In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This...In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This article considers subgroup analysis methods for longitudinal data containing multiple covariates and biomarkers.We divide subgroups based on whether a linear combination of these biomarkers exceeds a predetermined threshold,and assess the heterogeneity of treatment effects across subgroups using the interaction between subgroups and exposure variables.Quantile regression is used to better characterize the global distribution of the response variable and sparsity penalties are imposed to achieve variable selection of covariates and biomarkers.The effectiveness of our proposed methodology for both variable selection and parameter estimation is verified through random simulations.Finally,we demonstrate the application of this method by analyzing data from the PA.3 trial,further illustrating the practicality of the method proposed in this paper.展开更多
Real-time hand gesture recognition technology significantly improves the user's experience for virtual reality/augmented reality(VR/AR) applications, which relies on the identification of the orientation of the ha...Real-time hand gesture recognition technology significantly improves the user's experience for virtual reality/augmented reality(VR/AR) applications, which relies on the identification of the orientation of the hand in captured images or videos. A new three-stage pipeline approach for fast and accurate hand segmentation for the hand from a single depth image is proposed. Firstly, a depth frame is segmented into several regions by histogrambased threshold selection algorithm and by tracing the exterior boundaries of objects after thresholding. Secondly, each segmentation proposal is evaluated by a three-layers shallow convolutional neural network(CNN) to determine whether or not the boundary is associated with the hand. Finally, all hand components are merged as the hand segmentation result. Compared with algorithms based on random decision forest(RDF), the experimental results demonstrate that the approach achieves better performance with high-accuracy(88.34% mean intersection over union, mIoU) and a shorter processing time(≤8 ms).展开更多
Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class unifo...Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class uniformity of gray level,a method of reciprocal gray entropy threshold selection is proposed based on two-dimensional(2-D)histogram region oblique division and artificial bee colony(ABC)optimization.Firstly,the definition of reciprocal gray entropy is introduced.Then on the basis of one-dimensional(1-D)method,2-D threshold selection criterion function based on reciprocal gray entropy with histogram oblique division is derived.To accelerate the progress of searching the optimal threshold,the recently proposed ABC optimization algorithm is adopted.The proposed method not only avoids the undefined value points in Shannon entropy,but also achieves high accuracy and anti-noise performance due to reasonable 2-D histogram region division and the consideration of within-class uniformity of gray level.A large number of experimental results show that,compared with the maximum Shannon entropy method with 2-D histogram oblique division and the reciprocal entropy method with 2-D histogram oblique division based on niche chaotic mutation particle swarm optimization(NCPSO),the proposed method can achieve better segmentation results and can satisfy the requirement of real-time processing.展开更多
As the Mars probe,which has limited on-board ability in computation is unable to carry out the large-scale landmark solution,it is necessary to achieve optimal selection of landmarks while ensuring autonomous navigati...As the Mars probe,which has limited on-board ability in computation is unable to carry out the large-scale landmark solution,it is necessary to achieve optimal selection of landmarks while ensuring autonomous navigation accuracy during landing phase.This paper proposes an optimal landmark selection method based on the observability matrix for the Mars probe.Firstly,an observability matrix for navigation system is constructed with Fisher information quantity.Secondly,the optimal configuration of the landmark distribution is given by maximizing the scalar function of the observability matrix.Based on the optimal configuration,the greedy algorithm is used to determine the number of the landmarks at each moment adaptively.In addition,considering the fact that the number of the observable landmarks gradually decreases during the landing process,the convergence threshold of the greedy algorithm is set to a dynamic value regarding landing time.Finally,mathematical simulation verification is conducted,and the results show that the proposed optimal landmark selection method has higher navigation accuracy compared with the random landmark selection method.It can effectively suppress the influence of the measurement model errors and achieve a higher landing accuracy.展开更多
The image segmentation difficulties of small objects which are much smaller than their background often occur in target detection and recognition. The existing threshold segmentation methods almost fail under the circ...The image segmentation difficulties of small objects which are much smaller than their background often occur in target detection and recognition. The existing threshold segmentation methods almost fail under the circumstances. Thus, a threshold selection method is proposed on the basis of area difference between background and object and intra-class variance. The threshold selection formulae based on one-dimensional (1-D) histogram, two-dimensional (2-D) histogram vertical segmentation and 2-D histogram oblique segmentation are given. A fast recursive algorithm of threshold selection in 2-D histogram oblique segmentation is derived. The segmented images and processing time of the proposed method are given in experiments. It is compared with some fast algorithms, such as Otsu, maximum entropy and Fisher threshold selection methods. The experimental results show that the proposed method can effectively segment the small object images and has better anti-noise property.展开更多
Relay selection is an effective method to realize the cooperative diversity gain in wireless networks. In this paper, we study a threshold-based single relay selection algorithm. A reasonable threshold value is set at...Relay selection is an effective method to realize the cooperative diversity gain in wireless networks. In this paper, we study a threshold-based single relay selection algorithm. A reasonable threshold value is set at each relay node, and the first relay with the instantaneous channel gain larger than the threshold will be se-lected to cooperate with the source. The exact and closed form expression for its outage probability is de-rived over independent, non-identically distributed (i. n. i. d) Rayleigh channels. The complexity of the algo-rithm is also analyzed in detail. Simulation results are presented to verify our theoretical analysis.展开更多
In gene prediction, the Fisher discriminant analysis (FDA) is used to separate protein coding region (exon) from non-coding regions (intron). Usually, the positive data set and the negative data set are of the same si...In gene prediction, the Fisher discriminant analysis (FDA) is used to separate protein coding region (exon) from non-coding regions (intron). Usually, the positive data set and the negative data set are of the same size if the number of the data is big enough. But for some situations the data are not sufficient or not equal, the threshold used in FDA may have important influence on prediction results. This paper presents a study on the selection of the threshold. The eigen value of each exon/intron sequence is computed using the Z-curve method with 69 variables. The experiments results suggest that the size and the standard deviation of the data sets and the threshold are the three key elements to be taken into consideration to improve the prediction results.展开更多
The irregular defects and residual tumor tissue after surgery are challenges for effective breast cancer treatment.Herein,a smart hydrogel with self-adaptable size and dual responsive cargos release was fabricated to ...The irregular defects and residual tumor tissue after surgery are challenges for effective breast cancer treatment.Herein,a smart hydrogel with self-adaptable size and dual responsive cargos release was fabricated to treat breast cancer via accurate tumor elimination,on-demand adipose tissue regeneration and effective infection inhibition.The hydrogel consisted of thiol groups ended polyethylene glycol(SH-PEG-SH)and doxorubicin encapsulated mesoporous silica nanocarriers(DOX@MSNs)double crosslinked hyaluronic acid(HA)after loading of antibacterial peptides(AP)and adipose-derived stem cells(ADSCs).A pH-cleavable unsaturated amide bond was pre-introduced between MSNs and HA frame to perform the tumor-specific acidic environment dependent DOX@MSNs release,meanwhile an esterase degradable glyceryl dimethacrylate cap was grafted on MSNs,which contributed to the selective chemotherapy in tumor cells with over-expressed esterase.The bond cleavage between MSNs and HA would also cause the swelling of the hydrogel,which not only provide sufficient space for the growth of ADSCs,but allows the hydrogel to fully fill the irregular defects generated by surgery and residual tumor atrophy,resulting in the on-demand regeneration of adipose tissue.Moreover,the sustained release of AP could be simultaneously triggered along with the size change of hydrogel,which further avoided bacterial infection to promote tissue regeneration.展开更多
In order to predict the extreme load of the mechanical components during the entire life,an automatic method based on the bootstrapping technology(BT)is proposed to determine the most suitable threshold.Based on all t...In order to predict the extreme load of the mechanical components during the entire life,an automatic method based on the bootstrapping technology(BT)is proposed to determine the most suitable threshold.Based on all the turning points of the load history and a series of thresholds estimated in advance,the generalized Pareto distribution is established to fit the exceedances.The corresponding distribution parameters are estimated with the maximum likelihood method.Then,BT is employed to calculate the mean squared error(MSE)of each estimated threshold based on the exceedances and the specific distribution parameters.Finally,the threshold with the smallest MSE will be the optimal one.Compared to the kurtosis method and the mean excess function method,the average deviation of the probability density function of exceedances determined by BT reduces by 38.52%and 29.25%,respectively.Moreover,the quantile-quantile plot of the exceedances determined by BT is closer to a straight line.The results suggest the improvement of the modeling flexibility and the determined threshold precision.If the exceedances are insufficient,BT will enlarge their amount by resampling to solve the instability problem of the original distribution parameters.展开更多
This paper analyzes the characteristics of the output gradient histogram and shortages of several traditional automatic threshold methods in order to segment the gradient image better.Then an improved double-threshold...This paper analyzes the characteristics of the output gradient histogram and shortages of several traditional automatic threshold methods in order to segment the gradient image better.Then an improved double-threshold method is proposed,which is combined with the method of maximum classes variance,estimating-area method and double-threshold method.This method can automatically select two different thresholds to segment gradient images.The computer simulation is performed on the traditional methods and this algorithm and proves that this method can get satisfying result.展开更多
Vocalizations play a critical role in mate recognition and mate choice in a number of taxa, especially, but not limited to, orthopterans, frogs, and birds. But receivers can only recognize and prefer sounds that they ...Vocalizations play a critical role in mate recognition and mate choice in a number of taxa, especially, but not limited to, orthopterans, frogs, and birds. But receivers can only recognize and prefer sounds that they can hear. Thus a fundamental question linking neurobiology and sexual selection asks-what is the threshold for detecting acoustic sexual displays? In this study, we use 3 methods to assess such thresholds in tdngara frogs: behavioral responses, auditory brainstem responsesz and multi unit electrophysiological recordi ngs from the midbrain.We show that thresholds are lowest for multiunit recordings (ca. 45 dB SPL), and then for behavioral responses (ca. 61 dB SPL), with auditory brainstem responses exhibiting the highest thresholds (ca. 71 dB SPL). We discuss why these estimates differ and why, as with other studies, it is unlikely that they should be the same. Although all of these studies estimate thresholds they are not measuring the same thresholds;behavioral thresholds are based on signal salienee whereas the 2 neural assays estimate physiological thresholds. All 3 estimates, however, make it clear that to have an appreciation for detection and salienee of acoustic signals we must listen to those signals through the ears of the receivers.展开更多
In ghost imaging, an illumination light is split into test and reference beams which pass through two different optical systems respectively and an image is constructed with the second-order correlation between the tw...In ghost imaging, an illumination light is split into test and reference beams which pass through two different optical systems respectively and an image is constructed with the second-order correlation between the two light beams. Since both light beams are diffracted when passing through the optical systems, the spatial resolution of ghost imaging is in general lower than that of a corresponding conventional imaging system. When Gaussian-shaped light spots are used to illuminate an object, randomly scanning across the object plane, in the ghost imaging scheme, we show th√at by localizing central positions of the spots of the reference light beam, the resolution can be increased by a factor of 2^(1/2) same as that of the corresponding conventional imaging system. We also find that the resolution can be further enhanced by setting an appropriate threshold to the bucket measurement of ghost imaging.展开更多
The segmentation effect of Tsallis entropy method is superior to that of Shannon entropy method, and the computation speed of two-dimensional Shannon cross entropy method can be further improved by optimization. The e...The segmentation effect of Tsallis entropy method is superior to that of Shannon entropy method, and the computation speed of two-dimensional Shannon cross entropy method can be further improved by optimization. The existing two-dimensional Tsallis cross entropy method is not the strict two-dimensional extension. Thus two new methods of image thresholding using two-dimensional Tsallis cross entropy based on either Chaotic Particle Swarm Optimization (CPSO) or decomposition are proposed. The former uses CPSO to find the optimal threshold. The recursive algorithm is adopted to avoid the repetitive computation of fitness function in iterative procedure. The computing speed is improved greatly. The latter converts the two-dimensional computation into two one-dimensional spaces, which makes the computational complexity further reduced from O(L2) to O(L). The experimental results show that, compared with the proposed recently two-dimensional Shannon or Tsallis cross entropy method, the two new methods can achieve superior segmentation results and reduce running time greatly.展开更多
The high-resolution three-dimensional photoelectron momentum distributions via above-threshold ionization(ATI)of Xe atoms are measured in an intense near circularly polarized laser field using velocity map imaging and...The high-resolution three-dimensional photoelectron momentum distributions via above-threshold ionization(ATI)of Xe atoms are measured in an intense near circularly polarized laser field using velocity map imaging and tomography reconstruction. Compared to the linearly polarized laser field, the employed near circularly polarized laser field imposes a more strict selection rule for the transition via resonant excitation, and therefore we can selectively enhance the resonant ATI through certain atomic Rydberg states. Our results show the self-reference ionization delay, which is determined from the difference between the measured streaking angles for nonadiabatic ATI via the 4 f and 5 f Rydberg states, is 45.6 as. Our method provides an accessible route to highlight the role of resonant transition between selected states, which will pave the way for fully understanding the ionization dynamics toward manipulating electron motion as well as reaction in an ultrafast time scale.展开更多
针对视觉结构类似导致的文种相似性问题,基于局部三值模式的相邻共生矩阵(co-occurrence of adjacent local ternary patterns,CoALTP)提出一种具有判别性和鲁棒性的局部三值模式的相邻共生矩阵(discriminant and robust co-occurrence ...针对视觉结构类似导致的文种相似性问题,基于局部三值模式的相邻共生矩阵(co-occurrence of adjacent local ternary patterns,CoALTP)提出一种具有判别性和鲁棒性的局部三值模式的相邻共生矩阵(discriminant and robust co-occurrence of adjacent local ternary patterns,DRCoALTP)方法,用于获取图像纹理。计算文档图像的相邻稀疏局部三值模式(adjacent sparse local ternary patterns,ASLTP),将采样点数量设定为8,以便获得详细的局部纹理,设计出一种基于自适应中值滤波思想的半自适应阈值方法,用于提取灰度图像中心像素周边对角邻域像素的编码值。ASLTP在邻域像素位置存放稀疏局部三值模式(local ternary patterns,LTP)的值,提取灰度共生矩阵(gray-level co-occurrence matrix,GLCM),从4个方向统计使用ASLTP后灰度图像像素之间的频率关系。该算法在阿拉伯文、俄文、简体中文、哈萨克文、藏文、蒙古文、土耳其文、维吾尔文、英文、吉尔吉斯斯坦文和塔吉克斯坦文11个文种的自建印刷体文档图像数据集中验证。试验结果表明,相较于基线和先进的纹理方法,改进后的方法更具判别性,平均识别准确率为99.14%。为改善CoALTP方法可能产生低效分类特征的问题,提出半自适应阈值方法,有效提高识别率并抑制噪声。此外,针对算法产生的高维特征,采用基于均方差的特征选择方法,通过支持向量机(support vector machine,SVM)分类器特征选择后,识别速度提高284%,对11个文种的平均识别准确率达99.44%。展开更多
基金Supported by the Natural Science Foundation of Fujian Province(2022J011177,2024J01903)the Key Project of Fujian Provincial Education Department(JZ230054)。
文摘In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This article considers subgroup analysis methods for longitudinal data containing multiple covariates and biomarkers.We divide subgroups based on whether a linear combination of these biomarkers exceeds a predetermined threshold,and assess the heterogeneity of treatment effects across subgroups using the interaction between subgroups and exposure variables.Quantile regression is used to better characterize the global distribution of the response variable and sparsity penalties are imposed to achieve variable selection of covariates and biomarkers.The effectiveness of our proposed methodology for both variable selection and parameter estimation is verified through random simulations.Finally,we demonstrate the application of this method by analyzing data from the PA.3 trial,further illustrating the practicality of the method proposed in this paper.
文摘Real-time hand gesture recognition technology significantly improves the user's experience for virtual reality/augmented reality(VR/AR) applications, which relies on the identification of the orientation of the hand in captured images or videos. A new three-stage pipeline approach for fast and accurate hand segmentation for the hand from a single depth image is proposed. Firstly, a depth frame is segmented into several regions by histogrambased threshold selection algorithm and by tracing the exterior boundaries of objects after thresholding. Secondly, each segmentation proposal is evaluated by a three-layers shallow convolutional neural network(CNN) to determine whether or not the boundary is associated with the hand. Finally, all hand components are merged as the hand segmentation result. Compared with algorithms based on random decision forest(RDF), the experimental results demonstrate that the approach achieves better performance with high-accuracy(88.34% mean intersection over union, mIoU) and a shorter processing time(≤8 ms).
基金Supported by the CRSRI Open Research Program(CKWV2013225/KY)the Priority Academic Program Development of Jiangsu Higher Education Institution+2 种基金the Open Project Foundation of Key Laboratory of the Yellow River Sediment of Ministry of Water Resource(2014006)the State Key Lab of Urban Water Resource and Environment(HIT)(ES201409)the Open Project Program of State Key Laboratory of Food Science and Technology,Jiangnan University(SKLF-KF-201310)
文摘Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class uniformity of gray level,a method of reciprocal gray entropy threshold selection is proposed based on two-dimensional(2-D)histogram region oblique division and artificial bee colony(ABC)optimization.Firstly,the definition of reciprocal gray entropy is introduced.Then on the basis of one-dimensional(1-D)method,2-D threshold selection criterion function based on reciprocal gray entropy with histogram oblique division is derived.To accelerate the progress of searching the optimal threshold,the recently proposed ABC optimization algorithm is adopted.The proposed method not only avoids the undefined value points in Shannon entropy,but also achieves high accuracy and anti-noise performance due to reasonable 2-D histogram region division and the consideration of within-class uniformity of gray level.A large number of experimental results show that,compared with the maximum Shannon entropy method with 2-D histogram oblique division and the reciprocal entropy method with 2-D histogram oblique division based on niche chaotic mutation particle swarm optimization(NCPSO),the proposed method can achieve better segmentation results and can satisfy the requirement of real-time processing.
基金supported by the National Natural Science Foundation of China(62203458)the Stabilisation Support Project of the Bureau of Science and Industry(HTKJ2023KL502012)the Youth Autonomous Innovation Science Fund(ZK23-01).
文摘As the Mars probe,which has limited on-board ability in computation is unable to carry out the large-scale landmark solution,it is necessary to achieve optimal selection of landmarks while ensuring autonomous navigation accuracy during landing phase.This paper proposes an optimal landmark selection method based on the observability matrix for the Mars probe.Firstly,an observability matrix for navigation system is constructed with Fisher information quantity.Secondly,the optimal configuration of the landmark distribution is given by maximizing the scalar function of the observability matrix.Based on the optimal configuration,the greedy algorithm is used to determine the number of the landmarks at each moment adaptively.In addition,considering the fact that the number of the observable landmarks gradually decreases during the landing process,the convergence threshold of the greedy algorithm is set to a dynamic value regarding landing time.Finally,mathematical simulation verification is conducted,and the results show that the proposed optimal landmark selection method has higher navigation accuracy compared with the random landmark selection method.It can effectively suppress the influence of the measurement model errors and achieve a higher landing accuracy.
基金Sponsored by The National Natural Science Foundation of China(60872065)Science and Technology on Electro-optic Control Laboratory and Aviation Science Foundation(20105152026)State Key Laboratory Open Fund of Novel Software Technology,Nanjing University(KFKT2010B17)
文摘The image segmentation difficulties of small objects which are much smaller than their background often occur in target detection and recognition. The existing threshold segmentation methods almost fail under the circumstances. Thus, a threshold selection method is proposed on the basis of area difference between background and object and intra-class variance. The threshold selection formulae based on one-dimensional (1-D) histogram, two-dimensional (2-D) histogram vertical segmentation and 2-D histogram oblique segmentation are given. A fast recursive algorithm of threshold selection in 2-D histogram oblique segmentation is derived. The segmented images and processing time of the proposed method are given in experiments. It is compared with some fast algorithms, such as Otsu, maximum entropy and Fisher threshold selection methods. The experimental results show that the proposed method can effectively segment the small object images and has better anti-noise property.
文摘Relay selection is an effective method to realize the cooperative diversity gain in wireless networks. In this paper, we study a threshold-based single relay selection algorithm. A reasonable threshold value is set at each relay node, and the first relay with the instantaneous channel gain larger than the threshold will be se-lected to cooperate with the source. The exact and closed form expression for its outage probability is de-rived over independent, non-identically distributed (i. n. i. d) Rayleigh channels. The complexity of the algo-rithm is also analyzed in detail. Simulation results are presented to verify our theoretical analysis.
文摘In gene prediction, the Fisher discriminant analysis (FDA) is used to separate protein coding region (exon) from non-coding regions (intron). Usually, the positive data set and the negative data set are of the same size if the number of the data is big enough. But for some situations the data are not sufficient or not equal, the threshold used in FDA may have important influence on prediction results. This paper presents a study on the selection of the threshold. The eigen value of each exon/intron sequence is computed using the Z-curve method with 69 variables. The experiments results suggest that the size and the standard deviation of the data sets and the threshold are the three key elements to be taken into consideration to improve the prediction results.
基金the National High Level Talents Special Support Plan(X.C.)the“Young Talent Support Plan”of Xi'an Jiaotong University(X.C.)+2 种基金the Natural Science Foundation of Shaanxi Province(No.2022JZ-48 to X.C.)the National Natural Science Foundation of China(No.82272141 to X.C.)the Shaanxi Provincial Key Research and Development Plan Project(No.2023-JC-QN-0260 to X.Q.).
文摘The irregular defects and residual tumor tissue after surgery are challenges for effective breast cancer treatment.Herein,a smart hydrogel with self-adaptable size and dual responsive cargos release was fabricated to treat breast cancer via accurate tumor elimination,on-demand adipose tissue regeneration and effective infection inhibition.The hydrogel consisted of thiol groups ended polyethylene glycol(SH-PEG-SH)and doxorubicin encapsulated mesoporous silica nanocarriers(DOX@MSNs)double crosslinked hyaluronic acid(HA)after loading of antibacterial peptides(AP)and adipose-derived stem cells(ADSCs).A pH-cleavable unsaturated amide bond was pre-introduced between MSNs and HA frame to perform the tumor-specific acidic environment dependent DOX@MSNs release,meanwhile an esterase degradable glyceryl dimethacrylate cap was grafted on MSNs,which contributed to the selective chemotherapy in tumor cells with over-expressed esterase.The bond cleavage between MSNs and HA would also cause the swelling of the hydrogel,which not only provide sufficient space for the growth of ADSCs,but allows the hydrogel to fully fill the irregular defects generated by surgery and residual tumor atrophy,resulting in the on-demand regeneration of adipose tissue.Moreover,the sustained release of AP could be simultaneously triggered along with the size change of hydrogel,which further avoided bacterial infection to promote tissue regeneration.
基金The National Science and Technology Pillar Program of China(No.2015BAF07B00)
文摘In order to predict the extreme load of the mechanical components during the entire life,an automatic method based on the bootstrapping technology(BT)is proposed to determine the most suitable threshold.Based on all the turning points of the load history and a series of thresholds estimated in advance,the generalized Pareto distribution is established to fit the exceedances.The corresponding distribution parameters are estimated with the maximum likelihood method.Then,BT is employed to calculate the mean squared error(MSE)of each estimated threshold based on the exceedances and the specific distribution parameters.Finally,the threshold with the smallest MSE will be the optimal one.Compared to the kurtosis method and the mean excess function method,the average deviation of the probability density function of exceedances determined by BT reduces by 38.52%and 29.25%,respectively.Moreover,the quantile-quantile plot of the exceedances determined by BT is closer to a straight line.The results suggest the improvement of the modeling flexibility and the determined threshold precision.If the exceedances are insufficient,BT will enlarge their amount by resampling to solve the instability problem of the original distribution parameters.
基金Supported by the National Nature Science Foundation of China(50099620)the Project of Chenguang Plan in Wuhan(985003062)
文摘This paper analyzes the characteristics of the output gradient histogram and shortages of several traditional automatic threshold methods in order to segment the gradient image better.Then an improved double-threshold method is proposed,which is combined with the method of maximum classes variance,estimating-area method and double-threshold method.This method can automatically select two different thresholds to segment gradient images.The computer simulation is performed on the traditional methods and this algorithm and proves that this method can get satisfying result.
文摘Vocalizations play a critical role in mate recognition and mate choice in a number of taxa, especially, but not limited to, orthopterans, frogs, and birds. But receivers can only recognize and prefer sounds that they can hear. Thus a fundamental question linking neurobiology and sexual selection asks-what is the threshold for detecting acoustic sexual displays? In this study, we use 3 methods to assess such thresholds in tdngara frogs: behavioral responses, auditory brainstem responsesz and multi unit electrophysiological recordi ngs from the midbrain.We show that thresholds are lowest for multiunit recordings (ca. 45 dB SPL), and then for behavioral responses (ca. 61 dB SPL), with auditory brainstem responses exhibiting the highest thresholds (ca. 71 dB SPL). We discuss why these estimates differ and why, as with other studies, it is unlikely that they should be the same. Although all of these studies estimate thresholds they are not measuring the same thresholds;behavioral thresholds are based on signal salienee whereas the 2 neural assays estimate physiological thresholds. All 3 estimates, however, make it clear that to have an appreciation for detection and salienee of acoustic signals we must listen to those signals through the ears of the receivers.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11534008,11605126,and 11804271)the Fund from the Ministry of Science and Technology of China(Grant No.2016YFA0301404)+2 种基金the Natural Science Basic Research Plan in Shaanxi Province,China(Grant No.2017JQ1025)the Doctoral Fund of the Ministry of Education of China(Grant Nos.2016M592772 and 2018M631137)the Fundamental Research Funds for the Central Universities
文摘In ghost imaging, an illumination light is split into test and reference beams which pass through two different optical systems respectively and an image is constructed with the second-order correlation between the two light beams. Since both light beams are diffracted when passing through the optical systems, the spatial resolution of ghost imaging is in general lower than that of a corresponding conventional imaging system. When Gaussian-shaped light spots are used to illuminate an object, randomly scanning across the object plane, in the ghost imaging scheme, we show th√at by localizing central positions of the spots of the reference light beam, the resolution can be increased by a factor of 2^(1/2) same as that of the corresponding conventional imaging system. We also find that the resolution can be further enhanced by setting an appropriate threshold to the bucket measurement of ghost imaging.
基金supported by National Natural Science Foundation of China under Grant No.60872065Open Foundation of State Key Laboratory for Novel Software Technology at Nanjing University under Grant No.KFKT2010B17
文摘The segmentation effect of Tsallis entropy method is superior to that of Shannon entropy method, and the computation speed of two-dimensional Shannon cross entropy method can be further improved by optimization. The existing two-dimensional Tsallis cross entropy method is not the strict two-dimensional extension. Thus two new methods of image thresholding using two-dimensional Tsallis cross entropy based on either Chaotic Particle Swarm Optimization (CPSO) or decomposition are proposed. The former uses CPSO to find the optimal threshold. The recursive algorithm is adopted to avoid the repetitive computation of fitness function in iterative procedure. The computing speed is improved greatly. The latter converts the two-dimensional computation into two one-dimensional spaces, which makes the computational complexity further reduced from O(L2) to O(L). The experimental results show that, compared with the proposed recently two-dimensional Shannon or Tsallis cross entropy method, the two new methods can achieve superior segmentation results and reduce running time greatly.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11574101,11674116,11774111,and 11934006)the Open Fund of Hubei Provincial Key Laboratory of Optical Information and Pattern Recognition(Grant No.201902)the International Cooperation Program of Hubei Innovation Fund(Grant No.2019AHB052)。
文摘The high-resolution three-dimensional photoelectron momentum distributions via above-threshold ionization(ATI)of Xe atoms are measured in an intense near circularly polarized laser field using velocity map imaging and tomography reconstruction. Compared to the linearly polarized laser field, the employed near circularly polarized laser field imposes a more strict selection rule for the transition via resonant excitation, and therefore we can selectively enhance the resonant ATI through certain atomic Rydberg states. Our results show the self-reference ionization delay, which is determined from the difference between the measured streaking angles for nonadiabatic ATI via the 4 f and 5 f Rydberg states, is 45.6 as. Our method provides an accessible route to highlight the role of resonant transition between selected states, which will pave the way for fully understanding the ionization dynamics toward manipulating electron motion as well as reaction in an ultrafast time scale.
文摘针对视觉结构类似导致的文种相似性问题,基于局部三值模式的相邻共生矩阵(co-occurrence of adjacent local ternary patterns,CoALTP)提出一种具有判别性和鲁棒性的局部三值模式的相邻共生矩阵(discriminant and robust co-occurrence of adjacent local ternary patterns,DRCoALTP)方法,用于获取图像纹理。计算文档图像的相邻稀疏局部三值模式(adjacent sparse local ternary patterns,ASLTP),将采样点数量设定为8,以便获得详细的局部纹理,设计出一种基于自适应中值滤波思想的半自适应阈值方法,用于提取灰度图像中心像素周边对角邻域像素的编码值。ASLTP在邻域像素位置存放稀疏局部三值模式(local ternary patterns,LTP)的值,提取灰度共生矩阵(gray-level co-occurrence matrix,GLCM),从4个方向统计使用ASLTP后灰度图像像素之间的频率关系。该算法在阿拉伯文、俄文、简体中文、哈萨克文、藏文、蒙古文、土耳其文、维吾尔文、英文、吉尔吉斯斯坦文和塔吉克斯坦文11个文种的自建印刷体文档图像数据集中验证。试验结果表明,相较于基线和先进的纹理方法,改进后的方法更具判别性,平均识别准确率为99.14%。为改善CoALTP方法可能产生低效分类特征的问题,提出半自适应阈值方法,有效提高识别率并抑制噪声。此外,针对算法产生的高维特征,采用基于均方差的特征选择方法,通过支持向量机(support vector machine,SVM)分类器特征选择后,识别速度提高284%,对11个文种的平均识别准确率达99.44%。
