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This study is designed to identify the policy shift on migrant children's11There are various definitions of migrant children in urban China. In this research, migrant children refer to the children from rural areas who have resided with their parents at the urban areas for at least six months without local household registration status. education at national level in urban China22With the rapid socioeconomic development and urbanization in China, the definition of urban China is changing. In this research, urban China refers to the major cities in China, such as Beijing, Shanghai, Guangzhou, Tianjin, Chongqing, and so forth. during the past decades. Meanwhile, it is expected to explore the policy limitations reflected by the practice at school level regarding accommodating migrant children's education.

This study is conducted through policy review regarding education for migrant children and analysis of data collected through questionnaires and interviews at one public junior high school in Beijing.

This study identifies a positive change of involving migrant children in urban public schools. However, there is a need for flexible mechanism that can fully accommodate various needs regarding migrant children's education in urban public schools.

The study argues the necessity of a multipartnership for establishing a sustainable public education system for accommodating migrant children education in urban public schools.

Being different from other research on the same issue in urban China, this study leads a new round of discussion on the quality education for migrant children.

The purpose of this paper is to solve economic emission dispatch problem in connection of wind with hydro-thermal units.

The proposed hybrid methodology is the joined execution of both the modified salp swarm optimization algorithm (MSSA) with artificial intelligence technique aided with particle swarm optimization (PSO) technique.

The proposed approach is introduced to figure out the optimal power generated power from the thermal, wind farms and hydro units by minimizing the emission level and cost of generation simultaneously. The best compromise solution of the generation power outputs and related gas emission are subject to the equality and inequality constraints of the system. Here, MSSA is used to generate the optimal combination of thermal generator with the objective of minimum fuel and emission objective function. The proposed method also considers wind speed probability factor via PSO-artificial neural network (ANN) technique and hydro power generation at peak load demand condition to ensure economic utilization.

To validate the advantage of the proposed approach, six- and ten-units thermal systems are studied with fuel and emission cost. For minimizing the fuel and emission cost of the thermal system with the predicted wind speed factor, the proposed approach is used. The proposed approach is actualized in MATLAB/Simulink, and the results are examined with considering generation units and compared with various solution techniques. The comparison reveals the closeness of the proposed approach and proclaims its capability for handling multi-objective optimization problems of power systems.

An organization’s ability to successfully manage intellectual capital is determined by the actions of its employees to prevent or minimize information security incidents. To prevent more data breaches to intellectual capital, organizations must provide regular cybersecurity awareness training for all personnel. The purpose of this paper is to investigate the effect of different evidence-based cybersecurity training methods on employees’ cybersecurity risk perception and self-reported behavior.

The study participants were randomly assigned into four groups (i.e. malware report, malware videos, both malware report and malware videos and no interventions) to assess the effects of cybersecurity training on their perceptions of vulnerability, severity, self-efficacy, security intention as well as their self-reported cybersecurity behaviors.

The results show that evidence-based malware report is a relatively better training method in affecting employees’ intentions of engaging in recommended cybersecurity behaviors comparing with the other training methods used in this study. A closer analysis suggests whether the training method contains self-relevant information could make a difference to the training effects.

This paper reports an in-depth investigation on how different evidence-based cybersecurity training methods impact employees’ perceptions of susceptibility, severity, self-efficacy, security intention as well as on their self-reported cybersecurity behaviors.

To make an augmented image realistic, the virtual objects should be correctly occluded by foreground objects. The purpose of this paper is to propose a new approach that resolves occlusion problems in augmented reality (AR). The main interest is that it can automatically obtain the proper spatial relationship between virtual and real objects in real time.

The approach is divided into two steps: off‐line disparity map constructing and on‐line occlusion handling. In the off‐line stage, the disparity map of the real scene is constructed using the global stereo matching method prior and then the disparities are refined by means of the fast mean shift method. Since the depth values of objects in different positions are different, the real object that occludes the virtual object can be specified according to the depth value. In the on‐line stage, the contour of the specified object is tracked using the real time object tracking method with the combination of feature tracking method and minimum s‐t cut method. The augmented image with correct occlusions is produced by redrawing all the tracked object pixels on the augmented image.

Compared with the existing methods, the proposed approach can automatically resolve occlusion problem in real time. The effectiveness of the method is demonstrated with several experimental results.

This paper makes three contributions. First, a novel framework is proposed to handle occlusion problem in AR. This framework is different to the previously proposed methods. The main procedure includes: obtain occluding real object, track the object, and redraw the pixels of the object on the composed image. It is much easier to implement and can achieve satisfactory results. Second, the disparity map is used to automatically obtain the contour of the occluding real object. To get the contour of the occluding real object precisely, the mean shift method is used to refine the disparity map. By comparing the depth value, the occluding real object can be extracted automatically. Third, the tracking method combining feature tracking method and minimum s‐t cut method ensures the real‐time requirement. The occlusion problem can be handled in real‐time.

The purpose of this paper is to present an efficient, interactive foreground/background image segmentation method using mean shift (MS) and graph cuts, in order to improve the segmentation performance with little user interaction.

By incorporating the advantages of the mean shift method and the graph cut algorithm, the proposed approach ensures the accuracy of segmentation results. First, the user marks certain pixels as foreground or background. Then the graph is constructed and the cost function composed of the boundary properties and the region properties is defined. To obtain the hidden information of user interaction, the foreground and background marks are clustered separately by the mean shift method. The region properties are determined by the minimum distances from the unmarked pixels to the foreground and background clusters. The boundary properties are determined by the relationship between the unmarked pixels and its neighbor pixels. Finally, using the graph cuts method solves the energy minimization problem to get the foreground which is of interest.

The paper presents experimental results and compares the results to other methods. It can be seen from the comparison that this method can obtain a better segmentation performance in many cases.

The paper incorporates the advantages of the mean shift method and the graph cut algorithm to obtain better segmentation results, even though the scene is complex.

Since the early 1980s, with the implementation of the policy of economic modernization, China has experienced a significant increase in crime. In order to meet the challenge of the rising crime rate under the new social and economic conditions, China has implemented a series of police reforms. Based on the newly promulgated Police Law and other relevant laws and regulations, discusses the organization, functions, powers and accountability issues of the contemporary Chinese police system.

This paper aims to ascertain Indian consumers’ corporate social responsibility (CSR) perceptions; an affinity for stipulated causes and perceived fit between cause and industry in the current mandatory CSR era in India.

Primary data was collected through an online survey from 1,251 consumers via quota sampling and snowballing, across 36 Indian cities.

The findings indicate no skepticism, positive CSR support and company evaluation. Indian consumers have the greatest affinity for environmental protection. Segments of socially, environmentally and culturally conscious consumers were found. Under quasi-experimental conditions of CSR fit and cause-affinity, positive purchase intention is exhibited across fast-moving-consumer-goods sectors; in which case CSR perceptions cease to have a significant impact on purchase intention.

This result contributes to understanding Indian consumers’ perspective in the mandatory CSR era and adds to the literature on strategic CSR and communication by segmenting consumers by cause affinity.

CSR practitioners could align with consumer-relevant causes that fit with their company’s core business, as controllable initiatives, instead of depending on positive, but less controllable, CSR perceptions of consumers. Implications of the findings on CSR policymaking by the government are also discussed.

The mandatory CSR law has been viewed as a burden by corporate India. This research implies that it may be possible to look at it as an opportunity for strategic CSR, to create a win-win situation for both business and society.

One of the first studies on cause-affinity and CSR fit among Indian consumers using the government stipulated list of causes.

In response to the problem of insufficient traction/braking adhesion force caused by the existence of the third-body medium on the rail surface, this study aims to analyze the utilization of wheel-rail adhesion coefficient under different medium conditions and propose relevant measures for reasonable and optimized utilization of adhesion to ensure the traction/braking performance and operation safety of trains.

Based on the PLS-160 wheel-rail adhesion simulation test rig, the study investigates the variation patterns of maximum utilized adhesion characteristics on the rail surface under different conditions of small creepage and large slip. Through statistical analysis of multiple sets of experimental data, the statistical distribution patterns of maximum utilized adhesion on the rail surface are obtained, and a method for analyzing wheel-rail adhesion redundancy based on normal distribution is proposed. The study analyzes the utilization of traction/braking adhesion, as well as adhesion redundancy, for different medium under small creepage and large slip conditions. Based on these findings, relevant measures for the reasonable and optimized utilization of adhesion are derived.

When the third-body medium exists on the rail surface, the train should adopt the low-level service braking to avoid the braking skidding by extending the braking distance. Compared with the current adhesion control strategy of small creepage, adopting appropriate strategies to control the train’s adhesion coefficient near the second peak point of the adhesion coefficient-slip ratio curve in large slip can effectively improve the traction/braking adhesion redundancy and the upper limit of adhesion utilization, thereby ensuring the traction/braking performance and operation safety of the train.

Most existing studies focus on the wheel-rail adhesion coefficient values and variation patterns under different medium conditions, without considering whether the rail surface with different medium can provide sufficient traction/braking utilized adhesion coefficient for the train. Therefore, there is a risk of traction overspeeding/braking skidding. This study analyzes whether the rail surface with different medium can provide sufficient traction/braking utilized adhesion coefficient for the train and whether there is redundancy. Based on these findings, relevant measures for the reasonable and optimized utilization of adhesion are derived to further ensure operation safety of the train.

This survey focuses on two families of nonlinear vector time series models, the family of vector threshold regression (VTR) models and that of vector smooth transition regression (VSTR) models. These two model classes contain incomplete models in the sense that strongly exogeneous variables are allowed in the equations. The emphasis is on stationary models, but the considerations also include nonstationary VTR and VSTR models with cointegrated variables. Model specification, estimation and evaluation is considered, and the use of the models illustrated by macroeconomic examples from the literature.