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Article: 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.

Zhang, Shuai

2023 Volume 9, Issue 3, Page(s) e14286

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
Language	English
Publishing date	2023-03-14
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2023.e14286
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: An Intelligent and Fast Dance Action Recognition Model Using Two-Dimensional Convolution Network Method.

Zhang, Shuai

publication RETRACTED

Journal of environmental and public health

2022 Volume 2022, Page(s) 4713643

Abstract: In the field of computer vision, action recognition is a very difficult topic to study. This paper suggests a dance movement recognition method based on DL network in accordance with the characteristics of dance movements. The backbone network in this ... ...

Abstract	In the field of computer vision, action recognition is a very difficult topic to study. This paper suggests a dance movement recognition method based on DL network in accordance with the characteristics of dance movements. The backbone network in this study is a thin network called Mobile Net. The two-dimensional convolution network, which can only extract spatial features, can extract and fuse time domain features and use them for dance movement recognition by combining the time domain modelling strategy of time domain feature transfer between convolution layers. It uses fewer network parameters and less computation than the original multitarget detection model. Using the clustering method to preset the prior frames of human detection with various sizes and numbers also enhances the model's performance. Finally, the experimental findings demonstrate that the algorithm suggested in this paper outperforms the Incision v3 algorithm in F1 by 9.87 percent and outperforms the traditional CNN algorithm in identification accuracy by 6.51 percent and 10.76 percent, respectively. It is evident that the algorithm used in this paper reduces running time and, to a certain extent, improves the accuracy of dance movement recognition. For related research, it offers some references.
MeSH term(s)	Algorithms ; Dancing ; Humans
Language	English
Publishing date	2022-07-09
Publishing country	United States
Document type	Journal Article ; Retracted Publication
ZDB-ID	2526611-1
ISSN	1687-9813 ; 1687-9813
ISSN (online)	1687-9813
ISSN	1687-9813
DOI	10.1155/2022/4713643
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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

Zhang, Shuai

Heliyon. 2023 Mar., v. 9, no. 3 p.e14286-

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 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	control methods ; electric potential difference ; electricity ; Sudden-change law of frequency difference ; Out-of-step oscillation ; Distance protection unlocking
Language	English
Dates of publication	2023-03
Publishing place	Elsevier Ltd
Document type	Article ; Online
Note	Use and reproduction
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2023.e14286
Database	NAL-Catalogue (AGRICOLA)

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Book ; Online: Non-Convex Optimizations for Machine Learning with Theoretical Guarantee

Zhang, Shuai

Robust Matrix Completion and Neural Network Learning

2023

Abstract: Despite the recent development in machine learning, most learning systems are still under the concept of "black box", where the performance cannot be understood and derived. With the rise of safety and privacy concerns in public, designing an explainable ...

Abstract	Despite the recent development in machine learning, most learning systems are still under the concept of "black box", where the performance cannot be understood and derived. With the rise of safety and privacy concerns in public, designing an explainable learning system has become a new trend in machine learning. In general, many machine learning problems are formulated as minimizing (or maximizing) some loss function. Since real data are most likely generated from non-linear models, the loss function is non-convex in general. Unlike the convex optimization problem, gradient descent algorithms will be trapped in spurious local minima in solving non-convex optimization. Therefore, it is challenging to provide explainable algorithms when studying non-convex optimization problems. In this thesis, two popular non-convex problems are studied: (1) low-rank matrix completion and (2) neural network learning. Comment: PhD thesis
Keywords	Computer Science - Machine Learning ; Electrical Engineering and Systems Science - Signal Processing
Subject code	006
Publishing date	2023-06-28
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Multi-objective semantic segmentation based on PSPnet with attention mechanisms

ZHANG Shuai / YANG Chunxia

Journal of Shanghai Normal University (Natural Sciences), Vol 52, Iss 2, Pp 170-

2023 Volume 175

Abstract: A pyramid scene parsing network (PSPNet) with MobileNetV2 as enhanced feature extraction network was adopted to achieve semantic segmentation of images in complex scenes. Compared with the deep residual network ResNet50 and MobileNetV1, linear ... ...

Abstract	A pyramid scene parsing network (PSPNet) with MobileNetV2 as enhanced feature extraction network was adopted to achieve semantic segmentation of images in complex scenes. Compared with the deep residual network ResNet50 and MobileNetV1, linear bottlenecks and inverted residuals were introduced and the pyramid pooling module (PPM) was used to process the image feature information of different layers and to feature stitching, which could avoid missing key feature information between sub-regions under different segmentation sizes effectively. On this basis, the attention mechanism module was introduced to further improve the segmentation accuracy by combining the channel attention mechanism(CAM) with the spatial attention mechanism(SAM). The experimental results verified that the method could achieve the expected goals, improve the accuracy of image recognition and reduce the training time.
Keywords	semantic segmentation ; pyramid pooling module (ppm) ; attention mechanisms ; feature integration ; Science (General) ; Q1-390
Subject code	004
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	Academic Journals Center of Shanghai Normal University
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Spatiotemporal Change of Heat Stress and Its Impacts on Rice Growth in the Middle and Lower Reaches of the Yangtze River

Zhang, Shuai

Agriculture (Basel). 2022 July 26, v. 12, no. 8

2022

Abstract: Heat stress will restrict rice yield in the middle and lower reaches of the Yangtze River. An understanding of the meteorological conditions of heat stress of rice production is important for improving the accuracy of the phenology simulation. Based on ... ...

Abstract	Heat stress will restrict rice yield in the middle and lower reaches of the Yangtze River. An understanding of the meteorological conditions of heat stress of rice production is important for improving the accuracy of the phenology simulation. Based on the observations of phenology and heat stress of rice agrometeorological stations in this region, as well as meteorological observations and future scenarios, this study analyzed the spatiotemporal change of heat stress and its impacts on rice growth in this region from 1990 to 2009. The results showed that the heat stress frequency of early rice increased in this region from 2000 to 2009, and that of late rice and single-season rice decreased. Moreover, rice phenology will advance under heat stress conditions. The spatiotemporal consistency of the observations and the meteorological index of heat stress shows that the change in heat stress is attributed to climate changes and extreme meteorological events. Under future climate scenarios, it is found that the frequency of heat stress will increase, which will have a serious impact on rice production. The results suggest that positive and effective measures should be taken to adapt to climate change for rice production.
Keywords	agriculture ; climate ; climate change ; heat stress ; phenology ; rice ; Yangtze River
Language	English
Dates of publication	2022-0726
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2651678-0
ISSN	2077-0472
ISSN	2077-0472
DOI	10.3390/agriculture12081097
Database	NAL-Catalogue (AGRICOLA)

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Article: LcmUNet: A Lightweight Network Combining CNN and MLP for Real-Time Medical Image Segmentation.

Zhang, Shuai / Niu, Yanmin

Bioengineering (Basel, Switzerland)

2023 Volume 10, Issue 6

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.
Language	English
Publishing date	2023-06-12
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2746191-9
ISSN	2306-5354
ISSN	2306-5354
DOI	10.3390/bioengineering10060712
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Article ; Online: Adaptive Constraint Penalty-Based Multiobjective Operation Optimization of an Industrial Dynamic System With Complex Multiconstraint.

Zhou, Ping / Zhang, Shuai / Chai, Tianyou

IEEE transactions on cybernetics

2024 Volume PP

Abstract: Aiming at the operation optimization of the wastewater treatment process (WWTP) with nonstationary time-varying dynamics and complex multiconstraint, this article proposes a novel adaptive constraint penalty decomposed multiobjective evolutionary ... ...

Abstract	Aiming at the operation optimization of the wastewater treatment process (WWTP) with nonstationary time-varying dynamics and complex multiconstraint, this article proposes a novel adaptive constraint penalty decomposed multiobjective evolutionary algorithm with synthetical distance (SD)-based cross-generation crossover. First, the concept of spatial SD is presented to comprehensively evaluate the similarity of individual solutions from two aspects of distance and angle, and the individual information between two adjacent generations is used to enhance the diversity of individuals and accelerate the convergence of the algorithm. Second, aiming at the complex multiconstraint during the operation optimization of WWTP, an adaptive penalty algorithm is further adopted to punish the individual solutions that violate the constraints, so as to improve the handling efficiency and success rate of constraints. Furthermore, in view of the time-varying dynamics of actual WWTP, a recursive bilinear subspace identification method based on sliding window is adopted to establish the optimization models as well as the constraint models with self-learning parameter, which provides accurate model guarantee for high-performance multiobjective operation optimization. Finally, the effectiveness, superiority, and practicability of the proposed method are verified through test function experiments as well as operation optimization control experiments of WWTP.
Language	English
Publishing date	2024-01-10
Publishing country	United States
Document type	Journal Article
ISSN	2168-2275
ISSN (online)	2168-2275
DOI	10.1109/TCYB.2023.3341982
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Article ; Online: Moving morphable component (MMC) topology optimization with different void structure scaling factors.

Li, Zhao / Xu, Hongyu / Zhang, Shuai

PloS one

2024 Volume 19, Issue 1, Page(s) e0296337

Abstract: The explicit topology optimization method based on moving morphable component (MMC) has attracted more and more attention, and components are the basic building blocks of the implementation of MMC method. In the present work, a MMC topology optimization ... ...

Abstract	The explicit topology optimization method based on moving morphable component (MMC) has attracted more and more attention, and components are the basic building blocks of the implementation of MMC method. In the present work, a MMC topology optimization method based on component with void structure is followed with interest. On the basis of analyzing the characteristics of components used by MMC method, the topology description function for component with void structure is presented, where a quantitative scaling factor is introduced without increasing the number of design variables. Taking the minimum flexibility as the optimization objective, an example of short beam is analyzed with different void structure scaling factors. The results show that different scaling factors have a greater impact on the final topology optimization structure, and an ideal topology structure can be obtained with an appropriate scaling factor. Finally, some problems in the optimization process are analyzed and indicate that appropriate mesh density should be chose for component with void structure in order to achieve good optimization results.
Language	English
Publishing date	2024-01-02
Publishing country	United States
Document type	Journal Article
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0296337
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Article ; Online: Excited State Regulated Emission in Hybrid Indium Halides via Crystal Structure Switch.

Lin, Fangping / Zhang, Shuai / Zou, Bingsuo / Zeng, Ruosheng

Inorganic chemistry

2024 Volume 63, Issue 9, Page(s) 4355–4363

Abstract: Organic-inorganic metal halides have become one of the most promising materials in the next generation of optoelectronic applications due to their high charge carrier mobility and tunable band gaps. In this study, Sb: ... ...

Abstract	Organic-inorganic metal halides have become one of the most promising materials in the next generation of optoelectronic applications due to their high charge carrier mobility and tunable band gaps. In this study, Sb:PA
Language	English
Publishing date	2024-02-21
Publishing country	United States
Document type	Journal Article
ZDB-ID	1484438-2
ISSN	1520-510X ; 0020-1669
ISSN (online)	1520-510X
ISSN	0020-1669
DOI	10.1021/acs.inorgchem.3c04630
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