Single-pixel imaging(SPI)can transform 2D or 3D image data into 1D light signals,which offers promising prospects for image compression and transmission.However,during data communication these light signals in public ...Single-pixel imaging(SPI)can transform 2D or 3D image data into 1D light signals,which offers promising prospects for image compression and transmission.However,during data communication these light signals in public channels will easily draw the attention of eavesdroppers.Here,we introduce an efficient encryption method for SPI data transmission that uses the 3D Arnold transformation to directly disrupt 1D single-pixel light signals and utilizes the elliptic curve encryption algorithm for key transmission.This encryption scheme immediately employs Hadamard patterns to illuminate the scene and then utilizes the 3D Arnold transformation to permutate the 1D light signal of single-pixel detection.Then the transformation parameters serve as the secret key,while the security of key exchange is guaranteed by an elliptic curve-based key exchange mechanism.Compared with existing encryption schemes,both computer simulations and optical experiments have been conducted to demonstrate that the proposed technique not only enhances the security of encryption but also eliminates the need for complicated pattern scrambling rules.Additionally,this approach solves the problem of secure key transmission,thus ensuring the security of information and the quality of the decrypted images.展开更多
Monocular 3D object detection is challenging due to the lack of accurate depth information.Some methods estimate the pixel-wise depth maps from off-the-shelf depth estimators and then use them as an additional input t...Monocular 3D object detection is challenging due to the lack of accurate depth information.Some methods estimate the pixel-wise depth maps from off-the-shelf depth estimators and then use them as an additional input to augment the RGB images.Depth-based methods attempt to convert estimated depth maps to pseudo-LiDAR and then use LiDAR-based object detectors or focus on the perspective of image and depth fusion learning.However,they demonstrate limited performance and efficiency as a result of depth inaccuracy and complex fusion mode with convolutions.Different from these approaches,our proposed depth-guided vision transformer with a normalizing flows(NF-DVT)network uses normalizing flows to build priors in depth maps to achieve more accurate depth information.Then we develop a novel Swin-Transformer-based backbone with a fusion module to process RGB image patches and depth map patches with two separate branches and fuse them using cross-attention to exchange information with each other.Furthermore,with the help of pixel-wise relative depth values in depth maps,we develop new relative position embeddings in the cross-attention mechanism to capture more accurate sequence ordering of input tokens.Our method is the first Swin-Transformer-based backbone architecture for monocular 3D object detection.The experimental results on the KITTI and the challenging Waymo Open datasets show the effectiveness of our proposed method and superior performance over previous counterparts.展开更多
In this paper, we built upon the estimating primaries by sparse inversion （EPSI） method. We use the 3D curvelet transform and modify the EPSI method to the sparse inversion of the biconvex optimization and Ll-norm r...In this paper, we built upon the estimating primaries by sparse inversion （EPSI） method. We use the 3D curvelet transform and modify the EPSI method to the sparse inversion of the biconvex optimization and Ll-norm regularization, and use alternating optimization to directly estimate the primary reflection coefficients and source wavelet. The 3D curvelet transform is used as a sparseness constraint when inverting the primary reflection coefficients, which results in avoiding the prediction subtraction process in the surface-related multiples elimination （SRME） method. The proposed method not only reduces the damage to the effective waves but also improves the elimination of multiples. It is also a wave equation- based method for elimination of surface multiple reflections, which effectively removes surface multiples under complex submarine conditions.展开更多
激光雷达点云3D物体检测,对于小物体如行人、自行车的检测精度较低,容易漏检误检,提出一种多尺度Transformer激光雷达点云3D物体检测方法 MSPT-RCNN(multi-scale point transformer-RCNN),提高点云3D物体检测精度。该方法包含两个阶段,...激光雷达点云3D物体检测,对于小物体如行人、自行车的检测精度较低,容易漏检误检,提出一种多尺度Transformer激光雷达点云3D物体检测方法 MSPT-RCNN(multi-scale point transformer-RCNN),提高点云3D物体检测精度。该方法包含两个阶段,即第一阶段(RPN)和第二阶段(RCNN)。RPN阶段通过多尺度Transformer网络提取点云特征,该网络包含多尺度邻域嵌入模块和跳跃连接偏移注意力模块,获取多尺度邻域几何信息和不同层次全局语义信息,生成高质量初始3D包围盒;在RCNN阶段,引入包围盒内的点云多尺度邻域几何信息,优化了包围盒位置、尺寸、朝向和置信度等信息。实验结果表明,该方法(MSPT-RCNN)具有较高检测精度,特别是对于远处和较小物体,提升更高。MSPT-RCNN通过有效学习点云数据中的多尺度几何信息,提取不同层次有效的语义信息,能够有效提升3D物体检测精度。展开更多
By selecting any one limb of 3-RSR parallel robot as a research object, the paper establishes a position and orienta- tion relationship matrix between the moving platform and the base by means of Denavit-Hartenberg （...By selecting any one limb of 3-RSR parallel robot as a research object, the paper establishes a position and orienta- tion relationship matrix between the moving platform and the base by means of Denavit-Hartenberg （D-H） transformation matrix. The error mapping model is derived from original error to the error of the platform by using matrix differential method. This model contains all geometric original errors of the robot. The nonlinear implicit function relation between po- sition and orientation error of the platform and the original geometric errors is simplified as a linear explicit function rela- tion. The results provide a basis for further studying error analysis and error compensation.展开更多
目前主流人体动作识别大部分都是基于卷积神经网络(Convolutional Neural Network,CNN)实现,而CNN容易忽略视频中的空间位置信息,从而降低了视频空间频域中动作识别能力。同时传统CNN不能快速定位到关键的特征位置,并且在训练过程中不...目前主流人体动作识别大部分都是基于卷积神经网络(Convolutional Neural Network,CNN)实现,而CNN容易忽略视频中的空间位置信息,从而降低了视频空间频域中动作识别能力。同时传统CNN不能快速定位到关键的特征位置,并且在训练过程中不能并行计算导致效率低。为了解决传统CNN在处理时间频域和多并行计算问题,提出了基于视觉Transformer(Vision Transformer,ViT)和3D卷积网络学习时空特征(Learning Spatiotemporal Features with 3D Convolutional Network,C3D)的人体动作识别算法。使用C3D提取视频的多维特征图、ViT的特征切片窗口对多维特征进行全局特征分割;使用Transformer的编码-解码模块对视频中人体动作进行预测。实验结果表明,所提的人体动作识别算法在UCF-101、HMDB51数据集上提高了动作识别的准确率。展开更多
Fusion methods based on multi-scale transforms have become the mainstream of the pixel-level image fusion. However,most of these methods cannot fully exploit spatial domain information of source images, which lead to ...Fusion methods based on multi-scale transforms have become the mainstream of the pixel-level image fusion. However,most of these methods cannot fully exploit spatial domain information of source images, which lead to the degradation of image.This paper presents a fusion framework based on block-matching and 3D(BM3D) multi-scale transform. The algorithm first divides the image into different blocks and groups these 2D image blocks into 3D arrays by their similarity. Then it uses a 3D transform which consists of a 2D multi-scale and a 1D transform to transfer the arrays into transform coefficients, and then the obtained low-and high-coefficients are fused by different fusion rules. The final fused image is obtained from a series of fused 3D image block groups after the inverse transform by using an aggregation process. In the experimental part, we comparatively analyze some existing algorithms and the using of different transforms, e.g. non-subsampled Contourlet transform(NSCT), non-subsampled Shearlet transform(NSST), in the 3D transform step. Experimental results show that the proposed fusion framework can not only improve subjective visual effect, but also obtain better objective evaluation criteria than state-of-the-art methods.展开更多
BACKGROUND: Pancreatic stellate cells (PSCs) play a major role in promoting pancreatic fibrosis. Transforming growth factor beta 1 (TGF-beta 1) is a critical mediator of this process. This study aimed to determine the...BACKGROUND: Pancreatic stellate cells (PSCs) play a major role in promoting pancreatic fibrosis. Transforming growth factor beta 1 (TGF-beta 1) is a critical mediator of this process. This study aimed to determine the expression of the Smad3 and Smad7 genes in the process of PSC activation, and explore the mechanisms of chronic pancreatitis. METHODS: The expressions of Smad3 and Smad7 in PSCs before and after TGF-beta 1 treatment were detected by reverse transcription-polymerase chain reaction and Western blotting analysis. Smad3 expression was detected in PSCs after treatment with 5 ng/ml of TGF-beta 1 for 24 hours. RESULTS: Smad7 expression was decreased in TGF-beta 1 -activated PSCs (P<0.05) in a dose-dependent manner. When TGF-beta 1 concentration reached 10 ng/ml, the expression of p-Smad3, Smad3, and Smad7 was inhibited (P<0.05). CONCLUSIONS: TGF-beta 1 promotes the expression of Smad3 and inhibits the expression of Smad7 during the activation of PSCs. In contrast, high-dose TGF-beta 1 downregulates the expression of Smad3 in completely activated PSCs.展开更多
Three transformation models （Bursa-Wolf, Molodensky, and WTUSM） are generally used between two data systems transformation. The linear models are used when the rotation angles are small; however, when the rotation a...Three transformation models （Bursa-Wolf, Molodensky, and WTUSM） are generally used between two data systems transformation. The linear models are used when the rotation angles are small; however, when the rotation angles get bigger, model errors will be produced. In this paper, we present a method with three main terms：① the traditional rotation angles θ,φ,ψ are substituted with a,b,c which are three respective values in the anti-symmetrical or Lodrigues matrix; ② directly and accurately calculating the formula of seven parameters in any value of rotation angles; and ③ a corresponding adjustment model is established. This method does not use the triangle function. Instead it uses addition, subtraction, multiplication and division, and the complexity of the equation is reduced, making the calculation easy and quick.展开更多
In previous studies we have reported that a high levelof expression of mot-2 protein results in malignant transformation of NIH 3T3 cells as analyzed by anchorage indeopendent growth and nude mice assays [Kaul et al....In previous studies we have reported that a high levelof expression of mot-2 protein results in malignant transformation of NIH 3T3 cells as analyzed by anchorage indeopendent growth and nude mice assays [Kaul et al., Oncogene, 17, 907-11, 1998]. Mot-2 was found to interact withtumor suppressor protein p53. The transient overexpression of mot-2 was inhibitory to transcriptional activationfunction of p53 [Wadhwa et al., J. Biol. Chem., 273, 2958691, 1998]. We demonstrate here that mot-2 transfectedstable clonse of NIH 3T3 that showed malignant propertiesindeed show inactivation of p53 function as assayed byexogenous p53 dependent reporter. The expression levelof p53 in response to UV-irradiation was lower in NIH3T3/mot-2 as compared to NIH 3T3 cells and also exhibited delay in reaching peak. furthermore, upon serumstarvation p53 was seen to translocate to the 11ucleus inNIH 3T3, but not in its mot-2 derivative. The data suggests that mot-2 mediated cytoplasmic sequestration andinactivation of p53 may operate, at least in part, for malignant phenotype of NIH 3T3/mot-2 cells.NIH 3T3/mot-2 cells show inactivation of p53 protein展开更多
Image fusion is performed between one band of multi-spectral image and two bands of hyperspectral image to produce fused image with the same spatial resolution as source multi-spectral image and the same spectral reso...Image fusion is performed between one band of multi-spectral image and two bands of hyperspectral image to produce fused image with the same spatial resolution as source multi-spectral image and the same spectral resolution as source hyperspeetral image. According to the characteristics and 3-Dimensional （3-D） feature analysis of multi-spectral and hyperspectral image data volume, the new fusion approach using 3-D wavelet based method is proposed. This approach is composed of four major procedures： Spatial and spectral resampling, 3-D wavelet transform, wavelet coefficient integration and 3-D inverse wavelet transform. Especially, a novel method, Ratio Image Based Spectral Resampling （RIBSR）method, is proposed to accomplish data resampling in spectral domain by utilizing the property of ratio image. And a new fusion rule, Average and Substitution （A＆S） rule, is employed as the fusion rule to accomplish wavelet coefficient integration. Experimental results illustrate that the fusion approach using 3-D wavelet transform can utilize both spatial and spectral characteristics of source images more adequately and produce fused image with higher quality and fewer artifacts than fusion approach using 2-D wavelet transform. It is also revealed that RIBSR method is capable of interpolating the missing data more effectively and correctly, and A＆S rule can integrate coefficients of source images in 3-D wavelet domain to preserve both spatial and spectral features of source images more properly.展开更多
The isothermal tetragonal-to-monoclinic phase transformation of 3 mol fraction Y2O3-ZrO2 ceramics contain- ing different amounts of Al2O3 during ageing in water at 130℃ for periods of time up to 40 h was investigated...The isothermal tetragonal-to-monoclinic phase transformation of 3 mol fraction Y2O3-ZrO2 ceramics contain- ing different amounts of Al2O3 during ageing in water at 130℃ for periods of time up to 40 h was investigated to explore the effect of Al2O3 addition on this transformation. The propagation of the transformation into the specimen interiors was suppressed by the addition of Al2O3. The transformation kinetics showed a nucleation and growth mechanism on the specimen surface to be dominant in the low temperature ageing in water environment.展开更多
In the design of 3-D spherically symmetric FIR filters via the McClellan transformation, two methods are proposed to determine the transformation parameters. The first is to improve the original 3-D algorithm by explo...In the design of 3-D spherically symmetric FIR filters via the McClellan transformation, two methods are proposed to determine the transformation parameters. The first is to improve the original 3-D algorithm by exploiting the 2-D effective methods in 3-D. This method can change the constrained optimization algorithm into the unconstrained one and makes the design easier to realize. The second method is to solve the coupled equations under constrained conditions and a set of ideal parameters can be gotten. The design example shows that the two methods are all efficient and easier than the original algorithm.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.62075241).
文摘Single-pixel imaging(SPI)can transform 2D or 3D image data into 1D light signals,which offers promising prospects for image compression and transmission.However,during data communication these light signals in public channels will easily draw the attention of eavesdroppers.Here,we introduce an efficient encryption method for SPI data transmission that uses the 3D Arnold transformation to directly disrupt 1D single-pixel light signals and utilizes the elliptic curve encryption algorithm for key transmission.This encryption scheme immediately employs Hadamard patterns to illuminate the scene and then utilizes the 3D Arnold transformation to permutate the 1D light signal of single-pixel detection.Then the transformation parameters serve as the secret key,while the security of key exchange is guaranteed by an elliptic curve-based key exchange mechanism.Compared with existing encryption schemes,both computer simulations and optical experiments have been conducted to demonstrate that the proposed technique not only enhances the security of encryption but also eliminates the need for complicated pattern scrambling rules.Additionally,this approach solves the problem of secure key transmission,thus ensuring the security of information and the quality of the decrypted images.
基金supported in part by the Major Project for New Generation of AI (2018AAA0100400)the National Natural Science Foundation of China (61836014,U21B2042,62072457,62006231)the InnoHK Program。
文摘Monocular 3D object detection is challenging due to the lack of accurate depth information.Some methods estimate the pixel-wise depth maps from off-the-shelf depth estimators and then use them as an additional input to augment the RGB images.Depth-based methods attempt to convert estimated depth maps to pseudo-LiDAR and then use LiDAR-based object detectors or focus on the perspective of image and depth fusion learning.However,they demonstrate limited performance and efficiency as a result of depth inaccuracy and complex fusion mode with convolutions.Different from these approaches,our proposed depth-guided vision transformer with a normalizing flows(NF-DVT)network uses normalizing flows to build priors in depth maps to achieve more accurate depth information.Then we develop a novel Swin-Transformer-based backbone with a fusion module to process RGB image patches and depth map patches with two separate branches and fuse them using cross-attention to exchange information with each other.Furthermore,with the help of pixel-wise relative depth values in depth maps,we develop new relative position embeddings in the cross-attention mechanism to capture more accurate sequence ordering of input tokens.Our method is the first Swin-Transformer-based backbone architecture for monocular 3D object detection.The experimental results on the KITTI and the challenging Waymo Open datasets show the effectiveness of our proposed method and superior performance over previous counterparts.
基金supported by the National Science and Technology Major Project (No.2011ZX05023-005-008)
文摘In this paper, we built upon the estimating primaries by sparse inversion （EPSI） method. We use the 3D curvelet transform and modify the EPSI method to the sparse inversion of the biconvex optimization and Ll-norm regularization, and use alternating optimization to directly estimate the primary reflection coefficients and source wavelet. The 3D curvelet transform is used as a sparseness constraint when inverting the primary reflection coefficients, which results in avoiding the prediction subtraction process in the surface-related multiples elimination （SRME） method. The proposed method not only reduces the damage to the effective waves but also improves the elimination of multiples. It is also a wave equation- based method for elimination of surface multiple reflections, which effectively removes surface multiples under complex submarine conditions.
文摘激光雷达点云3D物体检测,对于小物体如行人、自行车的检测精度较低,容易漏检误检,提出一种多尺度Transformer激光雷达点云3D物体检测方法 MSPT-RCNN(multi-scale point transformer-RCNN),提高点云3D物体检测精度。该方法包含两个阶段,即第一阶段(RPN)和第二阶段(RCNN)。RPN阶段通过多尺度Transformer网络提取点云特征,该网络包含多尺度邻域嵌入模块和跳跃连接偏移注意力模块,获取多尺度邻域几何信息和不同层次全局语义信息,生成高质量初始3D包围盒;在RCNN阶段,引入包围盒内的点云多尺度邻域几何信息,优化了包围盒位置、尺寸、朝向和置信度等信息。实验结果表明,该方法(MSPT-RCNN)具有较高检测精度,特别是对于远处和较小物体,提升更高。MSPT-RCNN通过有效学习点云数据中的多尺度几何信息,提取不同层次有效的语义信息,能够有效提升3D物体检测精度。
基金National Natural Science Foundation of China(No.51275486)the Specialized Research Fund for the Doctoral Program of Higher Education(No.20111420110005)
文摘By selecting any one limb of 3-RSR parallel robot as a research object, the paper establishes a position and orienta- tion relationship matrix between the moving platform and the base by means of Denavit-Hartenberg （D-H） transformation matrix. The error mapping model is derived from original error to the error of the platform by using matrix differential method. This model contains all geometric original errors of the robot. The nonlinear implicit function relation between po- sition and orientation error of the platform and the original geometric errors is simplified as a linear explicit function rela- tion. The results provide a basis for further studying error analysis and error compensation.
文摘目前主流人体动作识别大部分都是基于卷积神经网络(Convolutional Neural Network,CNN)实现,而CNN容易忽略视频中的空间位置信息,从而降低了视频空间频域中动作识别能力。同时传统CNN不能快速定位到关键的特征位置,并且在训练过程中不能并行计算导致效率低。为了解决传统CNN在处理时间频域和多并行计算问题,提出了基于视觉Transformer(Vision Transformer,ViT)和3D卷积网络学习时空特征(Learning Spatiotemporal Features with 3D Convolutional Network,C3D)的人体动作识别算法。使用C3D提取视频的多维特征图、ViT的特征切片窗口对多维特征进行全局特征分割;使用Transformer的编码-解码模块对视频中人体动作进行预测。实验结果表明,所提的人体动作识别算法在UCF-101、HMDB51数据集上提高了动作识别的准确率。
基金supported by the National Natural Science Foundation of China(6157206361401308)+6 种基金the Fundamental Research Funds for the Central Universities(2016YJS039)the Natural Science Foundation of Hebei Province(F2016201142F2016201187)the Natural Social Foundation of Hebei Province(HB15TQ015)the Science Research Project of Hebei Province(QN2016085ZC2016040)the Natural Science Foundation of Hebei University(2014-303)
文摘Fusion methods based on multi-scale transforms have become the mainstream of the pixel-level image fusion. However,most of these methods cannot fully exploit spatial domain information of source images, which lead to the degradation of image.This paper presents a fusion framework based on block-matching and 3D(BM3D) multi-scale transform. The algorithm first divides the image into different blocks and groups these 2D image blocks into 3D arrays by their similarity. Then it uses a 3D transform which consists of a 2D multi-scale and a 1D transform to transfer the arrays into transform coefficients, and then the obtained low-and high-coefficients are fused by different fusion rules. The final fused image is obtained from a series of fused 3D image block groups after the inverse transform by using an aggregation process. In the experimental part, we comparatively analyze some existing algorithms and the using of different transforms, e.g. non-subsampled Contourlet transform(NSCT), non-subsampled Shearlet transform(NSST), in the 3D transform step. Experimental results show that the proposed fusion framework can not only improve subjective visual effect, but also obtain better objective evaluation criteria than state-of-the-art methods.
基金supported by grants from the Natural Science Foundation of Jiangsu Province,China (No. BK2006241)the Foundation for Talents in Six Fields of Jiangsu Province (No. 07-B-038)
文摘BACKGROUND: Pancreatic stellate cells (PSCs) play a major role in promoting pancreatic fibrosis. Transforming growth factor beta 1 (TGF-beta 1) is a critical mediator of this process. This study aimed to determine the expression of the Smad3 and Smad7 genes in the process of PSC activation, and explore the mechanisms of chronic pancreatitis. METHODS: The expressions of Smad3 and Smad7 in PSCs before and after TGF-beta 1 treatment were detected by reverse transcription-polymerase chain reaction and Western blotting analysis. Smad3 expression was detected in PSCs after treatment with 5 ng/ml of TGF-beta 1 for 24 hours. RESULTS: Smad7 expression was decreased in TGF-beta 1 -activated PSCs (P<0.05) in a dose-dependent manner. When TGF-beta 1 concentration reached 10 ng/ml, the expression of p-Smad3, Smad3, and Smad7 was inhibited (P<0.05). CONCLUSIONS: TGF-beta 1 promotes the expression of Smad3 and inhibits the expression of Smad7 during the activation of PSCs. In contrast, high-dose TGF-beta 1 downregulates the expression of Smad3 in completely activated PSCs.
文摘Three transformation models （Bursa-Wolf, Molodensky, and WTUSM） are generally used between two data systems transformation. The linear models are used when the rotation angles are small; however, when the rotation angles get bigger, model errors will be produced. In this paper, we present a method with three main terms：① the traditional rotation angles θ,φ,ψ are substituted with a,b,c which are three respective values in the anti-symmetrical or Lodrigues matrix; ② directly and accurately calculating the formula of seven parameters in any value of rotation angles; and ③ a corresponding adjustment model is established. This method does not use the triangle function. Instead it uses addition, subtraction, multiplication and division, and the complexity of the equation is reduced, making the calculation easy and quick.
文摘In previous studies we have reported that a high levelof expression of mot-2 protein results in malignant transformation of NIH 3T3 cells as analyzed by anchorage indeopendent growth and nude mice assays [Kaul et al., Oncogene, 17, 907-11, 1998]. Mot-2 was found to interact withtumor suppressor protein p53. The transient overexpression of mot-2 was inhibitory to transcriptional activationfunction of p53 [Wadhwa et al., J. Biol. Chem., 273, 2958691, 1998]. We demonstrate here that mot-2 transfectedstable clonse of NIH 3T3 that showed malignant propertiesindeed show inactivation of p53 function as assayed byexogenous p53 dependent reporter. The expression levelof p53 in response to UV-irradiation was lower in NIH3T3/mot-2 as compared to NIH 3T3 cells and also exhibited delay in reaching peak. furthermore, upon serumstarvation p53 was seen to translocate to the 11ucleus inNIH 3T3, but not in its mot-2 derivative. The data suggests that mot-2 mediated cytoplasmic sequestration andinactivation of p53 may operate, at least in part, for malignant phenotype of NIH 3T3/mot-2 cells.NIH 3T3/mot-2 cells show inactivation of p53 protein
文摘Image fusion is performed between one band of multi-spectral image and two bands of hyperspectral image to produce fused image with the same spatial resolution as source multi-spectral image and the same spectral resolution as source hyperspeetral image. According to the characteristics and 3-Dimensional （3-D） feature analysis of multi-spectral and hyperspectral image data volume, the new fusion approach using 3-D wavelet based method is proposed. This approach is composed of four major procedures： Spatial and spectral resampling, 3-D wavelet transform, wavelet coefficient integration and 3-D inverse wavelet transform. Especially, a novel method, Ratio Image Based Spectral Resampling （RIBSR）method, is proposed to accomplish data resampling in spectral domain by utilizing the property of ratio image. And a new fusion rule, Average and Substitution （A＆S） rule, is employed as the fusion rule to accomplish wavelet coefficient integration. Experimental results illustrate that the fusion approach using 3-D wavelet transform can utilize both spatial and spectral characteristics of source images more adequately and produce fused image with higher quality and fewer artifacts than fusion approach using 2-D wavelet transform. It is also revealed that RIBSR method is capable of interpolating the missing data more effectively and correctly, and A＆S rule can integrate coefficients of source images in 3-D wavelet domain to preserve both spatial and spectral features of source images more properly.
文摘The isothermal tetragonal-to-monoclinic phase transformation of 3 mol fraction Y2O3-ZrO2 ceramics contain- ing different amounts of Al2O3 during ageing in water at 130℃ for periods of time up to 40 h was investigated to explore the effect of Al2O3 addition on this transformation. The propagation of the transformation into the specimen interiors was suppressed by the addition of Al2O3. The transformation kinetics showed a nucleation and growth mechanism on the specimen surface to be dominant in the low temperature ageing in water environment.
文摘In the design of 3-D spherically symmetric FIR filters via the McClellan transformation, two methods are proposed to determine the transformation parameters. The first is to improve the original 3-D algorithm by exploiting the 2-D effective methods in 3-D. This method can change the constrained optimization algorithm into the unconstrained one and makes the design easier to realize. The second method is to solve the coupled equations under constrained conditions and a set of ideal parameters can be gotten. The design example shows that the two methods are all efficient and easier than the original algorithm.
