The e-mail network is a type of social network. This study analyzes user behavior in e-mail subject participation in organizations by using social network analysis. First, the Enron dataset and the position-related in...The e-mail network is a type of social network. This study analyzes user behavior in e-mail subject participation in organizations by using social network analysis. First, the Enron dataset and the position-related information of an employee are introduced, and methods for deletion of false data are presented. Next, the three-layer model(User, Subject, Keyword) is proposed for analysis of user behavior. Then, the proposed keyword selection algorithm based on a greedy approach, and the influence and propagation of an e-mail subject are defined. Finally, the e-mail user behavior is analyzed for the Enron organization. This study has considerable significance in subject recommendation and character recognition.展开更多
带钢的表面缺陷对带钢的质量影响极大。针对由于带钢缺陷存在类间相似且容易受背景干扰,导致检测模型的精度较差的问题,提出了一种基于YOLOv8n的轻量级实时检测模型EDD-YOLO(EnhanceDefectsDe-tectionYOLO)。首先,构造了一个特殊卷积ECC...带钢的表面缺陷对带钢的质量影响极大。针对由于带钢缺陷存在类间相似且容易受背景干扰,导致检测模型的精度较差的问题,提出了一种基于YOLOv8n的轻量级实时检测模型EDD-YOLO(EnhanceDefectsDe-tectionYOLO)。首先,构造了一个特殊卷积ECConv(EnhanceCoordConv),其使用额外的坐标通道更加清晰地感受待检测目标的空间位置信息;其次,将轻量级注意力机制EMA(EfficientMulti-ScaleAttention)嵌入特征融合网络中,使得计算资源高效且合理分配,增强特征融合能力;然后,采用CARAFE(Content-AwareReAssembly of Features Extraction)替代原融合网络的上采样模块;最后,在预测部分使用WIOU改进原损失函数,加速模型收敛。实验数据表明,该模型相较于YOLOv8n,检测精度提高3.6%,检测速度保持在166fps,并且模型大小、空间复杂度与原模型基本持平,更好地满足了复杂工业场景下带钢缺陷的实时检测要求。展开更多
基金sponsored by the National Natural Science Foundation of China under grant number No.61100008,61201084the China Postdoctoral Science Foundation under Grant No.2013M541346+3 种基金Heilongiiang Postdoctoral Special Fund(Postdoctoral Youth Talent Program)under Grant No.LBH-TZ0504Heilongjiang Postdoctoral Fund under Grant No.LBH-Z13058the Natural Science Foundation of Heilongjiang Province of China under Grant No.QC2015076The Fundamental Research Funds for the Central Universities of China under grant number HEUCF100602
文摘The e-mail network is a type of social network. This study analyzes user behavior in e-mail subject participation in organizations by using social network analysis. First, the Enron dataset and the position-related information of an employee are introduced, and methods for deletion of false data are presented. Next, the three-layer model(User, Subject, Keyword) is proposed for analysis of user behavior. Then, the proposed keyword selection algorithm based on a greedy approach, and the influence and propagation of an e-mail subject are defined. Finally, the e-mail user behavior is analyzed for the Enron organization. This study has considerable significance in subject recommendation and character recognition.
文摘带钢的表面缺陷对带钢的质量影响极大。针对由于带钢缺陷存在类间相似且容易受背景干扰,导致检测模型的精度较差的问题,提出了一种基于YOLOv8n的轻量级实时检测模型EDD-YOLO(EnhanceDefectsDe-tectionYOLO)。首先,构造了一个特殊卷积ECConv(EnhanceCoordConv),其使用额外的坐标通道更加清晰地感受待检测目标的空间位置信息;其次,将轻量级注意力机制EMA(EfficientMulti-ScaleAttention)嵌入特征融合网络中,使得计算资源高效且合理分配,增强特征融合能力;然后,采用CARAFE(Content-AwareReAssembly of Features Extraction)替代原融合网络的上采样模块;最后,在预测部分使用WIOU改进原损失函数,加速模型收敛。实验数据表明,该模型相较于YOLOv8n,检测精度提高3.6%,检测速度保持在166fps,并且模型大小、空间复杂度与原模型基本持平,更好地满足了复杂工业场景下带钢缺陷的实时检测要求。
