Tao Zhang, Yuntao Song, Huapeng Wu and Qi Wang
Every geometric model corresponding to a unique feature whose errors of parameters uncorrelated, so the linearization technique can be successfully applied. The solution of a…
Abstract
Purpose
Every geometric model corresponding to a unique feature whose errors of parameters uncorrelated, so the linearization technique can be successfully applied. The solution of a linear least square problem can be applied straightforwardly. This method has advantages especially in calibrate the redundant robot because it’s relatively small. The parameters of kinematics are unique and determined by this algorithm.
Design/methodology/approach
In this paper, a geometric identification method has been studied to estimate the parameters in the Denavit–Hartenberg (DH) model of the robot. Through studying the robot’s geometric features, specific trajectories are designed for calibrating the DH parameters. On the basis of these geometric features, several fitting methods have been deduced so that the important geometric parameters of robots, such as the actual rotation centers and rotate axes, can be found.
Findings
By measuring the corresponding motion trajectory at the end-effector, the trajectory feature can be identified by using curve fitting methods, and the trajectory feature will reflect back to the actual value of the DH parameters.
Originality/value
This method is especially suitable for rigid serial-link robots especially for redundant robots because of its specific calibration trajectory and geometric features. Besides, this method uses geometric features to calibrate the robot which is relatively small especially for the redundant robot comparing to the numerical algorithm.
Details
Keywords
Keqing Li, Xiaojia Wang, Changyong Liang and Wenxing Lu
The elderly service industry is emerging in China. The Chinese government introduced a series of policies to guide elderly service enterprises to improve their service quality…
Abstract
Purpose
The elderly service industry is emerging in China. The Chinese government introduced a series of policies to guide elderly service enterprises to improve their service quality. This study explores novel differentiated subsidy strategies that not only promote the improvement of service quality in elderly service enterprises but also alleviate the financial burden on the government.
Design/methodology/approach
Evolutionary game and Hotelling models are employed to investigate this issue. First, a Hotelling model that considers consumer word-of-mouth preferences is established. Subsequently, an evolutionary game model between local governments and enterprises is constructed, and the evolutionary stable strategies of both parties are analyzed. Finally, simulation experiments are conducted.
Findings
The findings indicate that local government decisions have a significant influence on the behavior of elderly service enterprises. Increasing the proportion of local governments opting for subsidy strategies helps incentivize elderly service enterprises to improve their service quality. Furthermore, providing differentiated subsidies based on the preferences of the customer base of elderly service enterprises can encourage service quality improvement while reducing government expenditure. The findings offer valuable insights into the design of government subsidy policies.
Originality/value
Compared with previous research, this study examines the role of consumer preferences in a differentiated subsidy policy. This enriches the authors’ understanding of the field by incorporating neglected aspects of consumer preferences in the context of the emerging elderly service industry.
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Xuhui Cong, Liang Wang, Li Ma and M. Skibnewski
This study aims to explore the critical influencing factors that lead to the site selection failure of waste-to-energy (WtE) projects in China under the influence of the “Not In…
Abstract
Purpose
This study aims to explore the critical influencing factors that lead to the site selection failure of waste-to-energy (WtE) projects in China under the influence of the “Not In My Back Yard” (NIMBY) effect, which can provide references to improve the decision-making process of similar projects in the future.
Design/methodology/approach
The fuzzy decision-making trial and evaluation laboratory (DEMATEL) method was used to propose an analytical framework for exploring the critical influencing factors affecting the site selection failure of WtE projects. The causal relationship between different influencing factors is finally determined on the basis of the opinions of 12 experts from universities, government departments, consulting units, planning and design units, construction units and WtE enterprises.
Findings
Results showed that six crucial factors resulted in the site selection failure of WtE projects from the NIMBY effect perspective: “Insufficient public participation,” “Near the place of residence,” “Nonstandard government decision-making processes,” “Low information disclosure,” “Destroys the surrounding environment,” and “Imperfect compensation scheme.”
Originality/value
Results can determine the priorities and causal relationships among the various influencing factors. The decision-making optimization suggestions can provide reference for decision- makers, thereby possibly promoting the scientific and standardization of site selection decision process.
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Lei Song, Ping Lyu and Yingui Cao
The purpose of this study was to analyze the interest conflicts and strategy evolution process of various stakeholders in the process of homestead withdrawal, to reveal which key…
Abstract
Purpose
The purpose of this study was to analyze the interest conflicts and strategy evolution process of various stakeholders in the process of homestead withdrawal, to reveal which key factors can balance the interests of all parties.
Design/methodology/approach
The authors developed an evolutionary game theoretical framework for homestead withdrawal in Yujiang District, Jiangxi Province, China. The authors compared the dynamic process of strategy change in different situations based on system dynamics.
Findings
Compared with indirect external factors, direct economic factors, such as increasing compensation standards or increasing fines, are more likely to encourage peasants to withdraw from their homesteads. The dynamic subsidy strategy can increase the probability of peasants withdrawing from their homestead. Additionally, awarding officials with promotions can effectively encourage local governments during the process.
Originality/value
Previous studies have conceptualized farmers' willingness to withdraw from their homestead as a static process, ignoring the underlying dynamism. This paper analyzes the game mechanism among the stakeholders of the homestead withdrawal process from a dynamic perspective, to provide efficient suggestions regarding policymaking for homestead withdrawal.
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A. George Assaf and Mike G. Tsionas
This paper aims to present several Bayesian specification tests for both in- and out-of-sample situations.
Abstract
Purpose
This paper aims to present several Bayesian specification tests for both in- and out-of-sample situations.
Design/methodology/approach
The authors focus on the Bayesian equivalents of the frequentist approach for testing heteroskedasticity, autocorrelation and functional form specification. For out-of-sample diagnostics, the authors consider several tests to evaluate the predictive ability of the model.
Findings
The authors demonstrate the performance of these tests using an application on the relationship between price and occupancy rate from the hotel industry. For purposes of comparison, the authors also provide evidence from traditional frequentist tests.
Research limitations/implications
There certainly exist other issues and diagnostic tests that are not covered in this paper. The issues that are addressed, however, are critically important and can be applied to most modeling situations.
Originality/value
With the increased use of the Bayesian approach in various modeling contexts, this paper serves as an important guide for diagnostic testing in Bayesian analysis. Diagnostic analysis is essential and should always accompany the estimation of regression models.
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This paper aims to improve the infilling efficiency and the quality of parts forming. It proposes two improved scanning path planning algorithm based on velocity orthogonal…
Abstract
Purpose
This paper aims to improve the infilling efficiency and the quality of parts forming. It proposes two improved scanning path planning algorithm based on velocity orthogonal decomposition.
Design/methodology/approach
The algorithms this paper proposes replace empty paths and corners with circular segments, driving each axis synchronously according to the SIN or COS velocity curve to make the extruder always moves at a constant speed at maximum during the infilling process. Also, to support the improved algorithms, a three-dimensional (3D) printing control system based on circular motion controller is also designed.
Findings
The simulation and experiment results show that the improved algorithms are effective, and the printing time is shortened more significantly, especially in the case of small or complex models. What’s more, the optimized algorithm is not only compact in shape but also not obvious in edge warping.
Research limitations/implications
The algorithms in this paper are not applicable to traditional motion controllers.
Practical implications
The algorithms in this paper improve the infilling efficiency and the quality of parts forming.
Social implications
There are no social implications in this paper.
Originality/value
The specific optimization method of parallel-line scanning algorithm based on velocity orthogonal decomposition is replacing the empty paths with arc corners. And the specific optimization method of contour offsetting algorithm based on velocity orthogonal decomposition is to add connection paths between adjacent contours and turn all straight corners into arcs. What’s more, the 3D printing control system based on the circular motion controller can achieve multi-axis parallel motion to support these two improved path scanning algorithms.
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Kedong Yin, Yun Cao, Shiwei Zhou and Xinman Lv
The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems…
Abstract
Purpose
The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.
Design/methodology/approach
Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.
Findings
Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.
Originality/value
The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.
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Bingwei Gao, Hongjian Zhao, Wenlong Han and Shilong Xue
This study proposes a predictive neural network model reference decoupling control method for the coupling problem between the leg joints of hydraulic quadruped robots, and…
Abstract
Purpose
This study proposes a predictive neural network model reference decoupling control method for the coupling problem between the leg joints of hydraulic quadruped robots, and verifies its decoupling effect..
Design/methodology/approach
The machine–hydraulic cross-linking coupling is studied as the coupling behavior of the hydraulically driven quadruped robot, and the mechanical dynamics coupling force of the robot system is controlled as the disturbance force of the hydraulic system through the Jacobian matrix transformation. According to the principle of multivariable decoupling, a prediction-based neural network model reference decoupling control method is proposed; each module of the control algorithm is designed one by one, and the stability of the system is analyzed by the Lyapunov stability theorem.
Findings
The simulation and experimental research on the robot joint decoupling control method is carried out, and the prediction-based neural network model reference decoupling control method is compared with the decoupling control method without any decoupling control method. The results show that taking the coupling effect experiment between the hip joint and knee joint as an example, after using the predictive neural network model reference decoupling control method, the phase lag of the hip joint response line was reduced from 20.3° to 14.8°, the amplitude attenuation was reduced from 1.82% to 0.21%, the maximum error of the knee joint coupling line was reduced from 0.67 mm to 0.16 mm and the coupling effect between the hip joint and knee joint was reduced from 1.9% to 0.48%, achieving good decoupling.
Originality/value
The prediction-based neural network model reference decoupling control method proposed in this paper can use the neural network model to predict the next output of the system according to the input and output. Finally, the weights of the neural network are corrected online according to the predicted output and the given reference output, so that the optimization index of the neural network decoupling controller is extremely small, and the purpose of decoupling control is achieved.
Details
Keywords
Bijuan Yan, Huijun Liang, Minjie Jin, Zhanlong Li and Yong Song
In the vibration reduction field, constrained stand-off layer damping cylindrical shell plays an important role. However, due to the lack of accurate analysis of its damping…
Abstract
Purpose
In the vibration reduction field, constrained stand-off layer damping cylindrical shell plays an important role. However, due to the lack of accurate analysis of its damping characteristics, this hinders its further research and application. Therefore, the purpose of this paper is concerned with an accurate solution for the vibration-damping characteristics of a constrained stand-off-layer damping cylindrical shell (CSDCS) under various classical boundary conditions and conducts a further analysis.
Design/methodology/approach
Based on the Rayleigh–Ritz method and the Hamilton principle, a dynamic model of CSDCS is established. Then the loss factor and the frequency of CSDCS are obtained. The correctness and convergence behavior of the present model are verified by comparing the calculation results with the literature. By using for various classical boundary conditions without any special modifications in the solution procedure, the characteristics of CSDCS with S-S, C-C, C-S, C-F and S-F boundaries are discussed.
Findings
The Rayleigh–Ritz method is effective in handling the problem of CSDCS with different boundaries and an accurate solution is obtained. The boundary conditions have an important influence on the vibration and damping behavior of the CSDCS.
Originality/value
Based on the Rayleigh–Ritz method and Hamilton principle, a dynamic model of CSDCS is established for the first time, and then the loss factor and frequency of CSDCS are obtained. In addition, the effectiveness of adding the stand-off layer between the base shell and the viscoelastic layer is confirmed by discussing the characteristics of CSDCS with S-S, C-C, C-S, C-F and S-F boundaries.
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Yang Song, Yanhe Jia and Jian Zhang
To solve the problems of annotation noise, ambiguity recognition and nested entity recognition in the field of Chinese furniture, this paper aims to design a new recognition model…
Abstract
Purpose
To solve the problems of annotation noise, ambiguity recognition and nested entity recognition in the field of Chinese furniture, this paper aims to design a new recognition model ALE-BiLSTM-CRF.
Design/methodology/approach
This paper addresses the relative independence of text characters in the Chinese furniture domain named entity recognition (NER) task. It also considers the limited information provided by these text characters in this task. Therefore, a model named ALE-BiLSTM-CRF for Chinese furniture domain NER is proposed. First, the ERNIE pre-trained model is used to transform text into a dynamic vector that integrates contextual information. And adversarial learning is combined to generate adversarial samples to enhance the robustness of the model. Next, the BiLSTM module captures the temporal information of the context, and the multi-head attention mechanism integrates long-distance semantic features into the character vectors. Finally, a CRF layer is used to learn the constraints between labels, enabling the model to generate more reasonable and semantically consistent label sequences. This paper conducts comparative experiments with mainstream models on the Weibo data set, achieving an F1 score of 75.52%, demonstrating its generality and robustness. Additionally, comparative and ablation experiments are conducted on a self-constructed furniture data set in the Chinese furniture field, achieving an F1 score of 89.62%, verifying the model’s superiority and effectiveness.
Findings
This paper conducts comparative experiments with mainstream models on the Weibo data set, achieving an F1 score of 75.52%, demonstrating its generality and robustness. Additionally, comparative and ablation experiments are conducted on a self-constructed furniture data set in the Chinese furniture field, achieving an F1 score of 89.62%, verifying the model’s superiority and effectiveness.
Research limitations/implications
This paper demonstrates its universality and generalization by conducting comparative experiments with mainstream models on the Weibo data set. It also conducts comparative experiments with representative pre-trained models on the furniture data set and conducts ablation experiments on the model itself, further demonstrating the superiority and effectiveness of the model.
Practical implications
In the furniture domain, NER aims to use various methods, including rule templates, machine learning and deep learning techniques, to extract structured information related to furniture from unstructured text. These pieces of information may include the name, material, brand, style and function of the furniture. By extracting and identifying these named entities, this paper can provide more accurate data support for furniture design, manufacturing and marketing, thereby promoting further development and innovation in the furniture industry.
Social implications
In the furniture field, NER faces some special challenges, which are different from entity recognition in general fields. Furniture terminology is often highly specialized and complex in structure. At the same time, there may be a large number of nested entities in the text of the furniture field. For example, the furniture name “sofa bed” contains two entities “sofa” and “bed.” Current sequence labeling methods often find it difficult to recognize such nested entity structures simultaneously. Additionally, because furniture terminology and descriptions may change with trends and design styles, the model also needs to have a certain degree of adaptability and update capabilities. These reasons make it more difficult to extract information in the furniture field, and NER in the furniture field faces huge challenges.
Originality/value
This paper conducts comparative experiments with mainstream models on the Weibo data set, achieving an F1 score of 75.52%, demonstrating its generality and robustness. Additionally, comparative and ablation experiments are conducted on a self-constructed furniture data set in the Chinese furniture field, achieving an F1 score of 89.62%, verifying the model’s superiority and effectiveness.