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Travel time at inter-stops is a set of important parameters in bus timetabling, which is usually assumed to be normal (log-normal) random variable in literature. With the development of digital technology and big data analytics ability in the bus industry, practitioners prefer to generate deterministic travel time based on the on-board GPS data under maximum probability rule and mean value rule, which simplifies the optimization procedure, but performs poorly in the timetabling practice due to the loss of uncertain nature on travel time. The purpose of this study is to propose a GPS-data-driven bus timetabling approach with consideration of the spatial-temporal characteristic of travel time.

The authors illustrate that the real-life on-board GPS data does not support the hypothesis of normal (log-normal) distribution on travel time at inter-stops, thereby formulating the travel time as a scenario-based spatial-temporal matrix, where K-means clustering approach is utilized to identify the scenarios of spatial-temporal travel time from daily observation data. A scenario-based robust timetabling model is finally proposed to maximize the expected profit of the bus carrier. The authors introduce a set of binary variables to transform the robust model into an integer linear programming model, and speed up the solving process by solution space compression, such that the optimal timetable can be well solved by CPLEX.

Case studies based on the Beijing bus line 628 are given to demonstrate the efficiency of the proposed methodology. The results illustrate that: (1) the scenario-based robust model could increase the expected profits by 15.8% compared with the maximum probability model; (2) the scenario-based robust model could increase the expected profit by 30.74% compared with the mean value model; (3) the solution space compression approach could effectively shorten the computing time by 97%.

This study proposes a scenario-based robust bus timetabling approach driven by GPS data, which significantly improves the practicality and optimality of timetable, and proves the importance of big data analytics in improving public transport operations management.

This study aims to provide a new method of multiscale directional Lyapunov exponents (MSDLE) calculated based on the state space reconstruction for the nonstationary time series, which can be applied to detect the small target covered by sea clutter.

Reconstructed state space is divided into non-overlapping submatrices whose columns are equal to a predetermined scale. The authors compute eigenvalues and eigenvectors of the covariance matrix of each submatrix and extract the principal components σ_ip and their corresponding eigenvectors. Then, the angles ψ_ip of eigenvectors between two successive submatrices were calculated. The curves of (σ_ip, ψ_ip) reflect the nonlinear dynamics both in kinetic and directional and form a spectrum with multiscale. The fluctuations of (σ_ip, ψ_ip), which are sensitive to the differences of backscatter between sea wave and target, are taken out as the features for the target detection.

The proposed method can reflect the local dynamics of sea clutter and the small target within sea clutter is easily detected. The test on the ice multiparameter imaging X-ban radar data and the comparison to K distribution based method illustrate the effectiveness of the proposed method.

The detection of a small target in sea clutter is a compelling issue, as the conventional statistical models cannot well describe the sea clutter on a larger timescale, and the methods based on statistics usually require the stationary sea clutter. It has been proven that sea clutter is nonlinear, nonstationary or cyclostationary and chaotic. The new method of MSDLE proposed in the paper can effectively and efficiently detect the small target covered by sea clutter, which can be also introduced and applied to military, aerospace and maritime fields.

Autonomous flight of unmanned aerial vehicles (UAVs) in global position system (GPS)-denied environments has become an increasing research hotspot. This paper aims to realize the indoor fixed-point hovering control and autonomous flight for UAVs based on visual inertial simultaneous localization and mapping (SLAM) and sensor fusion algorithm based on extended Kalman filter.

The fundamental of the proposed method is using visual inertial SLAM to estimate the position information of the UAV and position-speed double-loop controller to control the UAV. The motion and observation models of the UAV and the fusion algorithm are given. Finally, experiments are performed to test the proposed algorithms.

A position-speed double-loop controller is proposed, by fusing the position information obtained by visual inertial SLAM with the data of airborne sensors. The experiment results of the indoor fixed-points hovering show that UAV flight control can be realized based on visual inertial SLAM in the absence of GPS.

A position-speed double-loop controller for UAV is designed and tested, which provides a more stable position estimation and enabled UAV to fly autonomously and hover in GPS-denied environment.

This paper aims to use a fractional constitutive model with a nonlocal velocity gradient for replacing the nonlinear constitutive model to characterize its complex rheological behavior, where non-linear characteristics exist, for example, the inherent viscous behavior of the crude oil. The feasibility and flexibility of the fractional model are tested via a case study of non-Newtonian fluid. The finite element method is non-Newtonian used to numerically solve both momentum equation and energy equation to describe the fluid flow and convection heat transfer process.

This paper provides a comprehensive theoretical and numerical study of flow and heat transfer of non-Newtonian fluids in a pipe based on the fractional constitutive model. Contrary to fractional order a, the rheological property of non-Newtonian fluid changes from shear-thinning to shear-thickening with the increase of power-law index n, therefore the flow and heat transfer are hindered to some extent.

This paper discusses two dimensionless parameters on flow regime and thermal patterns, including Reynolds number (Re) and Nusselt number (Nu) in evaluating the flow rate and heat transfer rate. Analysis results show that the viscosity of the non-Newtonian fluid decreases with the rheological index (order α) increasing. While large fractional (order α) corresponds to the enhancement of heat transfer capacity.

First, it is observed that the increase of the Re results in an increase of the local Nusselt number (Nul). It means the heat transfer enhancement ratio increases with Re. Meanwhile, the increasement of the Nul indicating the enhancement in the heat transfer coefficient, produces a higher speed flow of crude oil.

This study presents a new numerical investigation on characteristics of steady-state pipe flow and forced convection heat transfer by using a fractional constitutive model. The influences of various non-dimensional characteristic parameters of fluid on the velocity and temperature fields are analyzed in detail.

This paper aims to convict the offender of real concurrence offenses of the most severe offense and applying the most severe penalty will result in no distinction between the perpetrator who conducted more than one act and the one who conducted only one act. This approach deviates from the purpose of criminal law. The real concurrence of offenses means several offenses, the perpetrator’s dangerousness and culpability are much higher than the perpetrator who commits just one crime, so combined punishments for several offenses should be applied to the real concurrence of offenses.

If the depositors are acquaintances or relatives and friends, the relationship can be explained by “personality trust.” If the depositors are strangers, but they have complied with their duties of care, the deposit relationship can be explained by “system trust.”

The real concurrence of offenses means several offenses, the perpetrator’s dangerousness and culpability are much higher than the perpetrator who commits just one crime, so combined punishments for several offenses should be applied to the real concurrence of offenses.

The principle of choosing the most severe punishment applied to the real concurrence of offense should be abolished. As the perpetrator separately conducts two acts at different times, these acts infringe on different legal interests. Although these acts exist closely, the authors cannot deny that these acts constitute more than one offense.

The purpose of this paper is to examine the association between firm performance and product market competition (PMC), and then examine the mitigation effect of corporate governance and/or state-ownership (SOEs) in the association between PMC and firm performance using Chinese listed firms.

The authors consider three determinants of the PMC that affect the nature of competition, and use market concentration, product substitutability and market size as proxies for PMC. The authors construct a corporate governance index which measures the extent of board independence, monitoring strength of supervisory board over board of directors, and monitoring strength of board of directors over CEO. The authors use Tobin’s Q as a proxy for firm performance. The authors use a sample of 20,706 firm-year observations listed on the Chinese stock market between 2001 and 2016 to empirically investigate the research questions proposed in the paper.

The authors find that higher PMC is associated with lower firm performance. The authors find that good corporate governance practices moderate the negative effect of higher PMC on firm performance. The association between higher PMC and lower performance is weaker for firms controlled by SOEs compared to non-SOEs. Further, the moderation effect of SOEs on the association between higher PMC and lower performance is more pronounced for firms with good corporate governance practices compared to firms with weak corporate governance practices.

Extant studies investigating the relationship between PMC and corporate governance suggest an either complementary or substitution relationship in developed economies. Our study highlights the interactive role played by SOEs and good corporate governance practices in firm performance in highly competitive product markets in an emerging economy. The findings provide insightful information to regulators of other emerging countries that SOEs with good corporate governance practices can play an important role in the economy by mitigating the negative effect of higher PMC on firm performance.

This paper seeks to investigate some current issues of ownership structure and corporate governance in China.

The methodology is a review, analysing issues of ownership structure and reviewing problems in corporate governance, followed by some suggestions for improvement.

It is found that the heavily concentrated equity ownership in the hands of large state‐owned shareholders mainly decides the status quo of the corporate governance system in China. In order to improve the effectiveness of corporate governance of Chinese‐listed companies, it is imperative to restructure roles of the government, restrict hands of controlling shareholders, enhance independence of the board of directors, reform the supervisory board, set up independent directors‐dominated sub‐committees and align the interests of managers with those of the shareholders.

This paper only investigates Chinese‐listed companies because of data availability.

It has implications for policy makers in China insofar as it offers evidence concerning ownership structure and corporate governance of Chinese‐listed companies. It also helps investors and trading partners (especially foreign ones) understand corporate governance and the investment environment in China.

This study contributes to the literature by extending the mainly US‐based board literature to China where there are important institutional differences in ownership structure and corporate governance system.

This study aims to identify the key factors that influence household pro-environmental behaviors (HPEBs) and explore the differences caused by the same influencing factors between household waste management behavior (HWM) and household energy-saving behavior (HES).

A meta-analysis was conducted on 90 articles about HPEBs published between 2009 and 2023 to find the key factors. HPEBs were further categorized into HWM and HES to investigate the difference influenced by the above factors on two behaviors. The correlation coefficient was used as the unified effect size, and the random-effect model was adopted to conduct both main effect and moderating effect tests.

The results showed that attitude, subjective norms, and perceived behavioral control all positively influenced intention and HPEBs, but their effects were stronger on intention than on HPEBs. Intention was found to be the strongest predictor of HPEBs. Subjective norms were found to have a more positive effect on HES compared to HWM, while habits had a more positive effect on HWM. Furthermore, household size was negatively correlated with HWM but positively correlated with HES.

The same variables have different influences on HWM and HES. These results can help develop targeted incentives to increase the adoption of HPEBs, ultimately reducing household energy consumption and greenhouse gas emissions and contributing to the mitigation of global warming.

This paper aims to investigate the application of 3D printing technology, particularly using sand-type materials, in the creation of artificial rock models for rock mechanics experimentation.

Using a comprehensive analysis, this research explores the utilization of 3D printing technology in rock mechanics. Sand-type materials are specifically investigated for their ability to replicate natural rock characteristics. The methodology involves a review of recent achievements and experimentation in this field.

The study reveals that sand-type 3D printing materials demonstrate comparable properties to natural rocks, including brittle characteristics, surface roughness, microstructural features and crack propagation patterns.

While the research establishes the viability of sand-type 3D printing materials, it acknowledges limitations such as the need for further exploration and validation. Generalizability may be constrained, warranting additional research to address these limitations.

This research contributes insights into the potential application of sand-type 3D printing materials in indoor rock physics experiments. The findings may guide future endeavors in fabricating rock specimens with consistent structures for practical rock mechanics applications.