

The purpose of this paper is to provide a thin tactile force sensor array based on conductive rubber and to offer descriptions of the sensor design, fabrication and test.

Abstract

Purpose

The purpose of this paper is to provide a thin tactile force sensor array based on conductive rubber and to offer descriptions of the sensor design, fabrication and test.

Design/methodology/approach

The sensor array consists of a sandwich structure. Sensing elements are distributed discretely in the sensor. Each sensing element has two electrodes and a piece of conductive rubber with piezoresistive property. The electrodes, as well as the conductive trace for signal transmission, are printed on the substrate layer by the screen printing technique. A scanning circuit based on zero potential method and an experimental set‐up based on balance to characterize the sensor array are designed and implemented in the test of the sensor array.

Findings

Experimental results verify the validity of the sensor array in measuring the vertical tactile force between the sensing elements and the object.

Research limitations/implications

In this paper, all the sensors are tested without calibration procedures and the procedure of the dynamic test is implemented by manual operation.

Practical implications

The sensor array could be applied to measure the plantar force for gait detection in clinical applications.

Originality/value

The paper presents a tactile force sensor array with discrete sensing elements to essentially restrict the cross‐talk among sensing elements. This paper will provide many practical details that can help others in the field.

Details

Sensor Review, vol. 32 no. 4
Type: Research Article
ISSN: 0260-2288

Keywords

Content available
Article
Publication date: 14 January 2014

Gary Hunter

Abstract

Details

Sensor Review, vol. 34 no. 1
Type: Research Article
ISSN: 0260-2288

Keywords

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Article
Publication date: 5 February 2018

Qiuhong Chen, Ning Geng and Kan Zhu

The purpose of this paper is to reveal the distributional characteristics and evolutional patterns in source periodicals, topics, authors, funding, and institutes of…

Abstract

Purpose

The purpose of this paper is to reveal the distributional characteristics and evolutional patterns in source periodicals, topics, authors, funding, and institutes of research papers in Chinese Agricultural Economics so as to understand the current situations and developmental tendency of Chinese agricultural economics research over the past decade.

Design/methodology/approach

Using the citation analysis method, this paper analyzed the distributional characteristics and evolution of source periodicals, fields, authors and topics of 2,203 highly cited journal papers from the database of China National Knowledge Infrastructure (CNKI) and 189 cited journal papers from database of Social Sciences Citation Index (SSCI) in agricultural economics first-authored by Chinese scholars from 2006 to 2015.

Findings

First, over the past decade, agricultural economics research in China has seen a rapid development. Specially, 103 scholars and 42 institutes have played key roles in the development, and 12 Chinese periodicals and 3 international journals have been the most influential outlets. Second, the coverage of the topics in Chinese agricultural economics research is broad and has expanded over the past decade. The rural land issue has been the most popular topic, while the issues regarding rural institutional arrangements and industrialization in rural areas have been explored extensively. However, issues in other fields, such as agricultural markets and trade, rural labor, food safety, etc. have to be further studied. Third, the improvements of economic theory and quantitative analytic techniques, the supports from research funding, and an increase in the collaboration between Chinese scholars and those from other countries have made great contribution to the rapid development of Chinese agricultural economics research over the past decade.

Originality/value

This paper is an original work that identifies the most influential journal papers including highly cited journal papers from CNKI and cited journal papers from SSCI, using citation frequency and standard Essential Science Indicators method. This is a contribution relative to the methods used by previous studies, which did not account for frequency of citation of a paper. Moreover, this study is based on data from two databases, CNKI and SSCI, suggesting that the coverage of sample papers is broader compared to those of previous studies.

Details

China Agricultural Economic Review, vol. 10 no. 1
Type: Research Article
ISSN: 1756-137X

Keywords

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Article
Publication date: 11 June 2018

Xuefeng Zhou, Li Jiang, Yisheng Guan, Haifei Zhu, Dan Huang, Taobo Cheng and Hong Zhang

Applications of robotic systems in agriculture, forestry and high-altitude work will enter a new and huge stage in the near future. For these application fields, climbing…

Abstract

Purpose

Applications of robotic systems in agriculture, forestry and high-altitude work will enter a new and huge stage in the near future. For these application fields, climbing robots have attracted much attention and have become one central topic in robotic research. The purpose of this paper is to propose an energy-optimal motion planning method for climbing robots that are applied in an outdoor environment.

Design/methodology/approach

First, a self-designed climbing robot named Climbot is briefly introduced. Then, an energy-optimal motion planning method is proposed for Climbot with simultaneous consideration of kinematic constraints and dynamic constraints. To decrease computing complexity, an acceleration continuous trajectory planner and a path planner based on spatial continuous curve are designed. Simulation and experimental results indicate that this method can search an energy-optimal path effectively.

Findings

Climbot can evidently reduce energy consumption when it moves along the energy-optimal path derived by the method used in this paper.

Research limitations/implications

Only one step climbing motion planning is considered in this method.

Practical implications

With the proposed motion planning method, climbing robots applied in an outdoor environment can commit more missions with limit power supply. In addition, it is also proved that this motion planning method is effective in a complicated obstacle environment with collision-free constraint.

Originality/value

The main contribution of this paper is that it establishes a two-planner system to solve the complex motion planning problem with kinodynamic constraints.

Details

Industrial Robot: An International Journal, vol. 45 no. 3
Type: Research Article
ISSN: 0143-991X

Keywords

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Article
Publication date: 19 January 2015

Wen Liu, Yingjun Zhang, Xuefeng Yang and Shengwei Xing

The aim of this article is to present a PIN (pedestrian inertial navigation) solution that incorporates altitude error correction, which eliminates the altitude error…

Abstract

Purpose

The aim of this article is to present a PIN (pedestrian inertial navigation) solution that incorporates altitude error correction, which eliminates the altitude error accurately without using external sensors. The main problem of PIN is the accumulation of positioning errors due to the drift caused by the noise in the sensors. Experiment results show that the altitude errors are significant when navigating in multilayer buildings, which always lead to localization to incorrect floors.

Design/methodology/approach

The PIN proposed is implemented over an inertial navigation systems (INS) framework and a foot-mounted IMU. The altitude error correction idea is identifying the most probable floor of each horizontal walking motion. To recognize gait types, the walking motion is described with angular rate measured by IMU, and the dynamic time warping algorithm is used to cope with the different dimension samples due to the randomness of walking motion. After gait recognition, the altitude estimated with INS of each horizontal walking is checked for association with one of the existing in a database.

Findings

Experiment results show that high accuracy altitude is achieved with altitude errors below 5 centimeters for upstairs and downstairs routes in a five floors building.

Research limitations/implications

The main limitations of the study is the assumption that accuracy floor altitude information is available.

Originality/value

Our PIN system eliminates altitude errors accurately and intelligently, which benefits from the new idea of combination of gait recognition and map-matching. In addition, only one IMU is used which is different from other approach that use external sensors.

Details

Sensor Review, vol. 35 no. 1
Type: Research Article
ISSN: 0260-2288

Keywords

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Article
Publication date: 16 August 2021

Bifeng Yin, Xuefeng Wang, Bo Xu, Gongyin Huang and Xin Kuang

The purpose of this paper was to improve the frictional wear resistance properties of piston skirts caused by the low viscosity lubricant by studying the tribological…

Abstract

Purpose

The purpose of this paper was to improve the frictional wear resistance properties of piston skirts caused by the low viscosity lubricant by studying the tribological performance of three novel coating materials.

Design/methodology/approach

Comparative tribological examinations were performed in a tribological tester using the ring-block arrangement under two viscosity lubricants, the loading force was applied as 100 N, the speed was set to 60 r/min and the testing time was 180 min.

Findings

Under low viscosity lubricant, the friction coefficient and wear of the three coatings all increase, and the friction coefficient and wear of the PTFE coating are the largest, while the MoS2 coating has the lowest friction coefficient and wear. Under low viscosity lubricant, the friction coefficient of the MoS2 coating is 2.1%–5.4% and 20.0%–24.3% lower than that of the SiO2 and PTFE coating, respectively. The friction coefficient and wear fluctuation rate of the MoS2 coating is the smallest when the lubricant viscosity decreases, which indicates that the MoS2 coating has excellent stability and adaptability under low viscosity lubricant.

Originality/value

To reduce the piston skirt wear caused by low viscosity lubricant in heavy-duty diesel engines, the friction and wear adaptability of three novel composite coating materials for piston skirts were compared under 0 W-20 low viscosity lubricant, which could provide a guidance for the application of wear-resistant materials for heavy-duty diesel engine piston skirt.

Details

Industrial Lubrication and Tribology, vol. 73 no. 6
Type: Research Article
ISSN: 0036-8792

Keywords

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Article
Publication date: 13 November 2017

Xing Wang and Xuefeng Shao

This paper aims to seek the optimal proportion of female executives in corporate management teams, and to analyze the threshold effect of the proportion of female…

Abstract

Purpose

This paper aims to seek the optimal proportion of female executives in corporate management teams, and to analyze the threshold effect of the proportion of female executives on the enterprise market value and enterprise management performance by using a panel threshold regression model. The purpose of this paper is to obtain the optimal interval, during which female executives exert positive effects on enterprise market value and enterprise management performance.

Design/methodology/approach

Based on the data of listed companies in SSE from 2003 to 2012, this paper conducts theoretical and empirical analysis by using a panel threshold regression model.

Findings

This paper proves that the proportion of female executives has a threshold effect on the enterprise market value and enterprise management performance. The results show that the proportion of female executives has an optimal interval. In other words, during the 53.8-68.4 percent interval, the proportion of female executives exerts the least negative effect on the enterprise market value and the most positive effect on the enterprise management performance.

Originality/value

In this paper, the non-linear relationship between female executives, enterprise market value and enterprise management performance has been verified, and the optimization interval of the female executives’ proportion has been figured out as well.

Details

Journal of Organizational Change Management, vol. 30 no. 7
Type: Research Article
ISSN: 0953-4814

Keywords

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Article
Publication date: 2 August 2019

Chengtao Wang, Wei Li, Yuqiao Wang, Xuefeng Yang, Shaoyi Xu, Kunpeng Li and Yunyun Zhao

The purpose of this paper is to predict quantitative level of stray current leaking to the buried metallic structure by establishing convolution neural network (CNN) model.

Abstract

Purpose

The purpose of this paper is to predict quantitative level of stray current leaking to the buried metallic structure by establishing convolution neural network (CNN) model.

Design/methodology/approach

First, corrosion experimental system of buried metallic structure is established. The research object of this paper is the polarization potential within 110 min, CNN model is used to predict the quantitative level of stray current leakage using the data from corrosion experimental system further. Finally, results are compared with the method using BP neural network.

Findings

Results show that the CNN model has better predictive effect and shorter prediction time than the BP model, the accuracy of which is 82.5507 per cent, and the prediction time is shortened by more than 10 times.

Originality/value

The established model can be used to forecast the level of stray current leakage in the subway system effectively, which provides a new theoretical basis for evaluating the stray current corrosion hazard of buried metallic structure.

Details

Anti-Corrosion Methods and Materials, vol. 66 no. 4
Type: Research Article
ISSN: 0003-5599

Keywords

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