Xia Cui, GuangWei Yuan and ZhiJun Shen
This paper aims to provide a well-behaved nonlinear scheme and accelerating iteration for the nonlinear convection diffusion equation with fundamental properties illustrated.
Abstract
Purpose
This paper aims to provide a well-behaved nonlinear scheme and accelerating iteration for the nonlinear convection diffusion equation with fundamental properties illustrated.
Design/methodology/approach
A nonlinear finite difference scheme is studied with fully implicit (FI) discretization used to acquire accurate simulation. A Picard–Newton (PN) iteration with a quadratic convergent ratio is designed to realize fast solution. Theoretical analysis is performed using the discrete function analysis technique. By adopting a novel induction hypothesis reasoning technique, the L∞ (H1) convergence of the scheme is proved despite the difficulty because of the combination of conservative diffusion and convection operator. Other properties are established consequently. Furthermore, the algorithm is extended from first-order temporal accuracy to second-order temporal accuracy.
Findings
Theoretical analysis shows that each of the two FI schemes is stable, its solution exists uniquely and has second-order spatial and first/second-order temporal accuracy. The corresponding PN iteration has the same order of accuracy and quadratic convergent speed. Numerical tests verify the conclusions and demonstrate the high accuracy and efficiency of the algorithms. Remarkable acceleration is gained.
Practical implications
The numerical method provides theoretical and technical support to accelerate resolving convection diffusion, non-equilibrium radiation diffusion and radiation transport problems.
Originality/value
The FI schemes and iterations for the convection diffusion problem are proposed with their properties rigorously analyzed. The induction hypothesis reasoning method here differs with those for linearization schemes and is applicable to other nonlinear problems.
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Keywords
Guangwei Yu, Yuan Yao and Zhuoyuan Song
This paper presents a novel design method for keyboard circuits. The purpose of this study is to enable a single-board computer with fewer pins to recognize a keyboard system…
Abstract
Purpose
This paper presents a novel design method for keyboard circuits. The purpose of this study is to enable a single-board computer with fewer pins to recognize a keyboard system consisting of a large number of switches. Through the study of different kinds of keyboard circuits, a general circuit schematic design method is abstracted. Several experiments are conducted to prove the feasibility of the proposed circuit design method.
Design/methodology/approach
Conventional circuit schematic diagrams are often limited to two-dimensional planes. Through investigating higher dimensional alternatives, this paper proposes to place components in high-dimensional geometry before connecting all components. A multi-pin switch construction method is proposed to allow the switches to be arranged on the vertices of high-dimensional geometry and be connected sequentially to form the keyboard system. This proposed system can allow a keyboard system consisting of a large number of switches to be recognized by a single-board computer with less available pins.
Findings
The design scheme proposed in this paper can read more switch states with limited Input/Output pins. With the increase of the number of Input/Output ports and pins, the number of simultaneously identifiable switches increases exponentially, which is suitable for sensor design of array type.
Research limitations/implications
Compared with the classical keyboard circuits, the circuit designed using the proposed method will lead to a slightly longer recognition time for each key. This can be compensated by a single-board computer with a modestly higher clock speed.
Originality/value
The circuit schematic design method based on high-dimensional geometry is introduced for the first time. The feasibility of the proposed method is verified by the original experiments. The proposed approach is of importance in guiding the design of new analog and digital sensor circuit systems.
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Md. Nurul Islam, Guangwei Hu, Murtaza Ashiq and Shakil Ahmad
This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of…
Abstract
Purpose
This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of the existing literature, this study aims to provide valuable insights into the emerging field of big data in librarianship and its potential impact on the future of libraries.
Design/methodology/approach
This study employed a rigorous four-stage process of identification, screening, eligibility and inclusion to filter and select the most relevant documents for analysis. The Scopus database was utilized to retrieve pertinent data related to big data applications in librarianship. The dataset comprised 430 documents, including journal articles, conference papers, book chapters, reviews and books. Through bibliometric analysis, the study examined the effectiveness of different publication types and identified the main topics and themes within the field.
Findings
The study found that the field of big data in librarianship is growing rapidly, with a significant increase in publications and citations over the past few years. China is the leading country in terms of publication output, followed by the United States of America. The most influential journals in the field are Library Hi Tech and the ACM International Conference Proceeding Series. The top authors in the field are Minami T, Wu J, Fox EA and Giles CL. The most common keywords in the literature are big data, librarianship, data mining, information retrieval, machine learning and webometrics.
Originality/value
This bibliometric study contributes to the existing body of literature by comprehensively analyzing the latest trends and patterns in big data applications within librarianship. It offers a systematic approach to understanding the state of the field and highlights the unique contributions made by various types of publications. The study’s findings and insights contribute to the originality of this research, providing a foundation for further exploration and advancement in the field of big data in librarianship.
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Keywords
Guangwei Liang, Zhiming Gao, Cheng-Man Deng and Wenbin Hu
The purpose of this study is to reveal the effect of nano-Al2O3 particle addition on the nucleation/growth kinetics, microhardness, wear resistance and corrosion resistance of…
Abstract
Purpose
The purpose of this study is to reveal the effect of nano-Al2O3 particle addition on the nucleation/growth kinetics, microhardness, wear resistance and corrosion resistance of Co–P–xAl2O3 nanocomposite plating.
Design/methodology/approach
The kinetics and properties of Co–P–xAl2O3 nanocomposite plating prepared by electroplating were investigated by electrochemical measurements, scanning electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, Vickers microhardness measurement, SRV5 friction and wear tester and atomic force microscopy.
Findings
A 12 g/L nano-Al2O3 addition in the plating solution can transform the nucleation/growth kinetics of the plating from the 3D progressive model to the 3D instantaneous model. The microhardness of the plating increased with the increase of nano-Al2O3 content in plating. The wear resistance of the plating did not adhere strictly to Archard’s law. An even and denser corrosion product film was generated due to the finer grains, with a high corrosion resistance.
Originality/value
The effect of different nano-Al2O3 addition on the nucleation/growth kinetics and properties of Co–P–xAl2O3 nanocomposite plating was investigated, and an anticorrosion mechanism of Co–P–xAl2O3 nanocomposite plating was proposed.
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Keywords
Siyuan Huang, Limin Liu, Jian Dong, Xiongjun Fu and Leilei Jia
Most of the existing ground filtering algorithms are based on the Cartesian coordinate system, which is not compatible with the working principle of mobile light detection and…
Abstract
Purpose
Most of the existing ground filtering algorithms are based on the Cartesian coordinate system, which is not compatible with the working principle of mobile light detection and ranging and difficult to obtain good filtering accuracy. The purpose of this paper is to improve the accuracy of ground filtering by making full use of the order information between the point and the point in the spherical coordinate.
Design/methodology/approach
First, the cloth simulation (CS) algorithm is modified into a sorting algorithm for scattered point clouds to obtain the adjacent relationship of the point clouds and to generate a matrix containing the adjacent information of the point cloud. Then, according to the adjacent information of the points, a projection distance comparison and local slope analysis are simultaneously performed. These results are integrated to process the point cloud details further and the algorithm is finally used to filter a point cloud in a scene from the KITTI data set.
Findings
The results show that the accuracy of KITTI point cloud sorting is 96.3% and the kappa coefficient of the ground filtering result is 0.7978. Compared with other algorithms applied to the same scene, the proposed algorithm has higher processing accuracy.
Research limitations/implications
Steps of the algorithm are parallel computing, which saves time owing to the small amount of computation. In addition, the generality of the algorithm is improved and it could be used for different data sets from urban streets. However, due to the lack of point clouds from the field environment with labeled ground points, the filtering result of this algorithm in the field environment needs further study.
Originality/value
In this study, the point cloud neighboring information was obtained by a modified CS algorithm. The ground filtering algorithm distinguish ground points and off-ground points according to the flatness, continuity and minimality of ground points in point cloud data. In addition, it has little effect on the algorithm results if thresholds were changed.