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With the yearly increase of mileage and passenger volume in China's high-speed railway, the problems of traditional paper railway tickets have become increasingly prominent, including complexity of business handling process, low efficiency of ticket inspection and high cost of usage and management. This paper aims to make extensive references to successful experiences of electronic ticket applications both domestically and internationally. The research on key technologies and system implementation of railway electronic ticket with Chinese characteristics has been carried out.

Research in key technologies is conducted including synchronization technique in distributed heterogeneous database system, the grid-oriented passenger service record (PSR) data storage model, efficient access to massive PSR data under high concurrency condition, the linkage between face recognition service platforms and various terminals in large scenarios, and two-factor authentication of the e-ticket identification code based on the key and the user identity information. Focusing on the key technologies and architecture the of existing ticketing system, multiple service resources are expanded and developed such as electronic ticket clusters, PSR clusters, face recognition clusters and electronic ticket identification code clusters.

The proportion of paper ticket printed has dropped to 20%, saving more than 2 billion tickets annually since the launch of the application of E-ticketing nationwide. The average time for passengers to pass through the automatic ticket gates has decreased from 3 seconds to 1.3 seconds, significantly improving the efficiency of passenger transport organization. Meanwhile, problems of paper ticket counterfeiting, reselling and loss have been generally eliminated.

E-ticketing has laid a technical foundation for the further development of railway passenger transport services in the direction of digitalization and intelligence.

Large displacement misalignment under the action of active faults can cause complex three-dimensional deformation in subway tunnels, resulting in severe damage, distortion and misalignment. There is no developed system of fortification and related codes to follow. There are scientific problems and technical challenges in this field that have never been encountered in past research and practices.

This paper adopted a self-designed large-scale active fault dislocation simulation loading system to conduct a similar model test of the tunnel under active fault dislocation based on the open-cut tunnel project of the Urumqi Rail Transit Line 2, which passes through the Jiujiawan normal fault. The test simulated the subway tunnel passing through the normal fault, which is inclined at 60°. This research compared and analyzed the differences in mechanical behavior between two types of lining section: the open-cut double-line box tunnel and the modified double-line box arch tunnel. The structural response and failure characteristics of the open-cut segmented lining of the tunnel under the stick-slip part of the normal fault were studied.

The results indicated that the double-line box arch tunnel improved the shear and longitudinal bending performance. Longitudinal cracks were mainly distributed in the baseplate, wall foot and arch foot, and the crack position was basically consistent with the longitudinal distribution of surrounding rock pressure. This indicated that the longitudinal cracks were due to the large local load of the cross-section of the structure, leading to an excessive local bending moment of the structure, which resulted in large eccentric failure of the lining and formation of longitudinal cracks. Compared with the ordinary box section tunnel, the improved double-line box arch tunnel significantly reduced the destroyed and damage areas of the hanging wall and footwall. The damage area and crack length were reduced by 39 and 59.3%, respectively. This indicates that the improved double-line box arch tunnel had good anti-sliding performance.

This paper adopted a self-designed large-scale active fault dislocation simulation loading system to conduct a similar model test of the tunnel under active fault dislocation. This system increased the similarity ratio of the test model, improved the dislocation loading rate and optimized the simulation scheme of the segmented flexible lining and other key factors affecting the test. It is of great scientific significance and engineering value to investigate the structure of subway tunnels under active fault misalignment, to study its force characteristics and damage modes, and to provide a technical reserve for the design and construction of subway tunnels through active faults.

Drawing on the transformational leadership (TL) and knowledge-based view (KBV) theory, the present study investigates the impact of TL on radical innovation (RI) through the mediation of knowledge management capabilities (KMCs) and moderation of competitive intensity (CI) of textile and apparel industries with an Asian context.

Data were collected from the relevant stakeholders of the industry-university collaboration teams with a structured survey questionnaire. Working with 304 textile and apparel industry respondents, structural equation modeling based partial least square (PLS-SEM) is used to test the conceptual framework. PLS-SEM technique was applied to test the hypothesis using Smart-PLS 3.8 packages program.

The results proposed TL has a positive impact on KMC and RI. Furthermore, the study reveals KMC positively mediated the relationship between TL and RI. This mediation is conditional on the moderating role of CI for the KMC (knowledge acquisition capability + knowledge-sharing capability) path to RI. Conversely, moderation of CI is insignificant and does not influence on fostering RI.

Leaders and managers have realized creative and innovative culture is built within the organizations by leader-follower collaboration through actual knowledge acquisition and knowledge sharing. Moreover, industry policymakers and practitioners establish the knowledge management department to enhance the innovation culture among the firms' stakeholders to encourage RI to sustain the global business market.

The study has introduced KMC as a mediator and CI as a moderator in the proposed model between TL-RI and KMC-RI. Further, it explores the linkages between TL, KMC, CI and RI.

Constant or decreasing returns and increasing returns to scale are two kinds of mechanism in economic growth. The goal of supply-side structural reform is to promote the establishment of the mechanism with increasing returns to scale. The paper aims to discuss this issue.

This paper argues that the overall economic structure of the developing economy has been divided into the sector of constant or decreasing returns to scale and the sector of increasing returns to scale due to the dual economic structure. Among them, the supply-side structural reform is mainly to reduce the sector of decreasing returns to scale and increase the sector of increasing returns to scale. Based on the hypothesis of such two-sector economic structure in the supply side of developing economies and on the industrial data, this paper empirically tests the returns to scale of China’s supply structure. The result suggests that so far the sector of constant or decreasing returns to scale dominates the supply structure of China’s economic growth, which results in the state of decreasing returns to scale in China’s overall economy.

Therefore, to realize the long-term sustained growth and transformation of the development pattern of China’s economy, the authors must carry out the supply-side structural reform, vigorously develop the modern industrial sectors characterized by modern knowledge and technology, and promote the development of an innovation-driven economy.

Besides, the authors must accelerate the transformation from traditional industrial sectors to modern industrial sectors, actively promote China’s industrial structure toward rationalization and high gradation, as well as build a modern industrial system so as to facilitate the formation of the mechanism of increasing returns to scale and accelerate the transformation of the driving force of China’s economic growth.

Steer-by-wire (SBW) system mainly relies on sensors, controllers and motors to replace the traditionally mechanical transmission mechanism to realize steering functions. However, the sensors in the SBW system are particularly vulnerable to external influences, which can cause systemic faults, leading to poor steering performance and even system instability. Therefore, this paper aims to adopt a fault-tolerant control method to solve the safety problem of the SBW system caused by sensors failure.

This paper proposes an active fault-tolerant control framework to deal with sensors failure in the SBW system by hierarchically introducing fault observer, fault estimator, fault reconstructor. Firstly, the fault observer is used to obtain the observation output of the SBW system and then obtain the residual between the observation output and the SBW system output. And then judge whether the SBW system fails according to the residual. Secondly, dependent on the residual obtained by the fault observer, a fault estimator is designed using bounded real lemma and regional pole configuration to estimate the amplitude and time-varying characteristics of the faulty sensor. Eventually, a fault reconstructor is designed based on the estimation value of sensors fault obtained by the fault estimator and SBW system output to tolerate the faulty sensor.

The numerical analysis shows that the fault observer can be rapidly activated to detect the fault while the sensors fault occurs. Moreover, the estimation accuracy of the fault estimator can reach to 98%, and the fault reconstructor can make the faulty SBW system to retain the steering characteristics, comparing to those of the fault-free SBW system. In addition, it was verified for the feasibility and effectiveness of the proposed control framework.

As the SBW fault diagnosis and fault-tolerant control in this paper only carry out numerical simulation research on sensors faults in matrix and laboratory/Simulink, the subsequent hardware in the loop test is needed for further verification.

Aiming at the SBW system with parameter perturbation and sensors failure, this paper proposes an active fault-tolerant control framework, which integrates fault observer, fault estimator and fault reconstructor so that the steering performance of SBW system with sensors faults is basically consistent with that of the fault-free SBW system.

This study aims to review the literature on sharing economy logistics and crowd logistics to answer the three following questions: How is the literature on sharing economy logistics structured? What are the main trends in sharing economy logistics and crowd logistics? What are the future research options?

Bibliometric analysis is used to evaluate 85 articles published over the past 12 years; it identifies the top academic journals, authors and research topics contributing to the field.

The sharing economy logistics and crowd logistics literature is structured around several disciplines and highlights that some are more scientifically advanced than others in their subject definitions, designs, modelling and innovative solutions. The main trends are organized around three clusters: Cluster 1 refers to the optimal allocation of costs, prices, distribution and supplier relationships; Cluster 2 corresponds to business related crowdsourcing and international industry practices; and Cluster 3 includes the impact of transport on last-mile delivery, crowd shipping and the environment.

The study is based on data from peer-reviewed scientific journals and conferences. A broader overview could include other data sources such as books, book chapters, working papers, etc.

Future research directions are discussed in the context of the evolution from crowd logistics to crowd intelligence, and the complexities of crowd logistics such as understanding how the social crowd can be integrated into the logistics process. Our results are part of the crowd science and engineering concept and provide some answers about crowd cyber-system questions regarding crowd intelligence in logistic sector.

Digital resources such as smart applications reviews and online feedback information are important sources to seek customers’ feedback and input. This paper aims to help government entities gain insights on the needs and expectations of their customers. Towards this end, we propose an aspect-based sentiment analysis hybrid approach that integrates domain lexicons and rules to analyse the entities smart apps reviews. The proposed model aims to extract the important aspects from the reviews and classify the corresponding sentiments. This approach adopts language processing techniques, rules, and lexicons to address several sentiment analysis challenges, and produce summarized results. According to the reported results, the aspect extraction accuracy improves significantly when the implicit aspects are considered. Also, the integrated classification model outperforms the lexicon-based baseline and the other rules combinations by 5% in terms of Accuracy on average. Also, when using the same dataset, the proposed approach outperforms machine learning approaches that uses support vector machine (SVM). However, using these lexicons and rules as input features to the SVM model has achieved higher accuracy than other SVM models.

This paper aims to create a new searchable 3D city model to help managers improve their decision-making.

This paper identifies data management basics and the key elements used in the new model design; it further analyzes five-city models, presents its findings and proposes analytical trends for the new model. It discusses the concepts underlying existing models, explains the benefit brought by the proposed model and demonstrates its robustness.

City systems can be interconnected, thanks to data digitization and the integration of new technologies into different management processes. Although there are several 3D city models available, none of those identified in this research can be queried for several sectors.

This model design can only be successfully realized in the presence of a public mandate. Potential limitations include information security risks and political non-acceptance.

The present work proposes a searchable and high performance model having the distinctive capacity to bring together city systems and perform real-time data analysis in order to extract important information needed to guide the city, and in the context of a global vision.

Ground Penetrating Radar is a multidisciplinary Nondestructive Evaluation technique that requires knowledge of electromagnetic wave propagation, material properties and antenna theory. Under some circumstances this tool may require auxiliary algorithms to improve the interpretation of the collected data. Detection, location and definition of target’s geometrical and physical properties with a low false alarm rate are the objectives of these signal post-processing methods. Basic approaches are focused in the first two objectives while more robust and complex techniques deal with all objectives at once. This work reviews the use of Artificial Neural Networks and Machine Learning for data interpretation of Ground Penetrating Radar surveys. We show that these computational techniques have progressed GPR forward from locating and testing to imaging and diagnosis approaches.