Frequency regulation reserve optimization of wind-PV-storage power station considering online regulation contribution by Changping Sun, Xiaodi Zhang, Wei Zhang, Jiahao Liu, Zubing Zou, Leying Li, Cheng Wang

“…Moreover, a station frequency regulation model was constructed, considering the field dynamic response and the coupling between the station and system frequency dynamics. …”
Get full text

In-Season Mapping of Sugarcane Planting Based on Sentinel-2 Imagery by Hui Li, Liping Di, Chen Zhang, Li Lin, Liying Guo, Ruopu Li, Haoteng Zhao

“…However, accurately remote-sensing-based mapping sugarcane remains challenging due to two reasons: 1) the scarcity of sugarcane training samples, and 2) the diverse sugarcane fields planting dates. This article proposed a novel transfer learning algorithm for accurate sugarcane planting mapping through space and temporary in the U.S. …”
Get full text

Determination of Anisotropic Mechanical Properties for Materials Processed by Laser Powder Bed Fusion by Even W. Hovig, Amin S. Azar, Frode Grytten, Knut Sørby, Erik Andreassen

“…An optimization algorithm is also proposed for determining the anisotropic elastic constants using only a few tensile test results. …”
Get full text

A Registration Method for Historical Maps Based on Self-Supervised Feature Matching by Zikang Qin, Yumin Feng, Gang Wu, Qing Dong, Tianxin Han

“…Image registration techniques in the field of computer vision can be applied to this task. …”
Get full text

SA3C-ID: a novel network intrusion detection model using feature selection and adversarial training by Wanwei Huang, Haobin Tian, Lei Wang, Sunan Wang, Kun Wang, Songze Li

“…Next, the network intrusion detection process is modeled as a Markov decision process and integrated with the Soft Actor-Critic (SAC) reinforcement learning algorithm, with a view to constructing agents; In the context of adversarial training, two agents, designated as the attacker and the defender, are defined to perform asynchronous adversarial training. …”
Get full text

Human joint motion data capture and fusion based on wearable sensors by Hua Wang

“…Abstract The field of human motion data capture and fusion has a broad range of potential applications and market opportunities. …”
Get full text

THE SELECTION OF GEOMETRIC CHARACTERISTICS FOR CIRCULAR MULTI-LAYERED PIEZOELECTRIC PLATES by O. V. Ratmanova, D. A. Shlyakhin

“…For the most efficient conversion of electrical energy into mechanical vibrations, there is a need for an in-depth analysis of the connectivity of physical fields of different nature in multilayer structures.Method. …”
Get full text

Classroom Expression Recognition Based on Deep Learning by Yang Gao, Linyan Zhou, Jialiang He

“…In the field of education, classroom expression recognition technology has important application value. …”
Get full text

Employing Fuzzy Adaptive and Event-Triggered Approaches to Achieve Formation Control of Nonholonomic Mobile Robots Under Complete State Constraints by Kai Wang, Jinnan Lu, Haodong Zhou

“…To guarantee that all system states remain within their constraint boundaries, barrier Lyapunov functions (BLFs) are meticulously constructed. Subsequently, within the framework of the backstepping control design algorithm, we propose a novel fuzzy adaptive ET formation controller. …”
Get full text

Optimizing the strategy of new media content distribution using fuzzy logic by Jianhua Qi, Jing Lin

“…Abstract In the field of new media content distribution, with the increasing complexity and personalization of user needs, traditional rule-based content recommendation systems have gradually shown their limitations. …”
Get full text

EEG analysis of speaking and quiet states during different emotional music stimuli by Xianwei Lin, Xinyue Wu, Zefeng Wang, Zhengting Cai, Zihan Zhang, Guangdong Xie, Lianxin Hu, Laurent Peyrodie

“…In the construction of EEG classification models, the classification performance of deep neural network algorithms is superior to other machine learning algorithms.…”
Get full text

Concrete Damage Identification and Localization for Structural Health Monitoring Based on Piezoelectric Sensors by Hongjie Li, Bo Di, Yu Zheng, Hongwei Ma, Xiaomiao Huang, Hekun Wu, Jize Zhang

Get full text

An Analysis of the Design and Kinematic Characteristics of an Octopedic Land–Air Bionic Robot by Jianwei Zhao, Jiaping Gao, Mingsong Bao, Hao Zhai, Xu Pei, Zheng Jiang

“…The effectiveness of the design and control strategy is verified through the construction of an experimental platform and field tests, significantly improving the robot’s adaptability and mobility in complex terrain. …”
Get full text

High resolution building facade dataset for facade elements parsingMendeley Data by Shuchang Xu, Fan Wu, Junjie Cheng, Wenzhen Yang

“…This dataset provides an valuable benchmark for facade parsing algorithms, contributing to the advancement of research and development in this field.…”
Get full text

Airfoil Optimization Design of Vertical-Axis Wind Turbine Based on Kriging Surrogate Model and MIGA by Quan Wang, Zhaogang Zhang

“…In response to this challenge, this study constructed a collaborative optimization framework based on the Kriging surrogate model and the multi-island genetic algorithm (MIGA). …”
Get full text

Large-scale S-box design and analysis of SPS structure by Lan ZHANG, Liangsheng HE, Bin YU

“…A class of optimal linear transformation P over a finite field<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> <msup> <mrow> <mrow><mo>(</mo> <mrow> <msubsup> <mi>F</mi> <mn>2</mn> <mi>m</mi> </msubsup> </mrow> <mo>)</mo></mrow></mrow> <mn>4</mn> </msup> </mrow></math></inline-formula> was constructed based on cyclic shift and XOR operation.Using the idea of inverse proof of input-output relation of linear transformation for reference, a proof method was put forward that transformed the objective problem of optimal linear transformation into several theorems of progressive relation, which not only solved the proof of that kind of optimal linear transformation, but also was suitable for the proof of any linear transformation.By means of small-scale S-box and optimal cyclic shift-XOR linear transformation P, a large-scale S-box model with 2-round SPS structure was established, and a series of lightweight large-scale S-boxes with good cryptographic properties were designed.Only three kind of basic operations such as look-up table, cyclic shift and XOR were used in the proposed design scheme, which improved the linearity and difference uniformity of large-scale S-boxes.Theoretical proof and case analysis show that, compared with the existing large-scale S-box construction methods, the proposed large-scale S-box design scheme has lower computational cost and better cryptographic properties such as difference and linearity, which is suitable for the design of nonlinear permutation coding of lightweight cryptographic algorithms.…”
Get full text

Gradient pooling distillation network for lightweight single image super-resolution reconstruction by Zhiyong Hong, GuanJie Liang, Liping Xiong

“…Thus, there is a pressing demand to devise efficient super-resolution algorithms. To address this issue, we propose a gradient pooling distillation network (GPDN), which can enable the efficient construction of a single image super-resolution system. …”
Get full text

Deep learning-based strategies for evaluating and enhancing university teaching quality by Ying Gao

“…By integrating deep learning algorithms, the study seeks to improve the objectivity and accuracy of evaluations, facilitate personalized feedback, and foster innovation in teaching methodologies. …”
Get full text

Picture Fuzzy Concept Lattice Models for Knowledge Structure Analysis by Chen Zhang, Zengtai Gong

“…The relationship between formal contexts and picture fuzzy skill mappings is discussed, and two models, namely the knowledge space picture fuzzy concept lattice and the closure space picture fuzzy concept lattice, are constructed. Based on skill atomic granules and problem atomic granules, corresponding concept construction algorithms are developed respectively, and the relationships between different fuzzy concept lattices are deeply explored. …”
Get full text

WaveAttention-ResNet: a deep learning-based intelligent diagnostic model for the auxiliary diagnosis of multiple retinal diseases by Biao Guo, Daqing Wang, Ruiqi Zhang, Jia Hou, Wenchao Liu, YongFei Wu, Xudong Yang, Lijuan Zhang, Lijuan Zhang

“…ObjectiveThis study constructs a deep learning-based combined algorithm named WaveAttention ResNet (WARN) to investigate the classification accuracy for seven common retinal diseases and the feasibility of AI-assisted diagnosis in this field.MethodsFirst, a deep learning-based classification network is constructed. …”
Get full text