Large visual language models such as CLIP have demonstrated impressive performance on various downstream tasks involving natural images,by leveraging prompt learning.However,these models often falter when applied to t...Large visual language models such as CLIP have demonstrated impressive performance on various downstream tasks involving natural images,by leveraging prompt learning.However,these models often falter when applied to tasks involving medical images.We provide an experimental insight into this phenomenon:CLIP is insensitive to the class names of medical images.For instance,replacing the class name“medulloblastoma”(a type of brain tumor)with“dog”in prompts has minimal impact on performance,a phenomenon not observed with natural images.To realign prompt learning with medical image recognition,we propose a novel prompt learning strategy,termed prompt reverse learning(PeLen).Different from the existing methods that adapt CLIP’s representations to downstream tasks,PeLen adapts task-specific representations to CLIP’s representations.Built upon the insensitivity to the class names of medical images,PeLen designates natural images and their class names to represent a specific class of medical images and class names,e.g.,allowing the image and text of a dog to correspond to the image and text of medulloblastoma.Consequently,PeLen learns prompts to align the representations between the medical images and the visual and textual representations of natural images.Our experiments demonstrate the efficacy of PeLen for medical image recognition.展开更多
Manipulating objects based on verbal commands in cluttered environments remains a critical challenge in robotic arm research.Verbal commands possess high semantic abstraction,while precise grasping and placement actio...Manipulating objects based on verbal commands in cluttered environments remains a critical challenge in robotic arm research.Verbal commands possess high semantic abstraction,while precise grasping and placement actions rely on fine-grained geometric perception.The disparity between these two domains is the primary cause of operational errors.Particularly in certain cluttered scenarios,visual-spatial noise and background redundancy further disrupt attention distribution,significantly degrading the generalization capabilities of existing methods in unseen environments.To address these issues,this paper proposes the Secondary Realignment(SR)framework.It decouples vision-language alignment and vision-action alignment into two stages,mitigating semantic-geometric discrepancies through a hierarchical approach to substantially reduce errors in cross-modal mapping.Simultaneously,to address noise and redundancy in visual-language features,we design a Deep Sparse Self-Attention(DSSA)module.This module dynamically fuses sparse and dense attention mechanisms through self-learning parameters,adaptively enhancing relevant features while suppressing irrelevant noise.Extensive simulation experimental results demonstrate that compared to the state-of-the-art method A2,our approach achieves 9.7%,9.9%,and 17.6%higher task success rates in grasping,placing,and pick-and-place tasks,respectively,further validating its effectiveness.展开更多
Knowledge of migration and retention mechanisms of elastic gel particles(EGPs)in pore-throats is essential for the effective application of EGPs as a smart sweep improvement and profile control agent for enhanced oil ...Knowledge of migration and retention mechanisms of elastic gel particles(EGPs)in pore-throats is essential for the effective application of EGPs as a smart sweep improvement and profile control agent for enhanced oil recovery(EOR).The matching coefficient(defined as the ratio of particle size to pore-throat size)is used to investigate its influence on migration,retention and profile control performance of EGPs.A 1-D continuous pore-throat visualization model(PTVM),a 2-D heterogeneous PTVM and a 3-D heterogeneous core model were constructed and used to investigate pore-scale migration,retention and controlling mechanism of migration and retention characteristics on EGPs profile control.The results of the 1-D continuous PTVM indicated that while the matching coefficient was in the optimal range(i.e.,0.20-0.32),the EGPs could not only smoothly migrate to the deeper pore-throats,but also form stable retention in the pores to resist the erosion of injected water,which was conducive to the effective indepth profile control.The results of the 2-D heterogeneous PTVM verified that the sweep efficiency in low-permeability regions could be significantly improved by in-depth migration and stable retention of EGPs in the pore-throats with an optimal matching coefficient(0.29),which was much better than that in cases with a smaller matching coefficient(0.17)or an excessive matching coefficient(0.39).Moreover,the NMR displacement experiments of 3-D heterogeneous cores were carried out to simulate the EGPs profile control in actual reservoir porous media.Saturation images and T2 spectrum curves of crude oil showed that EOR in the low-permeability layer was highest(56.1%)using EGPs profile control with an optimal matching coefficient,attributing to the in-depth migration and stable retention of EGPs.展开更多
Traditional Mamba-UNet integrations employ four-stage architectures,replacing conventional five-stage UNets with VMamba blocks for global dependency modeling.Unlike Transformers,which suffer from quadratic complexity ...Traditional Mamba-UNet integrations employ four-stage architectures,replacing conventional five-stage UNets with VMamba blocks for global dependency modeling.Unlike Transformers,which suffer from quadratic complexity and high memory consumption in self-attention,Mamba-UNet achieves efficient global modeling through linear-complexity state space modeling.This paper proposes TriLVM-UNet,a lightweight three-stage architecture that integrates parameter-efficient VMamba blocks and enhances cross-stage feature interaction via an improved skip-attention bridge(SAB)module inspired by UltraLight VM-UNet.The model incorporates a Lightweight Vision Mamba(LVM)layer for high-resolution feature extraction,alongside multi-scale dilated convolution(MSDC)and convolutional block attention module(CBAM)for enhanced feature fusion.Evaluated on the 3D ACDC dataset against six baseline models,TriLVM-UNet achieves 98.57%accuracy.The GitHub repository is available at:http://gffzz188fe103f8f1460as99p95nwq66un69uk.ffgz.tsg.suse.edu.cn/730432ch/TriLVM-UNet.展开更多
Brood parasitism and egg mimicry of Himalayan Cuckoo(Cuculus saturatus) on its host Blyth's Leaf Warbler(Phylloscopus reguloides) were studied in south-western China from April to July 2009.The cuckoo laid a whit...Brood parasitism and egg mimicry of Himalayan Cuckoo(Cuculus saturatus) on its host Blyth's Leaf Warbler(Phylloscopus reguloides) were studied in south-western China from April to July 2009.The cuckoo laid a white egg with fine brown markings on the blunt end.The eggs were conspicuously bigger than the host's own,with 2.06 g in mass and 1.91 cm3 in volume.Visual modeling showed that the cuckoo eggs,which from the human eye appeared to mimic the host eggs to a great extent,were completely different from the host eggs in both hue and chroma.The characters of the Himalayan Cuckoo nestling,reported for the first time,included two triangular and black patches on its gape,which appeared from four days old and became darker with age and growth.While this character also exists in nestlings of Oriental Cuckoo(C.optatus),it has not been found for other Cuculus species.Our results reveal cryptic aspects in the cuckoo-host egg color matching,which are not visible to the naked human eye,and indicate that high mimetic cuckoo eggs rejected by hosts,as determined by human observers in previous studies,might not be mimetic as birds see them.展开更多
This article elucidates the concept of large model technology,summarizes the research status of large model technology both domestically and internationally,provides an overview of the application status of large mode...This article elucidates the concept of large model technology,summarizes the research status of large model technology both domestically and internationally,provides an overview of the application status of large models in vertical industries,outlines the challenges and issues confronted in applying large models in the oil and gas sector,and offers prospects for the application of large models in the oil and gas industry.The existing large models can be briefly divided into three categories:large language models,visual large models,and multimodal large models.The application of large models in the oil and gas industry is still in its infancy.Based on open-source large language models,some oil and gas enterprises have released large language model products using methods like fine-tuning and retrieval augmented generation.Scholars have attempted to develop scenario-specific models for oil and gas operations by using visual/multimodal foundation models.A few researchers have constructed pre-trained foundation models for seismic data processing and interpretation,as well as core analysis.The application of large models in the oil and gas industry faces challenges such as current data quantity and quality being difficult to support the training of large models,high research and development costs,and poor algorithm autonomy and control.The application of large models should be guided by the needs of oil and gas business,taking the application of large models as an opportunity to improve data lifecycle management,enhance data governance capabilities,promote the construction of computing power,strengthen the construction of“artificial intelligence+energy”composite teams,and boost the autonomy and control of large model technology.展开更多
The dynamic multichannel binocular visual image modeling is studied based on Internet of Things (IoT) Perception Layer, using mobile robot self-organizing network. By employing multigroup mobile robots with binocular ...The dynamic multichannel binocular visual image modeling is studied based on Internet of Things (IoT) Perception Layer, using mobile robot self-organizing network. By employing multigroup mobile robots with binocular visual system, the real visual images of the object will be obtained. Then through the mobile self-organizing network, a three-dimensional model is rebuilt by synthesizing the returned images. On this basis, we formalize a novel algorithm for multichannel binocular visual three-dimensional images based on fast three-dimensional modeling. Compared with the method based on single binocular visual system, the new algorithm can improve the Integrity and accuracy of the dynamic three-dimensional object modeling. The simulation results show that the new method can effectively accelerate the modeling speed, improve the similarity and not increase the data size.展开更多
Any tidal defense engineering involves the collection and analysis of massive information about engineering structures and their surrounding environment. Traditional method, which is carried out mainly by means of two...Any tidal defense engineering involves the collection and analysis of massive information about engineering structures and their surrounding environment. Traditional method, which is carried out mainly by means of twodimensional drawings and textures, is not efficient and intuitive enough to analyze the whole project and reflect its spatial relationship. Three-dimensional visual simulation provides an advanced technical means of solving this problem. In this paper, triangular irregular network (TIN) model simplified by non-uniform rational B-splines (NURBS) technique was used to establish the digital terrain model (DTM) of a super large region. Simulation of dynamic water surface was realized by combining noise function with sine wave superposition method. Models of different objects were established with different modeling techniques according to their characteristics. Application of texture mapping technology remarkably improved the authenticity of the models. Taking the tidal defense engineering in the new coastal region of Tianjin as a case study, three-dimensional visual simulation and dynamic roaming of the study area were realized, providing visual analysis and visible demonstration method for the management and emergency decision-making associated with construction.展开更多
As a major food production crop in China,the growth and development of rice is an extremely complex systemic process,and the root system is the main organ for rice to obtain nutrients.Therefore,3D modeling and visuali...As a major food production crop in China,the growth and development of rice is an extremely complex systemic process,and the root system is the main organ for rice to obtain nutrients.Therefore,3D modeling and visualization of the rice root system can help to further understand its morphology,structure and function,and provide an aid for scientific cultivation of rice and improving rice yield for decision making.In this paper,a mathematical model of the rice root system is established based on the B spline curve combined with the L-system approach,using mathematical knowledge based on the 3D morphological characteristics of the real rice root system.The B-Spline Curve is chosen to simulate this,and the recursive definition of B-Spline Curve and its formula are used to realize the modeling of the rice root system curve.Based on the mathematical method of rice root system integration,the bending effect of rice root system at different periods and different growth positions is realized.Finally,the L-system combined with B-Spline Curve is used to construct a rice root system model and realize the rice root system visualization simulation.The simulated image is closer to the real rice root system image in terms of morphological structure and has a strong sense of realism.展开更多
Adaptive mate choice has been accepted as the leading theory to explain the colorful plumage of birds.This theory hypothesizes that conspicuous colors act as signals to advertise the qualities of the owners.However,a ...Adaptive mate choice has been accepted as the leading theory to explain the colorful plumage of birds.This theory hypothesizes that conspicuous colors act as signals to advertise the qualities of the owners.However,a dilemma arises in that conspicuous colors may not only attract mates,but also alert predators.The"private channels of communication"hypothesis proposes that some intraspecific signals may not be visible to heterospecific animals because of different visual systems.To better understand the evolution of plumage colors and sexual selection in birds,here we studied the chromatic difference and achromatic differences of melanin-and carotenoid-based plumage coloration in five minivet species(Pericrocotus spp.)under conspecific and predator visual systems.We found that either the chromatic or achromatic difference among male or female minivets’plumage was consistently higher under conspecific vision than under predator vision for all five studied species of minivets.This result indicated that individual differences in plumage colors of minivets were visible to the conspecific receivers and hidden from potential predators as a result of evolution under predation risk and conspecific communication.However,males were under a higher risk of predation because they were more conspicuous than females to the vision of a nocturnal predator.展开更多
A method to detect traffic dangers based on visual attention model of sparse sampling was proposed. The hemispherical sparse sampling model was used to decrease the amount of calculation which increases the detection ...A method to detect traffic dangers based on visual attention model of sparse sampling was proposed. The hemispherical sparse sampling model was used to decrease the amount of calculation which increases the detection speed. Bayesian probability model and Gaussian kernel function were applied to calculate the saliency of traffic videos. The method of multiscale saliency was used and the final saliency was the average of all scales, which increased the detection rates extraordinarily. The detection results of several typical traffic dangers show that the proposed method has higher detection rates and speed, which meets the requirement of real-time detection of traffic dangers.展开更多
To solve the unbalanced data problems of learning models for semantic concepts, an optimized modeling method based on the posterior probability support vector machine (PPSVM) is presented. A neighborbased posterior ...To solve the unbalanced data problems of learning models for semantic concepts, an optimized modeling method based on the posterior probability support vector machine (PPSVM) is presented. A neighborbased posterior probability estimator for visual concepts is provided. The proposed method has been applied in a high-level visual semantic concept classification system and the experiment results show that it results in enhanced performance over the baseline SVM models, as well as in improved robustness with respect to high-level visual semantic concept classification.展开更多
How do individual neurons develop and how are they in- tegrated into neuronal circuitry? To answer this question is essential to understand how the nervous system develops and how it is maintained during the adult li...How do individual neurons develop and how are they in- tegrated into neuronal circuitry? To answer this question is essential to understand how the nervous system develops and how it is maintained during the adult life. A neural stem cell must go through several stages of maturation, including proliferation, migration, differentiation, and integration, to become fully embedded to an existing neuronal circuit. The knowledge on this topic so far has come mainly from cell culture studies. Studying the development of individual neurons within intact neuronal networks in vivo is inherently difficult. Most neurons are generated form neural stem cells during embryonic and early postnatal development.展开更多
Structure of porous media and fluid distribution in rocks can significantly affect the transport characteristics during the process of microscale tracer flow.To clarify the effect of micro heterogeneity on aqueous tra...Structure of porous media and fluid distribution in rocks can significantly affect the transport characteristics during the process of microscale tracer flow.To clarify the effect of micro heterogeneity on aqueous tracer transport,this paper demonstrates microscopic experiments at pore level and proposes an improved mathematical model for tracer transport.The visualization results show a faster tracer movement into movable water than it into bound water,and quicker occupancy in flowing pores than in storage pores caused by the difference of tracer velocity.Moreover,the proposed mathematical model includes the effects of bound water and flowing porosity by applying interstitial flow velocity expression.The new model also distinguishes flowing and storage pores,accounting for different tracer transport mechanisms(dispersion,diffusion and adsorption)in different types of pores.The resulting analytical solution better matches with tracer production data than the standard model.The residual sum of squares(RSS)from the new model is 0.0005,which is 100 times smaller than the RSS from the standard model.The sensitivity analysis indicates that the dispersion coefficient and flowing porosity shows a negative correlation with the tracer breakthrough time and the increasing slope,whereas the superficial velocity and bound water saturation show a positive correlation.展开更多
Objectives" To deepen our understanding of the status quo and to identify the hot topics and develop- mental trends of research on nursing models in countries other than China in the most recent decade. Methods: The...Objectives" To deepen our understanding of the status quo and to identify the hot topics and develop- mental trends of research on nursing models in countries other than China in the most recent decade. Methods: The study subjects were the publications retrieved from the PubMed database using the MeSH terms of "Models, Nursing". Bibliographic item co-occurrence mining system (BICOMS) software was used for conventional bibliometric analysis of publications during two time periods, 2005-2009 and 2010-2014. The number of published journal articles, journal distribution, authors of publications, country of origin of journals, and language of publications were analyzed to establish a high-frequency keyword profile and co-occurrence matrix. Graphical clustering toolkit (gCLUTO) software was applied for two-way clustering analysis and visualized analysis. Results: A total of 1472 journal articles with a key theme of nursing models were retrieved for final analysis, including 771 published during 2005-2009 and 701 during 2010-2014. The bibliometric analysis revealed that publications other than China concerning nursing models were mostly concentrated in the United States and the United Kingdom and that the number of relevant publications has been continuously decreasing. The two-way clustering analysis showed that there were mainly four types of research themes in the relevant publications in countries other than China during 2005-2009, i.e., nursing education and theoretical research, clinical nursing and psychological care, nursing administration, and models of nursing education, whereas there were five types during 2010-2014, i.e., nursing theories and clinical nursing practice, nursing administration models and assessments of nurses' knowledge and skills, community nursing administration models, nursing human resource management, and nursing education models and approaches. Conclusions: Research on nursing models in countries other than China is relatively mature and stable with a broader view, but it has shown a declining trend in recent years. It emphasizes both theory and practice, with research content tending to be structured into four modules, i.e., nursing education, administration, clinical practice, and theoretical research. Community nursing models may become a key research direction in the international research on nursing models in the future.展开更多
Video summarization is applied to reduce redundancy and developa concise representation of key frames in the video, more recently, video summaries have been used through visual attention modeling. In these schemes,the...Video summarization is applied to reduce redundancy and developa concise representation of key frames in the video, more recently, video summaries have been used through visual attention modeling. In these schemes,the frames that stand out visually are extracted as key frames based on humanattention modeling theories. The schemes for modeling visual attention haveproven to be effective for video summaries. Nevertheless, the high cost ofcomputing in such techniques restricts their usability in everyday situations.In this context, we propose a method based on KFE (key frame extraction)technique, which is recommended based on an efficient and accurate visualattention model. The calculation effort is minimized by utilizing dynamicvisual highlighting based on the temporal gradient instead of the traditionaloptical flow techniques. In addition, an efficient technique using a discretecosine transformation is utilized for the static visual salience. The dynamic andstatic visual attention metrics are merged by means of a non-linear weightedfusion technique. Results of the system are compared with some existing stateof-the-art techniques for the betterment of accuracy. The experimental resultsof our proposed model indicate the efficiency and high standard in terms ofthe key frames extraction as output.展开更多
A Robust Adaptive Video Encoder (RAVE) based on human visual model is proposed. The encoder combines the best features of Fine Granularity Scalable (FGS) coding, framedropping coding, video redundancy coding, and huma...A Robust Adaptive Video Encoder (RAVE) based on human visual model is proposed. The encoder combines the best features of Fine Granularity Scalable (FGS) coding, framedropping coding, video redundancy coding, and human visual model. According to packet loss and available bandwidth of the network, the encoder adjust the output bit rate by jointly adapting quantization step-size instructed by human visual model, rate shaping, and periodically inserting key frame. The proposed encoder is implemented based on MPEG-4 encoder and is compared with the case of a conventional FGS algorithm. It is shown that RAVE is a very efficient robust video encoder that provides improved visual quality for the receiver and consumes equal or less network resource. Results are confirmed by subjective tests and simulation tests.展开更多
Taking the actual project of teaching and researching process for example, the relationship between the industrial engineering and product development is discussed. And use the novel visualization technology to suppor...Taking the actual project of teaching and researching process for example, the relationship between the industrial engineering and product development is discussed. And use the novel visualization technology to support the industrial engineering and product development. How to use the new computer modeling and simulating technologies to support the product development and industrial engineering, is introduced especially. The support includes both domestic products and industrial systems. The visualization and computer technologies take a very impo[tant role in some system or multi-direction modeling, those technologies mentioned above can help the industrial engineers study the effect of design on the whole life circle, including the producing steps. So the engineers can avoid making the wrong decision which may cause bad effects on the whole industrial engineering.展开更多
Vehicle recognition system (VRS) plays a very important role in the field of intelligent transportation systems.A novel and intuitive method is proposed for vehicle location.The method we provide for vehicle location ...Vehicle recognition system (VRS) plays a very important role in the field of intelligent transportation systems.A novel and intuitive method is proposed for vehicle location.The method we provide for vehicle location is based on human visual perception model technique. The perception color space HSI in this algorithm is adopted.Three color components of a color image and more potential edge patterns are integrated for solving the feature extraction problem.A fast and automatic threshold technique based on human visual perception model is also developed.The vertical edge projection and horizontal edge projection are adopted for locating left-right boundary of vehicle and top-bottom boundary of vehicle, respectively. Very promising experimental results are obtained using real-time vehicle image sequences, which have confirmed that this proposed location vehicle method is efficient and reliable, and its calculation speed meets the needs of the VRS.展开更多
The process of human natural scene categorization consists of two correlated stages: visual perception and visual cognition of natural scenes.Inspired by this fact,we propose a biologically plausible approach for natu...The process of human natural scene categorization consists of two correlated stages: visual perception and visual cognition of natural scenes.Inspired by this fact,we propose a biologically plausible approach for natural scene image classification.This approach consists of one visual perception model and two visual cognition models.The visual perception model,composed of two steps,is used to extract discriminative features from natural scene images.In the first step,we mimic the oriented and bandpass properties of human primary visual cortex by a special complex wavelets transform,which can decompose a natural scene image into a series of 2D spatial structure signals.In the second step,a hybrid statistical feature extraction method is used to generate gist features from those 2D spatial structure signals.Then we design a cognitive feedback model to realize adaptive optimization for the visual perception model.At last,we build a multiple semantics based cognition model to imitate human cognitive mode in rapid natural scene categorization.Experiments on natural scene datasets show that the proposed method achieves high efficiency and accuracy for natural scene classification.展开更多
基金supported by the National Natural Science Foundation of China(62222117).
摘要Large visual language models such as CLIP have demonstrated impressive performance on various downstream tasks involving natural images,by leveraging prompt learning.However,these models often falter when applied to tasks involving medical images.We provide an experimental insight into this phenomenon:CLIP is insensitive to the class names of medical images.For instance,replacing the class name“medulloblastoma”(a type of brain tumor)with“dog”in prompts has minimal impact on performance,a phenomenon not observed with natural images.To realign prompt learning with medical image recognition,we propose a novel prompt learning strategy,termed prompt reverse learning(PeLen).Different from the existing methods that adapt CLIP’s representations to downstream tasks,PeLen adapts task-specific representations to CLIP’s representations.Built upon the insensitivity to the class names of medical images,PeLen designates natural images and their class names to represent a specific class of medical images and class names,e.g.,allowing the image and text of a dog to correspond to the image and text of medulloblastoma.Consequently,PeLen learns prompts to align the representations between the medical images and the visual and textual representations of natural images.Our experiments demonstrate the efficacy of PeLen for medical image recognition.
基金Fujian Provincial Science and Technology Department:Collaborative Innovation Platform Project for Key Technologies of Smart Warehousing and Logistics System in Fuzhou-Xiamen-Quanzhou National Independent Innovation Demonstration Zone(2025E3024)Key Technical Innovation and Industrialization Project of Fujian Province’s Manufacturing Industry in 2025:Research and Development and Industrialization of Key Technologies for Ultra-Low Power Consumption Multi-Modal Intelligent Sensing Terminals and Anti-Interference AI Algorithms(2025G006).
摘要Manipulating objects based on verbal commands in cluttered environments remains a critical challenge in robotic arm research.Verbal commands possess high semantic abstraction,while precise grasping and placement actions rely on fine-grained geometric perception.The disparity between these two domains is the primary cause of operational errors.Particularly in certain cluttered scenarios,visual-spatial noise and background redundancy further disrupt attention distribution,significantly degrading the generalization capabilities of existing methods in unseen environments.To address these issues,this paper proposes the Secondary Realignment(SR)framework.It decouples vision-language alignment and vision-action alignment into two stages,mitigating semantic-geometric discrepancies through a hierarchical approach to substantially reduce errors in cross-modal mapping.Simultaneously,to address noise and redundancy in visual-language features,we design a Deep Sparse Self-Attention(DSSA)module.This module dynamically fuses sparse and dense attention mechanisms through self-learning parameters,adaptively enhancing relevant features while suppressing irrelevant noise.Extensive simulation experimental results demonstrate that compared to the state-of-the-art method A2,our approach achieves 9.7%,9.9%,and 17.6%higher task success rates in grasping,placing,and pick-and-place tasks,respectively,further validating its effectiveness.
基金supported by the National Key Research and Development Project(2019YFA0708700)the National Natural Science Foundation of China(52104061)+2 种基金the project funded by China Postdoctoral Science Foundation(2020M682264)the Shandong Provincial Natural Science Foundation(ZR2021QE075)the Fundamental Research Funds for the Central Universities(20CX06090A)。
摘要Knowledge of migration and retention mechanisms of elastic gel particles(EGPs)in pore-throats is essential for the effective application of EGPs as a smart sweep improvement and profile control agent for enhanced oil recovery(EOR).The matching coefficient(defined as the ratio of particle size to pore-throat size)is used to investigate its influence on migration,retention and profile control performance of EGPs.A 1-D continuous pore-throat visualization model(PTVM),a 2-D heterogeneous PTVM and a 3-D heterogeneous core model were constructed and used to investigate pore-scale migration,retention and controlling mechanism of migration and retention characteristics on EGPs profile control.The results of the 1-D continuous PTVM indicated that while the matching coefficient was in the optimal range(i.e.,0.20-0.32),the EGPs could not only smoothly migrate to the deeper pore-throats,but also form stable retention in the pores to resist the erosion of injected water,which was conducive to the effective indepth profile control.The results of the 2-D heterogeneous PTVM verified that the sweep efficiency in low-permeability regions could be significantly improved by in-depth migration and stable retention of EGPs in the pore-throats with an optimal matching coefficient(0.29),which was much better than that in cases with a smaller matching coefficient(0.17)or an excessive matching coefficient(0.39).Moreover,the NMR displacement experiments of 3-D heterogeneous cores were carried out to simulate the EGPs profile control in actual reservoir porous media.Saturation images and T2 spectrum curves of crude oil showed that EOR in the low-permeability layer was highest(56.1%)using EGPs profile control with an optimal matching coefficient,attributing to the in-depth migration and stable retention of EGPs.
基金The Key Project of Ningxia Natural Science Foundation under grant 2025AAC020006the Regional Program of National Natural Science Foundation of China under grant 62561002The Shaanxi University of Technology Foundation Project under grant SLGRCQD2137.
摘要Traditional Mamba-UNet integrations employ four-stage architectures,replacing conventional five-stage UNets with VMamba blocks for global dependency modeling.Unlike Transformers,which suffer from quadratic complexity and high memory consumption in self-attention,Mamba-UNet achieves efficient global modeling through linear-complexity state space modeling.This paper proposes TriLVM-UNet,a lightweight three-stage architecture that integrates parameter-efficient VMamba blocks and enhances cross-stage feature interaction via an improved skip-attention bridge(SAB)module inspired by UltraLight VM-UNet.The model incorporates a Lightweight Vision Mamba(LVM)layer for high-resolution feature extraction,alongside multi-scale dilated convolution(MSDC)and convolutional block attention module(CBAM)for enhanced feature fusion.Evaluated on the 3D ACDC dataset against six baseline models,TriLVM-UNet achieves 98.57%accuracy.The GitHub repository is available at:http://gffzz188fe103f8f1460as99p95nwq66un69uk.ffgz.tsg.suse.edu.cn/730432ch/TriLVM-UNet.
基金supported by National Natural Science Foundation of China(3086004431071938)+1 种基金Program for New Century Excellent Talents in University(NCET-10-0111)China Postdoctoral Science Foundation(20110490967)funded project
摘要Brood parasitism and egg mimicry of Himalayan Cuckoo(Cuculus saturatus) on its host Blyth's Leaf Warbler(Phylloscopus reguloides) were studied in south-western China from April to July 2009.The cuckoo laid a white egg with fine brown markings on the blunt end.The eggs were conspicuously bigger than the host's own,with 2.06 g in mass and 1.91 cm3 in volume.Visual modeling showed that the cuckoo eggs,which from the human eye appeared to mimic the host eggs to a great extent,were completely different from the host eggs in both hue and chroma.The characters of the Himalayan Cuckoo nestling,reported for the first time,included two triangular and black patches on its gape,which appeared from four days old and became darker with age and growth.While this character also exists in nestlings of Oriental Cuckoo(C.optatus),it has not been found for other Cuculus species.Our results reveal cryptic aspects in the cuckoo-host egg color matching,which are not visible to the naked human eye,and indicate that high mimetic cuckoo eggs rejected by hosts,as determined by human observers in previous studies,might not be mimetic as birds see them.
基金Supported by the National Natural Science Foundation of China(72088101,42372175)PetroChina Science and Technology Innovation Fund Program(2021DQ02-0904)。
摘要This article elucidates the concept of large model technology,summarizes the research status of large model technology both domestically and internationally,provides an overview of the application status of large models in vertical industries,outlines the challenges and issues confronted in applying large models in the oil and gas sector,and offers prospects for the application of large models in the oil and gas industry.The existing large models can be briefly divided into three categories:large language models,visual large models,and multimodal large models.The application of large models in the oil and gas industry is still in its infancy.Based on open-source large language models,some oil and gas enterprises have released large language model products using methods like fine-tuning and retrieval augmented generation.Scholars have attempted to develop scenario-specific models for oil and gas operations by using visual/multimodal foundation models.A few researchers have constructed pre-trained foundation models for seismic data processing and interpretation,as well as core analysis.The application of large models in the oil and gas industry faces challenges such as current data quantity and quality being difficult to support the training of large models,high research and development costs,and poor algorithm autonomy and control.The application of large models should be guided by the needs of oil and gas business,taking the application of large models as an opportunity to improve data lifecycle management,enhance data governance capabilities,promote the construction of computing power,strengthen the construction of“artificial intelligence+energy”composite teams,and boost the autonomy and control of large model technology.
基金supported by HiTech Researchand Development Program of China under Grant No.2007AA10Z235
摘要The dynamic multichannel binocular visual image modeling is studied based on Internet of Things (IoT) Perception Layer, using mobile robot self-organizing network. By employing multigroup mobile robots with binocular visual system, the real visual images of the object will be obtained. Then through the mobile self-organizing network, a three-dimensional model is rebuilt by synthesizing the returned images. On this basis, we formalize a novel algorithm for multichannel binocular visual three-dimensional images based on fast three-dimensional modeling. Compared with the method based on single binocular visual system, the new algorithm can improve the Integrity and accuracy of the dynamic three-dimensional object modeling. The simulation results show that the new method can effectively accelerate the modeling speed, improve the similarity and not increase the data size.
基金Supported by Tianjin Research Program of Application Foundation and Advanced Technology (No.12JCZDJC29200)Foundation for Innovative Research Groups of National Natural Science Foundation of China (No.51021004)National Key Technology R&D Program in the 12th Five-Year Plan of China(No.2011BAB10B06)
摘要Any tidal defense engineering involves the collection and analysis of massive information about engineering structures and their surrounding environment. Traditional method, which is carried out mainly by means of twodimensional drawings and textures, is not efficient and intuitive enough to analyze the whole project and reflect its spatial relationship. Three-dimensional visual simulation provides an advanced technical means of solving this problem. In this paper, triangular irregular network (TIN) model simplified by non-uniform rational B-splines (NURBS) technique was used to establish the digital terrain model (DTM) of a super large region. Simulation of dynamic water surface was realized by combining noise function with sine wave superposition method. Models of different objects were established with different modeling techniques according to their characteristics. Application of texture mapping technology remarkably improved the authenticity of the models. Taking the tidal defense engineering in the new coastal region of Tianjin as a case study, three-dimensional visual simulation and dynamic roaming of the study area were realized, providing visual analysis and visible demonstration method for the management and emergency decision-making associated with construction.
基金Supported by the National Natural Science Foundation of China(61862032)the Project of Natural Science Foundation of Jiangxi Province(20202BABL202034)the Special Foundation of Graduate Student Innovation of Jiangxi Province(YC2021-S347)
摘要As a major food production crop in China,the growth and development of rice is an extremely complex systemic process,and the root system is the main organ for rice to obtain nutrients.Therefore,3D modeling and visualization of the rice root system can help to further understand its morphology,structure and function,and provide an aid for scientific cultivation of rice and improving rice yield for decision making.In this paper,a mathematical model of the rice root system is established based on the B spline curve combined with the L-system approach,using mathematical knowledge based on the 3D morphological characteristics of the real rice root system.The B-Spline Curve is chosen to simulate this,and the recursive definition of B-Spline Curve and its formula are used to realize the modeling of the rice root system curve.Based on the mathematical method of rice root system integration,the bending effect of rice root system at different periods and different growth positions is realized.Finally,the L-system combined with B-Spline Curve is used to construct a rice root system model and realize the rice root system visualization simulation.The simulated image is closer to the real rice root system image in terms of morphological structure and has a strong sense of realism.
基金supported by the National Natural Science Foundation of China(32260127)the Education Department of Hainan Province(HnjgY2022-12)+1 种基金the Hainan Provincial Natural Science Foundation of China(320CXTD437)the Hainan Provincial Innovative Research Program for Graduates(Qhys2022-241)。
摘要Adaptive mate choice has been accepted as the leading theory to explain the colorful plumage of birds.This theory hypothesizes that conspicuous colors act as signals to advertise the qualities of the owners.However,a dilemma arises in that conspicuous colors may not only attract mates,but also alert predators.The"private channels of communication"hypothesis proposes that some intraspecific signals may not be visible to heterospecific animals because of different visual systems.To better understand the evolution of plumage colors and sexual selection in birds,here we studied the chromatic difference and achromatic differences of melanin-and carotenoid-based plumage coloration in five minivet species(Pericrocotus spp.)under conspecific and predator visual systems.We found that either the chromatic or achromatic difference among male or female minivets’plumage was consistently higher under conspecific vision than under predator vision for all five studied species of minivets.This result indicated that individual differences in plumage colors of minivets were visible to the conspecific receivers and hidden from potential predators as a result of evolution under predation risk and conspecific communication.However,males were under a higher risk of predation because they were more conspicuous than females to the vision of a nocturnal predator.
基金Project(50808025)supported by the National Natural Science Foundation of ChinaProject(20090162110057)supported by the Doctoral Fund of Ministry of Education of China
摘要A method to detect traffic dangers based on visual attention model of sparse sampling was proposed. The hemispherical sparse sampling model was used to decrease the amount of calculation which increases the detection speed. Bayesian probability model and Gaussian kernel function were applied to calculate the saliency of traffic videos. The method of multiscale saliency was used and the final saliency was the average of all scales, which increased the detection rates extraordinarily. The detection results of several typical traffic dangers show that the proposed method has higher detection rates and speed, which meets the requirement of real-time detection of traffic dangers.
基金Sponsored by the Beijing Municipal Natural Science Foundation(4082027)
摘要To solve the unbalanced data problems of learning models for semantic concepts, an optimized modeling method based on the posterior probability support vector machine (PPSVM) is presented. A neighborbased posterior probability estimator for visual concepts is provided. The proposed method has been applied in a high-level visual semantic concept classification system and the experiment results show that it results in enhanced performance over the baseline SVM models, as well as in improved robustness with respect to high-level visual semantic concept classification.
基金supported by DFG Schwerpunkt program 1392(project MA 4113/2-2)cluster of Excellence and DFG Research Center Nanoscale Microscopy and Molecular Physiology of the Brain(project B1-9)+1 种基金the German Ministry of Research and Education(BMBFproject 1364480)
摘要How do individual neurons develop and how are they in- tegrated into neuronal circuitry? To answer this question is essential to understand how the nervous system develops and how it is maintained during the adult life. A neural stem cell must go through several stages of maturation, including proliferation, migration, differentiation, and integration, to become fully embedded to an existing neuronal circuit. The knowledge on this topic so far has come mainly from cell culture studies. Studying the development of individual neurons within intact neuronal networks in vivo is inherently difficult. Most neurons are generated form neural stem cells during embryonic and early postnatal development.
基金funded by National Science and Technology Major Projects(2017ZX05009004,2016ZX05058003)Beijing Natural Science Foundation(2173061)and State Energy Center for Shale Oil Research and Development(G5800-16-ZS-KFNY005).
摘要Structure of porous media and fluid distribution in rocks can significantly affect the transport characteristics during the process of microscale tracer flow.To clarify the effect of micro heterogeneity on aqueous tracer transport,this paper demonstrates microscopic experiments at pore level and proposes an improved mathematical model for tracer transport.The visualization results show a faster tracer movement into movable water than it into bound water,and quicker occupancy in flowing pores than in storage pores caused by the difference of tracer velocity.Moreover,the proposed mathematical model includes the effects of bound water and flowing porosity by applying interstitial flow velocity expression.The new model also distinguishes flowing and storage pores,accounting for different tracer transport mechanisms(dispersion,diffusion and adsorption)in different types of pores.The resulting analytical solution better matches with tracer production data than the standard model.The residual sum of squares(RSS)from the new model is 0.0005,which is 100 times smaller than the RSS from the standard model.The sensitivity analysis indicates that the dispersion coefficient and flowing porosity shows a negative correlation with the tracer breakthrough time and the increasing slope,whereas the superficial velocity and bound water saturation show a positive correlation.
基金supported by Shanxi Provincial Health Department(No.201201031)
摘要Objectives" To deepen our understanding of the status quo and to identify the hot topics and develop- mental trends of research on nursing models in countries other than China in the most recent decade. Methods: The study subjects were the publications retrieved from the PubMed database using the MeSH terms of "Models, Nursing". Bibliographic item co-occurrence mining system (BICOMS) software was used for conventional bibliometric analysis of publications during two time periods, 2005-2009 and 2010-2014. The number of published journal articles, journal distribution, authors of publications, country of origin of journals, and language of publications were analyzed to establish a high-frequency keyword profile and co-occurrence matrix. Graphical clustering toolkit (gCLUTO) software was applied for two-way clustering analysis and visualized analysis. Results: A total of 1472 journal articles with a key theme of nursing models were retrieved for final analysis, including 771 published during 2005-2009 and 701 during 2010-2014. The bibliometric analysis revealed that publications other than China concerning nursing models were mostly concentrated in the United States and the United Kingdom and that the number of relevant publications has been continuously decreasing. The two-way clustering analysis showed that there were mainly four types of research themes in the relevant publications in countries other than China during 2005-2009, i.e., nursing education and theoretical research, clinical nursing and psychological care, nursing administration, and models of nursing education, whereas there were five types during 2010-2014, i.e., nursing theories and clinical nursing practice, nursing administration models and assessments of nurses' knowledge and skills, community nursing administration models, nursing human resource management, and nursing education models and approaches. Conclusions: Research on nursing models in countries other than China is relatively mature and stable with a broader view, but it has shown a declining trend in recent years. It emphasizes both theory and practice, with research content tending to be structured into four modules, i.e., nursing education, administration, clinical practice, and theoretical research. Community nursing models may become a key research direction in the international research on nursing models in the future.
基金This work was supported in part by Qatar National Library,Doha,Qatar,and in part by the Qatar University Internal under Grant IRCC-2021-010。
摘要Video summarization is applied to reduce redundancy and developa concise representation of key frames in the video, more recently, video summaries have been used through visual attention modeling. In these schemes,the frames that stand out visually are extracted as key frames based on humanattention modeling theories. The schemes for modeling visual attention haveproven to be effective for video summaries. Nevertheless, the high cost ofcomputing in such techniques restricts their usability in everyday situations.In this context, we propose a method based on KFE (key frame extraction)technique, which is recommended based on an efficient and accurate visualattention model. The calculation effort is minimized by utilizing dynamicvisual highlighting based on the temporal gradient instead of the traditionaloptical flow techniques. In addition, an efficient technique using a discretecosine transformation is utilized for the static visual salience. The dynamic andstatic visual attention metrics are merged by means of a non-linear weightedfusion technique. Results of the system are compared with some existing stateof-the-art techniques for the betterment of accuracy. The experimental resultsof our proposed model indicate the efficiency and high standard in terms ofthe key frames extraction as output.
基金Supported by Innovation Fund of China(00C26224210641)
摘要A Robust Adaptive Video Encoder (RAVE) based on human visual model is proposed. The encoder combines the best features of Fine Granularity Scalable (FGS) coding, framedropping coding, video redundancy coding, and human visual model. According to packet loss and available bandwidth of the network, the encoder adjust the output bit rate by jointly adapting quantization step-size instructed by human visual model, rate shaping, and periodically inserting key frame. The proposed encoder is implemented based on MPEG-4 encoder and is compared with the case of a conventional FGS algorithm. It is shown that RAVE is a very efficient robust video encoder that provides improved visual quality for the receiver and consumes equal or less network resource. Results are confirmed by subjective tests and simulation tests.
摘要Taking the actual project of teaching and researching process for example, the relationship between the industrial engineering and product development is discussed. And use the novel visualization technology to support the industrial engineering and product development. How to use the new computer modeling and simulating technologies to support the product development and industrial engineering, is introduced especially. The support includes both domestic products and industrial systems. The visualization and computer technologies take a very impo[tant role in some system or multi-direction modeling, those technologies mentioned above can help the industrial engineers study the effect of design on the whole life circle, including the producing steps. So the engineers can avoid making the wrong decision which may cause bad effects on the whole industrial engineering.
摘要Vehicle recognition system (VRS) plays a very important role in the field of intelligent transportation systems.A novel and intuitive method is proposed for vehicle location.The method we provide for vehicle location is based on human visual perception model technique. The perception color space HSI in this algorithm is adopted.Three color components of a color image and more potential edge patterns are integrated for solving the feature extraction problem.A fast and automatic threshold technique based on human visual perception model is also developed.The vertical edge projection and horizontal edge projection are adopted for locating left-right boundary of vehicle and top-bottom boundary of vehicle, respectively. Very promising experimental results are obtained using real-time vehicle image sequences, which have confirmed that this proposed location vehicle method is efficient and reliable, and its calculation speed meets the needs of the VRS.
摘要The process of human natural scene categorization consists of two correlated stages: visual perception and visual cognition of natural scenes.Inspired by this fact,we propose a biologically plausible approach for natural scene image classification.This approach consists of one visual perception model and two visual cognition models.The visual perception model,composed of two steps,is used to extract discriminative features from natural scene images.In the first step,we mimic the oriented and bandpass properties of human primary visual cortex by a special complex wavelets transform,which can decompose a natural scene image into a series of 2D spatial structure signals.In the second step,a hybrid statistical feature extraction method is used to generate gist features from those 2D spatial structure signals.Then we design a cognitive feedback model to realize adaptive optimization for the visual perception model.At last,we build a multiple semantics based cognition model to imitate human cognitive mode in rapid natural scene categorization.Experiments on natural scene datasets show that the proposed method achieves high efficiency and accuracy for natural scene classification.