The strength of cement-based materials,such as mortar,concrete and cement paste backfill(CPB),depends on its microstructures(e.g.pore structure and arrangement of particles and skeleton).Numerous studies on the relati...The strength of cement-based materials,such as mortar,concrete and cement paste backfill(CPB),depends on its microstructures(e.g.pore structure and arrangement of particles and skeleton).Numerous studies on the relationship between strength and pore structure(e.g.,pore size and its distribution)were performed,but the micro-morphology characteristics have been rarely concerned.Texture describing the surface properties of the sample is a global feature,which is an effective way to quantify the micro-morphological properties.In statistical analysis,GLCM features and Tamura texture are the most representative methods for characterizing the texture features.The mechanical strength and section image of the backfill sample prepared from three different solid concentrations of paste were obtained by uniaxial compressive strength test and scanning electron microscope,respectively.The texture features of different SEM images were calculated based on image analysis technology,and then the correlation between these parameters and the strength was analyzed.It was proved that the method is effective in the quantitative analysis on the micro-morphology characteristics of CPB.There is a significant correlation between the texture features and the unconfined compressive strength,and the prediction of strength is feasible using texture parameters of the CPB microstructure.展开更多
针对工业缺陷对比度低、周围干扰信息多导致的误检率和漏检率高的问题,提出一种基于改进YOLOv8的工业表面缺陷检测算法EML-YOLO。通过设计一种高效大卷积模块(efficient large kernel,ELK),在保留空间信息的同时提供多尺度的特征表示,...针对工业缺陷对比度低、周围干扰信息多导致的误检率和漏检率高的问题,提出一种基于改进YOLOv8的工业表面缺陷检测算法EML-YOLO。通过设计一种高效大卷积模块(efficient large kernel,ELK),在保留空间信息的同时提供多尺度的特征表示,从而提高模型的特征提取能力;提出多支路并行的特征融合模块(multi-scale context module,MCM),使得模型能够获取丰富的特征信息和全局上下文信息;在Neck模块中通过特征压缩和精简来减少模型的参数量和计算量,让模型更适用于资源有限的工业场景。采用GC10-DET和DeepPCB两个工业表面缺陷数据集来验证改进的EML-YOLO算法的有效性。实验结果表明,在GC10-DET数据集和DeepPCB数据集上,检测准确率上分别提高了4.3个百分点和2.9个百分点,参数量仅2.7×10^(6)。所提算法可以较好地应用于工业缺陷检测场景。展开更多
随着信息技术的发展,用户和组织对网络安全的关注度不断提高,数据加密传输逐渐成为主流,推动互联网中加密流量的比例不断攀升。然而,数据加密在保障隐私和安全的同时也成为非法内容逃避网络监管的手段。为实现加密流量的检测与分析,需...随着信息技术的发展,用户和组织对网络安全的关注度不断提高,数据加密传输逐渐成为主流,推动互联网中加密流量的比例不断攀升。然而,数据加密在保障隐私和安全的同时也成为非法内容逃避网络监管的手段。为实现加密流量的检测与分析,需要高效地识别出加密流量。但是,压缩流量的存在会严重干扰对加密流量的识别。针对上述问题,设计了基于滑动窗口和随机性特征的加密流量识别方案,以高效且准确地识别加密流量。具体来说,所提方案根据滑动窗口机制对会话中数据传输报文的有效载荷进行采样,获取能够反映原始流量信息模式的数据块序列,针对每个数据块使用随机性测度算法进行样本特征提取,为原始载荷构建随机性特征。此外,通过设计基于CART(classification and reqression tree)算法的决策树模型,在提高加密和压缩流量识别的准确率的同时,极大降低了针对加密流量识别的漏报率。基于对多个权威网站数据的随机抽样,构建均衡的数据集,并通过实验证明了所提方案的可行性和高效性。展开更多
基金Project(51722401)supported by the National Natural Science Foundation for Excellent Young Scholars of ChinaProject(FRF-TP-18-003C1)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(51734001)supported by the Key Program of National Natural Science Foundation of China
文摘The strength of cement-based materials,such as mortar,concrete and cement paste backfill(CPB),depends on its microstructures(e.g.pore structure and arrangement of particles and skeleton).Numerous studies on the relationship between strength and pore structure(e.g.,pore size and its distribution)were performed,but the micro-morphology characteristics have been rarely concerned.Texture describing the surface properties of the sample is a global feature,which is an effective way to quantify the micro-morphological properties.In statistical analysis,GLCM features and Tamura texture are the most representative methods for characterizing the texture features.The mechanical strength and section image of the backfill sample prepared from three different solid concentrations of paste were obtained by uniaxial compressive strength test and scanning electron microscope,respectively.The texture features of different SEM images were calculated based on image analysis technology,and then the correlation between these parameters and the strength was analyzed.It was proved that the method is effective in the quantitative analysis on the micro-morphology characteristics of CPB.There is a significant correlation between the texture features and the unconfined compressive strength,and the prediction of strength is feasible using texture parameters of the CPB microstructure.
文摘针对工业缺陷对比度低、周围干扰信息多导致的误检率和漏检率高的问题,提出一种基于改进YOLOv8的工业表面缺陷检测算法EML-YOLO。通过设计一种高效大卷积模块(efficient large kernel,ELK),在保留空间信息的同时提供多尺度的特征表示,从而提高模型的特征提取能力;提出多支路并行的特征融合模块(multi-scale context module,MCM),使得模型能够获取丰富的特征信息和全局上下文信息;在Neck模块中通过特征压缩和精简来减少模型的参数量和计算量,让模型更适用于资源有限的工业场景。采用GC10-DET和DeepPCB两个工业表面缺陷数据集来验证改进的EML-YOLO算法的有效性。实验结果表明,在GC10-DET数据集和DeepPCB数据集上,检测准确率上分别提高了4.3个百分点和2.9个百分点,参数量仅2.7×10^(6)。所提算法可以较好地应用于工业缺陷检测场景。
文摘随着信息技术的发展,用户和组织对网络安全的关注度不断提高,数据加密传输逐渐成为主流,推动互联网中加密流量的比例不断攀升。然而,数据加密在保障隐私和安全的同时也成为非法内容逃避网络监管的手段。为实现加密流量的检测与分析,需要高效地识别出加密流量。但是,压缩流量的存在会严重干扰对加密流量的识别。针对上述问题,设计了基于滑动窗口和随机性特征的加密流量识别方案,以高效且准确地识别加密流量。具体来说,所提方案根据滑动窗口机制对会话中数据传输报文的有效载荷进行采样,获取能够反映原始流量信息模式的数据块序列,针对每个数据块使用随机性测度算法进行样本特征提取,为原始载荷构建随机性特征。此外,通过设计基于CART(classification and reqression tree)算法的决策树模型,在提高加密和压缩流量识别的准确率的同时,极大降低了针对加密流量识别的漏报率。基于对多个权威网站数据的随机抽样,构建均衡的数据集,并通过实验证明了所提方案的可行性和高效性。
