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The purpose of this paper is to use the corresponding magnetic sensor and detection method to detect and image the defects of small diameter pipelines. Urban gas pipeline is an energy transportation tool for urban industrial production and social life, which is closely related to urban safety. Preventing the occurrence of urban gas pipeline transportation accidents and carrying out pipeline defect detection are of great significance for the urban economic and social stability. To perform pipeline defect detection, the magnetic flux leakage internal detection method is generally used in the detection of large-diameter long-distance oil and gas pipelines. However, in terms of the internal detection of small-diameter pipelines, due to the heavy weight, large structure of the detection device and small pipe diameter, the detection is more difficult.

In order to solve the above matters, self-made three-dimensional magnetic sensor and three-dimensional magnetic flux leakage imaging direct method are proposed for studying the defect identification. Firstly, for adapting to the diameter range of small-diameter pipelines, and containing the complete information of the defect, a self-made three-dimensional magnetic sensor is made in this paper to improve the accuracy of magnetic flux leakage detection. And on the basis of it, a small diameter pipeline defect detection system is built. Secondly, as detection signal may be affected by background magnetic field interference and the jitter interference, the complete ensemble empirical mode decomposition with adaptive noise method is utilized to screen the detected signal. As a result, the useful signal is reconstructed and the interference signal is removed. Finally, the defect contour inversion imaging of detection is realized based on the direct method of three-dimensional magnetic flux leakage imaging, which includes three-dimensional magnetic flux leakage detection data and data segmentation recognition.

The three-dimensional magnetic flux leakage imaging experimental results shown that, compared to the actual defects, the typical defects, irregular defects and crack groove defects can be analyzed by the magnetic flux leakage defect contour imaging method in qualitative and quantitative way respectively, which provides a new idea for the research of defect recognition.

A three-dimensional magnetic sensor is made to adapt the diameter range of small diameter pipeline, and based on it, a small-diameter pipeline defect detection system is built to collect and display the magnetic flux leakage signal.

Industrial land renewal is a significant constituent of urban environment and sustainable development. Most implementation in planning of renewal of industrial land has been mainly conducted at the site level of industrial zones or parks and the larger scale of township planning deserve further attention in China. To fill this gap, this paper aims to investigate the implementation of industrial land renewal for a whole urbanized area under the township master planning.

This study introduces a progressive approach to identify and evaluate the renewal of industrial land in township master planning to move toward a more practical understanding of industrial transition. The authors chose a typical industrialized town, Lijia in Changzhou City, under the development model of “Southern Jiangsu” to explain the measurement and assessment framework to identify and evaluate the renewable industrial land. Synthesizing the idea of sustainable development, the authors investigated the renewable industrial land with an econometric model including multiple-indexes of economic, social and ecological aspects, field observations and depth interviews.

The analysis demonstrated the spatial heterogeneity and complex generous structure of industrial land renewal in developing countries. It pointed out the major responsibility of enterprises as main industrial land users and indispensable responsibility of government and society. Following the idea of organic concentration and avoiding one-size-fits-all kind of deal, the master planning of Lijia emphasized the connection of industrial land and the combination of market force, social force and government regulation.

With original data and discussion, the authors provide more scientific renewal strategies for planners in sustainable development.

Docking technology plays a crucial role in enabling long-duration operations of autonomous underwater vehicles (AUVs). Visual positioning solutions alone are susceptible to abnormal drift values due to the challenging underwater optical imaging environment. When an AUV approaches the docking station, the absolute positioning method fails if the AUV captures an insufficient number of tracers. This study aims to to provide a more stable absolute position visual positioning method for underwater terminal visual docking.

This paper presents a six-degree-of-freedom positioning method for AUV terminal visual docking, which uses lights and triangle codes. The authors use an extended Kalman filter to fuse the visual calculation results with inertial measurement unit data. Moreover, this paper proposes a triangle code recognition and positioning algorithm.

The authors conducted a simulation experiment to compare the underwater positioning performance of triangle codes, AprilTag and Aruco. The results demonstrate that the implemented triangular code reduces the running time by over 70% compared to the other two codes, and also exhibits a longer recognition distance in turbid environments. Subsequent experiments were carried out in Qingjiang Lake, Hubei Province, China, which further confirmed the effectiveness of the proposed positioning algorithm.

This fusion approach effectively mitigates abnormal drift errors stemming from visual positioning and cumulative errors resulting from inertial navigation. The authors also propose a triangle code recognition and positioning algorithm as a supplementary approach to overcome the limitations of tracer light positioning beacons.

The purpose of this paper is to improve the robustness of the traditional Bhattacharyya metric for the effect of histogram quantization in the histogram-based visual tracking. However, the traditional Bhattacharyya metric neglects the correlation of crossing-bin and is not robust for the effect of histogram quantization.

In this paper, the authors propose a visual tracking method via crossing-bin histogram Bhattacharyya similarity in the particle filter.

A crossing-bin matrix is introduced into the traditional Bhattacharyya similarity for measuring the reference histogram and the candidate histogram, and the basic tasks of measure such as maximum similarity of self and the triangle inequality are proven. The authors use the proposed measure in the particle filter visual tracking framework and address a model update strategy based on the crossing-bin histogram Bhattacharyya similarity to improve the robustness of visual tracking.

In the experiments using the famous challenging benchmark sequences, precision of the proposed method increases by 12.8 per cent comparing the traditional Bhattacharyya similarity and the cost time decreases by 38 times comparing the incremental Bhattacharyya similarity. The experimental results show that the proposed method can track the object robustly and rapidly under illumination change and occlusion.

The construction collapse is one of the most serious accidents since it has several attributes (e.g. accident type and consequence) and its occurrence involves various kinds of causal factors (e.g. human factors). The impact of causal factors on construction collapse accidents and the interrelationships among causal factors remain poorly explored. Thus, the purpose of this paper is to use association rule mining (ARM) for cause analysis of construction collapse accidents.

An accident analytic framework is developed to determine the accident attributes and causal factors, and then ARM is introduced as the method for data mining. The data are from 620 historical accident records on government websites of China from 2010 to 2020. Through the generated association rules, the impact of causal factors and the interrelationships among causal factors are explored.

Collapse accident is easily caused by human factors, material and machine condition and management factors. Furthermore, the results show a close interrelationship between many causal factors and construction scheme and organization. The earthwork collapse is greatly related to environmental condition and the scaffolding collapse is greatly related to material and machine condition.

This study found relevant knowledge about the key causes for different types of construction collapses. Besides, several suggestions are further provided for construction units to prevent construction collapse accidents.

This study uses data mining methods to extract knowledge about the causes of collapse accidents. The impact of causal factors on various types of construction collapse accidents and the interrelationships among causal factors are explained from historical accident data.

Building on the theory of brand psychological ownership, this paper aims to explore the mediating role of brand psychological ownership in the relationship between brand personality (innocence/coolness) and consumers’ preferences, as well as identify the boundary conditions of this relationship.

To test the hypotheses, a series of four experiments were conducted in Wuhan, a city in southern China, using questionnaires administered at two universities and two supermarkets. Hypotheses were tested using PLS-SEM in SmartPLS 4.

The results indicate that brand personality, specifically the dimensions of innocence and coolness, has a significant impact on consumers’ brand preferences. Brands with a cool personality are preferred over those with an innocent personality. Moreover, the relationship between brand personality and consumers’ brand preferences is moderated by power motivation and identity centrality.

This study contributes to the literature by differentiating between brand personality of innocence and coolness as two separate constructs and proposing brand psychological ownership as a mechanism through which brand personality affects brand preferences. The study’s samples were drawn from universities and supermarkets in southern China, providing evidence for the significant moderating effects of power motivation and identity centrality on consumers’ brand preferences.

The purpose of this paper is to present an actuator fault detection method for unmanned aerial vehicles (UAVs) based on interval observer and extended state observer.

The proposed algorithm has very little model dependency. Therefore, a six-degree-of-freedom linear equation of UAVs is first established, and then, combined with actuator failure and external disturbances in flight control, a steering gear model with actuator failure (such as stuck bias and invalidation) is designed. Meanwhile, an extended state observer is designed for fault detection. Moreover, a fault detection scheme based on interval observer is designed by combining fault and disturbances.

The method is testified on the extended state observer and the interval observer under the failure of the steering gear and bounded disturbances. The simulation results show that the two types of fault detection schemes designed can successfully detect various types of faults and have high sensitivity.

This research paper studies the failure detection scheme of the UAVs’ actuator. The fault detection scheme in this paper has better performance on actuator faults and bounded disturbances than using regular fault detection schemes.

This study aims to explore the impact of leader emotional labor on employee voice. According to the emotion as information theory and the voice as a deliberate decision-making process framework, this study develops and tests a model that examines the mediating effects of psychological safety and perceived voice efficacy in this relationship.

This study conducted two studies to test hypotheses. Study 1 used a quantitative research methodology using a two-wave survey of 435 employees and 58 leaders in China. The research model was analyzed using multilevel path analyses. Study 2 collected 301 full-time employees from Prolific Platform. Hypotheses were tested using Mplus.

The results in Study 1 reveal that leader deep acting has a positive indirect relationship with employee voice via psychological safety. Conversely, leader surface acting has a negative indirect effect on employee voice through psychological safety. The results in Study 2 supported the hypotheses.

This study contributes to the voice as a deliberative process literature by introducing leader emotional labor as an antecedent of voice behavior. Additionally, this study indicates that perceived psychological safety and perceived voice efficacy are two important mediating mechanisms for implementing voice behavior.

Management science, operational and financial risk of overseas enterprises.

This case is mainly applicable to international business course and project management course.

Since 1992, the Great Mekong sub-regional economic cooperation between China and ASEAN countries was officially launched and set free economic zone. Hydropower is starting to develop in recent years in Cambodia, and it is a good significance to Cambodia's industry. Furthermore, most of hydropower plants in Cambodia are built by Chinese companies. Thus, this paper will analyze the current risk and condition of Kamchay hydropower, as well as the development of Chinese enterprise for Cambodia economic and social development.

This case study provides students concepts on international business, project management, and operational risk of overseas enterprises. The principle of project contracting, labor cooperation, and project financial in international process are considered together with the implications they have for advancing understanding of the problem of the host country's government interests and the various risk of enterprises in international BOT projects.

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