bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transferring a deep learning model from healthy subjects to stroke patients in a motor imagery brain–computer interface
Authors: Nagarajan Aarthy , Robinson Neethu , Ang Kai Keng , Chua Karen Sui Geok , Chew Effie , Guan Cuntai 
Published: December 2023

Abstract

Objective. Motor imagery (MI) brain–computer interfaces (BCIs) based on electroencephalogram (EEG) have been developed primarily for stroke rehabilitation, however, due to limited stroke data, current deep learning methods for cross-subject classification rely on healthy data. This study aims to assess the feasibility of applying MI-BCI models pre-trained using data from healthy individuals to detect MI in stroke patients. Approach. We introduce a new transfer learning approach where features from two-class MI data of healthy individuals are used to detect MI in stroke patients. We compare the results of the proposed method with those obtained from analyses within stroke data. Experiments were conducted using Deep ConvNet and state-of-the-art subject-specific machine learning MI classifiers, evaluated on OpenBMI two-class MI-EEG data from healthy subjects and two-class MI versus rest data from stroke patients. Main results. Results of our study indicate that through domain adaptation of a model pre-trained using healthy subjects’ data, an average MI detection accuracy of 71.15% (

±
12.46
%

) can be achieved across 71 stroke patients. We demonstrate that the accuracy of the pre-trained model increased by 18.15% after transfer learning (p

<

0.001). Additionally, the proposed transfer learning method outperforms the subject-specific results achieved by Deep ConvNet and FBCSP, with significant enhancements of 7.64% (p

<

0.001) and 5.55% (p

<

0.001) in performance, respectively. Notably, the healthy-to-stroke transfer learning approach achieved similar performance to stroke-to-stroke transfer learning, with no significant difference (p

>

0.05). Explainable AI analyses using transfer models determined channel relevance patterns that indicate contributions from the bilateral motor, frontal, and parietal regions of the cortex towards MI detection in stroke patients. Significance. Transfer learning from healthy to stroke can enhance the clinical use of BCI algorithms by overcoming the challenge of insufficient clinical data for optimal training.
Total Transfer Capacity Evaluation of HVDC Tie-Lines Considering Frequency Security Constraints
Authors: Cheng Yuming , Tian Chunzheng , Wu Sijia , Shao Hongbo , Chen Shuyu , Zhang Kainan 
Published: December 2023

Abstract
The high proportion of renewable energy access and the construction of HVDC transmission projects have led to a continuous decrease in the penetration rate of asynchronous power sources in the power system. Maintaining frequency stability and safe operation of the power system is a key issue that needs to be urgently addressed in the power grid. This article takes into account the participation of multiple types of power resources in inertia support and frequency modulation response and it also constructs an evaluation model for the total HVDC transfer capacity of the power grid. In response to the uncertainty of wind power and load power, scenario reduction methods are adopted to enhance the HVDC total transfer capacity of the power grid under frequency safety and stability constraints by the daily output of each power source. The simulation results indicate that the scheduling scheme evaluated by the proposed model has a higher frequency security level compared to traditional models.
False Data Injection Attack Against the Optimal Energy Management of Active Distribution Networks: A Bilevel Programming Model
Authors: Tang Xu , Wang Jing , Ran Xiaohong , Liu Kaipei , Qin Liang 
Published: December 2023

Abstract
With the wide integration of advanced measurement equipment and communication networks into active distribution networks (ADNs), the ADN cyber-physical system (CPS) is facing the risk of false data injection attacks (FDIAs). This paper proposes a bilevel attack model to obtain optimal false data, which maximizes power losses, photovoltaic (PV) curtailment, and load shedding while ensuring the concealment of the attack. Different from the FDIA for the transmission networks, the FDIA targeting ADNs not only injects false data into load demand but also further injects false data into PV output, achieving an attack through the cooperation of the two types of false data injection. Moreover, differing from a single-level attack model, the proposed bilevel model takes the optimal energy management model executed by the ADN system operators as the lower-level model, using a master-slave game to obtain the optimal false data that considers operator responses, making it more in line with practical engineering. Using the Karush-Kuhn-Tucker (KKT) conditions, the bilevel model is transformed into a single-level model for ease of solution. Simulation results based on the IEEE 33-bus test case confirm the effectiveness of the proposed model and reveal the risk of the ADN under FDIA.
Research on power sharing optimization strategy based on hybrid multi-microgrid
Authors: Huang Leiyu , Abuduwayiti Xiwang , Chao Qin , Zheng Zijie , Guo Chengkang 
Published: December 2023

Abstract
To alleviate the increasing distributed energy penetration problem in the distribution network under the “double carbon”, a P2P multi-microgrid power sharing and trading method based on the alternating direction method of multipliers (ADMM) are proposed in the hybrid multi-microgrid. The paper constructs the optimization model of each sub-microgrid and a multi-microgrid model for P2P power sharing transactions based on the ADMM algorithm. Finally, the proposed model is simulated and verified using a multi-microgrid composed of three microgrids. The results show that the electric energy trading tariff between microgrids obtained from the model in this paper is reasonable, which can improve the utilization rate of new energy and reduce the penetration rate of distributed energy in the distribution network.
Scenario Reduction of Power Systems with Renewable Generations Using Improved Time-GAN
Authors: Huang Wenqi , Liang Lingyu , Dai Zhen , Cao Shang , Zhang Huanming , Zhao Xiangyu , Hou Jiaxuan , Li Hanju , Ma Wenhao , Che Liang 
Published: December 2023

Abstract
To investigate the uncertainties and spatiotemporal complexities of renewable energy represented by wind and photovoltaic, a scenario reduction of power systems with renewable generations uses improved time series generative adversarial networks (Time GAN). The long short-term memory neural network is used to construct the generative adversarial networks, and the time-series supervision loss function and generative adversarial loss function are introduced to jointly optimize the generator network for better generating the daily renewable energy power scenarios. Based on the results of scenario generation, the silhouette coefficient method is used to improve K-means for constructing a scenario reduction model. Finally, the case analysis shows that the proposed method can obtain typical renewable energy power scenarios with spatiotemporal correlation and provide a reference for the analysis of power system operation scenarios.
Fast Evaluation Method for Steady State Frequency of Multi-DC Interconnected Asynchronous Power Grid after DC Blocking
Authors: Wang Shenglin , Xu Sheng , He Haihuan , Chen Haiyong , Gan Qingzhong , Yang Jiahao , Zhang Junjie 
Published: December 2023

Abstract
For a multi-DC interconnected asynchronous power grid, to quickly evaluate the steady-state frequency after DC blocking, a fast evaluation method is proposed in this paper. Firstly, the power flow model was established, including the DC transmission system, each interconnected asynchronous power grid model. The steady-state operation state before DC blocking was solved. Secondly, considering the adjustment of the model after DC blocking, the steady-state frequency analysis model considering the effects of primary frequency regulation and various stability control strategies was established. Finally, a case study was used to confirm the effectiveness of the proposed method. The simulation results and analysis show that the proposed method is fast and accurate.
Adaptation to the new energy side of the configuration of energy storage optimization analysis
Authors: Sun Qiao , Li Moujun , Zhang Lin , Zhao Shilin , Yang Zhuo , Li Sicheng 
Published: December 2023

Abstract
Energy storage technology is the key to achieving a high proportion of new energy generation, but the current optimization analysis of renewable energy side configuration of energy storage technology is not comprehensive enough and does not consider different application scenarios and operating conditions. In order to better select the appropriate energy storage technology and formulate the corresponding policy, this paper takes the western region of China as an example, and uses the particle swarm algorithm to determine the optimal energy storage configuration scheme; finally, comparing with the traditional scheme, the proposed optimization scheme takes into full consideration the stochastic nature of the wind and light power and the load in the microgrid, and reduces the cost of the energy storage configuration. Also, the grid operation loss is reduced and the economy of the grid operation is improved.
Defect detection of composite materials for cable insulation layer based on terahertz
Authors: Luo Guofang , Xu Qin , Song Ping , Chen Hongtao , Wang Dong , Chen Xi 
Published: December 2023

Abstract
Hidden defects can seriously affect the insulation performance of cables and pose safety hazards. In this article, a novel Non-Destructive evaluation technique for insulation materials based on terahertz time-domain spectroscopy technology is proposed. Firstly, terahertz time-domain spectroscopy technology was used to perform reflective scanning on insulation materials. Various imaging algorithms were used to image terahertz defects. The results showed that the maximum imaging and peak to peak time imaging were effective. At the same time, bilateral filtering was used to process terahertz defect images. The results showed that bilateral filtering not only filtered out noise in terahertz images, but also retained edge details. Terahertz time-domain spectroscopy technology offers a fresh approach for detecting cable insulation material defects non-destructively, and finds application in various electrical environment inspections.
Research on Cable Insulation Layer Defect Detection Based on Terahertz Technology
Authors: Luo Guofang , Lu Qiyu , Huang Hua , Chen Hongtao , Han Jingxin , Chen Xi 
Published: December 2023

Abstract
The insulation layer of a cable plays a very important role in protecting the cable. If defects such as voids and detachment occur in the insulation layer of the cable, it can lead to a short circuit in the cable and cause a fire. In this article, a new insulation layer detection method is proposed, which uses terahertz equipment to detect defects in cables and obtain terahertz images with defects. However, some defect images are relatively blurry. Morphological algorithms are used to denoise and enhance the blurry images to obtain high-quality defect images to determine the location and size of defects. Terahertz technology has become a new method for detecting defects in cable insulation layers and is increasingly widely used.
Fault Location of Grid-connected Microgrid Lines Based on AVMD and Double-ended Traveling Wave Ranging
Authors: Fu Linyao , Li Chunhua , Wang Benke , Ban Yongshuang 
Published: December 2023

Abstract
To enhance the accuracy of fault location in microgrid lines, a fault location method based on adaptive variational mode decomposition (AVMD) and double-ended traveling wave ranging is proposed. Firstly, a microgrid radial structure model, incorporating wind, light, and water systems, is established. The parameters of variational mode decomposition are optimized by using the Aquila optimizer (AO) algorithm, allowing the original fault signal to be decomposed into multiple modal components using AVMD. Only a limited number of modal components retain the fault signal information. The effective weighted peak relevance index (EWPR) is employed to select the sensitive modal components, identified as the four modes that best preserve the fault information, for signal reconstruction. Finally, the reconstructed signal is applied for fault localization. Simulation results indicate that the proposed method is scarcely influenced by the fault type, exhibiting superior accuracy compared to the single-ended traveling wave method.
Inter-pole Cooperative Control Strategy for True Bipolar MMC-HVDC System with Offshore Wind Power
Authors: Chen Yijing , Zhong Shuwei , Zhang Yu , Li Chunhua , Zhou Fengfeng , Che Yanbo 
Published: December 2023

Abstract
For offshore wind power via a true bipolar MMC-HVDC delivery system, when both poles of the offshore converter stations adopt fixed AC voltage and fixed frequency control (referred to as fixed V/f control), the converter stations are connected to the same bus and control the same target, resulting in unstable operation of the system. Therefore, this paper proposes an inter-pole cooperative control strategy for a true bipolar MMC-HVDC system with offshore wind power. One pole of the offshore converter station adopts fixed V/f control to supply stable AC voltage to the offshore AC system, and the other pole adopts inter-pole cooperative control to achieve balanced power distribution between the two poles, thus improving the system power transmission margin and reducing power losses. Finally, a simulation project is established on the PSCAD/EMTDC to confirm the usefulness of the inter-pole cooperative control strategy.
Limit cycle of Fitzhugh–Nagumo equation
Authors: Ding Xiang 
Published: December 2023

Abstract
In the 1950s Hodgkin and Huxley created a model to describe the electrochemical transmission of neuronal signals along the cell membrane, it’s a very important model. However, in view of its complexity, this paper takes the next step to study its simplified model -- Fitzhugh–Nagumo equation. In these equations x is similar to the voltage and represents the excitability of the system, the variable y represents a combination of other forces that tend to return the system to rest. The parameter I is a stimulus parameter that leads to excitation of the system, I is like an applied current. Many studies have been made on the traveling wave solutions and solitary wave solutions of Fitzhugh–Nagumo equation under different parameters, and many people have also studied its numerical solutions. In this paper, the existence and uniqueness of periodic solutions of Fitzhugh-Nagumo equation with different parameters are studied by using geometric analysis and the results of Van der Pol equation.
A review of UWB indoor positioning
Authors: Qu Junwei 
Published: December 2023

Abstract
With the development of science and technology, more accurate and stable location information can better serve people’s lives. As people spend more time indoors, traditional positioning technologies such as Wi-Fi can no longer meet their needs due to a lack of positioning accuracy and interference resistance. UWB is an emerging positioning technology with high accuracy, robustness, and stability. This paper compares the advantages and disadvantages of UWB technology with those of Bluetooth and Wi-Fi. Common UWB geometric positioning methods such as TOA, TDOA, etc. are introduced. By introducing the latest research progress in UWB indoor positioning, an outlook on the future development of UWB indoor positioning is made. Compared with Bluetooth and other indoor positioning technologies, UWB positioning technology has the advantages of high positioning accuracy and good anti-interference. The UWB positioning system usually uses TOA, TDOA, AOA, and other positioning algorithms. In the future, UWB positioning technology will serve more and more complex positioning environments.
Research and mechanism of iron-based superconductors
Authors: Bi Cheng 
Published: December 2023

Abstract
The discovery of new iron-based superconductor LaFeAsO1-xFx with Tc of 26 K in 2008 had quickly revived interest in the exploration of iron-based superconductors. After several years of research on this superconducting material, iron-based superconductors have become another family of high-temperature superconductors after copper-based superconductors. The crystal structure of LaOFeAs is P4/nmm family, and by doping with fluorine, LaO1-xFxFeAs exhibits superconductivity because both structural distortion and magnetic order are suppressed. In this review, the development and experimental results of such iron-based high Tc materials will be presented. We describe the synthetic method of this class of superconductors, the physical properties of the precursors, the doping methods that can produce superconductivity, the pressure effect, and the prospects of this new iron-based high Tc family.
Overview of gravitational waves: Formation, polarization and detection
Authors: Zhou Jing 
Published: December 2023

Abstract
Gravitational waves (GWs) are reliable for proving general relativities. Also, they can be used in detecting physics phenomena in the universe. Motions of bodies make spacetime curved, and then gravitational waves are formed. Additionally, GWs can be produced in the early universe. A mathematical description of gravitational waves derived using linearized theory and transverse-traceless gauge shows GWs polarizations and the relationship between perturbation and strain. GW signal was first detected in the binary system PSR1913+16. Data presented an orbital decay, which followed general relativity’s prediction. Direct detections today, designed according to GWs properties, are carried out by resonant detectors, interferometers, and pulsar timing arrays. Noise reduction is a key to accurate detection. Furthermore, analyzing the B-mode cosmic microwave background can be used in detecting primordial gravitational waves.
Rainbow link beamforming technology and relevant analysis
Authors: Ding Yuheng , Zhang Xueqing 
Published: December 2023

Abstract
In the 5G era, millimeter wave has been mentioned as an important position. Millimeter wave has some problems that cannot be ignored: the free space path loss and atmospheric attenuation. To overcome these problems, millimeter wave systems rely on beamforming to overcome losses. Traditional techniques utilize phase antenna arrays for beamforming, which can cause delays in the time consumption and beam scheduling, and due to limited beams, this technology can only be connected to a limited number of devices, and each transmission occupies the entire bandwidth. This paper introduces a new technology called rainbow link, which is implemented by a new true time delay (TTD) array structure. This technology can achieve the allocation of different subcarriers to a large number of users in the corresponding beamforming direction. Users only need to select appropriate frequency resources. In this work, we calculate the performance of rainbow link with different parameters, and our results show that given 1 GHz bandwidth using 64 element antenna arrays, a rainbow-link cell achieves 1ms latency and 0.6M symbols per second with 0.03 active user rate.
Effect of Mo on microstructure and sliding wear performance of CoCrFeNiMox high entropy alloy coatings by laser cladding
Authors: Chang Qingcheng , Liu Ying , Xia Yilong , Liu Xueyou , Xie Yongxin , Hu Jinkang , Li Wei 
Published: December 2023

Abstract
The CoCrFeNiMox (x = 0, 0.5, 1, 1.5 in molar ratio) high-entropy alloys (HEAs) coating were prepared on AISI1045 steel by laser cladding. The microstructure, hardness and tribological properties were investigated through x-ray diffraction, scanning electron microscopy (SEM), microhardness tester and reciprocating tribometer. The result shows that the coating is metallurgically bonded to the substrate and exhibits columnar and equiaxed grains microstructure consisted of main face-centered cubic (FCC) solid solution and few body-centered cubic (BCC) struture when x≤ 1.0. The (Fe, Cr, Mo)-riched σ phase shows up in the CoCrFeNiMo1.5 FCC matrix due to excess Mo addition. CoCrFeNiMox HEA coatings shows an obvious increase of surface hardness from 261 HV0.2 to 793 HV0.2 by increasing the Mo content to 1.5 in the molar ratio, and exhibited the most excellent wear resistance among all the compositions designed in this work. The wear resistance of the CoCrFeNiMo1.5 alloy coating is about 2.2 times higher than that of the coating without Mo. The wear mechanism changes with increasing Mo content, though abrasive wear is a common mechanism, more adhesive wear occurred at low Mo content but few oxidation and fatigue wear occured at high Mo content.
New insight into the relationship between the C-Cr ratio and carbides, mechanical property of cold working die steel
Authors: Hongxiao Chi , Yingnan Di , Nan Zhang , Jinbo Gu , Jian Zhou , Dangshen Ma 
Published: December 2023

Abstract
An new insight into the relationship between the C-Cr Ratio and carbides, mechanical property Cr Alloyed of cold working die Steel were investigated by optical microscopy (OM), scanning electron microscopy (SEM), energy dispersive spectrometer (EDS), rockwell hardness and impact toughness tests. The ‘C-Cr ratio’ and ‘Cr equivalent E
Cr ‘ parameters were introduced to characterize the carbide characteristics and mechanical properties. The results show that the precipitation temperature of M7C3 eutectic carbides grows linearly with E
Cr when the E
Cr value is less than about 22, and the precipitation temperature increases significantly when the E
Cr value exceeds 22, and the growth curve takes a plateau turn. The precipitation temperature of MC carbides decreases approximately linearly with E
Cr value, and the precipitation of MC eutectic carbides will be completely suppressed when the E
Cr value exceeds 19. The content of eutectic carbides in the as-cast organization is more, the shape is more complex and the size is larger. The ratio of Cr and Fe content in the composition of M7C3 eutectic carbides is linearly related to the Cr-C ratio; the content of carbides in the steel after forging and the E
Cr value are basically linear. The average particle size and the average length of longitudinal carbides after forging are basically proportional to the E
Cr value. The average particle size of longitudinal carbides after forging is greater than 4 μm and the E
Cr value are basically linear; when the Cr content is greater than 4%, the quenching peak hardness of steel and the C/Cr have a good linear relationship; as the E
Cr value gradually increases, the impact toughness of steel gradually decreases. These results are important not only for understanding the strengthening mechanisms of die steel, but also for the composition design and carbide control of cold working die steel.