Di Cheng, Yuqing Wen, Zhiqiang Guo, Xiaoyi Hu, Pengsong Wang and Zhikun Song
This paper aims to obtain the evolution law of dynamic performance of CR400BF electric multiple unit (EMU).
Abstract
Purpose
This paper aims to obtain the evolution law of dynamic performance of CR400BF electric multiple unit (EMU).
Design/methodology/approach
Using the dynamic simulation based on field test, stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers were tested. Stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to research the evolution law with running mileage of dynamic index of CR400BF EMU.
Findings
The results showed that stiffness and damping coefficient subjected to normal distribution, the mean and variance were computed and the evolution law of stiffness and damping coefficient with running mileage was obtained.
Originality/value
Firstly, based on the field test we found that stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers subjected to normal distribution, and the evolution law of stiffness and damping coefficient with running mileage was proposed. Secondly stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to the research to the evolution law with running mileage of dynamic index of CR400BF EMU.
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The purpose of this paper is to examine whether Fama–French common risk-factor portfolio investors herd on a daily basis for five developed markets, namely, Europe, Japan, Asia…
Abstract
Purpose
The purpose of this paper is to examine whether Fama–French common risk-factor portfolio investors herd on a daily basis for five developed markets, namely, Europe, Japan, Asia Pacific ex Japan, North America and Globe.
Design/methodology/approach
To examine the herd behavior of common risk-factor portfolio investors, this paper utilizes the cross-sectional absolute deviations (CSAD) methodology, covering a daily data sampling period of July 1990 to January 2019 from Kenneth R. French-Data Library. CSAD driven by fundamental and non-fundamental information is assessed using Fama–French five-factor model.
Findings
The results do not provide evidence for herding under normal market conditions, either when reacting to fundamental information or non-fundamental information, for any region under consideration. However, Fama–French common risk-factor portfolio investors mimic the underlying risk factors in returns related to size and book-to-market value, size and operating profitability, size and investment and size and momentum of the equity stocks in European and Japanese markets during crisis period. Also, no considerable evidence is found for herding (on fundamental information) under crisis and up-market conditions except for Japan. Ancillary findings are discussed under conclusion.
Research limitations/implications
Further research on new risk factors explaining stock return variation may help improve the model performance. The performance can be improved by adding new risk factors that are free from behavioral bias but significant in explaining common stock return variation. Also, it is necessary to revisit the existing common risk factors in order to understand behavioral aspects that may affect cost of capital calculations (e.g. pricing errors) and valuation of investment portfolios.
Originality/value
This is the first paper that examines the herd behavior (fundamental and non-fundamental) of Fama–French common risk-factor investors using five-factor model.
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Yanmin Zhou, Zheng Yan, Ye Yang, Zhipeng Wang, Ping Lu, Philip F. Yuan and Bin He
Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing…
Abstract
Purpose
Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.
Design/methodology/approach
This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.
Findings
This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.
Originality/value
The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.
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Tangjian Wei, Xingqi Yang, Guangming Xu and Feng Shi
This paper aims to propose a medium-term forecast model for the daily passenger volume of High Speed Railway (HSR) systems to predict the daily the Origin-Destination (OD) daily…
Abstract
Purpose
This paper aims to propose a medium-term forecast model for the daily passenger volume of High Speed Railway (HSR) systems to predict the daily the Origin-Destination (OD) daily volume for multiple consecutive days (e.g. 120 days).
Design/methodology/approach
By analyzing the characteristics of the historical data on daily passenger volume of HSR systems, the date and holiday labels were designed with determined value ranges. In accordance to the autoregressive characteristics of the daily passenger volume of HSR, the Double Layer Parallel Wavelet Neural Network (DLP-WNN) model suitable for the medium-term (about 120 d) forecast of the daily passenger volume of HSR was established. The DLP-WNN model obtains the daily forecast result by weighed summation of the daily output values of the two subnets. Subnet 1 reflects the overall trend of daily passenger volumes in the recent period, and subnet 2 the daily fluctuation of the daily passenger volume to ensure the accuracy of medium-term forecast.
Findings
According to the example application, in which the DLP-WNN model was used for the medium-term forecast of the daily passenger volumes for 120 days for typical O-D pairs at 4 different distances, the average absolute percentage error is 7%-12%, obviously lower than the results measured by the Back Propagation (BP) neural network, the ELM (extreme learning machine), the ELMAN neural network, the GRNN (generalized regression neural network) and the VMD-GA-BP. The DLP-WNN model was verified to be suitable for the medium-term forecast of the daily passenger volume of HSR.
Originality/value
This study proposed a Double Layer Parallel structure forecast model for medium-term daily passenger volume (about 120 days) of HSR systems by using the date and holiday labels and Wavelet Neural Network. The predict results are important input data for supporting the line planning, scheduling and other decisions in operation and management in HSR systems.
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Rudra P. Pradhan, Mak B. Arvin, Neville R. Norman and Sahar Bahmani
The paper investigates whether Granger causal relationships exist between bond market development, stock market development, economic growth and two other macroeconomic variables…
Abstract
Purpose
The paper investigates whether Granger causal relationships exist between bond market development, stock market development, economic growth and two other macroeconomic variables, namely, inflation rate and real interest rate. The study aims to expand the domain of economic growth by including a more in-depth analysis of the possible impact that bond market and stock market development has on economic growth than is normally found in the literature.
Design/methodology/approach
This paper uses a panel data set of the G-20 countries for the period 1991-2016. It uses a panel vector auto-regression model to reveal the nature of any Granger causality among the five variables.
Findings
The paper provides empirical insights that both bond market development and stock market development are cointegrated with economic growth, inflation rate and real interest rate. The most robust result from the panel Granger causality test is that bond market development, stock market development, inflation rate and real interest rate are demonstrable drivers of economic growth in the long run.
Research limitations/implications
Because of the chosen research approach, the research results may lack theoretical foundations. Therefore, perhaps the more fully grounded interactive findings of this study can inspire theorists to fill the missing gap.
Practical implications
This paper includes lessons for policymakers in the G-20 countries seeking to stimulate economic growth in the long run and how they need to ensure greater stability of the interest rate and inflation rate as well as fully developing their financial markets, as both bond markets and stock markets are obvious drivers of economic growth.
Originality/value
This paper fulfills an identified need to study causal relationships between bond market development, stock market development, economic growth and two other macroeconomic variables, i.e. inflation rate and real interest rate.
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The purpose of this paper is to explore and further the existing knowledge on supply chain integration (SCI). This study proposes a model and several hypotheses to better…
Abstract
Purpose
The purpose of this paper is to explore and further the existing knowledge on supply chain integration (SCI). This study proposes a model and several hypotheses to better understand some SCI antecedents, dependence and resource commitment and their relationships with performance.
Design/methodology/approach
Based on diverse theoretical approaches, the author develops and tests an integrated model in which dependence and resource commitment are proposed to enhance external integration, leading to an increase in economic performance. This study's empirical validity is reinforced by collecting data from 142 manufacturing firms in Spain and Germany and testing the model using structural equation model (SEM).
Findings
The results support dependence and resource commitment as antecedents of SCI, both with a positive effect. Also, discrepancies in the effect of external integration on performance are found where supplier integration seems not to have any effect on performance.
Originality/value
This study helps to better understand SCI antecedents. It makes both theoretical and managerial contributions by empirically analyzing both antecedents. This furthers extant knowledge regarding the joined impact of resource commitment and dependence on SCI. In particular, it incorporates resource commitment by considering it as the sacrifice firms need to implement to get involved in a long-term relationship.