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37 results on '"Luo, Shaojie"'

3. A lightweight deep learning based cloud detection method for Sentinel-2A imagery fusing multi-scale spectral and spatial features

Author

Li, Jun, Wu, Zhaocong, Hu, Zhongwen, Jian, Canliang, Luo, Shaojie, Mou, Lichao, Zhu, Xiao Xiang, and Molinier, Matthieu

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Clouds are a very important factor in the availability of optical remote sensing images. Recently, deep learning-based cloud detection methods have surpassed classical methods based on rules and physical models of clouds. However, most of these deep models are very large which limits their applicability and explainability, while other models do not make use of the full spectral information in multi-spectral images such as Sentinel-2. In this paper, we propose a lightweight network for cloud detection, fusing multi-scale spectral and spatial features (CDFM3SF) and tailored for processing all spectral bands in Sentinel- 2A images. The proposed method consists of an encoder and a decoder. In the encoder, three input branches are designed to handle spectral bands at their native resolution and extract multiscale spectral features. Three novel components are designed: a mixed depth-wise separable convolution (MDSC) and a shared and dilated residual block (SDRB) to extract multi-scale spatial features, and a concatenation and sum (CS) operation to fuse multi-scale spectral and spatial features with little calculation and no additional parameters. The decoder of CD-FM3SF outputs three cloud masks at the same resolution as input bands to enhance the supervision information of small, middle and large clouds. To validate the performance of the proposed method, we manually labeled 36 Sentinel-2A scenes evenly distributed over mainland China. The experiment results demonstrate that CD-FM3SF outperforms traditional cloud detection methods and state-of-theart deep learning-based methods in both accuracy and speed.

Published
2021
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10. Power system operational reliability assessment based on the data center energy consumption elastic space.

Author

Zhang, Sheng, Gao, Jinkun, Qian, Hao, Yu, Juan, Luo, Shaojie, Guo, Qiang, Yan, Bing, and Dan, Li

Subjects
SERVER farms (Computer network management), RELIABILITY in engineering, DATA privacy, ENERGY consumption, CONSUMPTION (Economics), BIG data, EVALUATION methodology
Abstract

In the era of big data, data centers with high energy consumption, interconnectivity, and load flexibility have developed rapidly. However, due to data privacy issues, the traditional power-system operational reliability assessment (ORA) struggles to precisely consider the load flexibility of data centers, leading to inaccurate evaluation. To this end, this article proposes an ORA method considering the load flexibility of data centers via the energy consumption elastic space. By transforming the inner operation constraints of data centers into an equivalent elastic space, the ORA does not require any private data to complete the evaluation. Specifically, the energy consumption model of data centers is established to accurately describe the load flexibility. Then, based on multi-parametric programming techniques, the energy consumption elastic space of data centers is characterized by data centers' power demand constraints, which do not involve privacy data, and no privacy concerns exist. Finally, the ORA model and the evaluation method based on the energy consumption elastic space can be constructed. With a lot of data center operation constraints being replaced by power demand constraints, the proposed method can complete an evaluation faster without accuracy loss. Its effectiveness is validated through simulations using the IEEE RTS 24-bus system and a provincial 661-bus system. [ABSTRACT FROM AUTHOR]

Published
2024
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18. Study on Morphology and Rheological Property of Organoclay Dispersions in Soybean Oil Fatty Acid Ethyl Ester over a Wide Temperature Range

Author

He Shi, Luo Shaojie, Guancheng Jiang, and Haimin Shi

Subjects
chemistry.chemical_classification, food.ingredient, Ion exchange, General Chemical Engineering, General Chemistry, Chloride, Soybean oil, Article, Viscosity, chemistry.chemical_compound, Chemistry, food, Montmorillonite, chemistry, Chemical engineering, medicine, Organoclay, Dispersion (chemistry), QD1-999, Alkyl, medicine.drug
Abstract

This work attempted to establish the relationship between the dispersion morphology and the viscous flow behavior of clay dispersions in soybean oil fatty acid ethyl ester (FAEE) at 2 and 65 °C. The clays used in this study include raw montmorillonite (Mt) and three kinds of organoclays prepared by ion exchange modification of Mt by cetyltrimethylammonium chloride (OC16), dihexadecyldimethylammonium chloride (ODC16), and trihexadecylmethylammonium chloride (OTC16), respectively. The X-ray diffraction and water contact angle results demonstrated that greater alkyl chain number of surfactants led to greater interlayer space and stronger hydrophobicity of organoclays. Due to the good affinity of the surfactant and FAEE, OC16 exhibited the most stable dispersion in FAEE between 2-65 °C, which resulted in the best flat rheological property. The molecular structures of multiple chain surfactants were quite different from that of FAEE, resulting in weak affinity between organoclays (ODC16 and OTC16) and FAEE. The sheets of ODC16 and OTC16 tended to aggregate at 2 °C, forming a gel structure, thus significantly increasing the low shear rate viscosity (LSRV) and yield stress. At 65 °C, with the expansion of FAEE and the stronger thermal motion of sheets, the dispersions of ODC16 and OTC16 were improved, destroying the original gel structure and resulting in significant decreases in LSRV and yield stress. This study confirmed that stable clay/FAEE dispersions tended to exhibit flat rheology, which could serve as a basis for the application of clay/biodiesel dispersion in deep-water drilling.

Published
2020

36. Effect of Gas-Wetness of Cores on Imbibition

Author

Zhang, Min, primary, Jiang, Guancheng, additional, Xing, Xiaoxuan, additional, Luo, Shaojie, additional, Zhang, Hong, additional, Pang, Jiangtao, additional, He, Pixiang, additional, and Xuan, Yang, additional

Published
2013
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