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1 – 4 of 4Huiliang Cao, Rang Cui, Wei Liu, Tiancheng Ma, Zekai Zhang, Chong Shen and Yunbo Shi
To reduce the influence of temperature on MEMS gyroscope, this paper aims to propose a temperature drift compensation method based on variational modal decomposition (VMD)…
Abstract
Purpose
To reduce the influence of temperature on MEMS gyroscope, this paper aims to propose a temperature drift compensation method based on variational modal decomposition (VMD), time-frequency peak filter (TFPF), mind evolutionary algorithm (MEA) and BP neural network.
Design/methodology/approach
First, VMD decomposes gyro’s temperature drift sequence to obtain multiple intrinsic mode functions (IMF) with different center frequencies and then Sample entropy calculates, according to the complexity of the signals, they are divided into three categories, namely, noise signals, mixed signals and temperature drift signals. Then, TFPF denoises the mixed-signal, the noise signal is directly removed and the denoised sub-sequence is reconstructed, which is used as training data to train the MEA optimized BP to obtain a temperature drift compensation model. Finally, the gyro’s temperature characteristic sequence is processed by the trained model.
Findings
The experimental result proved the superiority of this method, the bias stability value of the compensation signal is 1.279 × 10–3°/h and the angular velocity random walk value is 2.132 × 10–5°/h/vHz, which is improved compared to the 3.361°/h and 1.673 × 10–2°/h/vHz of the original output signal of the gyro.
Originality/value
This study proposes a multi-dimensional processing method, which treats different noises separately, effectively protects the low-frequency characteristics and provides a high-precision training set for drift modeling. TFPF can be optimized by SEVMD parallel processing in reducing noise and retaining static characteristics, MEA algorithm can search for better threshold and connection weight of BP network and improve the model’s compensation effect.
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Wenhua Liu, Zekai He and Qi Wang
This paper explores the relationship between state-led urbanization and primary industry development using the difference-in-differences (DiD) method.
Abstract
Purpose
This paper explores the relationship between state-led urbanization and primary industry development using the difference-in-differences (DiD) method.
Design/methodology/approach
The study uses the DiD method.
Findings
Exploiting county-city mergers during 2010–2018, the key strategy to expand the city outward and promote urbanization on the urban fringe by local government, the authors find that county-city mergers led to the growth of primary industry decline by 4.23%. The result can be explained by the loss of essential production factors, including land and labor used for farming. In addition, the negative effect is more pronounced for counties with more substantial manufacturing. The results indicate that urbanization in China relocates land and labor; however, it does not improve the efficiency of agricultural output.
Originality/value
This paper contributes to the understanding of urbanization and rural development from the perspective of the primary industry by showing production factor redistribution. Second, this study complements the literature on local government mergers.
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Examines the tenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects…
Abstract
Examines the tenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.
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Augustine Senanu Komla Kukah, Xiaohua Jin, Robert Osei-Kyei and Srinath Perera
While operational carbon (OC) emission reduction strategies have received substantial attention in past literature, very few studies have focused on embodied carbon (EC) emission…
Abstract
Purpose
While operational carbon (OC) emission reduction strategies have received substantial attention in past literature, very few studies have focused on embodied carbon (EC) emission reduction in the construction industry. Therefore, this study aims at undertaking a scientometric review of strategies to mitigate EC emissions in the construction industry.
Design/methodology/approach
Scopus search engine was used to search for articles. VOSViewer software was used for scientometric analysis using science mapping approach. Using a total of 151 documents, keywords, authors, papers and their sources were analysed. Furthermore, scientometric analysis was undertaken comprising co-occurrence of keywords, documents source analysis and author co-citation analysis.
Findings
The significant strategies identified to mitigate EC emissions were: offsite manufacturing/use of prefabricated elements, decarbonisation of energy grid, enhanced policies and regulations by governments, construction sector policies and regulations, guidelines for increased use of low EC materials and reuse and recovery of EC construction materials.
Practical implications
This study identifies practical strategies that contribute to reduction of EC emissions.
Originality/value
This study is significant and contributes to the construction industry’s agenda to mitigate greenhouse gas emissions.
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