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The conventional pedestrian detection algorithms lack in scale sensitivity. The purpose of this paper is to propose a novel algorithm of self-adaptive scale pedestrian detection, based on deep residual network (DRN), to address such lacks.

First, the “Edge boxes” algorithm is introduced to extract region of interests from pedestrian images. Then, the extracted bounding boxes are incorporated to different DRNs, one is a large-scale DRN and the other one is the small-scale DRN. The height of the bounding boxes is used to classify the results of pedestrians and to regress the bounding boxes to the entity of the pedestrian. At last, a weighted self-adaptive scale function, which combines the large-scale results and small-scale results, is designed for the final pedestrian detection.

To validate the effectiveness and feasibility of the proposed algorithm, some comparison experiments have been done on the common pedestrian detection data sets: Caltech, INRIA, ETH and KITTI. Experimental results show that the proposed algorithm is adapted for the various scales of the pedestrians. For the hard detected small-scale pedestrians, the proposed algorithm has improved the accuracy and robustness of detections.

By applying different models to deal with different scales of pedestrians, the proposed algorithm with the weighted calculation function has improved the accuracy and robustness for different scales of pedestrians.

For the large-scale power grid monitoring system equipment, its working environment is increasingly complex and the probability of fault or failure of the monitoring system is gradually increasing. This paper proposes a fault classification algorithm based on Gaussian mixture model (GMM), which can complete the automatic classification of fault and the elimination of fault sources in the monitoring system.

The algorithm first defines the GMM and obtains the detection value of the fault classification through a method based on the causal Mason Young Tracy (MYT) decomposition under each normal distribution in the GMM. Then, the weight value of GMM is used to calculate weighted classification value of fault detection and separation, and by comparing the actual control limits with the classification result of GMM, the fault classification results are obtained.

The experiment on the defined non-thermostatic continuous stirred-tank reactor model shows that the algorithm proposed in this paper is superior to the traditional algorithm based on the causal MYT decomposition in fault detection and fault separation.

The proposed algorithm fundamentally solves the problem of fault detection and fault separation in large-scale systems and provides support for troubleshooting and identifying fault sources.

Drawing on the framework of the trickle-down effect and social learning theory, this study aims to examine how and when leaders' voluntary green behavior (VGB) stimulates that of employees.

This study conducted a time-lagged multisource field survey. The final sample consisted of 417 employees matched to 67 leaders. The unconflated multilevel modeling (MLM) approach was employed.

A social learning mechanism underlies the trickle-down effect of leaders' VGB, which involves observation and imitation. The green role model influence serves as a mediator of these two processes. Moreover, leader-member exchange (LMX) moderates the strength of the social learning mechanism.

Leaders can gain useful insights of how to promote employees' VGB and are further inspired to reflect on the managerial philosophy of leading by example.

This study contributes to workplace green behavior literature by examining the trickle-down effect of leader VGB and uncovering a social learning mechanism. This study also offers promising directions for leadership research concerning about role modeling.

In order to solve the current imbalance of academic resources within the discipline, this article builds a three-dimensional talent evaluation model based on the topic–author–citation based on the z index and proposes the ZAS index to evaluate scholars on different research topics within the discipline.

Based on the sample data of the CSSCI journals in the discipline of physical education in the past five years, the keywords were classified into 13 categories of research topics including female sports. The ZAS index of scholars on topic of female sports and so on was calculated, and quantitative indexes such as h index p index and z index were calculated. Comparative analysis of the evaluation effect was performed.

It is found that compared with the h index and p index, the z index achieves a better balance between the quantity, quality and citation distribution of scholars' results and effectively recognizes that the citation quality is higher and the number of citations of each paper is more balanced. In addition, compared to the z index, this article is based on a ZAS index model with an improved three-dimensional topic–author–citation relationship in research fields such as female sports.

It can identify some outstanding scholars who are engaged in small-scale or emerging topic research such as female sports and are excellent in different research areas. Talents create an objective and fair evaluation environment. At the same time, the ranking ability of ZAS indicators in the evaluation of talents is the strongest, and it is expected to be used in practical evaluations.

The experiencescape is a relatively new concept, and research using it remains scarce. This study contributes to the understanding of the experiencescape and its role in tourism consumption by constructing a novel conceptual model of the experiencescape elements of a casino resort visit and their effects on its attractiveness.

Partial least squares structural equation modelling was employed, using data collected from 491 casino resort visitors in Macao, to establish a link between the experiencescape and visitors’ perceived overall attractiveness of the casino resort through the mediating effect of arousal.

The findings establish the relationship between experiencescapes and the perceived overall attractiveness of integrated casino resorts through the mediating effect of arousal.

Casino resort executives are advised to orchestrate various experience elements from the perspective of the experiencescape to trigger positive tourism experiences. Specifically, all factors related to tangible, gaming and non-gaming and social experiential stimuli need to be continually reviewed, improved and innovated.

This study presents novel insights into the role of emotions in an integrated casino resort context. It identifies a set of strategies through which managers can increase the attractiveness of their resorts by stimulating customers’ emotions.

The purpose of this paper is to provide an exploratory understanding of the impact of social support on job stress of shift working mothers in Macao casinos.

A qualitative research method was adopted in this study. A snowball sampling strategy was used to recruit participants, and in-depth semi-structured interviews were conducted on participants from different casinos of six Macao gaming operators.

The paper found out that emotional and instrumental supports from families and friends are the most important social support for shift working mothers to cope with their job stress in casinos.

A qualitative method may lead to a misinterpretation or ignorance of key information due to the researcher bias. The snowball sampling strategy may lead to a biased sample which may not represent the entire population.

The understanding of what types of social support that shift working mothers appreciate and need the most may provide managerial implications for casino operators for a better support to their female employees.

Aiming at the problems of poor accuracy and limitation in strength assessment of spot welding vehicle body caused by uncertain factors, such as key component size and nugget diameter, the numerical models of strength uncertainty analysis of spot-welded joints were constructed based on evidence theory and fuzzy theory.

Evidence theory and fuzzy theory are used to deal with the uncertainty of design parameter, and differential evolution algorithms are used to calculate the propagation process of uncertainty in this model. Furthermore, efficient relationship between the strength of welded joints and each design parameter is constructed by using response surface proxy model, which effectively avoids the problem of repeated complex finite element analysis in uncertainty analysis.

The results show that the constructed uncertainty numerical model is effective for the multiple uncertainties and give interval results under different probabilities and affiliations, which can more effectively evaluate the strength of the welded body structure to avoid overly conservative estimates for deterministic design.

The evidence theory is improved and combined with differential evolution algorithm and response surface method to effectively improve the computational efficiency. Based on the improved evidence theory and fuzzy algorithm, the numerical models for the uncertainty analysis of solder joint strength of welded structures are constructed and their feasibility is verified.

The aim of this study is to examine the relationships between taking charge, bootlegging innovation and innovative job performance, and to explore the moderating roles of felt responsibility for constructive change (FRCC) and creative self-efficacy (CSE).

Data for this research was collected from 503 employees working in a chain company. Through a longitudinal study design, a three-wave survey with 397 valid data provided support for the proposed theoretical model.

The results maintain a positive association between taking charge, bootlegging innovation and innovative job performance, indicating the mediating effect of bootlegging innovation. Additionally, both the FRCC and CSE facilitate the indirect effect of taking charge on innovative job performance through bootlegging innovation. Furthermore, the integrated moderated mediation model analysis suggested that FRCC is more vital in improving employees' innovative job performance.

This research aims to break the black box between taking charge and innovative job performance, which has been relatively unexplored. Drawing from self-determination theory (SDT) and the proactive motivation model, the authors verify the bridge-building role of bootlegging innovation and the dual-facilitating effects of FRCC and CSE while employees conduct taking charge. This study’s results provide new insight for managers to foster, encourage and support employees' proactive behavior.

This study explores the influencing factors on organizational efficiency of the smart logistics ecological chain, and designs the corresponding theoretical framework to guide the practice of enterprises

A multi-case study method is adopted in this study. It includes four companies A, B, C and D in China as the case study objects, collects data through enterprise survey and uses the combination of open coding and spindle coding to process the data. By testing the reliability and validity, the theoretical framework is summarized.

First, organizational efficiency in smart logistics ecological chains is directly related to their service and technology innovation capability. Second, symbiotic relationships, information sharing and customer demand affect the efficiency of smart logistics multi-case ecological chains by influencing their service capacity; their technological innovation capability regulates the mechanism of influence. Third, technological innovation in smart logistics ecological chains positively impacts their service capabilities. Improving technological innovation capability can enhance logistics service capabilities.

According to the characteristics of smart logistics, the theoretical framework about organizational efficiency of smart logistics ecological chain is constructed, which fills the research gap and can provide interesting perspectives for the future research related to the smart logistics ecological chain. At the same time, the findings can also help enterprises to better build the smart logistics ecological chain in practice.

The purpose of this paper was to study some effective evaluation methods for the biocide performance on sulfate-reducing bacteria (SRB) biofilm.

The most probable number method, electrochemical impedance spectroscopy (EIS) measurements, scanning electron microscopy (SEM), three-dimensional (3D) photos and epifluorescent microscopy were used in this study.

The results showed that the minimum inhibitory concentrations and minimum bactericidal concentrations of them to sessile SRB were greatly more than planktonic SRB. The EIS of the two biocides indicated that the biofilm exposed to higher concentrations of biocide were much more compact and flat, which perfectly coincided with the SEM, 3D photos and the epifluorescent microscopies.

In this paper, it, thus, appears that these methods evaluating biocide performance on the SRB biofilm were really effective by comparing the performance of bis-quaternary ammonium salt (BAQS) and tetrakis hydroxymethyl phosphonium sulfate.