The performance of two models,Jam and Baig,based on the modified version of Gaussian distribution function in estimating the daily total of global solar radiation and its distribution through the hours of the day from...The performance of two models,Jam and Baig,based on the modified version of Gaussian distribution function in estimating the daily total of global solar radiation and its distribution through the hours of the day from sunrise to sunset al any clear day is evaluated with our own measured data in the period from June 1992 to May 1993 in Qena Egypt The results show a high relative deviation of calculated values from measured ones,especially for Jain model,in the most hours of the day,except for those near to local noon.This misfit behavior is quite obvious in the early morning and late afternoon A new approach has been proposed in this paper to estimate the daily and hourly global solar radiation This model performs with very high accuracy on the recorded data in our region.The validity of this approach was verified with new measurements in some clear days in June and August 1994.The resultant very low relative deviation of the calculated values of global solar radiation from the measured ones confirms the high performance of the approach proposed in this work展开更多
In microcantilever-based label-free biodetection technologies, deflection changes induced by adsorptions of double-stranded DNA （dsDNA） molecules on Au-layer surface are greatly affected by the mechanical, thermal a...In microcantilever-based label-free biodetection technologies, deflection changes induced by adsorptions of double-stranded DNA （dsDNA） molecules on Au-layer surface are greatly affected by the mechanical, thermal and electrical properties of DNA biofilm. In this paper, the elastic properties of dsDNA biofilm are studied. First, the Parsegian＇s empirical potential based on a mesoscopic liq- uid crystal theory is employed to describe the interaction energy among coarse-grained DNA cylinders. Then, con- sidering a Gaussian distribution of DNA interaxial distance, the thought experiment method is used to derive an analyti- cal expression for Young＇s modulus of DNA biofilm with a stochastic packing pattern for the first time. Results show that Young＇s modulus of DNA biofilm is on the order of 10 MPa. These findings could provide a simple and effective method to evaluate the mechanical properties of soft biofilm on snbstrate.展开更多
The 2D NMR(T_(1)-T_(2))mapping technique,which can be used to separate different proton populations from various sources(hydroxyls,solid organic matter,free water,and free HC)has gained attention in petroleum industry...The 2D NMR(T_(1)-T_(2))mapping technique,which can be used to separate different proton populations from various sources(hydroxyls,solid organic matter,free water,and free HC)has gained attention in petroleum industry.To separate proton contributions,a fixed straight line is commonly employed to separate different regions representing proton sources on the map.However,some of these regions(Region 1 and 2)might overlap which makes extracting the NMR signal amplitude from these regions inaccurate.In order to solve this issue,in this study,we applied the Gaussian distribution deconvolution method to separate the T_(1)and T_(2)relaxation distributions and then derived the signal amplitude of each region instead of following the common fixed line approach.Next,we employed this method to analyze several shale samples from the literature and compared the results following both methods to verify our methodology.Finally,samples from the Bakken Shale were studied to separate signals from Region 1 and Region 2 and corelated the results with geochemical properties that were obtained from programmed(Rock Eval)pyrolysis.Results demonstrated an improvement in their relation when our approach is employed compared to the fixed line technique to differentiate signal from overlapping regions.This means the Gaussian distribution deconvolution method can be used with confidence to provide us with more accurate petrophysical and geochemical understanding of complex formations.展开更多
A Au/Bi4Ti3O12/n-Si structure is fabricated in order to investigate its current voltage （IV） characteristics in a temperature range of 300 K-400 K. Obtained I-V data are evaluated by the thermionic emission （TE） t...A Au/Bi4Ti3O12/n-Si structure is fabricated in order to investigate its current voltage （IV） characteristics in a temperature range of 300 K-400 K. Obtained I-V data are evaluated by the thermionic emission （TE） theory. Zero-bias barrier height （Ф0） and ideality factor （n） calculated from I-V characteristics, are found to be temperature-dependent such that ФB0 increases with temperature increasing, whereas n decreases. The obtained temperature dependence of ФB0 and linearity in ФB0 versus the n plot, together with a lower barrier height and Richardson constant values obtained from the Richardson plot, indicate that the barrier height of the structure is inhomogeneous in nature. Therefore, I-V characteristics are explained on the basis of Caussian distribution of barrier height.展开更多
This paper introduces a sliding-window mean removal high pass filter by which background clutter of infrared multispectral image is obtained. The method of selecting the optimum size of the sliding-window is based on ...This paper introduces a sliding-window mean removal high pass filter by which background clutter of infrared multispectral image is obtained. The method of selecting the optimum size of the sliding-window is based on the skewness-kurtosis test. In the end, a multivariate Gaussian distribution mathematical expression of background clutter image is given.展开更多
Gaze estimation,a crucial non-verbal communication cue,has achieved remarkable progress through convolutional neural networks.However,accurate gaze prediction in uncon-strained environments,particularly in extreme hea...Gaze estimation,a crucial non-verbal communication cue,has achieved remarkable progress through convolutional neural networks.However,accurate gaze prediction in uncon-strained environments,particularly in extreme head poses,partial occlusions,and abnormal lighting,remains challenging.Existing models often struggle to effectively focus on discriminative ocular features,leading to suboptimal performance.To address these limitations,this paper proposes dual-branch gaze estimation with Gaussian mixture distribution heatmaps and dynamic adaptive loss function(DMGDL),a novel dual-branch gaze estimation algorithm.By introducing Gaussian mixture distribution heatmaps centered on pupil positions as spatial attention guides,the model is enabled to prioritize ocular regions.Additionally,a dual-branch network architecture is designed to separately extract features for yaw and pitch angles,enhancing flexibility and mitigating cross-angle interference.A dynamic adaptive loss function is further formulated to address discontinuities in angle estimation,improving robustness and convergence stability.Experimental evaluations on three benchmark datasets demonstrate that DMGDL outperforms state-of-the-art methods,achiev-ing a mean angular error of 3.98°on the Max-Planck institute for informatics face gaze(MPI-IFaceGaze)dataset,10.21°on the physically unconstrained gaze estimation in the wild(Gaze360)dataset and 6.14°on the real-time eye gaze estimation in natural environments(RT-Gene)dataset,exhibiting superior generalization and robustness.展开更多
Magnetic nanoscale systems,including nanodots,nanofibers,nanowires and nanoparticles,are currently attracting great interest due to their interesting physical and promising applications in various fields,such as magne...Magnetic nanoscale systems,including nanodots,nanofibers,nanowires and nanoparticles,are currently attracting great interest due to their interesting physical and promising applications in various fields,such as magnetic recording,sensors,target drugs and catalysts,as well as others.To achieve ultrahigh recording density,the method of heat assisted magnetic recording(HAMR) has been introduced.In this work,with the help of a Monte Carlo method,the mechanisms of thermally assisted magnetization switching in FePt single-domain particles driven by an external magnetic field are investigated,where the temperature in the particles is assumed to follow a Gaussian distribution.Two nucleation modes are observed for different distributions of temperature.One is initiated by many droplets,which join each other at the boundary of the system;the other is ini-tiated by many droplets at the boundary,but in growth tending toward the inner part of the system.An inverse proportional relationship between the metastable lifetime and the distribution is also found.展开更多
The famous de Moivre’s Laplace limit theorem proved the probability density function of Gaussian distribution from binomial probability mass function under specified conditions. De Moivre’s Laplace approach is cumbe...The famous de Moivre’s Laplace limit theorem proved the probability density function of Gaussian distribution from binomial probability mass function under specified conditions. De Moivre’s Laplace approach is cumbersome as it relies heavily on many lemmas and theorems. This paper invented an alternative and less rigorous method of deriving Gaussian distribution from basic random experiment conditional on some assumptions.展开更多
A detailed comparative examination of the Weibull and Gaussian statistical methods is offered to analyze the mechanical properties of natural date palm fibers. Tensile tests were conducted on 35 fiber samples using a ...A detailed comparative examination of the Weibull and Gaussian statistical methods is offered to analyze the mechanical properties of natural date palm fibers. Tensile tests were conducted on 35 fiber samples using a universal testing machine to gather data on stress, strain, and Young's modulus. This data was then analyzed through both statistical approaches to evaluate their ability to model important mechanical characteristics, including tensile strength, strain at break, and Young's modulus. The study identifies the strengths and weaknesses of each statistical method when it is applied to natural fibers, emphasizing their suitability for modeling different mechanical properties. The results of this analysis provide important insights that can guide the selection of the most appropriate statistical method, depending on the type of mechanical property being studied and the specific characteristics of the data. This research makes significant contributions to advancing the understanding of natural fiber mechanics and improving the methods used for their characterization.展开更多
In this paper, we explore the process of emotional state transition. And the process is impacted by emotional state of interaction objects. First of all, the cognitive reasoning process and the micro-expressions recog...In this paper, we explore the process of emotional state transition. And the process is impacted by emotional state of interaction objects. First of all, the cognitive reasoning process and the micro-expressions recognition is the basis of affective computing adjustment process. Secondly, the threshold function and attenuation function are proposed to quantify the emotional changes. In the actual environment, the emotional state of the robot and external stimulus are also quantified as the transferring probability. Finally, the Gaussian cloud distribution is introduced to the Gross model to calculate the emotional transitional probabilities. The experimental results show that the model in human-computer interaction can effectively regulate the emotional states, and can significantly improve the humanoid and intelligent ability of the robot. This model is consistent with experimental and emulational significance of the psychology, and allows the robot to get rid of the mechanical emotional transfer process.展开更多
Accurate modeling and parameter estimation of sea clutter are fundamental for effective sea surface target detection.With the improvement of radar resolution,sea clutter exhibits a pronounced heavy-tailed characterist...Accurate modeling and parameter estimation of sea clutter are fundamental for effective sea surface target detection.With the improvement of radar resolution,sea clutter exhibits a pronounced heavy-tailed characteristic,rendering traditional distribution models and parameter estimation methods less effective.To address this,this paper proposes a dual compound-Gaussian model with inverse Gaussian texture(CG-IG)distribution model and combines it with an improved Adam algorithm to introduce a method for parameter correction.This method effectively fits sea clutter with heavy-tailed characteristics.Experiments with real measured sea clutter data show that the dual CGIG distribution model,after parameter correction,accurately describes the heavy-tailed phenomenon in sea clutter amplitude distribution,and the overall mean square error of the distribution is reduced.展开更多
Securing restricted zones such as airports,research facilities,and military bases requires robust and reliable access control mechanisms to prevent unauthorized entry and safeguard critical assets.Face recognition has...Securing restricted zones such as airports,research facilities,and military bases requires robust and reliable access control mechanisms to prevent unauthorized entry and safeguard critical assets.Face recognition has emerged as a key biometric approach for this purpose;however,existing systems are often sensitive to variations in illumination,occlusion,and pose,which degrade their performance in real-world conditions.To address these challenges,this paper proposes a novel hybrid face recognition method that integrates complementary feature descriptors such as Fuzzy-Gabor 2D Fisher Linear Discriminant(FG-2DFLD),Generalized 2D Linear Discriminant Analysis(G2DLDA),andModular-Local Binary Patterns(Modular-LBP)with Dempster–Shafer(DS)evidence theory for decision fusion.The proposed framework extracts global,structural,and local texture features,models them using Gaussian distributions to estimate belief factors,and fuses these belief factors through DS theory to explicitly handle uncertainty and conflict among descriptors.Experimental validation was performed on two widely used benchmark datasets,ORL and Cropped Yale B,achieving recognition rates exceeding 98%,which outperform traditional methods as well as recent deep learning-based approaches.Furthermore,the method demonstrated strong robustness under noisy conditions,maintaining accuracies above 96%with salt-and-pepper and Gaussian noise.These results highlight the effectiveness of the proposed integration strategy in enhancing accuracy,reliability,and resilience compared to single-descriptor and conventional fusion methods.Given its high performance and efficiency,the proposed method shows strong potential for deployment in real-world restricted-zone applications such as smart parking systems,secure facility access,and other high-security domains.展开更多
With the increasing complexity of industrial processes, the high-dimensional industrial data exhibit a strong nonlinearity, bringing considerable challenges to the fault diagnosis of industrial processes. To efficient...With the increasing complexity of industrial processes, the high-dimensional industrial data exhibit a strong nonlinearity, bringing considerable challenges to the fault diagnosis of industrial processes. To efficiently extract deep meaningful features that are crucial for fault diagnosis, a sparse Gaussian feature extractor(SGFE) is designed to learn a nonlinear mapping that projects the raw data into the feature space with the fault label dimension. The feature space is described by the one-hot encoding of the fault category label as an orthogonal basis. In this way, the deep sparse Gaussian features related to fault categories can be gradually learned from the raw data by SGFE. In the feature space,the sparse Gaussian(SG) loss function is designed to constrain the distribution of features to multiple sparse multivariate Gaussian distributions. The sparse Gaussian features are linearly separable in the feature space, which is conducive to improving the accuracy of the downstream fault classification task. The feasibility and practical utility of the proposed SGFE are verified by the handwritten digits MNIST benchmark and Tennessee-Eastman(TE) benchmark process,respectively.展开更多
The Gaussian spin model with periodic interactions on the diamond-type hierarchical lattices is constructed by generalizing that with uniform interactions on translationally invariant lattices according to a class of ...The Gaussian spin model with periodic interactions on the diamond-type hierarchical lattices is constructed by generalizing that with uniform interactions on translationally invariant lattices according to a class of substitution sequences. The Gaussian distribution constants and imposed external magnetic fields are also periodic depending on the periodic characteristic of the interaction bonds. The critical behaviors of this generalized Gaussian model in external magnetic fields are studied by the exact renormalization-group approach and spin rescaling method. The critical points and all the critical exponents are obtained. The critical behaviors are found to be determined by the Gaussian distribution constants and the fractal dimensions of the lattices. When all the Gaussian distribution constants are the same, the dependence of the critical exponents on the dimensions of the lattices is the same as that of the Gaussian model with uniform interactions on translationally invariant lattices.展开更多
The multi-pass turning operation is one of the most commonly used machining methods in manufacturing field.The main objective of this operation is to minimize the unit production cost.This paper proposes a Gaussian qu...The multi-pass turning operation is one of the most commonly used machining methods in manufacturing field.The main objective of this operation is to minimize the unit production cost.This paper proposes a Gaussian quantum-behaved bat algorithm(GQBA)to solve the problem of multi-pass turning operation.The proposed algorithm mainly includes the following two improvements.The first improvement is to incorporate the current optimal positions of quantum bats and the global best position into the stochastic attractor to facilitate population diversification.The second improvement is to use a Gaussian distribution instead of the uniform distribution to update the positions of the quantum-behaved bats,thus performing a more accurate search and avoiding premature convergence.The performance of the presented GQBA is demonstrated through numerical benchmark functions and amulti-pass turning operation problem.Thirteen classical benchmark functions are utilized in the comparison experiments,and the experimental results for accuracy and convergence speed demonstrate that,in most cases,the GQBA can provide a better search capability than other algorithms.Furthermore,GQBA is applied to an optimization problem formulti-pass turning,which is designed tominimize the production cost while considering many practical machining constraints in the machining process.The experimental results indicate that the GQBA outperforms other comparison algorithms in terms of cost reduction,which proves the effectiveness of the GQBA.展开更多
Within the framework of the correlation theory of electromagnetic laser beams,the far field cross-spectral density matrix of the light radiated from an electromagnetic Hermite-Gaussian model source is derived.By utili...Within the framework of the correlation theory of electromagnetic laser beams,the far field cross-spectral density matrix of the light radiated from an electromagnetic Hermite-Gaussian model source is derived.By utilizing the convergence property of Hermite polynomials,the conditions of the matrices for the source to generate an electromagnetic Hermite-Gaussian beam are obtained.Furthermore,in order to generate a scalar Hermite-Gaussian model beam,it is required that the source should be locally rather coherent in the spatial domain.展开更多
Deep Neural Networks(DNNs)are integral to various aspects of modern life,enhancing work efficiency.Nonethe-less,their susceptibility to diverse attack methods,including backdoor attacks,raises security concerns.We aim...Deep Neural Networks(DNNs)are integral to various aspects of modern life,enhancing work efficiency.Nonethe-less,their susceptibility to diverse attack methods,including backdoor attacks,raises security concerns.We aim to investigate backdoor attack methods for image categorization tasks,to promote the development of DNN towards higher security.Research on backdoor attacks currently faces significant challenges due to the distinct and abnormal data patterns of malicious samples,and the meticulous data screening by developers,hindering practical attack implementation.To overcome these challenges,this study proposes a Gaussian Noise-Targeted Universal Adversarial Perturbation(GN-TUAP)algorithm.This approach restricts the direction of perturbations and normalizes abnormal pixel values,ensuring that perturbations progress as much as possible in a direction perpendicular to the decision hyperplane in linear problems.This limits anomalies within the perturbations improves their visual stealthiness,and makes them more challenging for defense methods to detect.To verify the effectiveness,stealthiness,and robustness of GN-TUAP,we proposed a comprehensive threat model.Based on this model,extensive experiments were conducted using the CIFAR-10,CIFAR-100,GTSRB,and MNIST datasets,comparing our method with existing state-of-the-art attack methods.We also tested our perturbation triggers using various defense methods and further experimented on the robustness of the triggers against noise filtering techniques.The experimental outcomes demonstrate that backdoor attacks leveraging perturbations generated via our algorithm exhibit cross-model attack effectiveness and superior stealthiness.Furthermore,they possess robust anti-detection capabilities and maintain commendable performance when subjected to noise-filtering methods.展开更多
Based on the coherence theory of diffracted optical field and the model for partially coherent beams,analytical expressions for the cross-spectral density and the irradiance spectral density in the far zone are derive...Based on the coherence theory of diffracted optical field and the model for partially coherent beams,analytical expressions for the cross-spectral density and the irradiance spectral density in the far zone are derived,respectively.Utilizing the theoretical model of radiation from secondary planar sources,the physical conditions for sources generating a cosh-Gaussian(CHG) beam are investigated.Analytical results demonstrate that the parametric conditions strongly depend on the coherence property of sources.When almost coherence property is satisfied in the source plane,the conditions are the same as those for fundamental Gaussian beams;when partial coherence or almost incoherence property is satisfied in the spatial source plane,the conditions are the same as those for Gaussian-Schell model beams.The results also indicate that the variance of cosine parameters has no influence on the conditions.Our results may provide potential applications for some investigations such as the modulations of cosh-Gaussian beams and the designs of source beam parameters.展开更多
In order to explore the seed drop characteristics by aerial seeding equipment,taking aerial seeding for Pinus tabulaeformis as an example,the Gaussian curve fitting and chi-square goodness-of-fit test were carried out...In order to explore the seed drop characteristics by aerial seeding equipment,taking aerial seeding for Pinus tabulaeformis as an example,the Gaussian curve fitting and chi-square goodness-of-fit test were carried out on the data of fallen seed distribution,and the seed distribution models of domestic FB-85 and imported PZLM-18 equipment were established.The seeding performance indexes of the two kinds of equipment were calculated and compared by using the model,the existing problems of domestic equipment and their causes are analyzed,and finally,some suggestions for equipment optimization were put forward.The results indicated that the seed drop of the two kinds of equipment showed the characteristics of dense distribution in the middle and sparse distribution on both sides,and followed the Gaussian distribution as a whole;compared with PZLM-18,FB-85 had better seeding performance,but it also had the problem of uneven seed distribution;in addition to the influence of aircraft flow field,the fishtail structure design of diffuser is another important reason for the uneven seed distribution of domestic equipment;without changing the fishtail structure design,it is suggested that the principle of cross-superposition of two seeding belts should be used to replace a single large-size diffuser with two small-size diffusers,which can reduce the number of seeds in the middle and increase the number of seeds on both sides,so as to improve the uniformity of seed distribution.展开更多
Based on the Eigen and Crow-Kimura models with a single-peak fitness landscape, we propose the fitness values of all sequence types to be Gausslan distributed random variables to incorporate the effects of the fluctua...Based on the Eigen and Crow-Kimura models with a single-peak fitness landscape, we propose the fitness values of all sequence types to be Gausslan distributed random variables to incorporate the effects of the fluctuations of the fitness landscapes （noise of environments） and investigate the concentration distribution and error threshold of quasispecies by performing an ensemble average within this theoretical framework. We find that a small fluctuation of the fitness landscape causes only a slight change in the concentration distribution and error threshold, which implies that the error threshold is stable against small perturbations. However, for a sizable fluctuation, quite different from the previous deterministic models, our statistical results show that the transition from quasi-species to error catastrophe is not so sharp, indicating that the error threshold is located within a certain range and has a shift toward a larger value. Our results are qualitatively in agreement with the experimental data and provide a new implication for antiviral strategies.展开更多
文摘The performance of two models,Jam and Baig,based on the modified version of Gaussian distribution function in estimating the daily total of global solar radiation and its distribution through the hours of the day from sunrise to sunset al any clear day is evaluated with our own measured data in the period from June 1992 to May 1993 in Qena Egypt The results show a high relative deviation of calculated values from measured ones,especially for Jain model,in the most hours of the day,except for those near to local noon.This misfit behavior is quite obvious in the early morning and late afternoon A new approach has been proposed in this paper to estimate the daily and hourly global solar radiation This model performs with very high accuracy on the recorded data in our region.The validity of this approach was verified with new measurements in some clear days in June and August 1994.The resultant very low relative deviation of the calculated values of global solar radiation from the measured ones confirms the high performance of the approach proposed in this work
基金supported by the National Natural Science Foundation of China(11272193 and 10872121)the Shanghai Leading Academic Discipline Project(S30106)
文摘In microcantilever-based label-free biodetection technologies, deflection changes induced by adsorptions of double-stranded DNA （dsDNA） molecules on Au-layer surface are greatly affected by the mechanical, thermal and electrical properties of DNA biofilm. In this paper, the elastic properties of dsDNA biofilm are studied. First, the Parsegian＇s empirical potential based on a mesoscopic liq- uid crystal theory is employed to describe the interaction energy among coarse-grained DNA cylinders. Then, con- sidering a Gaussian distribution of DNA interaxial distance, the thought experiment method is used to derive an analyti- cal expression for Young＇s modulus of DNA biofilm with a stochastic packing pattern for the first time. Results show that Young＇s modulus of DNA biofilm is on the order of 10 MPa. These findings could provide a simple and effective method to evaluate the mechanical properties of soft biofilm on snbstrate.
基金support from the National Natural Science Foundation of China(42090020,42090025,42272150)the Sinopec Science and Technology Department(No.P20049-1).
文摘The 2D NMR(T_(1)-T_(2))mapping technique,which can be used to separate different proton populations from various sources(hydroxyls,solid organic matter,free water,and free HC)has gained attention in petroleum industry.To separate proton contributions,a fixed straight line is commonly employed to separate different regions representing proton sources on the map.However,some of these regions(Region 1 and 2)might overlap which makes extracting the NMR signal amplitude from these regions inaccurate.In order to solve this issue,in this study,we applied the Gaussian distribution deconvolution method to separate the T_(1)and T_(2)relaxation distributions and then derived the signal amplitude of each region instead of following the common fixed line approach.Next,we employed this method to analyze several shale samples from the literature and compared the results following both methods to verify our methodology.Finally,samples from the Bakken Shale were studied to separate signals from Region 1 and Region 2 and corelated the results with geochemical properties that were obtained from programmed(Rock Eval)pyrolysis.Results demonstrated an improvement in their relation when our approach is employed compared to the fixed line technique to differentiate signal from overlapping regions.This means the Gaussian distribution deconvolution method can be used with confidence to provide us with more accurate petrophysical and geochemical understanding of complex formations.
基金Project supported by the Diizce University Scientific Research Project(Grant Nos.2010.05.02.056 and 2012.05.02.110)
文摘A Au/Bi4Ti3O12/n-Si structure is fabricated in order to investigate its current voltage （IV） characteristics in a temperature range of 300 K-400 K. Obtained I-V data are evaluated by the thermionic emission （TE） theory. Zero-bias barrier height （Ф0） and ideality factor （n） calculated from I-V characteristics, are found to be temperature-dependent such that ФB0 increases with temperature increasing, whereas n decreases. The obtained temperature dependence of ФB0 and linearity in ФB0 versus the n plot, together with a lower barrier height and Richardson constant values obtained from the Richardson plot, indicate that the barrier height of the structure is inhomogeneous in nature. Therefore, I-V characteristics are explained on the basis of Caussian distribution of barrier height.
文摘This paper introduces a sliding-window mean removal high pass filter by which background clutter of infrared multispectral image is obtained. The method of selecting the optimum size of the sliding-window is based on the skewness-kurtosis test. In the end, a multivariate Gaussian distribution mathematical expression of background clutter image is given.
基金supported by the Key Project of the NationalLanguage Commission(No.ZDI145-110)the AcademicResearch Projects of Beijing Union University(No.ZK20202514)+1 种基金the Key Laboratory Project(No.YYZN-2024-6)the Project for the Construction and Support of High-Level Innovative Teams in Beijing Municipal Institutions(No.BPHR20220121).
文摘Gaze estimation,a crucial non-verbal communication cue,has achieved remarkable progress through convolutional neural networks.However,accurate gaze prediction in uncon-strained environments,particularly in extreme head poses,partial occlusions,and abnormal lighting,remains challenging.Existing models often struggle to effectively focus on discriminative ocular features,leading to suboptimal performance.To address these limitations,this paper proposes dual-branch gaze estimation with Gaussian mixture distribution heatmaps and dynamic adaptive loss function(DMGDL),a novel dual-branch gaze estimation algorithm.By introducing Gaussian mixture distribution heatmaps centered on pupil positions as spatial attention guides,the model is enabled to prioritize ocular regions.Additionally,a dual-branch network architecture is designed to separately extract features for yaw and pitch angles,enhancing flexibility and mitigating cross-angle interference.A dynamic adaptive loss function is further formulated to address discontinuities in angle estimation,improving robustness and convergence stability.Experimental evaluations on three benchmark datasets demonstrate that DMGDL outperforms state-of-the-art methods,achiev-ing a mean angular error of 3.98°on the Max-Planck institute for informatics face gaze(MPI-IFaceGaze)dataset,10.21°on the physically unconstrained gaze estimation in the wild(Gaze360)dataset and 6.14°on the real-time eye gaze estimation in natural environments(RT-Gene)dataset,exhibiting superior generalization and robustness.
基金support by the Fund for Talents Introduction of Chongqing University of Arts and Sciences (Grant No. Z2011RCYJ03)
文摘Magnetic nanoscale systems,including nanodots,nanofibers,nanowires and nanoparticles,are currently attracting great interest due to their interesting physical and promising applications in various fields,such as magnetic recording,sensors,target drugs and catalysts,as well as others.To achieve ultrahigh recording density,the method of heat assisted magnetic recording(HAMR) has been introduced.In this work,with the help of a Monte Carlo method,the mechanisms of thermally assisted magnetization switching in FePt single-domain particles driven by an external magnetic field are investigated,where the temperature in the particles is assumed to follow a Gaussian distribution.Two nucleation modes are observed for different distributions of temperature.One is initiated by many droplets,which join each other at the boundary of the system;the other is ini-tiated by many droplets at the boundary,but in growth tending toward the inner part of the system.An inverse proportional relationship between the metastable lifetime and the distribution is also found.
文摘The famous de Moivre’s Laplace limit theorem proved the probability density function of Gaussian distribution from binomial probability mass function under specified conditions. De Moivre’s Laplace approach is cumbersome as it relies heavily on many lemmas and theorems. This paper invented an alternative and less rigorous method of deriving Gaussian distribution from basic random experiment conditional on some assumptions.
文摘A detailed comparative examination of the Weibull and Gaussian statistical methods is offered to analyze the mechanical properties of natural date palm fibers. Tensile tests were conducted on 35 fiber samples using a universal testing machine to gather data on stress, strain, and Young's modulus. This data was then analyzed through both statistical approaches to evaluate their ability to model important mechanical characteristics, including tensile strength, strain at break, and Young's modulus. The study identifies the strengths and weaknesses of each statistical method when it is applied to natural fibers, emphasizing their suitability for modeling different mechanical properties. The results of this analysis provide important insights that can guide the selection of the most appropriate statistical method, depending on the type of mechanical property being studied and the specific characteristics of the data. This research makes significant contributions to advancing the understanding of natural fiber mechanics and improving the methods used for their characterization.
文摘In this paper, we explore the process of emotional state transition. And the process is impacted by emotional state of interaction objects. First of all, the cognitive reasoning process and the micro-expressions recognition is the basis of affective computing adjustment process. Secondly, the threshold function and attenuation function are proposed to quantify the emotional changes. In the actual environment, the emotional state of the robot and external stimulus are also quantified as the transferring probability. Finally, the Gaussian cloud distribution is introduced to the Gross model to calculate the emotional transitional probabilities. The experimental results show that the model in human-computer interaction can effectively regulate the emotional states, and can significantly improve the humanoid and intelligent ability of the robot. This model is consistent with experimental and emulational significance of the psychology, and allows the robot to get rid of the mechanical emotional transfer process.
文摘Accurate modeling and parameter estimation of sea clutter are fundamental for effective sea surface target detection.With the improvement of radar resolution,sea clutter exhibits a pronounced heavy-tailed characteristic,rendering traditional distribution models and parameter estimation methods less effective.To address this,this paper proposes a dual compound-Gaussian model with inverse Gaussian texture(CG-IG)distribution model and combines it with an improved Adam algorithm to introduce a method for parameter correction.This method effectively fits sea clutter with heavy-tailed characteristics.Experiments with real measured sea clutter data show that the dual CGIG distribution model,after parameter correction,accurately describes the heavy-tailed phenomenon in sea clutter amplitude distribution,and the overall mean square error of the distribution is reduced.
文摘Securing restricted zones such as airports,research facilities,and military bases requires robust and reliable access control mechanisms to prevent unauthorized entry and safeguard critical assets.Face recognition has emerged as a key biometric approach for this purpose;however,existing systems are often sensitive to variations in illumination,occlusion,and pose,which degrade their performance in real-world conditions.To address these challenges,this paper proposes a novel hybrid face recognition method that integrates complementary feature descriptors such as Fuzzy-Gabor 2D Fisher Linear Discriminant(FG-2DFLD),Generalized 2D Linear Discriminant Analysis(G2DLDA),andModular-Local Binary Patterns(Modular-LBP)with Dempster–Shafer(DS)evidence theory for decision fusion.The proposed framework extracts global,structural,and local texture features,models them using Gaussian distributions to estimate belief factors,and fuses these belief factors through DS theory to explicitly handle uncertainty and conflict among descriptors.Experimental validation was performed on two widely used benchmark datasets,ORL and Cropped Yale B,achieving recognition rates exceeding 98%,which outperform traditional methods as well as recent deep learning-based approaches.Furthermore,the method demonstrated strong robustness under noisy conditions,maintaining accuracies above 96%with salt-and-pepper and Gaussian noise.These results highlight the effectiveness of the proposed integration strategy in enhancing accuracy,reliability,and resilience compared to single-descriptor and conventional fusion methods.Given its high performance and efficiency,the proposed method shows strong potential for deployment in real-world restricted-zone applications such as smart parking systems,secure facility access,and other high-security domains.
基金Projects(62125306, 62133003) supported by the National Natural Science Foundation of ChinaProject(TPL2019C03) supported by the Open Fund of Science and Technology on Thermal Energy and Power Laboratory,ChinaProject supported by the Fundamental Research Funds for the Central Universities(Zhejiang University NGICS Platform),China。
文摘With the increasing complexity of industrial processes, the high-dimensional industrial data exhibit a strong nonlinearity, bringing considerable challenges to the fault diagnosis of industrial processes. To efficiently extract deep meaningful features that are crucial for fault diagnosis, a sparse Gaussian feature extractor(SGFE) is designed to learn a nonlinear mapping that projects the raw data into the feature space with the fault label dimension. The feature space is described by the one-hot encoding of the fault category label as an orthogonal basis. In this way, the deep sparse Gaussian features related to fault categories can be gradually learned from the raw data by SGFE. In the feature space,the sparse Gaussian(SG) loss function is designed to constrain the distribution of features to multiple sparse multivariate Gaussian distributions. The sparse Gaussian features are linearly separable in the feature space, which is conducive to improving the accuracy of the downstream fault classification task. The feasibility and practical utility of the proposed SGFE are verified by the handwritten digits MNIST benchmark and Tennessee-Eastman(TE) benchmark process,respectively.
文摘The Gaussian spin model with periodic interactions on the diamond-type hierarchical lattices is constructed by generalizing that with uniform interactions on translationally invariant lattices according to a class of substitution sequences. The Gaussian distribution constants and imposed external magnetic fields are also periodic depending on the periodic characteristic of the interaction bonds. The critical behaviors of this generalized Gaussian model in external magnetic fields are studied by the exact renormalization-group approach and spin rescaling method. The critical points and all the critical exponents are obtained. The critical behaviors are found to be determined by the Gaussian distribution constants and the fractal dimensions of the lattices. When all the Gaussian distribution constants are the same, the dependence of the critical exponents on the dimensions of the lattices is the same as that of the Gaussian model with uniform interactions on translationally invariant lattices.
基金supported by the the National Natural Science Foundation of Fujian Province of China (2020J01697,2020J01699).
文摘The multi-pass turning operation is one of the most commonly used machining methods in manufacturing field.The main objective of this operation is to minimize the unit production cost.This paper proposes a Gaussian quantum-behaved bat algorithm(GQBA)to solve the problem of multi-pass turning operation.The proposed algorithm mainly includes the following two improvements.The first improvement is to incorporate the current optimal positions of quantum bats and the global best position into the stochastic attractor to facilitate population diversification.The second improvement is to use a Gaussian distribution instead of the uniform distribution to update the positions of the quantum-behaved bats,thus performing a more accurate search and avoiding premature convergence.The performance of the presented GQBA is demonstrated through numerical benchmark functions and amulti-pass turning operation problem.Thirteen classical benchmark functions are utilized in the comparison experiments,and the experimental results for accuracy and convergence speed demonstrate that,in most cases,the GQBA can provide a better search capability than other algorithms.Furthermore,GQBA is applied to an optimization problem formulti-pass turning,which is designed tominimize the production cost while considering many practical machining constraints in the machining process.The experimental results indicate that the GQBA outperforms other comparison algorithms in terms of cost reduction,which proves the effectiveness of the GQBA.
基金supported by the National High Technology Research and Development Program of China (No. 2007AA04Z181)the National Natural Science Foundation of China (No. 61077012)+1 种基金the Research Fund of this University (No.2010ZYTS031)the Excellent Doctorial Candidate Training Fund in this University
文摘Within the framework of the correlation theory of electromagnetic laser beams,the far field cross-spectral density matrix of the light radiated from an electromagnetic Hermite-Gaussian model source is derived.By utilizing the convergence property of Hermite polynomials,the conditions of the matrices for the source to generate an electromagnetic Hermite-Gaussian beam are obtained.Furthermore,in order to generate a scalar Hermite-Gaussian model beam,it is required that the source should be locally rather coherent in the spatial domain.
基金funded by National Natural Science Foundation of China under Grant No.61806171The Sichuan University of Science&Engineering Talent Project under Grant No.2021RC15Sichuan University of Science&Engineering Graduate Student Innovation Fund under Grant No.Y2023115,The Scientific Research and Innovation Team Program of Sichuan University of Science and Technology under Grant No.SUSE652A006.
文摘Deep Neural Networks(DNNs)are integral to various aspects of modern life,enhancing work efficiency.Nonethe-less,their susceptibility to diverse attack methods,including backdoor attacks,raises security concerns.We aim to investigate backdoor attack methods for image categorization tasks,to promote the development of DNN towards higher security.Research on backdoor attacks currently faces significant challenges due to the distinct and abnormal data patterns of malicious samples,and the meticulous data screening by developers,hindering practical attack implementation.To overcome these challenges,this study proposes a Gaussian Noise-Targeted Universal Adversarial Perturbation(GN-TUAP)algorithm.This approach restricts the direction of perturbations and normalizes abnormal pixel values,ensuring that perturbations progress as much as possible in a direction perpendicular to the decision hyperplane in linear problems.This limits anomalies within the perturbations improves their visual stealthiness,and makes them more challenging for defense methods to detect.To verify the effectiveness,stealthiness,and robustness of GN-TUAP,we proposed a comprehensive threat model.Based on this model,extensive experiments were conducted using the CIFAR-10,CIFAR-100,GTSRB,and MNIST datasets,comparing our method with existing state-of-the-art attack methods.We also tested our perturbation triggers using various defense methods and further experimented on the robustness of the triggers against noise filtering techniques.The experimental outcomes demonstrate that backdoor attacks leveraging perturbations generated via our algorithm exhibit cross-model attack effectiveness and superior stealthiness.Furthermore,they possess robust anti-detection capabilities and maintain commendable performance when subjected to noise-filtering methods.
文摘Based on the coherence theory of diffracted optical field and the model for partially coherent beams,analytical expressions for the cross-spectral density and the irradiance spectral density in the far zone are derived,respectively.Utilizing the theoretical model of radiation from secondary planar sources,the physical conditions for sources generating a cosh-Gaussian(CHG) beam are investigated.Analytical results demonstrate that the parametric conditions strongly depend on the coherence property of sources.When almost coherence property is satisfied in the source plane,the conditions are the same as those for fundamental Gaussian beams;when partial coherence or almost incoherence property is satisfied in the spatial source plane,the conditions are the same as those for Gaussian-Schell model beams.The results also indicate that the variance of cosine parameters has no influence on the conditions.Our results may provide potential applications for some investigations such as the modulations of cosh-Gaussian beams and the designs of source beam parameters.
文摘In order to explore the seed drop characteristics by aerial seeding equipment,taking aerial seeding for Pinus tabulaeformis as an example,the Gaussian curve fitting and chi-square goodness-of-fit test were carried out on the data of fallen seed distribution,and the seed distribution models of domestic FB-85 and imported PZLM-18 equipment were established.The seeding performance indexes of the two kinds of equipment were calculated and compared by using the model,the existing problems of domestic equipment and their causes are analyzed,and finally,some suggestions for equipment optimization were put forward.The results indicated that the seed drop of the two kinds of equipment showed the characteristics of dense distribution in the middle and sparse distribution on both sides,and followed the Gaussian distribution as a whole;compared with PZLM-18,FB-85 had better seeding performance,but it also had the problem of uneven seed distribution;in addition to the influence of aircraft flow field,the fishtail structure design of diffuser is another important reason for the uneven seed distribution of domestic equipment;without changing the fishtail structure design,it is suggested that the principle of cross-superposition of two seeding belts should be used to replace a single large-size diffuser with two small-size diffusers,which can reduce the number of seeds in the middle and increase the number of seeds on both sides,so as to improve the uniformity of seed distribution.
基金The project supported by National Natural Science Foundation of China under Grant Nos. 10475008, 10675170, and 10435020, and the Department of Nuclear Physics of China Institute of Atomic Energy under Grant Nos. 11SZZ-200501 and 11SZZ-200601
文摘Based on the Eigen and Crow-Kimura models with a single-peak fitness landscape, we propose the fitness values of all sequence types to be Gausslan distributed random variables to incorporate the effects of the fluctuations of the fitness landscapes （noise of environments） and investigate the concentration distribution and error threshold of quasispecies by performing an ensemble average within this theoretical framework. We find that a small fluctuation of the fitness landscape causes only a slight change in the concentration distribution and error threshold, which implies that the error threshold is stable against small perturbations. However, for a sizable fluctuation, quite different from the previous deterministic models, our statistical results show that the transition from quasi-species to error catastrophe is not so sharp, indicating that the error threshold is located within a certain range and has a shift toward a larger value. Our results are qualitatively in agreement with the experimental data and provide a new implication for antiviral strategies.
