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Article ; Online: Fault detection during power system out-of-step oscillation using frequency difference sudden-change of voltage and current at a single terminal bus and a novel setting-free distance protection unlocking scheme

Shuai Zhang

Heliyon, Vol 9, Iss 3, Pp e14286- (2023)

2023

Abstract: Setting blocking on the electricity transmission network distance protection is an important control measure to prevent it from malfunctioning in the out-of-step oscillation (OOSO) process. However, this operation makes it lose the ability to cut off ... ...

Abstract	Setting blocking on the electricity transmission network distance protection is an important control measure to prevent it from malfunctioning in the out-of-step oscillation (OOSO) process. However, this operation makes it lose the ability to cut off faults. Once fault occurs, the consequences are serious, which might bring huge energy loss. How to effectively identify faults and quickly restore its protection capability is an important engineering task, but it's also filled with challenges. For the symmetrical faults occurring at δ≈180∘, the traditional technologies are susceptible to failure because the system seems to be oscillating continuously. For asymmetric faults, the sequence component method can be adopted, but limited by the sequence component extraction speed. Aiming at the above existing problems, this paper launches the targeted study and gives the corresponding solutions. To the former, it innovatively analyzes the variation law about the frequency difference of bus voltage (BV) and system current (SC) before and after fault occurs in the OOSO process, and gives its change range through strict mathematical derivation. Based on this, it proposes a novel one terminal setting-free distance protection unlocking scheme for symmetrical fault. Experiments show that the new variables defined in the criterion change abruptly and last for 3 sampling points after a fault. The new method can effectively identify faults occurring at δ≈180∘. This is an important advantage over the traditional methods. To the latter, it constructs a phasor imaginary part estimator, and proposes a sequence component transient calculation method. It greatly improves the asymmetric fault identification speed of the related method.
Keywords	Sudden-change law of frequency difference ; Out-of-step oscillation ; Distance protection unlocking ; Science (General) ; Q1-390 ; Social sciences (General) ; H1-99
Language	English
Publishing date	2023-03-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: LcmUNet

Shuai Zhang / Yanmin Niu

Bioengineering, Vol 10, Iss 712, p

A Lightweight Network Combining CNN and MLP for Real-Time Medical Image Segmentation

2023 Volume 712

Abstract: In recent years, UNet and its improved variants have become the main methods for medical image segmentation. Although these models have achieved excellent results in segmentation accuracy, their large number of network parameters and high computational ... ...

Abstract	In recent years, UNet and its improved variants have become the main methods for medical image segmentation. Although these models have achieved excellent results in segmentation accuracy, their large number of network parameters and high computational complexity make it difficult to achieve medical image segmentation in real-time therapy and diagnosis rapidly. To address this problem, we introduce a lightweight medical image segmentation network (LcmUNet) based on CNN and MLP. We designed LcmUNet’s structure in terms of model performance, parameters, and computational complexity. The first three layers are convolutional layers, and the last two layers are MLP layers. In the convolution part, we propose an LDA module that combines asymmetric convolution, depth-wise separable convolution, and an attention mechanism to reduce the number of network parameters while maintaining a strong feature-extraction capability. In the MLP part, we propose an LMLP module that helps enhance contextual information while focusing on local information and improves segmentation accuracy while maintaining high inference speed. This network also covers skip connections between the encoder and decoder at various levels. Our network achieves real-time segmentation results accurately in extensive experiments. With only 1.49 million model parameters and without pre-training, LcmUNet demonstrated impressive performance on different datasets. On the ISIC2018 dataset, it achieved an IoU of 85.19%, 92.07% recall, and 92.99% precision. On the BUSI dataset, it achieved an IoU of 63.99%, 79.96% recall, and 76.69% precision. Lastly, on the Kvasir-SEG dataset, LcmUNet achieved an IoU of 81.89%, 88.93% recall, and 91.79% precision.
Keywords	medical image segmentation ; lightweight network ; UNet ; CNN ; MLP ; Technology ; T ; Biology (General) ; QH301-705.5
Subject code	006
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Moving morphable component (MMC) topology optimization with different void structure scaling factors

Zhao Li / Hongyu Xu / Shuai Zhang

PLoS ONE, Vol 19, Iss

2024 Volume 1

Keywords	Medicine ; R ; Science ; Q
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Assessing Integrated Effectiveness of Rural Socio-Economic Development and Environmental Protection of Wenchuan County in Southwestern China

Jifei Zhang / Shuai Zhang

Land, Vol 11, Iss 1912, p

An Approach Using Game Theory and VIKOR

2022 Volume 1912

Abstract: A scientific and comprehensive effectiveness evaluation is a prerequisite for clarifying the guiding direction of rural socio-economic development and environmental protection. By using the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) ... ...

Abstract	A scientific and comprehensive effectiveness evaluation is a prerequisite for clarifying the guiding direction of rural socio-economic development and environmental protection. By using the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method and weight combination based on game theory, this paper systematically assessed the integrated effectiveness of rural socio-economic development and environmental protection (IERSE) of Wenchuan County in 2018 from the administrative village scale perspective. Results showed that: (1) VIKOR with combined weight and Jenks Natural Breaks Classification is both comprehensive and feasible for large-sample-size evaluation, such as IERSE assessment. (2) The general IERSE of Wenchuan demonstrated considerable positive outcomes. The villages with favorable scores were located along the northwest-central-southeast, whereas unfavorable ones were principally distributed in the northeast and south-central regions. Local spatial agglomeration of favorable IERSE was found in Miansi, Wolong, and Sanjiang Town, whereas the agglomeration of unfavorable IERSE was seen in Yingxiu and Xuankou Town. (3) The IERSE of Wenchuan is mainly constrained by ecological conservation and villagers’ autonomy from the village-scale perspective. Villages with favorable IERSE are chiefly constrained by the education level of the village heads or Party secretaries, while villages with unfavorable IERSE are restricted by ecological conservation. To improve the IERSE in rural Wenchuan, thoroughly taking into account the restrictive factors of local IERSE is an essential step for putting forward differentiated and targeted recommendations connected with ecological environment management, as well as social development initiatives.
Keywords	integrated effectiveness of rural socio-economic development and environmental protection ; VIKOR method ; combined weight based on game theory ; Jenks Natural Breaks Classification method ; Wenchuan County ; Agriculture ; S
Subject code	910
Language	English
Publishing date	2022-10-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Identification of Urban Agglomeration Spatial Range Based on Social and Remote-Sensing Data—For Evaluating Development Level of Urban Agglomeration

Shuai Zhang / Hua Wei

ISPRS International Journal of Geo-Information, Vol 11, Iss 8, p

2022 Volume 456

Abstract: The accurate identification of urban agglomeration spatial area is helpful in understanding the internal spatial relationship under urban expansion and in evaluating the development level of urban agglomeration. Previous studies on the identification of ... ...

Abstract	The accurate identification of urban agglomeration spatial area is helpful in understanding the internal spatial relationship under urban expansion and in evaluating the development level of urban agglomeration. Previous studies on the identification of spatial areas often ignore the functional distribution and development of urban agglomerations by only using nighttime light data (NTL). In this study, a new method is firstly proposed to identify the accurate spatial area of urban agglomerations by fusing night light data (NTL) and point of interest data (POI); then an object-oriented method is used by this study to identify the spatial area, finally the identification results obtained by different data are verified. The results show that the accuracy identified by NTL data is 82.90% with the Kappa coefficient of 0.6563, the accuracy identified by POI data is 81.90% with the Kappa coefficient of 0.6441, and the accuracy after data fusion is 90.70%, with the Kappa coefficient of 0.8123. The fusion of these two kinds of data has higher accuracy in identifying the spatial area of urban agglomeration, which can play a more important role in evaluating the development level of urban agglomeration; this study proposes a feasible method and path for urban agglomeration spatial area identification, which is not only helpful to optimize the spatial structure of urban agglomeration, but also to formulate the spatial development policy of urban agglomeration.
Keywords	Central Plains Urban Agglomeration (CPUA) ; nighttime light ; urban expansion ; spatial range ; big data ; Geography (General) ; G1-922
Subject code	710 ; 910
Language	English
Publishing date	2022-08-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Comparison of Atmospheric Carbon Dioxide Concentrations Based on GOSAT, OCO-2 Observations and Ground-Based TCCON Data

Jinhui Zheng / Huifang Zhang / Shuai Zhang

Remote Sensing, Vol 15, Iss 21, p

2023 Volume 5172

Abstract: Carbon dioxide (CO 2 ) is one of the most significant greenhouse gases, and its concentration and distribution in the atmosphere have always been a research hotspot. To study the temporal and spatial characteristics of atmospheric CO 2 globally, it is ... ...

Abstract	Carbon dioxide (CO 2 ) is one of the most significant greenhouse gases, and its concentration and distribution in the atmosphere have always been a research hotspot. To study the temporal and spatial characteristics of atmospheric CO 2 globally, it is crucial to evaluate the consistency of observation data from different carbon observation satellites. This study utilizes data from the Total Carbon Column Observing Network (TCCON) to verify the column-averaged dry air mole fractions of atmospheric CO 2 (XCO 2 ) retrieved by satellites from October 2014 to May 2016, specifically comparing the XCO 2 distributions from the Greenhouse Gases Observing Satellite (GOSAT) and Orbiting Carbon Observatory 2 (OCO-2). Our analysis indicates a strong correlation between the TCCON and both the GOSAT (correlation coefficient of 0.85) and OCO-2 (correlation coefficient of 0.91). Cross-validation further reveals that the measurements of the GOSAT and OCO-2 are highly consistent, with an average deviation and standard deviation of 0.92 ± 1.16 ppm and a correlation coefficient of 0.92. These differences remain stable over time, indicating that the calibration in the data set is reliable. Moreover, monthly averaged time-series and seasonal climatology comparisons were also performed separately over the six continents, i.e., Asia, North America, Europe, Africa, South America, and Oceania. The investigation of monthly XCO 2 values across continents highlights greater consistency in Asia, North America, and Oceania (standard deviation from 0.15 to 0.27 ppm) as compared to Europe, South America, and Africa (standard deviation from 0.45 to 0.84 ppm). A seasonal analysis exhibited a high level of consistency in spring (correlation coefficient of 0.97), but lower agreement in summer (correlation coefficient of 0.78), potentially due to cloud cover and aerosol interference. Although some differences exist among the datasets, the overall findings demonstrate a strong correlation between the satellite measurements of XCO 2 . These results ...
Keywords	carbon dioxide ; GOSAT ; OCO-2 ; TCCON ; XCO 2 ; climate change ; Science ; Q
Subject code	290
Language	English
Publishing date	2023-10-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Landslide Hazard Assessment Method Considering the Deformation Factor

Cong Dai / Weile Li / Huiyan Lu / Shuai Zhang

Remote Sensing, Vol 15, Iss 596, p

A Case Study of Zhouqu, Gansu Province, Northwest China

2023 Volume 596

Abstract: Landslides are geological disasters that can cause great damage to natural and social environments. Landslide hazard assessments are crucial for disaster prevention and mitigation. Conventional regional landslide hazard assessment results are static and ... ...

Abstract	Landslides are geological disasters that can cause great damage to natural and social environments. Landslide hazard assessments are crucial for disaster prevention and mitigation. Conventional regional landslide hazard assessment results are static and do not take into account the dynamic changes in landslides; thus, areas with landslides that have been treated and stabilized are often still identified as high-risk areas. Therefore, a new hazard assessment method is proposed in this paper that combines the deformation rate results obtained by interferometric synthetic aperture radar (InSAR) with the results of conventional hazard assessments to obtain the hazard assessment level while considering the deformation factor of the study area, with Zhouqu, Gansu Province, selected as the case study. First, to obtain the latest landslide inventory map of Zhouqu, the hazard assessment results of the study area were obtained based on a neural network and statistical analysis, and an innovative combination of the deformation rate results of the steepest slope direction from the ascending and descending data were obtained by InSAR technology. Finally, the hazard assessment level considering the deformation factor of Zhouqu was obtained. The method proposed in this paper allows for a near-term hazard assessment of the study area, which in turn enables dynamic regional landslide hazard assessments and improves the efficiency of authorities when conducting high-risk-area identification and management.
Keywords	landslides ; hazard assessment ; InSAR ; Zhouqu ; Science ; Q
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Adaptive Compressive Sensing

Shuai Zhang / Jinhai Liu / Xin Zhang

Sustainability, Vol 15, Iss 14591, p

An Optimization Method for Pipeline Magnetic Flux Leakage Detection

2023 Volume 14591

Abstract: Leakage from a submarine oil pipeline would have a great impact on the environment and ecological balance. Accurate detection of pipeline defects can ensure safety in the transportation of oil resources. The traditional detection optimization algorithm ... ...

Abstract	Leakage from a submarine oil pipeline would have a great impact on the environment and ecological balance. Accurate detection of pipeline defects can ensure safety in the transportation of oil resources. The traditional detection optimization algorithm may lead to the absence of effective features. An adaptive compressive sensing image data augmentation method that analyzes the pixel distribution of small defect features has been proposed to solve these issues. On the basis of Focal-EIoU, a new box loss of Focal-GIoU is proposed which is suitable for pipeline defect detection. Furthermore, the incorporation of bi-level routing attention diminishes the reliance of Yolov5 on specific inputs effectively, thereby enhancing the generalization ability of the detection model. Comparative experiments show that compared with the conventional Yolov5 model, this method improves mAP50 and mAP50:95 by 6.4% and 15.1%, respectively, with mAP50 reaching 91.5% and mAP50:95 reaching 52.9%.
Keywords	magnetic leakage internal detection ; compressive sensing ; small object detection ; image data augmentation ; attention mechanism ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Language	English
Publishing date	2023-10-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Hydrogen-rich water treatment targets RT1-Db1 and RT1-Bb to alleviate premature ovarian failure in rats

Xiaoyin Meng / Shuai Zhang / Lu Zhao / Yingmei Wang

PeerJ, Vol 11, p e

2023 Volume 15564

Abstract: Background Premature ovarian failure (POF) is defined as the cessation of ovarian function before the age of 40 years, imposing a significant health burden on patients. However, effective etiological therapy for POF is scarce. Thus, we aimed to explore ... ...

Abstract	Background Premature ovarian failure (POF) is defined as the cessation of ovarian function before the age of 40 years, imposing a significant health burden on patients. However, effective etiological therapy for POF is scarce. Thus, we aimed to explore the protective role and targets of hydrogen-rich water (HRW) in POF. Methods Based on cyclophosphamide (CTX)-induced POF rat models, the protective role of HRW treatment was mainly determined through serum 17-β-estradiol (E2), follicle-stimulating hormone (FSH), anti-mullerian hormone (AMH) levels, ovarian histomorphological analysis, and TUNEL assay. Tandem mass tag (TMT)-based quantitative proteomic analysis was then conducted on ovarian tissues, and the targets of HRW in POF were identified integrating differential expression analysis, functional enrichment analysis, and interaction analysis. Results In HRW treatment of POF rats, the serum AMH and E2 levels significantly increased, and FSH level significantly reduced, indicating the protective role of HRW. After TMT quantitative proteomic analysis, a total of 16 candidate differentially expressed proteins (DEPs) were identified after the cross analysis of DEPs from POF vs. control and POF+HRW vs. POF groups, which were found to be significantly enriched in 296 GO terms and 36 KEGG pathways. The crucial targets, RT1-Db1 and RT1-Bb, were finally identified based on both protein-protein interaction network and GeneMANIA network. Conclusions The HRW treatment could significantly alleviate the ovarian injury of POF rats; RT1-Db1 and RT1-Bb are identified as two crucial targets of HRW treatment in POF rats.
Keywords	Hydrogen-rich water ; RT1-Db1 ; RT1-Bb ; Premature ovarian failure ; Tandem mass tag (TMT)-based quantitative proteomic analysis ; Medicine ; R ; Biology (General) ; QH301-705.5
Subject code	616
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	PeerJ Inc.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Hierarchical Refined Composite Multi-Scale Fractal Dimension and Its Application in Feature Extraction of Ship-Radiated Noise

Yuxing Li / Lili Liang / Shuai Zhang

Remote Sensing, Vol 15, Iss 3406, p

2023 Volume 3406

Abstract: The fractal dimension (FD) is a classical nonlinear dynamic index that can effectively reflect the dynamic transformation of a signal. However, FD can only reflect signal information of a single scale in the whole frequency band. To solve this problem, ... ...

Abstract	The fractal dimension (FD) is a classical nonlinear dynamic index that can effectively reflect the dynamic transformation of a signal. However, FD can only reflect signal information of a single scale in the whole frequency band. To solve this problem, we combine refined composite multi-scale processing with FD and propose the refined composite multi-scale FD (RCMFD), which can reflect the information of signals at a multi-scale. Furthermore, hierarchical RCMFD (HRCMFD) is proposed by introducing hierarchical analysis, which successfully represents the multi-scale information of signals in each sub-frequency band. Moreover, two ship-radiated noise (SRN) multi-feature extraction methods based on RCMFD and HRCMFD are proposed. The simulation results indicate that RCMFD and HRCMFD can effectively discriminate different simulated signals. The experimental results show that the proposed two-feature extraction methods are more effective for distinguishing six types of SRN than other feature-extraction methods. The HRCMFD-based multi-feature extraction method has the best performance, and the recognition rate reaches 99.7% under the combination of five features.
Keywords	fractal dimension ; refined composite multi-scale fractal dimension ; hierarchical refined composite multi-scale fractal dimension ; feature extraction ; ship-radiated noise ; Science ; Q
Subject code	518
Language	English
Publishing date	2023-07-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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