It is of great scientific significance to construct a 3D dynamic structural color with a special color effect based on the microlens array.However,the problems of imperfect mechanisms and poor color quality need to be...It is of great scientific significance to construct a 3D dynamic structural color with a special color effect based on the microlens array.However,the problems of imperfect mechanisms and poor color quality need to be solved.A method of 3D structural color turning on periodic metasurfaces fabricated by the microlens array and self-assembly technology was proposed in this study.In the experiment,Polydimethylsiloxane(PDMS)flexible film was used as a substrate,and SiO2 microspheres were scraped into grooves of the PDMS film to form 3D photonic crystal structures.By adjusting the number of blade-coated times and microsphere concentrations,high-saturation structural color micropatterns were obtained.These films were then matched with microlens arrays to produce dynamic graphics with iridescent effects.The results showed that by blade-coated two times and SiO2 microsphere concentrations of 50%are the best conditions.This method demonstrates the potential for being widely applied in the anticounterfeiting printing and ultra-high-resolution display.展开更多
In the context of the deep integration of digitalization and innovation and entrepreneurship education,this study focuses on the characteristics of schools and courses,investigates students’expectations and needs for...In the context of the deep integration of digitalization and innovation and entrepreneurship education,this study focuses on the characteristics of schools and courses,investigates students’expectations and needs for ideological and political elements,and deeply explores ideological and political cases such as the Beidahuang spirit,Daqing spirit,model worker spirit,and role models around them.It explores the integration practice of“curriculum ideological and political”in extracurricular tutoring teaching of engineering graphics,aiming to guide students to establish patriotism,love for schools,knowledge of agriculture,and love for agriculture,and effectively enhance the coordinated development of students’graphic skills and ideological and political literacy.Practice has shown that integrating ideological and political resources,incorporating ideological and political elements into curriculum content and practical activities,can effectively enhance the collaborative development of students’graphic skills and ideological and political literacy.At the same time,it provides new ideas and references for expanding ideological and political education to extracurricular tutoring courses.展开更多
The newly emerging neural radiance fields(NeRF)methods can implicitly fulfill three-dimensional(3D)reconstruction via training a neural network to render novel-view images of a given scene with given posed images.The ...The newly emerging neural radiance fields(NeRF)methods can implicitly fulfill three-dimensional(3D)reconstruction via training a neural network to render novel-view images of a given scene with given posed images.The Instant Neural Graphics Primitives(Instant-NGP)method further improves the position encoding of NeRF.It obtains state-of-the-art efficiency.However,only a local pixel-wised loss is considered when training the Instant-NGP while overlooking the nonlocal structural information between pixels.Despite a good quantitative result,it leads to a poor visual effect,especially the completeness.Inspired by the stochastic structural similarity(S3IM)method that exploits nonlocal structural information of groups of pixels,this paper proposes a new method to improve the completeness of fast novel view synthesis.The proposed method first extends the thread-wised processing of the Instant-NGP to the processing in a customthread block(i.e.,a group of threads).Then,the relative dimensionless global error in synthesis,i.e.,Erreur Relative Globale Adimensionnelle de Synthese(ERGAS),of a group of pixels corresponding to a group of threads is computed and incorporated into the loss function.Extensive experiments validate the proposed method.It can obtain better quantitative results than the original Instant-NGP with fewer iteration steps.PSNR is increased by 1%.Amazing qualitative results are obtained,especially for delicate structures and details such as lines and continuous structures.With the dramatic improvements in the visual effects,our method can boost the practicability of implicit 3D reconstruction in applications such as self-driving and augmented reality.展开更多
Graph neural networks(GNN)have shown strong performance in node classification tasks,yet most existing models rely on uniform or shared weight aggregation,lacking flexibility in modeling the varying strength of relati...Graph neural networks(GNN)have shown strong performance in node classification tasks,yet most existing models rely on uniform or shared weight aggregation,lacking flexibility in modeling the varying strength of relationships among nodes.This paper proposes a novel graph coupling convolutional model that introduces an adaptive weighting mechanism to assign distinct importance to neighboring nodes based on their similarity to the central node.Unlike traditional methods,the proposed coupling strategy enhances the interpretability of node interactions while maintaining competitive classification performance.The model operates in the spatial domain,utilizing adjacency list structures for efficient convolution and addressing the limitations of weight sharing through a coupling-based similarity computation.Extensive experiments are conducted on five graph-structured datasets,including Cora,Citeseer,PubMed,Reddit,and BlogCatalog,as well as a custom topology dataset constructed from the Open University Learning Analytics Dataset(OULAD)educational platform.Results demonstrate that the proposed model achieves good classification accuracy,while significantly reducing training time through direct second-order neighbor fusion and data preprocessing.Moreover,analysis of neighborhood order reveals that considering third-order neighbors offers limited accuracy gains but introduces considerable computational overhead,confirming the efficiency of first-and second-order convolution in practical applications.Overall,the proposed graph coupling model offers a lightweight,interpretable,and effective framework for multi-label node classification in complex networks.展开更多
Word cloud visualization is a compelling graphical representation that visually depicts the frequency of words within a given text or dataset[1].Research on word clouds focuses on two main aspects.The first emphasizes...Word cloud visualization is a compelling graphical representation that visually depicts the frequency of words within a given text or dataset[1].Research on word clouds focuses on two main aspects.The first emphasizes processing words,such as using the latent Dirichlet allocation(LDA)algorithm to uncover topics in the documents[2],while the second involves visual impact through striking word arrangements[3,4].In the realm of extensive biomedical data,effectiveknowledge delivery to biologists is crucial.展开更多
Currently,some photorealistic computer graphics are very similar to photographic images.Photorealistic computer generated graphics can be forged as photographic images,causing serious security problems.The aim of this...Currently,some photorealistic computer graphics are very similar to photographic images.Photorealistic computer generated graphics can be forged as photographic images,causing serious security problems.The aim of this work is to use a deep neural network to detect photographic images(PI)versus computer generated graphics(CG).In existing approaches,image feature classification is computationally intensive and fails to achieve realtime analysis.This paper presents an effective approach to automatically identify PI and CG based on deep convolutional neural networks(DCNNs).Compared with some existing methods,the proposed method achieves real-time forensic tasks by deepening the network structure.Experimental results show that this approach can effectively identify PI and CG with average detection accuracy of 98%.展开更多
This paper discuss the stereographic method of martensitic transformation (MT)in the view of computer graphics (CG) and programs are programmed to realize this method. Habit plane resulting from the programs agrees wi...This paper discuss the stereographic method of martensitic transformation (MT)in the view of computer graphics (CG) and programs are programmed to realize this method. Habit plane resulting from the programs agrees with that of numerical analysis in terms of the lattice parameters of austenite and martensite and shear mechanism supposed in Fe-22%Ni-0.8%C alloy, so does orientation relationships.展开更多
The paper presents a set of techniques of digital watermarking by which copyright and user rights messages are hidden into geo-spatial graphics data,as well as techniques of compressing and encrypting the watermarked ...The paper presents a set of techniques of digital watermarking by which copyright and user rights messages are hidden into geo-spatial graphics data,as well as techniques of compressing and encrypting the watermarked geo-spatial graphics data.The technology aims at tracing and resisting the illegal distribution and duplication of the geo-spatial graphics data product,so as to effectively protect the data producer＇s rights as well as to facilitate the secure sharing of geo-spatial graphics data.So far in the CIS field throughout the world,few researches have been made on digital watermarking.The research is a novel exploration both in the field of security management of geo-spatial graphics data and in the applications of digital watermarking technique.An application software employing the proposed technology has been developed.A number of experimental tests on the 1：500,000 digital bathymetric chart of the South China Sea and 1：10,000 digital topographic map of Jiangsu Province have been conducted to verify the feasibility of the proposed technology.展开更多
文摘It is of great scientific significance to construct a 3D dynamic structural color with a special color effect based on the microlens array.However,the problems of imperfect mechanisms and poor color quality need to be solved.A method of 3D structural color turning on periodic metasurfaces fabricated by the microlens array and self-assembly technology was proposed in this study.In the experiment,Polydimethylsiloxane(PDMS)flexible film was used as a substrate,and SiO2 microspheres were scraped into grooves of the PDMS film to form 3D photonic crystal structures.By adjusting the number of blade-coated times and microsphere concentrations,high-saturation structural color micropatterns were obtained.These films were then matched with microlens arrays to produce dynamic graphics with iridescent effects.The results showed that by blade-coated two times and SiO2 microsphere concentrations of 50%are the best conditions.This method demonstrates the potential for being widely applied in the anticounterfeiting printing and ultra-high-resolution display.
基金financed by Project of Heilongjiang Higher Education Society“Research on Graphics Curriculum Based on Innovation and Entrepreneurship Education under the Background of Digital Education”(23GJYB035)the 2024 Annual Planning Project of the“14th Five Year Plan”of Educational Science in Heilongjiang Province“Research and Exploration on Ideological and Political Teaching of‘Computer Graphics’Course under the Concept of OBE in New Engineering”(GJB1424113).
文摘In the context of the deep integration of digitalization and innovation and entrepreneurship education,this study focuses on the characteristics of schools and courses,investigates students’expectations and needs for ideological and political elements,and deeply explores ideological and political cases such as the Beidahuang spirit,Daqing spirit,model worker spirit,and role models around them.It explores the integration practice of“curriculum ideological and political”in extracurricular tutoring teaching of engineering graphics,aiming to guide students to establish patriotism,love for schools,knowledge of agriculture,and love for agriculture,and effectively enhance the coordinated development of students’graphic skills and ideological and political literacy.Practice has shown that integrating ideological and political resources,incorporating ideological and political elements into curriculum content and practical activities,can effectively enhance the collaborative development of students’graphic skills and ideological and political literacy.At the same time,it provides new ideas and references for expanding ideological and political education to extracurricular tutoring courses.
基金supported in part by National Natural Science Foundation of China under Grant No.62473013Key Project of Science and Technology Innovation and Entrepreneurship of TDTEC(No.2022-TDZD004).
文摘The newly emerging neural radiance fields(NeRF)methods can implicitly fulfill three-dimensional(3D)reconstruction via training a neural network to render novel-view images of a given scene with given posed images.The Instant Neural Graphics Primitives(Instant-NGP)method further improves the position encoding of NeRF.It obtains state-of-the-art efficiency.However,only a local pixel-wised loss is considered when training the Instant-NGP while overlooking the nonlocal structural information between pixels.Despite a good quantitative result,it leads to a poor visual effect,especially the completeness.Inspired by the stochastic structural similarity(S3IM)method that exploits nonlocal structural information of groups of pixels,this paper proposes a new method to improve the completeness of fast novel view synthesis.The proposed method first extends the thread-wised processing of the Instant-NGP to the processing in a customthread block(i.e.,a group of threads).Then,the relative dimensionless global error in synthesis,i.e.,Erreur Relative Globale Adimensionnelle de Synthese(ERGAS),of a group of pixels corresponding to a group of threads is computed and incorporated into the loss function.Extensive experiments validate the proposed method.It can obtain better quantitative results than the original Instant-NGP with fewer iteration steps.PSNR is increased by 1%.Amazing qualitative results are obtained,especially for delicate structures and details such as lines and continuous structures.With the dramatic improvements in the visual effects,our method can boost the practicability of implicit 3D reconstruction in applications such as self-driving and augmented reality.
基金Support by Sichuan Science and Technology Program[2023YFSY0026,2023YFH0004]Guangzhou Huashang University[2024HSZD01,HS2023JYSZH01].
文摘Graph neural networks(GNN)have shown strong performance in node classification tasks,yet most existing models rely on uniform or shared weight aggregation,lacking flexibility in modeling the varying strength of relationships among nodes.This paper proposes a novel graph coupling convolutional model that introduces an adaptive weighting mechanism to assign distinct importance to neighboring nodes based on their similarity to the central node.Unlike traditional methods,the proposed coupling strategy enhances the interpretability of node interactions while maintaining competitive classification performance.The model operates in the spatial domain,utilizing adjacency list structures for efficient convolution and addressing the limitations of weight sharing through a coupling-based similarity computation.Extensive experiments are conducted on five graph-structured datasets,including Cora,Citeseer,PubMed,Reddit,and BlogCatalog,as well as a custom topology dataset constructed from the Open University Learning Analytics Dataset(OULAD)educational platform.Results demonstrate that the proposed model achieves good classification accuracy,while significantly reducing training time through direct second-order neighbor fusion and data preprocessing.Moreover,analysis of neighborhood order reveals that considering third-order neighbors offers limited accuracy gains but introduces considerable computational overhead,confirming the efficiency of first-and second-order convolution in practical applications.Overall,the proposed graph coupling model offers a lightweight,interpretable,and effective framework for multi-label node classification in complex networks.
基金supported by the National Key R&D Program of China(2022YFC2704304 and 2021YFF0702000)the National Natural Science Foundation of China(32341020 and 32341021)+1 种基金Hubei Innovation Group Project(2021CFA005)the Research Core Facilities for Life Science(HUST).
文摘Word cloud visualization is a compelling graphical representation that visually depicts the frequency of words within a given text or dataset[1].Research on word clouds focuses on two main aspects.The first emphasizes processing words,such as using the latent Dirichlet allocation(LDA)algorithm to uncover topics in the documents[2],while the second involves visual impact through striking word arrangements[3,4].In the realm of extensive biomedical data,effectiveknowledge delivery to biologists is crucial.
基金This work is supported,in part,by the National Natural Science Foundation of China under grant numbers U1536206,U1405254,61772283,61602253,61672294,61502242In part,by the Jiangsu Basic Research Programs-Natural Science Foundation under grant numbers BK20150925 and BK20151530+1 种基金In part,by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fundIn part,by the Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET)fund,China.
文摘Currently,some photorealistic computer graphics are very similar to photographic images.Photorealistic computer generated graphics can be forged as photographic images,causing serious security problems.The aim of this work is to use a deep neural network to detect photographic images(PI)versus computer generated graphics(CG).In existing approaches,image feature classification is computationally intensive and fails to achieve realtime analysis.This paper presents an effective approach to automatically identify PI and CG based on deep convolutional neural networks(DCNNs).Compared with some existing methods,the proposed method achieves real-time forensic tasks by deepening the network structure.Experimental results show that this approach can effectively identify PI and CG with average detection accuracy of 98%.
文摘This paper discuss the stereographic method of martensitic transformation (MT)in the view of computer graphics (CG) and programs are programmed to realize this method. Habit plane resulting from the programs agrees with that of numerical analysis in terms of the lattice parameters of austenite and martensite and shear mechanism supposed in Fe-22%Ni-0.8%C alloy, so does orientation relationships.
基金Under the auspices of Jiangsu Provincial Science and Technology Fundation of Surveying and Mapping (No. 200416 )
文摘The paper presents a set of techniques of digital watermarking by which copyright and user rights messages are hidden into geo-spatial graphics data,as well as techniques of compressing and encrypting the watermarked geo-spatial graphics data.The technology aims at tracing and resisting the illegal distribution and duplication of the geo-spatial graphics data product,so as to effectively protect the data producer＇s rights as well as to facilitate the secure sharing of geo-spatial graphics data.So far in the CIS field throughout the world,few researches have been made on digital watermarking.The research is a novel exploration both in the field of security management of geo-spatial graphics data and in the applications of digital watermarking technique.An application software employing the proposed technology has been developed.A number of experimental tests on the 1：500,000 digital bathymetric chart of the South China Sea and 1：10,000 digital topographic map of Jiangsu Province have been conducted to verify the feasibility of the proposed technology.
