Mingwei Lin, Yanqiu Chen and Riqing Chen
The purpose of this paper is to make a comprehensive analysis of 354 publications about Pythagorean fuzzy sets (PFSs) from 2013 to 2020 in order to comprehensively understand…
Abstract
Purpose
The purpose of this paper is to make a comprehensive analysis of 354 publications about Pythagorean fuzzy sets (PFSs) from 2013 to 2020 in order to comprehensively understand their historical progress and current situation, as well as future development trend.
Design/methodology/approach
First, this paper describes the fundamental information of these publications on PFSs, including their data information, annual trend and prediction and basic features. Second, the most productive and influential authors, countries/regions, institutions and the most cited documents are presented in the form of evaluation indicators. Third, with the help of VOSviewer software, the visualization analysis is conducted to show the development status of PFSs publications at the level of authors, countries/regions, institutions and keywords. Finally, the burst detection of keywords, timezone review and timeline review are exported from CiteSpace software to analyze the hotspots and development trend on PFSs.
Findings
The annual PFSs publications present a quickly increasing trend. The most productive author is Wei Guiwu (China). Wei Guiwu and Wei Cun have the strongest cooperative relationship.
Research limitations/implications
The implication of this study is to provide a comprehensive perspective for the scholars who take a fancy to PFSs, and it is valuable for scholars to grasp the hotspots in this field in time.
Originality/value
It is the first paper that uses the bibliometric analysis to comprehensively analyze the publications on PFSs. It can help the scholars in the field of PFSs to quickly understand the development status and trend of PFSs.
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Lili Zhang, Jie Ling and Mingwei Lin
The aim of this paper is to present a comprehensive analysis of risk management in East Asia from 1998 to 2021 by using bibliometric methods and tools to explore research trends…
Abstract
Purpose
The aim of this paper is to present a comprehensive analysis of risk management in East Asia from 1998 to 2021 by using bibliometric methods and tools to explore research trends, hotspots, and directions for future research.
Design/methodology/approach
The data source for this paper is the Web of Science Core Collection, and 7,154 publications and related information have been derived. We use recognized bibliometric indicators to evaluate publications and visually analyze them through scientific mapping tools (VOS Viewer and CiteSpace).
Findings
The analysis results show that China is the most productive and influential country/region. East Asia countries have strong cooperation with each other and also have cooperation with other countries. The study shows that risk management has been involved in various fields such as credit, supply chain, health emergency and disaster especially in the background of COVID-19. We also found that machine learning, especially deep learning, has been playing an increasingly important role in risk management due to its excellent performance.
Originality/value
This paper focuses on studying risk management in East Asia, exploring its publication's fundamental information, citation and cooperation networks, hotspots, and research trends. It provides some reference value for scholars who are interested or further research in this field.
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Yuhan Luo and Mingwei Lin
The purpose of this paper is to make an overview of 474 publications and 512 patents of FTL from 1987 to 2020 in order to provide a conclusive and comprehensive analysis for…
Abstract
Purpose
The purpose of this paper is to make an overview of 474 publications and 512 patents of FTL from 1987 to 2020 in order to provide a conclusive and comprehensive analysis for researchers in this field, as well as a preliminary knowledge of FTL for interested researchers.
Design/methodology/approach
Firstly, the FTL algorithms are classified and its functions are introduced in detail. Secondly, the structures of the publications are analyzed in terms of the fundamental information and the publication of the most productive countries/regions, institutions and authors. After that, co-citation networks of institutions, authors and papers illustrated by VOS Viewer are given to show the relationship among those and the most influential of them is further analyzed. Then, the characteristics of the patent are analyzed based on the basic information and classification of the patent and the most productive inventors. In order to obtain research hotspots and trends in this field, the time-line review and citation burst detection of keywords carried out by Cite Space are made to be visual. Finally, based on the above analysis, it draws some other important conclusions and the development trend of this field.
Findings
The research on FTL algorithm is still the top priority in the future, and how to improve the performance of SSD in the era of big data is one of the research hotspots.
Research limitations/implications
This paper makes a comprehensive analysis of FTL with the method of bibliometrics, and it is valuable for researchers can quickly grasp the hotspots in this area.
Originality/value
This article draws the structural characteristics of the publications in this field and summarizes the research hotspots and trends in this field in recent years, aiming to inspire new ideas for researchers.
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Jianpeng Zhang and Mingwei Lin
The purpose of this paper is to make an overview of 6,618 publications of Apache Hadoop from 2008 to 2020 in order to provide a conclusive and comprehensive analysis for…
Abstract
Purpose
The purpose of this paper is to make an overview of 6,618 publications of Apache Hadoop from 2008 to 2020 in order to provide a conclusive and comprehensive analysis for researchers in this field, as well as a preliminary knowledge of Apache Hadoop for interested researchers.
Design/methodology/approach
This paper employs the bibliometric analysis and visual analysis approaches to systematically study and analyze publications about Apache Hadoop in the Web of Science database. This study aims to investigate the topic of Apache Hadoop by means of bibliometric analysis with the aid of visualization applications. Through the bibliometric analysis of the collected documents, this paper analyzes the main statistical characteristics and cooperation networks. Research themes, research hotspots and future development trends are also investigated through the keyword analysis.
Findings
The research on Apache Hadoop is still the top priority in the future, and how to improve the performance of Apache Hadoop in the era of big data is one of the research hotspots.
Research limitations/implications
This paper makes a comprehensive analysis of Apache Hadoop with methods of bibliometrics, and it is valuable for researchers can quickly grasp the hot topics in this area.
Originality/value
This paper draws the structural characteristics of the publications in this field and summarizes the research hotspots and trends in this field in recent years, aiming to understand the development status and trends in this field and inspire new ideas for researchers.
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Zhuoyu Zhang, Lijia Zhong, Mingwei Lin, Ri Lin and Dejun Li
Docking technology plays a crucial role in enabling long-duration operations of autonomous underwater vehicles (AUVs). Visual positioning solutions alone are susceptible to…
Abstract
Purpose
Docking technology plays a crucial role in enabling long-duration operations of autonomous underwater vehicles (AUVs). Visual positioning solutions alone are susceptible to abnormal drift values due to the challenging underwater optical imaging environment. When an AUV approaches the docking station, the absolute positioning method fails if the AUV captures an insufficient number of tracers. This study aims to to provide a more stable absolute position visual positioning method for underwater terminal visual docking.
Design/methodology/approach
This paper presents a six-degree-of-freedom positioning method for AUV terminal visual docking, which uses lights and triangle codes. The authors use an extended Kalman filter to fuse the visual calculation results with inertial measurement unit data. Moreover, this paper proposes a triangle code recognition and positioning algorithm.
Findings
The authors conducted a simulation experiment to compare the underwater positioning performance of triangle codes, AprilTag and Aruco. The results demonstrate that the implemented triangular code reduces the running time by over 70% compared to the other two codes, and also exhibits a longer recognition distance in turbid environments. Subsequent experiments were carried out in Qingjiang Lake, Hubei Province, China, which further confirmed the effectiveness of the proposed positioning algorithm.
Originality/value
This fusion approach effectively mitigates abnormal drift errors stemming from visual positioning and cumulative errors resulting from inertial navigation. The authors also propose a triangle code recognition and positioning algorithm as a supplementary approach to overcome the limitations of tracer light positioning beacons.
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Jiaqi Liu, Jialong Jiang, Mingwei Lin, Hong Chen and Zeshui Xu
When recommending products to consumers, it is important to be able to accurately predict how consumers will rate them. However, existing collaborative filtering models are…
Abstract
Purpose
When recommending products to consumers, it is important to be able to accurately predict how consumers will rate them. However, existing collaborative filtering models are difficult to achieve a balance between rating prediction accuracy and complexity. Therefore, the purpose of this paper is to propose an accurate and effective model to predict users’ ratings of products for the accurate recommendation of products to users.
Design/methodology/approach
First, we introduce an attention mechanism that dynamically assigns weights to user preferences, highlighting key interaction information and enhancing the model’s understanding of user behavior. Second, a fold embedding strategy is employed to segment user interaction data, increasing the information density of each subset while reducing the complexity of the attention mechanism. Finally, a masking strategy is integrated to mitigate overfitting by concealing portions of user-item interactions, thereby improving the model’s generalization ability.
Findings
The experimental results demonstrate that the proposed model significantly minimizes prediction error across five real-world datasets. On average, the evaluation metrics root mean square error (RMSE) and mean absolute error (MAE) are reduced by 9.11 and 13.3%, respectively. Additionally, the Friedman test results confirm that these improvements are statistically significant. Consequently, the proposed model more accurately captures the intrinsic correlation between users and products, leading to a substantial reduction in prediction error.
Originality/value
We propose a novel collaborative filtering model to learn the user-item interaction matrix effectively. Additionally, we introduce a fold embedding strategy to reduce the computational resource consumption of the attention mechanism. Finally, we implement a masking strategy to encourage the model to focus on key features and patterns, thereby mitigating overfitting.
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Rui Yu, Hua Zhou, Siyu Ma, Guifu Luo and Mingwei Lin
Hydrodynamic parameter estimation is significant for the velocity prediction of unmanned surface vehicles. Considering the field data’s uncertain nonlinearities (environmental…
Abstract
Purpose
Hydrodynamic parameter estimation is significant for the velocity prediction of unmanned surface vehicles. Considering the field data’s uncertain nonlinearities (environmental disturbances and measurement noise), this paper aims to propose a hybrid adaptive parameter estimation (HAPE) strategy.
Design/methodology/approach
First, a rough estimation of hydrodynamic parameters is used by the least squares method. Second, an improved adaptive parameter estimation algorithm is applied to compensate for the influence of uncertain nonlinearities and adjust the parameters within the rough range. Finally, it is proved that the calculated velocity asymptotically converges to the actual value during the parameter estimation procedure.
Findings
The numerical simulation and pool experiments are conducted in two scenarios of steady turning and sinusoidal thrust to verify the effectiveness of the proposed HAPE method. The results validate that the accuracy of the predicted velocity using the hydrodynamic model obtained by the HAPE strategy is better than the APE algorithm. In addition, the hydrodynamic parameters estimated with the sinusoidal thrust data are more applicable than the steady turning data.
Originality/value
This study proposes a HAPE strategy that considers the uncertain nonlinearities of the field data. This method provides a more accurate predicted velocity. Besides, as far as we know, it is the first time to analyze the influence of different test conditions on the accuracy of the predicted velocity.
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Weixing Wang, Yixia Chen and Mingwei Lin
Based on the strong feature representation ability of the convolutional neural network (CNN), generous object detection methods in remote sensing (RS) have been proposed one after…
Abstract
Purpose
Based on the strong feature representation ability of the convolutional neural network (CNN), generous object detection methods in remote sensing (RS) have been proposed one after another. However, due to the large variation in scale and the omission of relevant relationships between objects, there are still great challenges for object detection in RS. Most object detection methods fail to take the difficulties of detecting small and medium-sized objects and global context into account. Moreover, inference time and lightness are also major pain points in the field of RS.
Design/methodology/approach
To alleviate the aforementioned problems, this study proposes a novel method for object detection in RS, which is called lightweight object detection with a multi-receptive field and long-range dependency in RS images (MFLD). The multi-receptive field extraction (MRFE) and long-range dependency information extraction (LDIE) modules are put forward.
Findings
To concentrate on the variability of objects in RS, MRFE effectively expands the receptive field by a combination of atrous separable convolutions with different dilated rates. Considering the shortcomings of CNN in extracting global information, LDIE is designed to capture the relationships between objects. Extensive experiments over public datasets in RS images demonstrate that our MFLD method surpasses the state-of-the-art methods. Most of all, on the NWPU VHR-10 dataset, our MFLD method achieves 94.6% mean average precision with 4.08 M model volume.
Originality/value
This paper proposed a method called lightweight object detection with multi-receptive field and long-range dependency in RS images.
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Mingyue Xie, Jun Liu, Shuyu Chen and Mingwei Lin
As the core technology of blockchain, various consensus mechanisms have emerged to satisfy the demands of different application scenarios. Since determining the security…
Abstract
Purpose
As the core technology of blockchain, various consensus mechanisms have emerged to satisfy the demands of different application scenarios. Since determining the security, scalability and other related performance of the blockchain, how to reach consensus efficiently of consensus mechanism is a critical issue in the blockchain.
Design/methodology/approach
The paper opted for a research overview on the blockchain consensus mechanism, including the consensus mechanisms' consensus progress, classification and comparison, which are complemented by documentary analysis.
Findings
This survey analyzes solutions for the improvement of consensus mechanisms in blockchain that have been proposed during the last few years and suggests future research directions around consensus mechanisms. First, the authors outline the consensus processes, the advantages and disadvantages of the mainstream consensus mechanisms. Additionally, the consensus mechanisms are subdivided into four types according to their characteristics. Then, the consensus mechanisms are compared and analyzed based on four evaluation criteria. Finally, the authors summarize the representative progress of consensus mechanisms and provide some suggestions on the design of consensus mechanisms to make further advances in this field.
Originality/value
This paper summarizes the future research development of the consensus mechanisms.
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Canjun Yang, Weitao Wu, Xin Wu, Jifei Zhou, Zhangpeng Tu, Mingwei Lin and Sheng Zhang
Variable stiffness structure can significantly improve the interactive capabilities of grippers. Shape memory alloys have become a popular option for materials with variable…
Abstract
Purpose
Variable stiffness structure can significantly improve the interactive capabilities of grippers. Shape memory alloys have become a popular option for materials with variable stiffness structures. However, its variable stiffness range is limited by its stiffness in two phases. The purpose of this paper is to enhance the manipulation capabilities of tendon-driven flexible grippers by designing a wide-range variable stiffness structure.
Design/methodology/approach
Constitutive models of shape memory alloy and mechanical models are used to analyze the performance of the variable stiffness structure. A separated solution was used to combine the tendon-driven gripper and the variable stiffness structure. The feed-forward control algorithm is used to enhance the control stability of the variable stiffness structure.
Findings
The stiffness variable capability of the proposed variable stiffness structure is verified by experiments. The stability of the feedback control algorithm was verified by sinusoidal tracking experiments. The variable stiffness range of 8.41 times of the flexible gripper was tested experimentally. The interaction capability of the variable stiffness flexible gripper is verified by the object grasping experiments.
Originality/value
A new wide-range variable stiffness structure is proposed and validated. The new variable stiffness structure has a larger range of stiffness variation and better control stability. The new flexible structure can be applied to conventional grippers to help them gain stiffness variable capability and improve their interaction ability.