This study focuses on tool condition recognition through data-driven approaches to enhance the intelligence level of computerized numerical control(CNC)machining processes and improve tool utilization efficiency.Tradi...This study focuses on tool condition recognition through data-driven approaches to enhance the intelligence level of computerized numerical control(CNC)machining processes and improve tool utilization efficiency.Traditional tool monitoring methods that rely on empirical knowledge or limited mathematical models struggle to adapt to complex and dynamic machining environments.To address this,we implement real-time tool condition recognition by introducing deep learning technology.Aiming to the insufficient recognition accuracy,we propose a pyramid pooling-based vision Transformer network(P2ViT-Net)method for tool condition recognition.Using images as input effectively mitigates the issue of low-dimensional signal features.We enhance the vision Transformer(ViT)framework for image classification by developing the P2ViT model and adapt it to tool condition recognition.Experimental results demonstrate that our improved P2ViT model achieves 94.4%recognition accuracy,showing a 10%improvement over conventional ViT and outperforming all comparative convolutional neural network models.展开更多
The aim of this paper is to study an extended modified Korteweg-de Vries-Calogero-Bogoyavlenskii-Schiff(mKdV-CBS)equation and present its Lax pair with a spectral parameter.Meanwhile,a Miura transformation is explored...The aim of this paper is to study an extended modified Korteweg-de Vries-Calogero-Bogoyavlenskii-Schiff(mKdV-CBS)equation and present its Lax pair with a spectral parameter.Meanwhile,a Miura transformation is explored,which reveals the relationship between solutions of the extended mKdV-CBS equation and the extended(2+1)-dimensional Korteweg-de Vries(KdV)equation.On the basis of the obtained Lax pair and the existing research results,the Darboux transformation is derived,which plays a crucial role in presenting soliton solutions.In addition,soliton molecules are given by the velocity resonance mechanism.展开更多
Objective:This study primarily focuses on analyzing the inductive effects of emotional disturbances on the malignant transformation process of mammary gland epithelial cells.Methods:A total of 42 patients with maligna...Objective:This study primarily focuses on analyzing the inductive effects of emotional disturbances on the malignant transformation process of mammary gland epithelial cells.Methods:A total of 42 patients with malignant transformation of mammary gland epithelial cells(breast cancer,observation group)and 42 patients without malignant transformation of mammary gland epithelial cells(non-breast tumors,control group)were selected as research subjects.The earliest consultation time was January 2022,and the latest was January 2024.The extent of psychological stress impact on these patients was compared.Results:Compared with the control group,the observation group experienced a higher frequency and intensity(LEU value)of adverse life events,with P<0.05.The intensity of adverse life events in the observation group,except for mild events,was significantly higher than that in the control group(P<0.05).In terms of the content distribution of adverse life events,the proportion of marital and family problems in the observation group was significantly higher than that in the control group(P<0.05).The negative coping score and positive coping score in the observation group were significantly different from those in the control group(P<0.05).Regarding social support,the objective support score in the observation group was higher than that in the control group(P<0.05).Conclusion:During the malignant transformation process of mammary gland epithelial cells,long-term emotional disturbances have a significant impact,indicating a close relationship between psychological stress and the occurrence of breast cancer.展开更多
虚拟同步发电机固态变压器(Virtual Synchronous Generator-Solid State Transformer,VSG-SST)具有高低压交直流端口,可有效改善电网电压/频率调节能力,提高分布式电源的接入适应性。然而低压配电网电压暂降易导致VSG-SST输出级并网电...虚拟同步发电机固态变压器(Virtual Synchronous Generator-Solid State Transformer,VSG-SST)具有高低压交直流端口,可有效改善电网电压/频率调节能力,提高分布式电源的接入适应性。然而低压配电网电压暂降易导致VSG-SST输出级并网电流超限及不对称,且故障过程中难以提供无功支撑,不具备低电压穿越能力。针对上述问题,文中提出改进VSG控制策略。通过分析传统低电压穿越控制与VSG控制存在的问题,设计VSG电流平衡控制模式来消除电压不对称暂降下产生的负序分量。结合低电压穿越数学模型设计了适用于VSG的低电压穿越控制模式。通过计算有功/无功电流和功率参考值保持输出信号与跟踪量一致,实现两种控制模式间的切换。仿真实验验证了所提控制策略可保障SST在不同电压暂降下完成穿越。展开更多
针对现有深度学习算法在壁画修复时,存在全局语义一致性约束不足及局部特征提取不充分,导致修复后的壁画易出现边界效应和细节模糊等问题,提出一种双向自回归Transformer与快速傅里叶卷积增强的壁画修复方法.首先,设计基于Transformer...针对现有深度学习算法在壁画修复时,存在全局语义一致性约束不足及局部特征提取不充分,导致修复后的壁画易出现边界效应和细节模糊等问题,提出一种双向自回归Transformer与快速傅里叶卷积增强的壁画修复方法.首先,设计基于Transformer结构的全局语义特征修复模块,利用双向自回归机制与掩码语言模型(masked language modeling,MLM),提出改进的多头注意力全局语义壁画修复模块,提高对全局语义特征的修复能力.然后,构建了由门控卷积和残差模块组成的全局语义增强模块,增强全局语义特征一致性约束.最后,设计局部细节修复模块,采用大核注意力机制(large kernel attention,LKA)与快速傅里叶卷积提高细节特征的捕获能力,同时减少局部细节信息的丢失,提升修复壁画局部和整体特征的一致性.通过对敦煌壁画数字化修复实验,结果表明,所提算法修复性能更优,客观评价指标均优于比较算法.展开更多
基金supported by China Postdoctoral Science Foundation(No.2024M754122)the Postdoctoral Fellowship Programof CPSF(No.GZB20240972)+3 种基金the Jiangsu Funding Program for Excellent Postdoctoral Talent(No.2024ZB194)Natural Science Foundation of Jiangsu Province(No.BK20241389)Basic Science ResearchFund of China(No.JCKY2023203C026)2024 Jiangsu Province Talent Programme Qinglan Project.
文摘This study focuses on tool condition recognition through data-driven approaches to enhance the intelligence level of computerized numerical control(CNC)machining processes and improve tool utilization efficiency.Traditional tool monitoring methods that rely on empirical knowledge or limited mathematical models struggle to adapt to complex and dynamic machining environments.To address this,we implement real-time tool condition recognition by introducing deep learning technology.Aiming to the insufficient recognition accuracy,we propose a pyramid pooling-based vision Transformer network(P2ViT-Net)method for tool condition recognition.Using images as input effectively mitigates the issue of low-dimensional signal features.We enhance the vision Transformer(ViT)framework for image classification by developing the P2ViT model and adapt it to tool condition recognition.Experimental results demonstrate that our improved P2ViT model achieves 94.4%recognition accuracy,showing a 10%improvement over conventional ViT and outperforming all comparative convolutional neural network models.
基金supported by the National Natural Science Foundation of China(Grant No.12271488)。
文摘The aim of this paper is to study an extended modified Korteweg-de Vries-Calogero-Bogoyavlenskii-Schiff(mKdV-CBS)equation and present its Lax pair with a spectral parameter.Meanwhile,a Miura transformation is explored,which reveals the relationship between solutions of the extended mKdV-CBS equation and the extended(2+1)-dimensional Korteweg-de Vries(KdV)equation.On the basis of the obtained Lax pair and the existing research results,the Darboux transformation is derived,which plays a crucial role in presenting soliton solutions.In addition,soliton molecules are given by the velocity resonance mechanism.
基金Bayan Nur Science and Technology Plan Project(Project No.:K202148)。
文摘Objective:This study primarily focuses on analyzing the inductive effects of emotional disturbances on the malignant transformation process of mammary gland epithelial cells.Methods:A total of 42 patients with malignant transformation of mammary gland epithelial cells(breast cancer,observation group)and 42 patients without malignant transformation of mammary gland epithelial cells(non-breast tumors,control group)were selected as research subjects.The earliest consultation time was January 2022,and the latest was January 2024.The extent of psychological stress impact on these patients was compared.Results:Compared with the control group,the observation group experienced a higher frequency and intensity(LEU value)of adverse life events,with P<0.05.The intensity of adverse life events in the observation group,except for mild events,was significantly higher than that in the control group(P<0.05).In terms of the content distribution of adverse life events,the proportion of marital and family problems in the observation group was significantly higher than that in the control group(P<0.05).The negative coping score and positive coping score in the observation group were significantly different from those in the control group(P<0.05).Regarding social support,the objective support score in the observation group was higher than that in the control group(P<0.05).Conclusion:During the malignant transformation process of mammary gland epithelial cells,long-term emotional disturbances have a significant impact,indicating a close relationship between psychological stress and the occurrence of breast cancer.
文摘虚拟同步发电机固态变压器(Virtual Synchronous Generator-Solid State Transformer,VSG-SST)具有高低压交直流端口,可有效改善电网电压/频率调节能力,提高分布式电源的接入适应性。然而低压配电网电压暂降易导致VSG-SST输出级并网电流超限及不对称,且故障过程中难以提供无功支撑,不具备低电压穿越能力。针对上述问题,文中提出改进VSG控制策略。通过分析传统低电压穿越控制与VSG控制存在的问题,设计VSG电流平衡控制模式来消除电压不对称暂降下产生的负序分量。结合低电压穿越数学模型设计了适用于VSG的低电压穿越控制模式。通过计算有功/无功电流和功率参考值保持输出信号与跟踪量一致,实现两种控制模式间的切换。仿真实验验证了所提控制策略可保障SST在不同电压暂降下完成穿越。
文摘针对现有深度学习算法在壁画修复时,存在全局语义一致性约束不足及局部特征提取不充分,导致修复后的壁画易出现边界效应和细节模糊等问题,提出一种双向自回归Transformer与快速傅里叶卷积增强的壁画修复方法.首先,设计基于Transformer结构的全局语义特征修复模块,利用双向自回归机制与掩码语言模型(masked language modeling,MLM),提出改进的多头注意力全局语义壁画修复模块,提高对全局语义特征的修复能力.然后,构建了由门控卷积和残差模块组成的全局语义增强模块,增强全局语义特征一致性约束.最后,设计局部细节修复模块,采用大核注意力机制(large kernel attention,LKA)与快速傅里叶卷积提高细节特征的捕获能力,同时减少局部细节信息的丢失,提升修复壁画局部和整体特征的一致性.通过对敦煌壁画数字化修复实验,结果表明,所提算法修复性能更优,客观评价指标均优于比较算法.
