彩色图像隐写方法具有秘密传输、不易察觉的特性。其中,基于频率域的彩色图像隐写方法不论在传统图像隐写方法还是深度学习图像隐写方法中都取得了更好的隐写性能。然而,当前大多基于自编码器结构的彩色图像隐写模型在提升重构秘密图像...彩色图像隐写方法具有秘密传输、不易察觉的特性。其中,基于频率域的彩色图像隐写方法不论在传统图像隐写方法还是深度学习图像隐写方法中都取得了更好的隐写性能。然而,当前大多基于自编码器结构的彩色图像隐写模型在提升重构秘密图像能力方面均存在局限性。针对这一问题,本文基于频率域彩色图像隐写方法的现有优势,提出了一种基于分离训练与图像去噪的频率域彩色图像隐写方法,并构建了相应的隐写模型。面对自编码器的编码网络与解码网络在训练过程中的性能权衡问题,本文的隐写方法采用分离训练对默认的神经网络训练方式进行优化。除此之外,为了进一步提升重构秘密图像的质量,模型还添加了去噪卷积神经网络(Denoising Convolutional Neural Network,DnCNN)结构的图像去噪模块。经实验验证,本文模型生成的彩色载密图像与重构秘密图像的峰值信噪比(Peak Signal to Noise Ratio,PSNR)高达82.31 dB和39.27 dB,结构相似度(Structural Similarity Index Measure,SSIM)均达到0.99。与同类型的深度学习彩色图像隐写模型相比,提出的隐写模型不仅具有更强的不可察觉性,而且具有更好的重构秘密图像的能力。展开更多
Deep beam anchorage structures based on spatial distribution analysis of the cable prestressed field have been proposed for roadway roof support, Stability and other factors that influence deep beam structures are stu...Deep beam anchorage structures based on spatial distribution analysis of the cable prestressed field have been proposed for roadway roof support, Stability and other factors that influence deep beam structures are studied in this paper using mechanical calculations, numerical analysis and field measurements, A mechanical model of deep beam structure subjected to multiple loading is established, including analysis of roof support in the return airway of S1203 working face in the Yuwu coal mine, China, The expression of maximum shear stress in the deep beam structure is deduced according to the stress superposition criterion, It is found that the primary factors affecting deep beam structure stability are deep beam thickness, cable pre-tension and cable spacing, The variation of maximum shear stress distribution and prestressed field diffusion effects according to various factors are analyzed using Matlah and FLAC3DTM software, and practical support parameters of the S1203 return airway roof are determined, According to the observations of rock pressure, there is no evidence of roof separation, and the maximum values of roof subsidence and convergence of wall rock are 72 and 48 mm, respectively, The results show that the proposed roof support design with a deep beam structure is feasible and achieves effective control of the roadway roof,展开更多
背景目前下肢动脉疾病(LEAD)的发病率正逐渐上升,LEAD与心脑血管疾病及全因死亡率之间的相关性也得到大量研究证明。以往,LEAD的确诊依赖于异常踝臂指数(ABI≤0.9),其主要通过多普勒法获得。示波血压测量法同步测量四肢血压不仅能获得...背景目前下肢动脉疾病(LEAD)的发病率正逐渐上升,LEAD与心脑血管疾病及全因死亡率之间的相关性也得到大量研究证明。以往,LEAD的确诊依赖于异常踝臂指数(ABI≤0.9),其主要通过多普勒法获得。示波血压测量法同步测量四肢血压不仅能获得示波踝臂指数(OS-ABI),还能同时获得臂间血压差异(IAD)及踝间血压差异(IAND)。目的评价OS-ABI及IAND筛查LEAD的价值。方法选取2017年10月-2018年4月在南昌大学第二附属医院就诊的206例血管外科患者。采用示波血压测量法同时测量患者四肢血压,得到OS-ABI和IAND,以OS-ABI≤0.9或IAND≥15 mm Hg(1 mm Hg=0.133 kPa)作为LEAD的诊断标准。同时患者完善CT血管造影检查(CTA),以CTA检查结果为金标准。结果依据CTA结果,206例患者中,182例(88.3%)诊断为LEAD,169例(82.0%)OS-ABI≤0.9,106例(51.5%)IAND≥15 mm Hg。OS-ABI≤0.9诊断LEAD的灵敏度、特异度和准确性分别为91.8%、91.7%和91.7%。IAND≥15 mm Hg诊断LEAD的灵敏度、特异度和准确性分别为55.5%、79.2%和58.3%。当OS-ABI≤0.9和IAND≥15 mm Hg联合应用时,诊断LEAD的灵敏度、特异度和准确性分别提高至96.2%、70.8%和93.2%。结论 OS-ABI是筛查LEAD的有效指标,联合IAND可提高其筛查价值,值得在临床上推广应用。展开更多
文摘彩色图像隐写方法具有秘密传输、不易察觉的特性。其中,基于频率域的彩色图像隐写方法不论在传统图像隐写方法还是深度学习图像隐写方法中都取得了更好的隐写性能。然而,当前大多基于自编码器结构的彩色图像隐写模型在提升重构秘密图像能力方面均存在局限性。针对这一问题,本文基于频率域彩色图像隐写方法的现有优势,提出了一种基于分离训练与图像去噪的频率域彩色图像隐写方法,并构建了相应的隐写模型。面对自编码器的编码网络与解码网络在训练过程中的性能权衡问题,本文的隐写方法采用分离训练对默认的神经网络训练方式进行优化。除此之外,为了进一步提升重构秘密图像的质量,模型还添加了去噪卷积神经网络(Denoising Convolutional Neural Network,DnCNN)结构的图像去噪模块。经实验验证,本文模型生成的彩色载密图像与重构秘密图像的峰值信噪比(Peak Signal to Noise Ratio,PSNR)高达82.31 dB和39.27 dB,结构相似度(Structural Similarity Index Measure,SSIM)均达到0.99。与同类型的深度学习彩色图像隐写模型相比,提出的隐写模型不仅具有更强的不可察觉性,而且具有更好的重构秘密图像的能力。
基金provided by the National Natural Science Foundation of China (Nos. 51504259 and 51234005)the Fundamental Research Funds for the Central Universities (No. 2010QZ06)
文摘Deep beam anchorage structures based on spatial distribution analysis of the cable prestressed field have been proposed for roadway roof support, Stability and other factors that influence deep beam structures are studied in this paper using mechanical calculations, numerical analysis and field measurements, A mechanical model of deep beam structure subjected to multiple loading is established, including analysis of roof support in the return airway of S1203 working face in the Yuwu coal mine, China, The expression of maximum shear stress in the deep beam structure is deduced according to the stress superposition criterion, It is found that the primary factors affecting deep beam structure stability are deep beam thickness, cable pre-tension and cable spacing, The variation of maximum shear stress distribution and prestressed field diffusion effects according to various factors are analyzed using Matlah and FLAC3DTM software, and practical support parameters of the S1203 return airway roof are determined, According to the observations of rock pressure, there is no evidence of roof separation, and the maximum values of roof subsidence and convergence of wall rock are 72 and 48 mm, respectively, The results show that the proposed roof support design with a deep beam structure is feasible and achieves effective control of the roadway roof,
文摘背景目前下肢动脉疾病(LEAD)的发病率正逐渐上升,LEAD与心脑血管疾病及全因死亡率之间的相关性也得到大量研究证明。以往,LEAD的确诊依赖于异常踝臂指数(ABI≤0.9),其主要通过多普勒法获得。示波血压测量法同步测量四肢血压不仅能获得示波踝臂指数(OS-ABI),还能同时获得臂间血压差异(IAD)及踝间血压差异(IAND)。目的评价OS-ABI及IAND筛查LEAD的价值。方法选取2017年10月-2018年4月在南昌大学第二附属医院就诊的206例血管外科患者。采用示波血压测量法同时测量患者四肢血压,得到OS-ABI和IAND,以OS-ABI≤0.9或IAND≥15 mm Hg(1 mm Hg=0.133 kPa)作为LEAD的诊断标准。同时患者完善CT血管造影检查(CTA),以CTA检查结果为金标准。结果依据CTA结果,206例患者中,182例(88.3%)诊断为LEAD,169例(82.0%)OS-ABI≤0.9,106例(51.5%)IAND≥15 mm Hg。OS-ABI≤0.9诊断LEAD的灵敏度、特异度和准确性分别为91.8%、91.7%和91.7%。IAND≥15 mm Hg诊断LEAD的灵敏度、特异度和准确性分别为55.5%、79.2%和58.3%。当OS-ABI≤0.9和IAND≥15 mm Hg联合应用时,诊断LEAD的灵敏度、特异度和准确性分别提高至96.2%、70.8%和93.2%。结论 OS-ABI是筛查LEAD的有效指标,联合IAND可提高其筛查价值,值得在临床上推广应用。
