Search results

The purpose of this paper is to propose a multi-objective differential evolution algorithm named as MOMR-DE to resolve multicast routing problem. In mobile ad hoc network (MANET), multicast routing is a non-deterministic polynomial -complete problem that deals with the various objectives and constraints. Quality of service (QoS) in the multicast routing problem mainly depends on cost, delay, jitter and bandwidth. So the cost, delay, jitter and bandwidth are always considered as multi-objective for designing multicast routing protocols. However, mobile node battery energy is finite and the network lifetime depends on node battery energy. If the battery power consumption is high in any one of the nodes, the chances of network’s life reduction due to path breaks are also more. On the other hand, node’s battery energy had to be consumed to guarantee high-level QoS in multicast routing to transmit correct data anywhere and at any time. Hence, the network lifetime should be considered as one objective of the multi-objective in the multicast routing problem.

Recently, many metaheuristic algorithms formulate the multicast routing problem as a single-objective problem, although it obviously is a multi-objective optimization problem. In the MOMR-DE, the network lifetime, cost, delay, jitter and bandwidth are considered as five objectives. Furthermore, three QoS constraints which are maximum allowed delay, maximum allowed jitter and minimum requested bandwidth are included. In addition, we modify the crossover and mutation operators to build the shortest-path multicast tree to maximize network lifetime and bandwidth, minimize cost, delay and jitter.

Two sets of experiments are conducted and compared with other algorithms for these problems. The simulation results show that our proposed method is capable of achieving faster convergence and is more preferable for multicast routing in MANET.

In MANET, most metaheuristic algorithms formulate the multicast routing problem as a single-objective problem. However, this paper proposes a multi-objective differential evolution algorithm to resolve multicast routing problem, and the proposed algorithm is capable of achieving faster convergence and more preferable for multicast routing.

The debate over differences in the behaviors of firms facing globalization is ongoing. This study examines whether globalization impacts the behavior of family firms and if this influence differs between family and non-family firms.

Drawing on panel data from the Amadeus database on 62 family firms and 98 non-family firms in Europe, the authors employ panel vector autoregression estimation and the Wald test of Granger causality to verify our conjecture. Additional impulse response functions and the forecast error variance decomposition technique were applied to illustrate complementary shock dynamics. Additionally, the KOF globalization index is used as a proxy for globalization.

The results show that globalization visibly impacts family and non-family firms, but the polarity and extent of the effect are different. The authors demonstrate that family firms are in a more favorable position regarding globalization and are less vulnerable to the adverse effects of the globalization process. In contrast, non-family firms fare worse, generating adverse effects. Non-family firms take a more open stance toward globalization than family firms' more conservative behaviors.

Of course, there are some limitations to the work presented in this paper. On the one hand, the authors’ data span only ten years due to data limitations. This causes the generalizability of the results to be hindered. Therefore, the authors encourage scholars to collect more time series data to increase confidence in the empirical results in future studies. On the other hand, the selection of proxy indicators concerning family firm behavior is mainly focused on financial and employment facets. A multidimensional selection of indicators could make the findings of this study more convincing. Despite its limitations, the study certainly adds to the authors’ understanding of its behavior and globalization activities.

The authors’ findings have twofold theoretical and practical implications, as they highlight the necessity of developing specific policies aimed at reducing the gap between family and non-family facing globalization and promoting sustainable operations of non-family firms. Although family firms tend to be more frugal and conservative in their overall decision-making, it should be acknowledged that stockholder and stakeholder interest-oriented corporate management policies have made them more capable of steadily improving corporate performance in the sweep of globalization.

To this end, this study deepens the authors’ understanding of the theory of global governance of family firms. It also provides possible paths and directions for future theoretical research on family firms. Globalization affects both family and non-family firms, but our results suggest that family firms are better able to withstand the adverse effects of globalization shocks and adopt efficient governance paths and strategic thinking to gain a competitive advantage. In this regard, the authors encourage non-family firms to actively learn from family firms' operational practices and systems to achieve better adaptability.

This study provides strong empirical evidence on the effectiveness of family firms' governance patterns and business behavior under globalization. Additionally, this study also reveals that managers can learn from the practical experience of family firms to help them confront business crises and gain a sustainable competitive advantage.

This paper aims to provide a better understanding of the challenges and potential solutions in Visual Simultaneous Localization and Mapping (SLAM), laying the foundation for its applications in autonomous navigation, intelligent driving and other related domains.

In analyzing the latest research, the review presents representative achievements, including methods to enhance efficiency, robustness and accuracy. Additionally, the review provides insights into the future development direction of Visual SLAM, emphasizing the importance of improving system robustness when dealing with dynamic environments. The research methodology of this review involves a literature review and data set analysis, enabling a comprehensive understanding of the current status and prospects in the field of Visual SLAM.

This review aims to comprehensively evaluate the latest advances and challenges in the field of Visual SLAM. By collecting and analyzing relevant research papers and classic data sets, it reveals the current issues faced by Visual SLAM in complex environments and proposes potential solutions. The review begins by introducing the fundamental principles and application areas of Visual SLAM, followed by an in-depth discussion of the challenges encountered when dealing with dynamic objects and complex environments. To enhance the performance of SLAM algorithms, researchers have made progress by integrating different sensor modalities, improving feature extraction and incorporating deep learning techniques, driving advancements in the field.

To the best of the authors’ knowledge, the originality of this review lies in its in-depth analysis of current research hotspots and predictions for future development, providing valuable references for researchers in this field.

Fault diagnosis methods based on blind source separation (BSS) for rolling element bearings are necessary tools to prevent any unexpected accidents. In the field application, the actual signal acquisition is usually hindered by certain restrictions, such as the limited number of signal channels. The purpose of this study is to fulfill the weakness of the existed BSS method.

To deal with this problem, this paper proposes a blind source extraction (BSE) method for bearing fault diagnosis based on empirical mode decomposition (EMD) and temporal correlation. First, a single-channel undetermined BSS problem is transformed into a determined BSS problem using the EMD algorithm. Then, the desired fault signal is extracted from selected intrinsic mode functions with a multi-shift correlation method.

Experimental results prove the extracted fault signal can be easily identified through the envelope spectrum. The application of the proposed method is validated using simulated signals and rolling element bearing signals of the train axle.

This paper proposes an underdetermined BSE method based on the EMD and the temporal correlation method for rolling element bearings. A simulated signal and two bearing fault signal from the train rolling element bearings show that the proposed method can well extract the bearing fault signal. Note that the proposed method can extract the periodic fault signal for bearing fault diagnosis. Thus, it should be helpful in the diagnosis of other rotating machinery, such as gears or blades.

This paper aims to investigate the reliability, availability, maintenance and safety analysis method for railway network operation.

The reliability of the railway network is proposed based on the accident frequency and the topology of the railway network. Network efficiency and capacity are proposed to evaluate the availability of the railway network. The maintenance of the railway network is analyzed from the perspective of accident recovery time. The safety index of the railway network is proposed to measure the safety of railway stations and sections and the K-means method is proposed to find the safety critical stations and sections. Finally, the effectiveness of the proposed method is illustrated through a real-world case study.

The case study shows that the proposed model can produce a big-picture averaged view of the network-wide safety level and help us identify the safety critical stations and sections by considering both the expected reduction of network efficiency and capacity.

The potential application of the proposed model is to help the safety managers determine the investments in safety management of each section and station and then increase the safety and robustness of railway network operation.

The safety analysis of the railway network should consider the reliability, availability and maintenance of the railway network. In this paper, the reliability of the railway network is proposed based on the accident frequency and the topology of the railway network. Network efficiency and capacity are proposed to evaluate the availability of the railway network. The maintenance of the railway network is analyzed from the perspective of recovery time. Finally, the safety index of the railway network is proposed to analyze the safety critical stations and sections.

This paper aim at providing decision support for operational adjustment. In order to effectively reduce the external interference impact on train operation.

According to the reality that there are two kinds of high-speed trains running in China, considering the reality that there are two speed level train running in Chinese high-speed railway, this paper proposed the high-speed railway operation adjustment model based on priority, and the objective function is to minimize interference impact on train operation.

Adjustment strategy based on priority than based on sequence can effectively reduce the interference influence on train operation, which makes the train resume the planned operation back on schedule more quickly.

The solution of large-scale cases is too slow, and the practical application is limited.

The model was verified by a case, and the case results proved that adjustment strategy based on priority than based on sequence can effectively reduce the interference influence on train operation, which makes the train resume the planned operation back on schedule more quickly.

This paper aims to propose an enhanced densely dehazing network to suit railway scenes’ features and improve the visual quality degraded by haze and fog.

It is an end-to-end network based on DenseNet. The authors design enhanced dense blocks and fuse them in a pyramid pooling module for visual data’s local and global features. Multiple ablation studies have been conducted to show the effects of each module proposed in this paper.

The authors have compared dehazed results on real hazy images and railway hazy images of state-of-the-art dehazing networks with the dehazed results in data quality. Finally, an object-detection test is taken to judge the edge information preservation after haze removal. All results demonstrate that the proposed dehazing network performs better under railway scenes in detail.

This study provides a new method for image enhancing in the railway monitoring system.

Based on complex network theory, a method for critical elements identification of China Railway High-speed 2 (CRH2) train system is introduced in this paper.

First, two methods, reliability theory and complex theory, are introduced, and the advantages and disadvantages for their application in identifying critical elements of high-speed train system are summarized. Second, a multi-layer multi-granularity network model including virtual and actual nodes is proposed, and the corresponding fusion rules for the same nodes in different layers are given.

Finally, taking CRH2 train system as an example, the critical elements are identified by using complex network theory, which provides a reference for train operation and maintenance.

A method of identifying key elements of CRH2 train system based on integrated importance indices is introduced, which is a meaningful extension of the application of complex network theory to identify key components.

Since the mid-1990s most Australian jurisdictions have adopted, either through subordinate legislation or through internal government directives, rules regarding how government agencies should behave when participating in litigation. While these rules met an immediate need associated with the outsourcing of legal work to private law firms, this chapter argues that they are unsuited for enduring use: they lack a proper rationale, they are poorly worded and uncertain in their meaning; it is unclear whether and how courts should enforce them, and they have not been reviewed to take account of the more recent developments in civil procedure.

Through three case studies, the authors aim to examine how Confucian humanistic philosophy can be applied to leadership practices and show how it is possible to practice humanistic leadership in the Chinese context.

The authors use case studies of three exemplary humanistic leaders and the companies they lead to describe their leadership practices and influence on others and their companies.

The authors identify three common elements that connect their observations to an emerging scholarly conceptualization of humanistic leadership and develop a framework of Confucian humanistic leadership consisting of five attributes. The cases the authors studied suggest that the five attributes should be understood as being mutually reinforcing and acting in concert, rather than each acting independently of the others. The authors found that there is inherent consistency and connection between the core values of Confucianism and humanistic leadership.

The research contributes to the leadership literature, specifically the emerging literature on humanistic leadership, by introducing a framework for Confucian humanistic leadership. While much of the extant literature on humanistic leadership has been conceptual, the study shows how it is possible to practice humanistic leadership in the Chinese context by drawing on the foundation provided by Confucian humanistic philosophy. The findings also contribute to humanistic leadership research by providing important insights into specific capabilities that can help put the principles of humanistic leadership into practice, but that have not been considered to date.