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1 – 10 of 643Kang Min, Fenglei Ni, Guojun Zhang, Xin Shu and Hong Liu
The purpose of this paper is to propose a smooth double-spline interpolation method for six-degree-of-freedom rotational robot manipulators, achieving the global C2 continuity of…
Abstract
Purpose
The purpose of this paper is to propose a smooth double-spline interpolation method for six-degree-of-freedom rotational robot manipulators, achieving the global C2 continuity of the robot trajectory.
Design/methodology/approach
This paper presents a smooth double-spline interpolation method, achieving the global C2 continuity of the robot trajectory. The tool center positions and quaternion orientations are first fitted by a cubic B-spline curve and a quartic-polynomial-based quaternion spline curve, respectively. Then, a parameter synchronization model is proposed to realize the synchronous and smooth movement of the robot along the double spline curves. Finally, an extra u-s function is used to record the relationship between the B-spline parameter and its arc length parameter, which may reduce the feed rate fluctuation in interpolation. The seven segments jerk-limited feed rate profile is used to generate motion commands for algorithm validation.
Findings
The simulation and experimental results demonstrate that the proposed method is effective and can generate the global C2-continuity robot trajectory.
Originality/value
The main contributions of this paper are as follows: guarantee the C2 continuity of the position path and quaternion orientation path simultaneously; provide a parameter synchronization model to realize the synchronous and smooth movement of the robot along the double spline curves; and add an extra u-s function to realize arc length parameterization of the B-spline path, which may reduce the feed rate fluctuation in interpolation.
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Dongfei Li, Hongtao Wang and Ning Dai
This paper aims to propose a method for automatic design of additive manufacturing (AM) flow channel paths driven by path length and pressure loss. The research focuses on the…
Abstract
Purpose
This paper aims to propose a method for automatic design of additive manufacturing (AM) flow channel paths driven by path length and pressure loss. The research focuses on the automatic design of channel paths, intending to achieve the shortest flow channel length or minimum pressure loss and improve the design efficiency of AM parts.
Design/methodology/approach
The initial layout of the flow channels is redesigned to consider the channels print supports. Boundary conditions and constraints are defined according to the redesigned channels layout, and the equation consisting of channel length and pressure loss is used as the objective function. Then the path planning simulation is performed based on particle swarm algorithm. The proposed method describes the path of flow channels using spline cures. The spline curve is controlled by particle (one particle represents a path), and the particle is randomly generated within the design space. After the path planning simulation is completed, the generated paths are used to create 3D parts.
Findings
Case study 1 demonstrates the automatic design of hydraulic spool valve. Compared to conventional spool valve, the pressure loss was reduced by 86% and the mass was reduced by 83%. The design results of case study 2 indicate that this approach is able to find the shortest channel path with lower computational cost.
Originality/value
The automatic design method of flow channel paths driven by path length and pressure loss presented in this paper provides a novel solution for the creation of AM flow components.
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Yu Wu and Calum G. Turvey
The purpose of this paper is to determine the effects of the 2018–2020 China–US trade war on US farm bankruptcies as filed under Chapter 12. The key task is to identify the…
Abstract
Purpose
The purpose of this paper is to determine the effects of the 2018–2020 China–US trade war on US farm bankruptcies as filed under Chapter 12. The key task is to identify the economic factors affecting farm bankruptcies generally, and to then control for the trade war impacts including the Market Facilitation Program (MFP), floods, agricultural conditions and the health of agricultural finance leading into the trade war.
Design/methodology/approach
Results were obtained using ordinary least square regression and panel fixed effect model using bankruptcy rates and number as the dependent variable. Independent variables included market effects, credit conditions, yield variation, trade impacts, 2019 flooding, macroeconomic conditions and regional fixed effects. The authors use cubic splines to interpolate annual and quarterly data to a monthly base.
Findings
Based on a fixed effect model, the authors find that all other things being equal the China–USA trade war would have had a significant impact on Chapter 12 farm bankruptcies, increasing the bankruptcy rate by 25.7%. The flooding in 2009 had minor effects of increasing the rate by only 0.05%. The overall impact will, however be substantially lower than the 25.7% because of the MFP. The MFP variables (binary) had mixed effects and its true impact is unknowable at this time; however, the authors also find that a 1% increase in the producer price index decreases bankruptcy rates by 2.62% and farm bankruptcy numbers by 3.70%. Likewise a 1% increase in GDP reduces bankruptcies by 3.25%. These suggest that the MFP program will have likely reduced farm bankruptcies considerably than what would have occurred in their absence. The authors also find that states heavily dependent on trade faced lower market uncertainty. Broader economic factors (net charge-offs of farm loans held by insured commercial banks, US real GDP, the average effective interest rate on nonreal estate farm loans) affect farm bankruptcy.
Research limitations/implications
The authors use monthly bankruptcy statistics, however not all data were available in monthly measures requiring interpolation using cubic spline functions to approximate monthly changes in some variables. Although the MFP had mixed effects in the model, the mid- to longer-term effects may be more impactful. These longer-term effects (and even shorter-term effects through 2020) are complicated by the coronavirus disease 2019 (COVID-19) pandemic, which will require a different identification strategy than that employed in this paper.
Originality/value
The analysis and results of this paper are, to the authors' knowledge, the first to investigate the impact of the China–US trade war on Chapter 12 farm bankruptcy filings. The use of cubic splines in the interpolation of agricultural data is also a technical innovation.
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Timo Hülsmann, Andreas Bartel, Sebastian Schöps and Herbert De Gersem
The purpose of this paper is to develop a fast and accurate analytic model function for the single-valued H-B curve of ferromagnetic materials, where hysteresis can be disregarded…
Abstract
Purpose
The purpose of this paper is to develop a fast and accurate analytic model function for the single-valued H-B curve of ferromagnetic materials, where hysteresis can be disregarded (normal magnetization curve). Nonlinear magnetoquasistatic simulations demand smooth monotone material models to ensure physical correctness and good convergence in Newton's method.
Design/methodology/approach
The Brauer model has these beneficial properties, but is not sufficiently accurate for low and high fields in the normal magnetization curve. The paper extends the Brauer model to better fit material behavior in the Rayleigh region (low fields) and in full saturation. Procedures for obtaining optimal parameters from given measurement points are proposed and tested for two technical materials. The approach is compared with cubic spline and monotonicity preserving spline interpolation with respect to error and computational effort.
Findings
The extended Brauer model is more accurate and even maintains the computational advantages of the classical Brauer model. The methods for obtaining optimal parameters yield good results if the measurement points have a distinctive Rayleigh region.
Originality/value
The model function for ferromagnetic materials enhances the precision of the classical Brauer model without notable additional simulation cost.
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Ming-min Liu, L.Z. Li and Jun Zhang
The purpose of this paper is to discuss a data interpolation method of curved surfaces from the point of dimension reduction and manifold learning.
Abstract
Purpose
The purpose of this paper is to discuss a data interpolation method of curved surfaces from the point of dimension reduction and manifold learning.
Design/methodology/approach
Instead of transmitting data of curved surfaces in 3D space directly, the method transmits data by unfolding 3D curved surfaces into 2D planes by manifold learning algorithms. The similarity between surface unfolding and manifold learning is discussed. Projection ability of several manifold learning algorithms is investigated to unfold curved surface. The algorithms’ efficiency and their influences on the accuracy of data transmission are investigated by three examples.
Findings
It is found that the data interpolations using manifold learning algorithms LLE, HLLE and LTSA are efficient and accurate.
Originality/value
The method can improve the accuracies of coupling data interpolation and fluid-structure interaction simulation involving curved surfaces.
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João Gabriel Ribeiro and Sônia Maria de Stefano Piedade
The state of Mato Grosso represents the largest producer and exporter of soybeans in Brazil; given this importance, it was aimed to propose to use the univariate imputation tool…
Abstract
Purpose
The state of Mato Grosso represents the largest producer and exporter of soybeans in Brazil; given this importance, it was aimed to propose to use the univariate imputation tool for time series, through applications of splines interpolations, in 46 of its municipalities that had missing data in the variables soybean production in thousand tons, production value and soy derivatives in R$ thousand, and also to assess the differences between the observed series and those with imputed values, in each of these municipalities, in these variables.
Design/methodology/approach
The proposed methodology was based on the use of the univariate imputation method through the application of cubic spline interpolation in each of the 46 municipalities, for each of the 3 variables. Then, for each municipality, the original series were compared with each observed series plus the values imputed in these variables by the Quenouille test of correlation of time series.
Findings
It was observed that, after imputation, all series were compared with those observed and are equal by the Queinouille test in the 46 municipalities analyzed, and the Wilcoxon test also showed equality for the accumulated total of the three variables involved with the production of soybeans. And there were increases of 5.92%, 3.58% and 2.84% for soy production, soy production value and soy derivatives value accumulated in the state after imputation in the 46 municipalities.
Originality/value
The present research and its results facilitate the process of estimates and monitoring the total soy production in the state of Mato Grosso and its municipalities from 1990 to 2018.
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Mingyu Gao, Da Chen, Yuxiang Yang and Zhiwei He
The purpose of this paper is to propose a new trajectory planning algorithm for industrial robots, which can let the robots move through a desired spatial trajectory, avoid…
Abstract
Purpose
The purpose of this paper is to propose a new trajectory planning algorithm for industrial robots, which can let the robots move through a desired spatial trajectory, avoid colliding with other objects and achieve accurate movements. Trajectory planning algorithms are the soul of motion control of industrial robots. A predefined space trajectory can let the robot move through the desired spatial coordinates, avoid colliding with other objects and achieve accurate movements.
Design/methodology/approach
The mathematical expressions of the proposed algorithm are deduced. The speed control, position control and orientation control strategies are realized and verified with simulations, and then implemented on a six degrees of freedom (6-DOF) industrial robot platform.
Findings
A fixed-distance trajectory planning algorithm based on Cartesian coordinates was presented. The linear trajectory, circular trajectory, helical trajectory and parabolic trajectory in Cartesian coordinates were implemented on the 6-DOF industrial robot.
Originality/value
A simple and efficient algorithm is proposed. Enrich the kind of trajectory which the industrial robot can realize. In addition, the industrial robot can move more concisely, smoothly and precisely.
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Mona Soufian, David McMillan and Stuart Horsburgh
The paper examines the conditional capital asset pricing model (CCAPM) of Jagannathan and Wang using the UK data and develops a data-driven measure of beta instability risk that…
Abstract
Purpose
The paper examines the conditional capital asset pricing model (CCAPM) of Jagannathan and Wang using the UK data and develops a data-driven measure of beta instability risk that is pertinent to the UK stock market. In contrast to the view that the main part of the Jagannathan and Wang's model is the inclusion of human capital, however, the paper finds that human capital remains insignificant in most tests.
Design/methodology/approach
Data were taken from the London Share Price Database and Datastream. This paper therefore examines the premium labour (PL) model of Jagannathan and Wang using the UK data, while the paper attaches particular importance to the measure of beta instability as a source of time variation in betas. In analysing the measure of beta instability risk, this study considers a testable measure of instability risk that varies across markets and across time as the interaction between the stock market and the economy varies across different time periods. Hence, this paper develops a data-driven measure of beta instability risk that is pertinent to the UK stock market.
Findings
The results confirm the premium version of the model, that is, the CCAPM without a proxy for human capital. In particular, the paper finds that over the entire time period of this study, the measure for beta instability risk and market portfolio has significant explanatory power for the variations of returns. More specifically, when using the average earnings index as a proxy for human capital in the PL model, the premium model performs better than the PL model. When total income from employment is used as a proxy for human capital, the performance of the PL model improves for the full period. However, the results for the two sub-periods are less favourable for the PL model as, again, labour income is not priced for these periods. These results indicate that the PL model is sensitive to proxies used for human capital.
Originality/value
The results revive the importance of beta instability risk in CCAPM of Jagannathan and Wang's model and suggest that the beta instability drives this model.
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The accurate interpolation of magnetization tables is of paramount importance in the design of high‐precision magnets used for particle accelerators or for magnetic resonance…
Abstract
The accurate interpolation of magnetization tables is of paramount importance in the design of high‐precision magnets used for particle accelerators or for magnetic resonance imaging of the human body. Cubic spline interpolation is normally used in combination with the fast converging Newton‐Raphson scheme in the two‐dimensional finite element modelling of such magnets. We compare cubic spline interpolation with experiment, using the magnetization tables as a source of carefully measured experimental data. We show that, in all examined cases, cubic spline interpolation introduces errors large enough to invalidate a design. We also propose a simple solution to the problem, thus combining the best of all worlds: the speed and convergence properties of Newton‐Raphson, the accuracy of a good interpolation scheme, and the convenient mathematical properties of cubic splines. We examine both two‐dimensional and three‐dimensional cases.
Xiuping Li and Ye Yang
Coordinating low-carbonization and digitalization is a practical implementation pathway to achieve high-quality economic development. Regions are under great emission reduction…
Abstract
Purpose
Coordinating low-carbonization and digitalization is a practical implementation pathway to achieve high-quality economic development. Regions are under great emission reduction pressure to achieve low-carbon development. However, why and how regional emission reduction pressure influences enterprise digital transformation is lacking in the literature. This study empirically tests the impact of emission reduction pressure on enterprise digital transformation and its mechanism.
Design/methodology/approach
This article takes the data of non-financial listed companies from 2011 to 2020 as a sample. The digital transformation index is measured by entropy value method. The bidirectional fixed effect model was used to test the hypothesis.
Findings
The research results show that emission reduction pressure forces enterprise digital transformation. The mechanism lies in that emission reduction pressure improves digital transformation by promoting enterprise innovation, and digital economy moderates the nexus between emission reduction pressure and digital transformation. Furthermore, the effect of emission reduction pressure on digital transformation is more significant for non-state-owned, mature and high-tech enterprises.
Originality/value
This paper discusses the mediating role of enterprise innovation between carbon emission reduction pressure and enterprise digital transformation, as well as the moderating role of digital economy. The research expands the body of knowledge about dual carbon targets, digitization and technological innovation. The author’s findings help update the impact of regional digital economy development on enterprise digital transformation. It also provides theoretical guidance for the realization of digital transformation by enterprise innovation.
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