Dongfang Yang, Vladimir Pankov, Linruo Zhao and Prakash Patnaik
Accurate measurements of the temperature distributions in hot section components are indispensable for the prognostic and health management of gas turbines. Thin film thermocouple…
Abstract
Purpose
Accurate measurements of the temperature distributions in hot section components are indispensable for the prognostic and health management of gas turbines. Thin film thermocouple (TFTC) sensors, directly fabricated on the surface of a component, add negligible mass and create little or no disturbance to airflow, and therefore, can provide accurate measurements of fast temperature fluctuations of gas turbines. The purpose of this paper is to evaluate TFTC sensors fabricated by combining pulsed laser deposition (PLD) and micromachining techniques (LM).
Design/methodology/approach
The “dry” PLD/LM fabrication approach allows for excellent control of the chemical composition and physical characteristics of the constituent layers and their interfaces, thus achieving good adhesion of the layers to the substrate.
Findings
The results of thermal cyclic durability testing of the fabricated TFTC sensors demonstrated that the proposed PLD-based approach can be used to fabricate sensors that are fully functional at temperatures up to 750°C. Analyses of the sensor performance during durability testing revealed: the existence of a threshold temperature below which accurate temperature measurements were achieved; an abrupt drop in the sensor output occurring when the sensor temperature exceeded the threshold value, with a fast recovery of the sensor output once the temperature was reduced below the threshold level; and sensor “training” capable of increasing the threshold value of the TFTC through its exposure to above-the-threshold temperatures.
Originality/value
The work is the first time to demonstrate that simple PLD and LM processes can be used to fabricate TFTC that are fully functional at temperatures up to 750°C.
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Hao He, Dongfang Yang, Shicheng Wang, Shuyang Wang and Xing Liu
The purpose of this paper is to study the road segmentation problem of cross-modal remote sensing images.
Abstract
Purpose
The purpose of this paper is to study the road segmentation problem of cross-modal remote sensing images.
Design/methodology/approach
First, the baseline network based on the U-net is trained under a large-scale dataset of remote sensing imagery. Then, the cross-modal training data are used to fine-tune the first two convolutional layers of the pre-trained network to achieve the adaptation to the local features of the cross-modal data. For the cross-modal data of different band, an autoencoder is designed to achieve data conversion and local feature extraction.
Findings
The experimental results show the effectiveness and practicability of the proposed method. Compared with the ordinary method, the proposed method gets much better metrics.
Originality/value
The originality is the transfer learning strategy that fine-tunes the low-level layers for the cross-modal data application. The proposed method can achieve satisfied road segmentation with a small amount of cross-modal training data, so that is has a good application value. Still, for the similar application of cross-modal data, the idea provided by this paper is helpful.
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Wang Shicheng, Yang Dongfang, Liu Zhiguo, Luo Dacheng, Zhang Jinsheng and Liu Taiyang
The purpose of this paper is to present a novel scheme of high‐dynamic global positioning system (GPS) software receiver in order to improve the capturing speed and trading…
Abstract
Purpose
The purpose of this paper is to present a novel scheme of high‐dynamic global positioning system (GPS) software receiver in order to improve the capturing speed and trading accuracy of GPS receiver.
Design/methodology/approach
First, the beginning of C/A code can be found through the delay and multiply approach. To solve the problems of estimating a certain satellite's Doppler shift from the signals of several visible satellites, the “delay and accumulation unit” is put forward, and besides, performance of inertial navigation system‐assisted tracking loop in high‐dynamic circumstance is analysed by means of mathematical modelling and simulation experiments, whose results verified the validity of the proposed tracking scheme.
Findings
In this paper, the two‐dimension searching process in conventional acquisition scheme is transformed into two one‐dimension searching processes, thus improving the capturing speed.
Research limitations/implications
This software receiver has only been verified by means of mathematical simulation, and the validity in hardware receiver is still obscured.
Originality/value
This paper presents a novel high‐dynamic GPS software receiver scheme, which can be seen as a reference of engineering application and simulation research.
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Shiying Zhang, Yang Li and Dongfang Sheng
With the rapid development of society, major emergencies occur frequently, posing a serious threat to people’s lives and property. This study focuses on the chain reaction of…
Abstract
Purpose
With the rapid development of society, major emergencies occur frequently, posing a serious threat to people’s lives and property. This study focuses on the chain reaction of major emergencies, aiming to improve the overall situational awareness and capabilities for managing major emergencies in complex scenarios.
Design/methodology/approach
We proposed an information support framework for the chain reaction of major emergencies based on a causality eventic graph (CEG). The framework consists of three modules: the data layer, the analysis layer and the service layer. The data layer focuses on the perception and collection of major emergency information. The analysis layer includes key components such as causality recognition, causality extraction, event fusion and generalization. In this layer, we developed several deep learning (DL)-based models using a joint extraction approach to obtain causal pairs. The service layer depicts the event evolution logic from both industry and public perspectives.
Findings
The empirical study has demonstrated the feasibility and effectiveness of the proposed information support framework. First, the BERT-BiLSTM-CRF model achieved the best performance in the causality extraction task. Second, the SBERT model was found to be more suitable for event fusion. Third, the analysis results of CEG revealed that the impact of pandemics on industries in turn affects other industries as well as people’s livelihoods and vice versa. The framework shows a better information support, discovery and reasoning effect. This study, however, still has several limitations. We focused primarily on causal logic and did not fully explore other logical relationships. In future work, we will incorporate more logical relations to further refine the eventic graph (EG).
Originality/value
This study proposes a novel information support framework for the chain reaction of major emergencies, leveraging CEG to provide targeted and hierarchical information to industry and public stakeholders. It solves several problems in the emergency management of major emergencies.
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This paper aims to reveal how different types of events and top management teams' (TMTs’) cognitive frames affect the generation of breakthrough innovations.
Abstract
Purpose
This paper aims to reveal how different types of events and top management teams' (TMTs’) cognitive frames affect the generation of breakthrough innovations.
Design/methodology/approach
Drawing on the event system theory and upper echelon theory, this study chose a Chinese manufacturing enterprise as the case firm and conducted an exploratory single-case study to unpack how breakthrough innovation generates over time.
Findings
By conducting the in-depth case analysis, the study revealed that firms do not produce breakthrough innovation in the catch-up stage and parallel-running stage but achieve it in the leading stage. It also indicated that when facing proactive events in the catch-up stage, TMTs often adopt a contracted lens, being manifested as consistency orientation, less elastic organizational identity and narrower competitive boundaries. In addition, they tend to adopt a contracted lens when facing reactive and proactive events in the parallel-running stage. In the face of reactive and proactive events in the leading stage, they are more inclined to adopt an expanded lens, being manifested as a coexistence orientation, more elastic organizational identity and wider competitive boundaries.
Originality/value
First, by untangling how TMT's cognitive frame functions in breakthrough innovations, this paper provides a micro-foundation for producing breakthrough innovations and deepens the understanding of upper echelon theory by considering the cognitive dimension of TMTs. Second, by teasing out several typical events experienced by the firm, this paper is the first attempt to reveal how events affect the generation of breakthrough innovation. Third, the work extends the application of the event system theory in technological innovation. It also provides insightful implications for promoting breakthrough innovations by considering the role of proactive and reactive events a firm experiences and TMT's perceptions.
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Jiaqi Li, Guangyi Zhou, Dongfang Li, Mingyuan Zhang and Xuefeng Zhao
Recognizing every worker's working status instead of only describing the existing construction activities in static images or videos as most computer vision-based approaches do;…
Abstract
Purpose
Recognizing every worker's working status instead of only describing the existing construction activities in static images or videos as most computer vision-based approaches do; identifying workers and their activities simultaneously; establishing a connection between workers and their behaviors.
Design/methodology/approach
Taking a reinforcement processing area as a research case, a new method for recognizing each different worker's activity through the position relationship of objects detected by Faster R-CNN is proposed. Firstly, based on four workers and four kinds of high-frequency activities, a Faster R-CNN model is trained. Then, by inputting the video into the model, with the coordinate of the boxes at each moment, the status of each worker can be judged.
Findings
The Faster R-CNN detector shows a satisfying performance with an mAP of 0.9654; with the detected boxes, a connection between the workers and activities is established; Through this connection, the average accuracy of activity recognition reached 0.92; with the proposed method, the labor consumption of each worker can be viewed more intuitively on the visualization graphics.
Originality/value
With this proposed method, the visualization graphics generated will help managers to evaluate the labor consumption of each worker more intuitively. Furthermore, human resources can be allocated more efficiently according to the information obtained. It is especially suitable for some small construction scenarios, in which the recognition model can work for a long time after it is established. This is potentially beneficial for the healthy operation of the entire project, and can also have a positive indirect impact on structural health and safety.
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Dongfang Wang, Arthur Tarasov and Huarong Zhang
The purpose of this paper is to test the relationship between environmental regulations and green total factor productivity (GTFP) of China's logistics industry. The high-factor…
Abstract
Purpose
The purpose of this paper is to test the relationship between environmental regulations and green total factor productivity (GTFP) of China's logistics industry. The high-factor input, high-energy consumption, and high-pollution emissions model of the logistics industry developed within China faces challenges from severe resource and environmental constraints. It is generally believed that environmental regulations effectively restrain pollution emissions and help protect the environment.
Design/methodology/approach
The authors employ the undesirable slack-based Malmquist Luenberger model to calculate the GTFP across the provincial logistics industry and use the mediation effect model and threshold effect model to explore the effects and mechanics of environmental transmission regulations on the GTFP.
Findings
The main results show significant regional differences in the GTFP of logistics industry across China. In the transmission path of the impact of environmental regulations on the GTFP, regional innovation capabilities have mediation effects. Regional innovation capacities have a masking effect on the transmission path of environmental regulations on accumulated technical efficiency changes (AEC) and accumulated technical changes (ATC). The threshold effect test results show a dual-threshold effect between environmental regulations and the GTFP, with environmental regulations as threshold variable. Furthermore, the impact of regional innovation capability on the GTFP has a dual-threshold effect, with environmental regulation as threshold variable.
Practical implications
First, it is advisable to plan the environmental regulation policy system thoroughly and add supporting measures to ensure the efficiency and smooth implementation of the nation's environmental policies. Second, it is important to further understand the critical role of innovation capability in improving the GTFP. Third, there is an urgent need to standardize the operating behavior and market order of the leading players in the logistics market and to improve the operational efficiency of logistics enterprises.
Originality/value
So far, a systematical study researched on effect of environmental regulation on the GTFP in logistics industry was not published. This study can provide experience for the high-quality development of the logistics industry.
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Shijian Wang, Qiyuan He, Quanwei Liang, Jie Cui, Qing Jiang, Chang Liu, Chao He, Lang Li and Yao Chen
The study aims to examine the effect of inclusions and inherent microstructure on fatigue behavior of 34Cr2Ni2Mo steel.
Abstract
Purpose
The study aims to examine the effect of inclusions and inherent microstructure on fatigue behavior of 34Cr2Ni2Mo steel.
Design/methodology/approach
Fatigue behavior of 34Cr2Ni2Mo steel was investigated for up to 1E10 cycles.
Findings
Results showed that both inclusion and inherent microstructure have an influence on the crack initiation mechanism. Fatigue cracks mostly initiated from inclusions, whereas substrate-induced crack initiations were also observed. Fatigue life of inclusion-induced failures is mostly determined by the location of inclusions rather than the loading stress. The inherent microstructure seems to tolerate inclusions at a lower stress level in very high-cycle regime owing to the absence of internal inclusion-induced failure. For the substrate-induced crack initiations, high-density dislocations are found to be accumulated around the carbide particle-matrix interface, which may be the cause of crack initiation in the inherent structure due to strain localization.
Originality/value
The effect of inclusions and inherent microstructure on fatigue behavior of 34Cr2Ni2Mo steel up to 1E10 cycles.
Highlights
Fatigue failure occurs even at a lifetime of 5.76E9 cycles.
Surface inclusion induced premature failures.
Inherent microstructure tolerates inclusions at lower stress level.
Internal carbides promote substrate-induced crack initiations.
Fatigue failure occurs even at a lifetime of 5.76E9 cycles.
Surface inclusion induced premature failures.
Inherent microstructure tolerates inclusions at lower stress level.
Internal carbides promote substrate-induced crack initiations.
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Xiaohui Li, Dongfang Fan, Yi Deng, Yu Lei and Owen Omalley
This study aims to offer a comprehensive exploration of the potential and challenges associated with sensor fusion-based virtual reality (VR) applications in the context of…
Abstract
Purpose
This study aims to offer a comprehensive exploration of the potential and challenges associated with sensor fusion-based virtual reality (VR) applications in the context of enhanced physical training. The main objective is to identify key advancements in sensor fusion technology, evaluate its application in VR systems and understand its impact on physical training.
Design/methodology/approach
The research initiates by providing context to the physical training environment in today’s technology-driven world, followed by an in-depth overview of VR. This overview includes a concise discussion on the advancements in sensor fusion technology and its application in VR systems for physical training. A systematic review of literature then follows, examining VR’s application in various facets of physical training: from exercise, skill development and technique enhancement to injury prevention, rehabilitation and psychological preparation.
Findings
Sensor fusion-based VR presents tangible advantages in the sphere of physical training, offering immersive experiences that could redefine traditional training methodologies. While the advantages are evident in domains such as exercise optimization, skill acquisition and mental preparation, challenges persist. The current research suggests there is a need for further studies to address these limitations to fully harness VR’s potential in physical training.
Originality/value
The integration of sensor fusion technology with VR in the domain of physical training remains a rapidly evolving field. Highlighting the advancements and challenges, this review makes a significant contribution by addressing gaps in knowledge and offering directions for future research.
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Gang Sheng, Huabin Wu and Xiangdong Xu
The implementation of the digital economy has had a considerable influence on the manufacturing industry, and this paper aims to address the important issues of how to capture the…
Abstract
Purpose
The implementation of the digital economy has had a considerable influence on the manufacturing industry, and this paper aims to address the important issues of how to capture the opportunities presented by digital innovation and promote the transformation and upgrading of the manufacturing industry, as well as the improvement of quality and efficiency.
Design/methodology/approach
Using panel data from 30 Chinese provinces and cities between 2010 and 2021, this study establishes the panel vector autoregression (PVAR) model and uses impulse response function analysis to evaluate the influence of the digital economy on the high-quality transformation and upgrading of China's small home appliance industry across five dimensions under the digital economy.
Findings
The development of digital infrastructure has not demonstrated a noteworthy capacity for advancing the transformation and upgrading of the small home appliance industry. Furthermore, digital industrialization has exerted a minimal restraining influence on this process. Nevertheless, digital governance has consistently exhibited a substantial impact on facilitating the transformation and upgrading of the small home appliance industry. While both industrial digitization and digital innovation hold significant potential for promoting the transformation and upgrading of the small home appliance industry, their sustainability remains limited.
Practical implications
The organization should logically join independent innovation and open innovation, construct an industrial ecosystem for the profound convergence of the digital economy and compact household appliances, use digital-wise science and technology to empower the establishment of brand effects, strengthen the portrayal of the digital standard framework for the intelligent compact household appliance industry, advance the development of a public stage for computerized administrations in the compact household appliance industry and develop a strategy ecosystem for computerized assets in the compact household appliance industry.
Originality/value
This study offers systematic evidence of the relationship between the digital economy and the development of the small home appliance industry. The results of this research contribute to the literature on the impact of the digital economy on the manufacturing sector and provide a logical explanation for the transformation and upgrading of the small home appliance industry within the context of the digital economy.