Cloud detection from satellite and drone imagery is crucial for applications such as weather forecasting and environmentalmonitoring.Addressing the limitations of conventional convolutional neural networks,we propose ...Cloud detection from satellite and drone imagery is crucial for applications such as weather forecasting and environmentalmonitoring.Addressing the limitations of conventional convolutional neural networks,we propose an innovative transformer-based method.This method leverages transformers,which are adept at processing data sequences,to enhance cloud detection accuracy.Additionally,we introduce a Cyclic Refinement Architecture that improves the resolution and quality of feature extraction,thereby aiding in the retention of critical details often lost during cloud detection.Our extensive experimental validation shows that our approach significantly outperforms established models,excelling in high-resolution feature extraction and precise cloud segmentation.By integrating Positional Visual Transformers(PVT)with this architecture,our method advances high-resolution feature delineation and segmentation accuracy.Ultimately,our research offers a novel perspective for surmounting traditional challenges in cloud detection and contributes to the advancement of precise and dependable image analysis across various domains.展开更多
The analysis of microstates in EEG signals is a crucial technique for understanding the spatiotemporal dynamics of brain electrical activity.Traditional methods such as Atomic Agglomerative Hierarchical Clustering(AAH...The analysis of microstates in EEG signals is a crucial technique for understanding the spatiotemporal dynamics of brain electrical activity.Traditional methods such as Atomic Agglomerative Hierarchical Clustering(AAHC),K-means clustering,Principal Component Analysis(PCA),and Independent Component Analysis(ICA)are limited by a fixed number of microstate maps and insufficient capability in cross-task feature extraction.Tackling these limitations,this study introduces a Global Map Dissimilarity(GMD)-driven density canopy K-means clustering algorithm.This innovative approach autonomously determines the optimal number of EEG microstate topographies and employs Gaussian kernel density estimation alongside the GMD index for dynamic modeling of EEG data.Utilizing this advanced algorithm,the study analyzes the Motor Imagery(MI)dataset from the GigaScience database,GigaDB.The findings reveal six distinct microstates during actual right-hand movement and five microstates across other task conditions,with microstate C showing superior performance in all task states.During imagined movement,microstate A was significantly enhanced.Comparison with existing algorithms indicates a significant improvement in clustering performance by the refined method,with an average Calinski-Harabasz Index(CHI)of 35517.29 and a Davis-Bouldin Index(DBI)average of 2.57.Furthermore,an information-theoretical analysis of the microstate sequences suggests that imagined movement exhibits higher complexity and disorder than actual movement.By utilizing the extracted microstate sequence parameters as features,the improved algorithm achieved a classification accuracy of 98.41%in EEG signal categorization for motor imagery.A performance of 78.183%accuracy was achieved in a four-class motor imagery task on the BCI-IV-2a dataset.These results demonstrate the potential of the advanced algorithm in microstate analysis,offering a more effective tool for a deeper understanding of the spatiotemporal features of EEG signals.展开更多
Motor imagery(MI)based electroencephalogram(EEG)represents a frontier in enabling direct neural control of external devices and advancing neural rehabilitation.This study introduces a novel time embedding technique,te...Motor imagery(MI)based electroencephalogram(EEG)represents a frontier in enabling direct neural control of external devices and advancing neural rehabilitation.This study introduces a novel time embedding technique,termed traveling-wave based time embedding,utilized as a pseudo channel to enhance the decoding accuracy of MI-EEG signals across various neural network architectures.Unlike traditional neural network methods that fail to account for the temporal dynamics in MI-EEG in individual difference,our approach captures time-related changes for different participants based on a priori knowledge.Through extensive experimentation with multiple participants,we demonstrate that this method not only improves classification accuracy but also exhibits greater adaptability to individual differences compared to position encoding used in Transformer architecture.Significantly,our results reveal that traveling-wave based time embedding crucially enhances decoding accuracy,particularly for participants typically considered“EEG-illiteracy”.As a novel direction in EEG research,the traveling-wave based time embedding not only offers fresh insights for neural network decoding strategies but also expands new avenues for research into attention mechanisms in neuroscience and a deeper understanding of EEG signals.展开更多
Imagery analysis is a commonly used analytical method in literary analysis.In Angela Carter’s work,the image of wolves is particularly prominent.Her“Werewolf Tetralogy”rewrites traditional culture and subverts trad...Imagery analysis is a commonly used analytical method in literary analysis.In Angela Carter’s work,the image of wolves is particularly prominent.Her“Werewolf Tetralogy”rewrites traditional culture and subverts traditional consciousness,and is the research object of many scholars.Starting from the analysis of the wolf image in The Company of Wolves,this paper uses Deleuze’s Becoming-Animal Theory to explore the construction of harmony between nature,humans and gender relations in The Company of Wolves.展开更多
Oil painting is a traditional Western painting form.With the introduction of China and the influence of China’s traditional painting and aesthetics,the painting style became more distinctive,expanding a new developme...Oil painting is a traditional Western painting form.With the introduction of China and the influence of China’s traditional painting and aesthetics,the painting style became more distinctive,expanding a new development direction of oil painting,and thus imagery oil painting came into being.Color,as the most important element in imagery oil painting,mainly plays the role of mood creation and emotional expression.Many creators are good at injecting their thoughts and emotions into the paintings through color matching,so as to enhance the artistic expression of the paintings.This paper analyzes the color expression characteristics of imagery oil painting and explores the color expression techniques in imagery oil painting and mood creation of imagery oil painting from several aspects.展开更多
BACKGROUND Rehabilitation nursing is considered an indispensable part of the cerebral infarction treatment system.The hospital–community–family trinity rehabilitation nursing model can provide continuous nursing ser...BACKGROUND Rehabilitation nursing is considered an indispensable part of the cerebral infarction treatment system.The hospital–community–family trinity rehabilitation nursing model can provide continuous nursing services across hospitals,communities,and families for patients.AIM To explore the application of a hospital–community–family rehabilitation nursing model combined with motor imagery therapy in patients with cerebral infarction.METHODS From January 2021 to December 2021,88 patients with cerebral infarction were divided into a study(n=44)and a control(n=44)group using a simple random number table.The control group received routine nursing and motor imagery therapy.The study group was given hospital–community–family trinity rehabilitation nursing based on the control group.Motor function(FMA),balance ability(BBS),activities of daily living(BI),quality of life(SS-QOL),activation status of the contralateral primary sensorimotor cortical area to the affected side,and nursing satisfaction were evaluated before and after intervention in both groups.RESULTS Before intervention,FMA and BBS were similar(P>0.05).After 6 months’intervention,FMA and BBS were significantly higher in the study than in the control group(both P<0.05).Before intervention,BI and SS-QOL scores were not different between the study and control group(P>0.05).However,after 6months’intervention,BI and SS-QOL were higher in the study than in the control group(P<0.05).Before intervention,activation frequency and volume were similar between the study and the control group(P>0.05).After 6 months’intervention,the activation frequency and volume were higher in the study than in the control group(P<0.05).The reliability,empathy,reactivity,assurance,and tangibles scores for quality of nursing service were higher in the study than in the control group(P<0.05).CONCLUSION Combining a hospital–community–family trinity rehabilitation nursing model and motor imagery therapy enhances the motor function and balance ability of patients with cerebral infarction,improving their quality of life.展开更多
Seabed sediment recognition is vital for the exploitation of marine resources.Side-scan sonar(SSS)is an excellent tool for acquiring the imagery of seafloor topography.Combined with ocean surface sampling,it provides ...Seabed sediment recognition is vital for the exploitation of marine resources.Side-scan sonar(SSS)is an excellent tool for acquiring the imagery of seafloor topography.Combined with ocean surface sampling,it provides detailed and accurate images of marine substrate features.Most of the processing of SSS imagery works around limited sampling stations and requires manual interpretation to complete the classification of seabed sediment imagery.In complex sea areas,with manual interpretation,small targets are often lost due to a large amount of information.To date,studies related to the automatic recognition of seabed sediments are still few.This paper proposes a seabed sediment recognition method based on You Only Look Once version 5 and SSS imagery to perform real-time sedi-ment classification and localization for accuracy,particularly on small targets and faster speeds.We used methods such as changing the dataset size,epoch,and optimizer and adding multiscale training to overcome the challenges of having a small sample and a low accuracy.With these methods,we improved the results on mean average precision by 8.98%and F1 score by 11.12%compared with the original method.In addition,the detection speed was approximately 100 frames per second,which is faster than that of previous methods.This speed enabled us to achieve real-time seabed sediment recognition from SSS imagery.展开更多
The accurate and rapid estimation of canopy nitrogen content(CNC)in crops is the key to optimizing in-season nitrogen fertilizer application in precision agriculture.However,the determination of CNC from field samplin...The accurate and rapid estimation of canopy nitrogen content(CNC)in crops is the key to optimizing in-season nitrogen fertilizer application in precision agriculture.However,the determination of CNC from field sampling data for leaf area index(LAI),canopy photosynthetic pigments(CPP;including chlorophyll a,chlorophyll b and carotenoids)and leaf nitrogen concentration(LNC)can be time-consuming and costly.Here we evaluated the use of high-precision unmanned aerial vehicle(UAV)multispectral imagery for estimating the LAI,CPP and CNC of winter wheat over the whole growth period.A total of 23 spectral features(SFs;five original spectrum bands,17 vegetation indices and the gray scale of the RGB image)and eight texture features(TFs;contrast,entropy,variance,mean,homogeneity,dissimilarity,second moment,and correlation)were selected as inputs for the models.Six machine learning methods,i.e.,multiple stepwise regression(MSR),support vector regression(SVR),gradient boosting decision tree(GBDT),Gaussian process regression(GPR),back propagation neural network(BPNN)and radial basis function neural network(RBFNN),were compared for the retrieval of winter wheat LAI,CPP and CNC values,and a double-layer model was proposed for estimating CNC based on LAI and CPP.The results showed that the inversion of winter wheat LAI,CPP and CNC by the combination of SFs+TFs greatly improved the estimation accuracy compared with that by using only the SFs.The RBFNN and BPNN models outperformed the other machine learning models in estimating winter wheat LAI,CPP and CNC.The proposed double-layer models(R^(2)=0.67-0.89,RMSE=13.63-23.71 mg g^(-1),MAE=10.75-17.59 mg g^(-1))performed better than the direct inversion models(R^(2)=0.61-0.80,RMSE=18.01-25.12 mg g^(-1),MAE=12.96-18.88 mg g^(-1))in estimating winter wheat CNC.The best winter wheat CNC accuracy was obtained by the double-layer RBFNN model with SFs+TFs as inputs(R^(2)=0.89,RMSE=13.63 mg g^(-1),MAE=10.75 mg g^(-1)).The results of this study can provide guidance for the accurate and rapid determination of winter wheat canopy nitrogen content in the field.展开更多
The back propagation(BP)neural network method is widely used in bathymetry based on multispectral satellite imagery.However,the classical BP neural network method faces a potential problem because it easily falls into...The back propagation(BP)neural network method is widely used in bathymetry based on multispectral satellite imagery.However,the classical BP neural network method faces a potential problem because it easily falls into a local minimum,leading to model training failure.This study confirmed that the local minimum problem of the BP neural network method exists in the bathymetry field and cannot be ignored.Furthermore,to solve the local minimum problem of the BP neural network method,a bathymetry method based on a BP neural network and ensemble learning(BPEL)is proposed.First,the remote sensing imagery and training sample were used as input datasets,and the BP method was used as the base learner to produce multiple water depth inversion results.Then,a new ensemble strategy,namely the minimum outlying degree method,was proposed and used to integrate the water depth inversion results.Finally,an ensemble bathymetric map was acquired.Anda Reef,northeastern Jiuzhang Atoll,and Pingtan coastal zone were selected as test cases to validate the proposed method.Compared with the BP neural network method,the root-mean-square error and the average relative error of the BPEL method can reduce by 0.65–2.84 m and 16%–46%in the three test cases at most.The results showed that the proposed BPEL method could solve the local minimum problem of the BP neural network method and obtain highly robust and accurate bathymetric maps.展开更多
The graphic design industry has been developing rapidly in recent years.People have begun to focus on steering the development of graphic design in the direction of localization,integrating more traditional Chinese el...The graphic design industry has been developing rapidly in recent years.People have begun to focus on steering the development of graphic design in the direction of localization,integrating more traditional Chinese elements,raising the level of acceptance toward graphic design content,and disseminating traditional culture on this basis.Ink art plays an important role in the historical and cultural development process.It uses simple color contrast to construct different situations and possesses unique artistic charm and cultural heritage.Incorporating ink elements into graphic design may enhance the graphic design style and provide inspiration.This article focuses on the reasons,advantages,and strategies of using ink art in graphic design imagery,hoping to provide references for graphic design activities.展开更多
The concise and informative representation of hyperspectral imagery is achieved via the introduced diffusion geometric coordinates derived from nonlinear dimension reduction maps - diffusion maps. The huge-volume high...The concise and informative representation of hyperspectral imagery is achieved via the introduced diffusion geometric coordinates derived from nonlinear dimension reduction maps - diffusion maps. The huge-volume high- dimensional spectral measurements are organized by the affinity graph where each node in this graph only connects to its local neighbors and each edge in this graph represents local similarity information. By normalizing the affinity graph appropriately, the diffusion operator of the underlying hyperspectral imagery is well-defined, which means that the Markov random walk can be simulated on the hyperspectral imagery. Therefore, the diffusion geometric coordinates, derived from the eigenfunctions and the associated eigenvalues of the diffusion operator, can capture the intrinsic geometric information of the hyperspectral imagery well, which gives more enhanced representation results than traditional linear methods, such as principal component analysis based methods. For large-scale full scene hyperspectral imagery, by exploiting the backbone approach, the computation complexity and the memory requirements are acceptable. Experiments also show that selecting suitable symmetrization normalization techniques while forming the diffusion operator is important to hyperspectral imagery representation.展开更多
By the brief introduction of Kate Chopin and her achievement, this paper elaborates the awakening of consciousness of the feminism of the protagonist in Kate Chopin's The Story of an Hour. In the short story, the ...By the brief introduction of Kate Chopin and her achievement, this paper elaborates the awakening of consciousness of the feminism of the protagonist in Kate Chopin's The Story of an Hour. In the short story, the author uses many literary elements to describe the characters, especially the irony and imagery. This thesis uses those rhetorical devices to vividly describe the characters and to criticize the inequality between men and women in the late 19th century.[1]展开更多
Application of continuous repetition of motor imagery can improve the performance of exercise tasks.However,there is a lack of more detailed neurophysiological evidence to support the formulation of clear standards fo...Application of continuous repetition of motor imagery can improve the performance of exercise tasks.However,there is a lack of more detailed neurophysiological evidence to support the formulation of clear standards for interventions using motor imagery.Moreover,identification of motor imagery intervention time is necessary because it exhibits possible central fatigue.Therefore,the purpose of this study was to elucidate the development of fatigue during continuous repetition of motor imagery through objective and subjective evaluation.The study involved two experiments.In experiment 1,14 healthy young volunteers were required to imagine grasping and lifting a 1.5-L plastic bottle using the whole hand.Each participant performed the motor imagery task 100 times under each condition with 48 hours interval between two conditions:500 mL or 1500 mL of water in the bottle during the demonstration phase.Mental fatigue and a decrease in pinch power appeared under the 1500-mL condition.There were changes in concentration ability or corticospinal excitability,as assessed by motor evoked potentials,between each set with continuous repetition of motor imagery also under the 1500-mL condition.Therefore,in experiment 2,12 healthy volunteers were required to perform the motor imagery task 200 times under the 1500-mL condition.Both concentration ability and corticospinal excitability decreased.This is the first study to show that continuous repetition of motor imagery can decrease corticospinal excitability in addition to producing mental fatigue.This study was approved by the Institutional Ethics Committee at the Nagasaki University Graduate School of Biomedical and Health Sciences(approval No.18121302)on January 30,2019.展开更多
Purpose： This study aimed to investigate the construct of external visual imagery （EVI） vs. internal visual imagery （IV/） by comparing the athletes＇ imagery ability with their levels of skill and types of sports...Purpose： This study aimed to investigate the construct of external visual imagery （EVI） vs. internal visual imagery （IV/） by comparing the athletes＇ imagery ability with their levels of skill and types of sports. Methods： Seventy-two young athletes in open （n = 45） or closed （n = 27） sports and with different skill levels completed 2 custom-designed tasks. The EVI task involved the subject generating and visualizing the rotated images of different body parts, whereas the IVI task involved the subject visualizing himself or herself performing specific movements. Results： The significant Skill-Level x Sport Type interactions for the EVI task revealed that participants who specialized in open sports and had higher skill-levels had a higher accuracy rate as compared to the other subgroups. For the IVI task, the differences between the groups were less clear： those with higher skill-levels or open sports had a higher accuracy rate than those with lower skill-levels or closed sports. Conclusion： EVI involves the visualization of others and the environment, and would be relevant to higher skill-level athletes who engage in open sports. IVI, in contrast, tends to be more self-oriented and would be relevant for utilization by higher skill-level athletes regardless of sport type.展开更多
Wordsworth was famous as one of those"Lake Poets".His famous romantic poem the Daffodils has been read and analyzed by now.This paper elucidates on Wordsworth’s choice of words and also on the greater profo...Wordsworth was famous as one of those"Lake Poets".His famous romantic poem the Daffodils has been read and analyzed by now.This paper elucidates on Wordsworth’s choice of words and also on the greater profound concept that he is trying to depict to his readers,and explains the poem showing how Wordsworth eloquently uses figurative language,imagery,and personification to describe a scenic display of the daffodils and demonstrate his thought"emotion recollected in tranquility"in hope of helping reader understand Wordsworth’s poetry much better.展开更多
Due to the practical problems of the high costs and the long development cycle of China’s cabinet production,a computer-aided design method of the cabinet based on style imagery is proposed.According to the principle...Due to the practical problems of the high costs and the long development cycle of China’s cabinet production,a computer-aided design method of the cabinet based on style imagery is proposed.According to the principle of the conjoint analysis method, the rough set theory and the weight coefficient of different components of the cabinet,a multi-dimensional model of style imagery to evaluate the cabinet is built. Then the related constants of style imagery are calculated and the cabinet components library is also built by the three-dimensional modeling.Finally,with recombinant technology and the mapping model between cabinet style and external characteristics,the prototype system based on Visual Studio is proposed.This system actualizes the bidirectional reasoning between product style imagery and the shape features,which can assist designers to produce more creative designs,greatly improve the efficiency of cabinet development and increase the profits of companies.展开更多
The Thorn Birds and Scarlet Letter both explore the theme of love and religion, and both show the skilful use of imagism and symbolism. This essay analyzes the common images of the two novels and compares their simila...The Thorn Birds and Scarlet Letter both explore the theme of love and religion, and both show the skilful use of imagism and symbolism. This essay analyzes the common images of the two novels and compares their similarities and differences.展开更多
Jean Toomer was an important figure in African-American literature. He was an American poet,novelist and an important figure of the Harlem Renaissance. His most famous work,Cane,was published in 1923 and considered by...Jean Toomer was an important figure in African-American literature. He was an American poet,novelist and an important figure of the Harlem Renaissance. His most famous work,Cane,was published in 1923 and considered by many as a masterpiece of the Harlem Renaissance. Reapers is the first poem in Cane which is related to the reapers in southern plantation and rich in imagery. Toomer conveys profound theme by using various images in Reapers.展开更多
Motor imagery is the mental representation of an action without overt movement or muscle activation. However, the effects of motor imagery on stroke-induced hand dysfunction and brain neural networks are still unknown...Motor imagery is the mental representation of an action without overt movement or muscle activation. However, the effects of motor imagery on stroke-induced hand dysfunction and brain neural networks are still unknown. We conducted a randomized controlled trial in the China Rehabilitation Research Center. Twenty stroke patients, including 13 males and 7 females, 32–51 years old, were recruited and randomly assigned to the traditional rehabilitation treatment group（PP group, n = 10） or the motor imagery training combined with traditional rehabilitation treatment group（MP group, n = 10）. All patients received rehabilitation training once a day, 45 minutes per session, five times per week, for 4 consecutive weeks. In the MP group, motor imagery training was performed for 45 minutes after traditional rehabilitation training, daily. Action Research Arm Test and the Fugl-Meyer Assessment of the upper extremity were used to evaluate hand functions before and after treatment. Transcranial magnetic stimulation was used to analyze motor evoked potentials in the affected extremity. Diffusion tensor imaging was used to assess changes in brain neural networks. Compared with the PP group, the MP group showed better recovery of hand function, higher amplitude of the motor evoked potential in the abductor pollicis brevis, greater fractional anisotropy of the right dorsal pathway, and an increase in the fractional anisotropy of the bilateral dorsal pathway. Our findings indicate that 4 weeks of motor imagery training combined with traditional rehabilitation treatment improves hand function in stroke patients by enhancing the dorsal pathway. This trial has been registered with the Chinese Clinical Trial Registry（registration number： Chi CTR-OCH-12002238）.展开更多
The problem of combined radar imagery from multiple sparse frequency subbands initially incoherent to each other is of practical importance for radar target discrimination.A new coherent processing technique based on ...The problem of combined radar imagery from multiple sparse frequency subbands initially incoherent to each other is of practical importance for radar target discrimination.A new coherent processing technique based on probability density analysis of the subband data is proposed,which is applicable for radar imaging from measurements of two or more initially incoherent radar subbands.The coherence parameters for both amplitude and phase are obtained by combining modern spectral analysis with probability density estimation.The major advantage of the proposed technique lies in that it enables much more robust cohering for the sparse subband data of real-world complex targets.展开更多
基金funded by the Chongqing Normal University Startup Foundation for PhD(22XLB021)supported by the Open Research Project of the State Key Laboratory of Industrial Control Technology,Zhejiang University,China(No.ICT2023B40).
文摘Cloud detection from satellite and drone imagery is crucial for applications such as weather forecasting and environmentalmonitoring.Addressing the limitations of conventional convolutional neural networks,we propose an innovative transformer-based method.This method leverages transformers,which are adept at processing data sequences,to enhance cloud detection accuracy.Additionally,we introduce a Cyclic Refinement Architecture that improves the resolution and quality of feature extraction,thereby aiding in the retention of critical details often lost during cloud detection.Our extensive experimental validation shows that our approach significantly outperforms established models,excelling in high-resolution feature extraction and precise cloud segmentation.By integrating Positional Visual Transformers(PVT)with this architecture,our method advances high-resolution feature delineation and segmentation accuracy.Ultimately,our research offers a novel perspective for surmounting traditional challenges in cloud detection and contributes to the advancement of precise and dependable image analysis across various domains.
基金funded by National Nature Science Foundation of China,Yunnan Funda-Mental Research Projects,Special Project of Guangdong Province in Key Fields of Ordinary Colleges and Universities and Chaozhou Science and Technology Plan Project of Funder Grant Numbers 82060329,202201AT070108,2023ZDZX2038 and 202201GY01.
文摘The analysis of microstates in EEG signals is a crucial technique for understanding the spatiotemporal dynamics of brain electrical activity.Traditional methods such as Atomic Agglomerative Hierarchical Clustering(AAHC),K-means clustering,Principal Component Analysis(PCA),and Independent Component Analysis(ICA)are limited by a fixed number of microstate maps and insufficient capability in cross-task feature extraction.Tackling these limitations,this study introduces a Global Map Dissimilarity(GMD)-driven density canopy K-means clustering algorithm.This innovative approach autonomously determines the optimal number of EEG microstate topographies and employs Gaussian kernel density estimation alongside the GMD index for dynamic modeling of EEG data.Utilizing this advanced algorithm,the study analyzes the Motor Imagery(MI)dataset from the GigaScience database,GigaDB.The findings reveal six distinct microstates during actual right-hand movement and five microstates across other task conditions,with microstate C showing superior performance in all task states.During imagined movement,microstate A was significantly enhanced.Comparison with existing algorithms indicates a significant improvement in clustering performance by the refined method,with an average Calinski-Harabasz Index(CHI)of 35517.29 and a Davis-Bouldin Index(DBI)average of 2.57.Furthermore,an information-theoretical analysis of the microstate sequences suggests that imagined movement exhibits higher complexity and disorder than actual movement.By utilizing the extracted microstate sequence parameters as features,the improved algorithm achieved a classification accuracy of 98.41%in EEG signal categorization for motor imagery.A performance of 78.183%accuracy was achieved in a four-class motor imagery task on the BCI-IV-2a dataset.These results demonstrate the potential of the advanced algorithm in microstate analysis,offering a more effective tool for a deeper understanding of the spatiotemporal features of EEG signals.
文摘Motor imagery(MI)based electroencephalogram(EEG)represents a frontier in enabling direct neural control of external devices and advancing neural rehabilitation.This study introduces a novel time embedding technique,termed traveling-wave based time embedding,utilized as a pseudo channel to enhance the decoding accuracy of MI-EEG signals across various neural network architectures.Unlike traditional neural network methods that fail to account for the temporal dynamics in MI-EEG in individual difference,our approach captures time-related changes for different participants based on a priori knowledge.Through extensive experimentation with multiple participants,we demonstrate that this method not only improves classification accuracy but also exhibits greater adaptability to individual differences compared to position encoding used in Transformer architecture.Significantly,our results reveal that traveling-wave based time embedding crucially enhances decoding accuracy,particularly for participants typically considered“EEG-illiteracy”.As a novel direction in EEG research,the traveling-wave based time embedding not only offers fresh insights for neural network decoding strategies but also expands new avenues for research into attention mechanisms in neuroscience and a deeper understanding of EEG signals.
文摘Imagery analysis is a commonly used analytical method in literary analysis.In Angela Carter’s work,the image of wolves is particularly prominent.Her“Werewolf Tetralogy”rewrites traditional culture and subverts traditional consciousness,and is the research object of many scholars.Starting from the analysis of the wolf image in The Company of Wolves,this paper uses Deleuze’s Becoming-Animal Theory to explore the construction of harmony between nature,humans and gender relations in The Company of Wolves.
文摘Oil painting is a traditional Western painting form.With the introduction of China and the influence of China’s traditional painting and aesthetics,the painting style became more distinctive,expanding a new development direction of oil painting,and thus imagery oil painting came into being.Color,as the most important element in imagery oil painting,mainly plays the role of mood creation and emotional expression.Many creators are good at injecting their thoughts and emotions into the paintings through color matching,so as to enhance the artistic expression of the paintings.This paper analyzes the color expression characteristics of imagery oil painting and explores the color expression techniques in imagery oil painting and mood creation of imagery oil painting from several aspects.
基金Supported by the Key Research and Development Programs of Shaanxi Province,No.2021SF-059。
文摘BACKGROUND Rehabilitation nursing is considered an indispensable part of the cerebral infarction treatment system.The hospital–community–family trinity rehabilitation nursing model can provide continuous nursing services across hospitals,communities,and families for patients.AIM To explore the application of a hospital–community–family rehabilitation nursing model combined with motor imagery therapy in patients with cerebral infarction.METHODS From January 2021 to December 2021,88 patients with cerebral infarction were divided into a study(n=44)and a control(n=44)group using a simple random number table.The control group received routine nursing and motor imagery therapy.The study group was given hospital–community–family trinity rehabilitation nursing based on the control group.Motor function(FMA),balance ability(BBS),activities of daily living(BI),quality of life(SS-QOL),activation status of the contralateral primary sensorimotor cortical area to the affected side,and nursing satisfaction were evaluated before and after intervention in both groups.RESULTS Before intervention,FMA and BBS were similar(P>0.05).After 6 months’intervention,FMA and BBS were significantly higher in the study than in the control group(both P<0.05).Before intervention,BI and SS-QOL scores were not different between the study and control group(P>0.05).However,after 6months’intervention,BI and SS-QOL were higher in the study than in the control group(P<0.05).Before intervention,activation frequency and volume were similar between the study and the control group(P>0.05).After 6 months’intervention,the activation frequency and volume were higher in the study than in the control group(P<0.05).The reliability,empathy,reactivity,assurance,and tangibles scores for quality of nursing service were higher in the study than in the control group(P<0.05).CONCLUSION Combining a hospital–community–family trinity rehabilitation nursing model and motor imagery therapy enhances the motor function and balance ability of patients with cerebral infarction,improving their quality of life.
基金funded by the Natural Science Foundation of Fujian Province(No.2018J01063)the Project of Deep Learning Based Underwater Cultural Relics Recognization(No.38360041)the Project of the State Administration of Cultural Relics(No.2018300).
文摘Seabed sediment recognition is vital for the exploitation of marine resources.Side-scan sonar(SSS)is an excellent tool for acquiring the imagery of seafloor topography.Combined with ocean surface sampling,it provides detailed and accurate images of marine substrate features.Most of the processing of SSS imagery works around limited sampling stations and requires manual interpretation to complete the classification of seabed sediment imagery.In complex sea areas,with manual interpretation,small targets are often lost due to a large amount of information.To date,studies related to the automatic recognition of seabed sediments are still few.This paper proposes a seabed sediment recognition method based on You Only Look Once version 5 and SSS imagery to perform real-time sedi-ment classification and localization for accuracy,particularly on small targets and faster speeds.We used methods such as changing the dataset size,epoch,and optimizer and adding multiscale training to overcome the challenges of having a small sample and a low accuracy.With these methods,we improved the results on mean average precision by 8.98%and F1 score by 11.12%compared with the original method.In addition,the detection speed was approximately 100 frames per second,which is faster than that of previous methods.This speed enabled us to achieve real-time seabed sediment recognition from SSS imagery.
基金funded by the Key Research and Development Program of Shaanxi Province of China(2022NY-063)the Chinese Universities Scientific Fund(2452020018).
文摘The accurate and rapid estimation of canopy nitrogen content(CNC)in crops is the key to optimizing in-season nitrogen fertilizer application in precision agriculture.However,the determination of CNC from field sampling data for leaf area index(LAI),canopy photosynthetic pigments(CPP;including chlorophyll a,chlorophyll b and carotenoids)and leaf nitrogen concentration(LNC)can be time-consuming and costly.Here we evaluated the use of high-precision unmanned aerial vehicle(UAV)multispectral imagery for estimating the LAI,CPP and CNC of winter wheat over the whole growth period.A total of 23 spectral features(SFs;five original spectrum bands,17 vegetation indices and the gray scale of the RGB image)and eight texture features(TFs;contrast,entropy,variance,mean,homogeneity,dissimilarity,second moment,and correlation)were selected as inputs for the models.Six machine learning methods,i.e.,multiple stepwise regression(MSR),support vector regression(SVR),gradient boosting decision tree(GBDT),Gaussian process regression(GPR),back propagation neural network(BPNN)and radial basis function neural network(RBFNN),were compared for the retrieval of winter wheat LAI,CPP and CNC values,and a double-layer model was proposed for estimating CNC based on LAI and CPP.The results showed that the inversion of winter wheat LAI,CPP and CNC by the combination of SFs+TFs greatly improved the estimation accuracy compared with that by using only the SFs.The RBFNN and BPNN models outperformed the other machine learning models in estimating winter wheat LAI,CPP and CNC.The proposed double-layer models(R^(2)=0.67-0.89,RMSE=13.63-23.71 mg g^(-1),MAE=10.75-17.59 mg g^(-1))performed better than the direct inversion models(R^(2)=0.61-0.80,RMSE=18.01-25.12 mg g^(-1),MAE=12.96-18.88 mg g^(-1))in estimating winter wheat CNC.The best winter wheat CNC accuracy was obtained by the double-layer RBFNN model with SFs+TFs as inputs(R^(2)=0.89,RMSE=13.63 mg g^(-1),MAE=10.75 mg g^(-1)).The results of this study can provide guidance for the accurate and rapid determination of winter wheat canopy nitrogen content in the field.
基金The National Natural Science Foundation of China under contract No.42001401the China Postdoctoral Science Foundation under contract No.2020M671431+1 种基金the Fundamental Research Funds for the Central Universities under contract No.0209-14380096the Guangxi Innovative Development Grand Grant under contract No.2018AA13005.
文摘The back propagation(BP)neural network method is widely used in bathymetry based on multispectral satellite imagery.However,the classical BP neural network method faces a potential problem because it easily falls into a local minimum,leading to model training failure.This study confirmed that the local minimum problem of the BP neural network method exists in the bathymetry field and cannot be ignored.Furthermore,to solve the local minimum problem of the BP neural network method,a bathymetry method based on a BP neural network and ensemble learning(BPEL)is proposed.First,the remote sensing imagery and training sample were used as input datasets,and the BP method was used as the base learner to produce multiple water depth inversion results.Then,a new ensemble strategy,namely the minimum outlying degree method,was proposed and used to integrate the water depth inversion results.Finally,an ensemble bathymetric map was acquired.Anda Reef,northeastern Jiuzhang Atoll,and Pingtan coastal zone were selected as test cases to validate the proposed method.Compared with the BP neural network method,the root-mean-square error and the average relative error of the BPEL method can reduce by 0.65–2.84 m and 16%–46%in the three test cases at most.The results showed that the proposed BPEL method could solve the local minimum problem of the BP neural network method and obtain highly robust and accurate bathymetric maps.
文摘The graphic design industry has been developing rapidly in recent years.People have begun to focus on steering the development of graphic design in the direction of localization,integrating more traditional Chinese elements,raising the level of acceptance toward graphic design content,and disseminating traditional culture on this basis.Ink art plays an important role in the historical and cultural development process.It uses simple color contrast to construct different situations and possesses unique artistic charm and cultural heritage.Incorporating ink elements into graphic design may enhance the graphic design style and provide inspiration.This article focuses on the reasons,advantages,and strategies of using ink art in graphic design imagery,hoping to provide references for graphic design activities.
基金The National Key Technologies R & D Program during the 11th Five-Year Plan Period (No.2006BAB15B01)
文摘The concise and informative representation of hyperspectral imagery is achieved via the introduced diffusion geometric coordinates derived from nonlinear dimension reduction maps - diffusion maps. The huge-volume high- dimensional spectral measurements are organized by the affinity graph where each node in this graph only connects to its local neighbors and each edge in this graph represents local similarity information. By normalizing the affinity graph appropriately, the diffusion operator of the underlying hyperspectral imagery is well-defined, which means that the Markov random walk can be simulated on the hyperspectral imagery. Therefore, the diffusion geometric coordinates, derived from the eigenfunctions and the associated eigenvalues of the diffusion operator, can capture the intrinsic geometric information of the hyperspectral imagery well, which gives more enhanced representation results than traditional linear methods, such as principal component analysis based methods. For large-scale full scene hyperspectral imagery, by exploiting the backbone approach, the computation complexity and the memory requirements are acceptable. Experiments also show that selecting suitable symmetrization normalization techniques while forming the diffusion operator is important to hyperspectral imagery representation.
文摘By the brief introduction of Kate Chopin and her achievement, this paper elaborates the awakening of consciousness of the feminism of the protagonist in Kate Chopin's The Story of an Hour. In the short story, the author uses many literary elements to describe the characters, especially the irony and imagery. This thesis uses those rhetorical devices to vividly describe the characters and to criticize the inequality between men and women in the late 19th century.[1]
文摘Application of continuous repetition of motor imagery can improve the performance of exercise tasks.However,there is a lack of more detailed neurophysiological evidence to support the formulation of clear standards for interventions using motor imagery.Moreover,identification of motor imagery intervention time is necessary because it exhibits possible central fatigue.Therefore,the purpose of this study was to elucidate the development of fatigue during continuous repetition of motor imagery through objective and subjective evaluation.The study involved two experiments.In experiment 1,14 healthy young volunteers were required to imagine grasping and lifting a 1.5-L plastic bottle using the whole hand.Each participant performed the motor imagery task 100 times under each condition with 48 hours interval between two conditions:500 mL or 1500 mL of water in the bottle during the demonstration phase.Mental fatigue and a decrease in pinch power appeared under the 1500-mL condition.There were changes in concentration ability or corticospinal excitability,as assessed by motor evoked potentials,between each set with continuous repetition of motor imagery also under the 1500-mL condition.Therefore,in experiment 2,12 healthy volunteers were required to perform the motor imagery task 200 times under the 1500-mL condition.Both concentration ability and corticospinal excitability decreased.This is the first study to show that continuous repetition of motor imagery can decrease corticospinal excitability in addition to producing mental fatigue.This study was approved by the Institutional Ethics Committee at the Nagasaki University Graduate School of Biomedical and Health Sciences(approval No.18121302)on January 30,2019.
基金supported by the Dr.and Mrs.Sui Kau Chan donation grant for sports training and rehabilitation held by Chetwyn C.H.Chan and Amy S.N.Fuand by an internal grant awarded to Chetwyn C.H.Chan by The Hong Kong Polytechnic University
文摘Purpose： This study aimed to investigate the construct of external visual imagery （EVI） vs. internal visual imagery （IV/） by comparing the athletes＇ imagery ability with their levels of skill and types of sports. Methods： Seventy-two young athletes in open （n = 45） or closed （n = 27） sports and with different skill levels completed 2 custom-designed tasks. The EVI task involved the subject generating and visualizing the rotated images of different body parts, whereas the IVI task involved the subject visualizing himself or herself performing specific movements. Results： The significant Skill-Level x Sport Type interactions for the EVI task revealed that participants who specialized in open sports and had higher skill-levels had a higher accuracy rate as compared to the other subgroups. For the IVI task, the differences between the groups were less clear： those with higher skill-levels or open sports had a higher accuracy rate than those with lower skill-levels or closed sports. Conclusion： EVI involves the visualization of others and the environment, and would be relevant to higher skill-level athletes who engage in open sports. IVI, in contrast, tends to be more self-oriented and would be relevant for utilization by higher skill-level athletes regardless of sport type.
文摘Wordsworth was famous as one of those"Lake Poets".His famous romantic poem the Daffodils has been read and analyzed by now.This paper elucidates on Wordsworth’s choice of words and also on the greater profound concept that he is trying to depict to his readers,and explains the poem showing how Wordsworth eloquently uses figurative language,imagery,and personification to describe a scenic display of the daffodils and demonstrate his thought"emotion recollected in tranquility"in hope of helping reader understand Wordsworth’s poetry much better.
基金The National Natural Science Foundation of China(No.71271053)the Scientific Innovation Research of College Graduates in Jiangsu Province(No.CXLX13_082)
文摘Due to the practical problems of the high costs and the long development cycle of China’s cabinet production,a computer-aided design method of the cabinet based on style imagery is proposed.According to the principle of the conjoint analysis method, the rough set theory and the weight coefficient of different components of the cabinet,a multi-dimensional model of style imagery to evaluate the cabinet is built. Then the related constants of style imagery are calculated and the cabinet components library is also built by the three-dimensional modeling.Finally,with recombinant technology and the mapping model between cabinet style and external characteristics,the prototype system based on Visual Studio is proposed.This system actualizes the bidirectional reasoning between product style imagery and the shape features,which can assist designers to produce more creative designs,greatly improve the efficiency of cabinet development and increase the profits of companies.
文摘The Thorn Birds and Scarlet Letter both explore the theme of love and religion, and both show the skilful use of imagism and symbolism. This essay analyzes the common images of the two novels and compares their similarities and differences.
文摘Jean Toomer was an important figure in African-American literature. He was an American poet,novelist and an important figure of the Harlem Renaissance. His most famous work,Cane,was published in 1923 and considered by many as a masterpiece of the Harlem Renaissance. Reapers is the first poem in Cane which is related to the reapers in southern plantation and rich in imagery. Toomer conveys profound theme by using various images in Reapers.
基金supported by the National Natural Science Foundation of China,No.U1613228a grant from the Sub-Project under National “Twelfth Five-Year” Plan for Science & Technology Support Project in China,No.2011BAI08B11+1 种基金a grant from the Beijing Municipal Science & Technology Commission in China,No.Z161100002616018the Special Fund for Basic Scientific Research Business of Central Public Scientific Research Institutes in China,No.2014CZ-5,2015CZ-30
文摘Motor imagery is the mental representation of an action without overt movement or muscle activation. However, the effects of motor imagery on stroke-induced hand dysfunction and brain neural networks are still unknown. We conducted a randomized controlled trial in the China Rehabilitation Research Center. Twenty stroke patients, including 13 males and 7 females, 32–51 years old, were recruited and randomly assigned to the traditional rehabilitation treatment group（PP group, n = 10） or the motor imagery training combined with traditional rehabilitation treatment group（MP group, n = 10）. All patients received rehabilitation training once a day, 45 minutes per session, five times per week, for 4 consecutive weeks. In the MP group, motor imagery training was performed for 45 minutes after traditional rehabilitation training, daily. Action Research Arm Test and the Fugl-Meyer Assessment of the upper extremity were used to evaluate hand functions before and after treatment. Transcranial magnetic stimulation was used to analyze motor evoked potentials in the affected extremity. Diffusion tensor imaging was used to assess changes in brain neural networks. Compared with the PP group, the MP group showed better recovery of hand function, higher amplitude of the motor evoked potential in the abductor pollicis brevis, greater fractional anisotropy of the right dorsal pathway, and an increase in the fractional anisotropy of the bilateral dorsal pathway. Our findings indicate that 4 weeks of motor imagery training combined with traditional rehabilitation treatment improves hand function in stroke patients by enhancing the dorsal pathway. This trial has been registered with the Chinese Clinical Trial Registry（registration number： Chi CTR-OCH-12002238）.
文摘The problem of combined radar imagery from multiple sparse frequency subbands initially incoherent to each other is of practical importance for radar target discrimination.A new coherent processing technique based on probability density analysis of the subband data is proposed,which is applicable for radar imaging from measurements of two or more initially incoherent radar subbands.The coherence parameters for both amplitude and phase are obtained by combining modern spectral analysis with probability density estimation.The major advantage of the proposed technique lies in that it enables much more robust cohering for the sparse subband data of real-world complex targets.
