Optical Character Recognition(OCR)refers to a technology that uses image processing technology and character recognition algorithms to identify characters on an image.This paper is a deep study on the recognition effe...Optical Character Recognition(OCR)refers to a technology that uses image processing technology and character recognition algorithms to identify characters on an image.This paper is a deep study on the recognition effect of OCR based on Artificial Intelligence(AI)algorithms,in which the different AI algorithms for OCR analysis are classified and reviewed.Firstly,the mechanisms and characteristics of artificial neural network-based OCR are summarized.Secondly,this paper explores machine learning-based OCR,and draws the conclusion that the algorithms available for this form of OCR are still in their infancy,with low generalization and fixed recognition errors,albeit with better recognition effect and higher recognition accuracy.Finally,this paper explores several of the latest algorithms such as deep learning and pattern recognition algorithms.This paper concludes that OCR requires algorithms with higher recognition accuracy.展开更多
The utilization of visual attention enhances the performance of image classification tasks.Previous attentionbased models have demonstrated notable performance,but many of these models exhibit reduced accuracy when co...The utilization of visual attention enhances the performance of image classification tasks.Previous attentionbased models have demonstrated notable performance,but many of these models exhibit reduced accuracy when confronted with inter-class and intra-class similarities and differences.Neural-Controlled Differential Equations(N-CDE’s)and Neural Ordinary Differential Equations(NODE’s)are extensively utilized within this context.NCDE’s possesses the capacity to effectively illustrate both inter-class and intra-class similarities and differences with enhanced clarity.To this end,an attentive neural network has been proposed to generate attention maps,which uses two different types of N-CDE’s,one for adopting hidden layers and the other to generate attention values.Two distinct attention techniques are implemented including time-wise attention,also referred to as bottom N-CDE’s;and element-wise attention,called topN-CDE’s.Additionally,a trainingmethodology is proposed to guarantee that the training problem is sufficiently presented.Two classification tasks including fine-grained visual classification andmulti-label classification,are utilized to evaluate the proposedmodel.The proposedmethodology is employed on five publicly available datasets,including CUB-200-2011,ImageNet-1K,PASCAL VOC 2007,PASCAL VOC 2012,and MS COCO.The obtained visualizations have demonstrated that N-CDE’s are better appropriate for attention-based activities in comparison to conventional NODE’s.展开更多
Multi-modal histological image registration tasks pose significant challenges due to tissue staining operations causing partial loss and folding of tissue.Convolutional neural network(CNN)and generative adversarial ne...Multi-modal histological image registration tasks pose significant challenges due to tissue staining operations causing partial loss and folding of tissue.Convolutional neural network(CNN)and generative adversarial network(GAN)are pivotal inmedical image registration.However,existing methods often struggle with severe interference and deformation,as seen in histological images of conditions like Cushing’s disease.We argue that the failure of current approaches lies in underutilizing the feature extraction capability of the discriminator inGAN.In this study,we propose a novel multi-modal registration approach GAN-DIRNet based on GAN for deformable histological image registration.To begin with,the discriminators of two GANs are embedded as a new dual parallel feature extraction module into the unsupervised registration networks,characterized by implicitly extracting feature descriptors of specific modalities.Additionally,modal feature description layers and registration layers collaborate in unsupervised optimization,facilitating faster convergence and more precise results.Lastly,experiments and evaluations were conducted on the registration of the Mixed National Institute of Standards and Technology database(MNIST),eight publicly available datasets of histological sections and the Clustering-Registration-Classification-Segmentation(CRCS)dataset on the Cushing’s disease.Experimental results demonstrate that our proposed GAN-DIRNet method surpasses existing approaches like DIRNet in terms of both registration accuracy and time efficiency,while also exhibiting robustness across different image types.展开更多
Hyperspectral image classification stands as a pivotal task within the field of remote sensing,yet achieving highprecision classification remains a significant challenge.In response to this challenge,a Spectral Convol...Hyperspectral image classification stands as a pivotal task within the field of remote sensing,yet achieving highprecision classification remains a significant challenge.In response to this challenge,a Spectral Convolutional Neural Network model based on Adaptive Fick’s Law Algorithm(AFLA-SCNN)is proposed.The Adaptive Fick’s Law Algorithm(AFLA)constitutes a novel metaheuristic algorithm introduced herein,encompassing three new strategies:Adaptive weight factor,Gaussian mutation,and probability update policy.With adaptive weight factor,the algorithmcan adjust theweights according to the change in the number of iterations to improve the performance of the algorithm.Gaussianmutation helps the algorithm avoid falling into local optimal solutions and improves the searchability of the algorithm.The probability update strategy helps to improve the exploitability and adaptability of the algorithm.Within the AFLA-SCNN model,AFLA is employed to optimize two hyperparameters in the SCNN model,namely,“numEpochs”and“miniBatchSize”,to attain their optimal values.AFLA’s performance is initially validated across 28 functions in 10D,30D,and 50D for CEC2013 and 29 functions in 10D,30D,and 50D for CEC2017.Experimental results indicate AFLA’s marked performance superiority over nine other prominent optimization algorithms.Subsequently,the AFLA-SCNN model was compared with the Spectral Convolutional Neural Network model based on Fick’s Law Algorithm(FLA-SCNN),Spectral Convolutional Neural Network model based on Harris Hawks Optimization(HHO-SCNN),Spectral Convolutional Neural Network model based onDifferential Evolution(DE-SCNN),SpectralConvolutionalNeuralNetwork(SCNN)model,and SupportVector Machines(SVM)model using the Indian Pines dataset and PaviaUniversity dataset.The experimental results show that the AFLA-SCNN model outperforms other models in terms of Accuracy,Precision,Recall,and F1-score on Indian Pines and Pavia University.Among them,the Accuracy of the AFLA-SCNN model on Indian Pines reached 99.875%,and the Accuracy on PaviaUniversity reached 98.022%.In conclusion,our proposed AFLA-SCNN model is deemed to significantly enhance the precision of hyperspectral image classification.展开更多
Health care is an important part of human life and is a right for everyone. One of the most basic human rights is to receive health care whenever they need it. However, this is simply not an option for everyone due to...Health care is an important part of human life and is a right for everyone. One of the most basic human rights is to receive health care whenever they need it. However, this is simply not an option for everyone due to the social conditions in which some communities live and not everyone has access to it. This paper aims to serve as a reference point and guide for users who are interested in monitoring their health, particularly their blood analysis to be aware of their health condition in an easy way. This study introduces an algorithmic approach for extracting and analyzing Complete Blood Count (CBC) parameters from scanned images. The algorithm employs Optical Character Recognition (OCR) technology to process images containing tabular data, specifically targeting CBC parameter tables. Upon image processing, the algorithm extracts data and identifies CBC parameters and their corresponding values. It evaluates the status (High, Low, or Normal) of each parameter and subsequently presents evaluations, and any potential diagnoses. The primary objective is to automate the extraction and evaluation of CBC parameters, aiding healthcare professionals in swiftly assessing blood analysis results. The algorithmic framework aims to streamline the interpretation of CBC tests, potentially improving efficiency and accuracy in clinical diagnostics.展开更多
In this paper, a novel approach is proposed for denoising of Chinese calligraphy tablet documents. The method includes two phases: First, a partial differential equations (PDE) based the total variation model and Otsu...In this paper, a novel approach is proposed for denoising of Chinese calligraphy tablet documents. The method includes two phases: First, a partial differential equations (PDE) based the total variation model and Otsu thresholding method are used to preprocess the calligraphy document image. Second, a new method based on run-length statistics and structure charac- teristics of Chinese characters is proposed to remove some random and ant-like noises. This includes the optimal threshold se- lection from histogram of run-length probability density, and improved Hough transform algorithm for line shape noise detection and removal. Examples are given in the paper to demonstrate the proposed method.展开更多
An image segmentation algorithm of the restrained fuzzy Kohonen clustering network （RFKCN） based on high- dimension fuzzy character is proposed. The algorithm includes two steps. The first step is the fuzzification ...An image segmentation algorithm of the restrained fuzzy Kohonen clustering network （RFKCN） based on high- dimension fuzzy character is proposed. The algorithm includes two steps. The first step is the fuzzification of pixels in which two redundant images are built by fuzzy mean value and fuzzy median value. The second step is to construct a three-dimensional （3-D） feature vector of redundant images and their original images and cluster the feature vector through RFKCN, to realize image seg- mentation. The proposed algorithm fully takes into account not only gray distribution information of pixels, but also relevant information and fuzzy information among neighboring pixels in constructing 3- D character space. Based on the combination of competitiveness, redundancy and complementary of the information, the proposed algorithm improves the accuracy of clustering. Theoretical anal- yses and experimental results demonstrate that the proposed algorithm has a good segmentation performance.展开更多
As the typical representative of love and marriage drama in Yuan variety play,Qiuhu philander his wife plays a relatively important role in it.This paper carries on the analysis in a few typical character image,which ...As the typical representative of love and marriage drama in Yuan variety play,Qiuhu philander his wife plays a relatively important role in it.This paper carries on the analysis in a few typical character image,which are Luo Meiying who has the courage to fight,the hypocritical and insidious Qiu Hu,the ugly and vicious Li Dahu,the greedy and hard-hearted Luo Dahu,the kind and helpless mother-in-law Mei Ying,these five different images apparently jumping on the paper.展开更多
Image is a term that mainly embodies in the composition of classical Chinese poetry(CCP). Effective translation of images is crucial to the grasp of original meanings in a poem. As aesthetic beauty is the primary conc...Image is a term that mainly embodies in the composition of classical Chinese poetry(CCP). Effective translation of images is crucial to the grasp of original meanings in a poem. As aesthetic beauty is the primary concern in poetry,the conveyance of beauty in image has a direct impact in translation. To analyze translation strategies of imagery beauty,the theory of"translation levels"by Xu Jun is adopted as a criterion in comparing variant English versions of CCP in the aesthetic level. Images are selected from Seven-character quatrains typified for abundant sources of images,and features of images are put forward at the aesthetic level. Through the analysis,images are rendered by recreation of the sensuous and emotional beauty.展开更多
Nowadays,presynaptic dopaminergic positron emission tomography,which assesses deficiencies in dopamine synthesis,storage,and transport,is widely utilized for early diagnosis and differential diagnosis of parkinsonism....Nowadays,presynaptic dopaminergic positron emission tomography,which assesses deficiencies in dopamine synthesis,storage,and transport,is widely utilized for early diagnosis and differential diagnosis of parkinsonism.This review provides a comprehensive summary of the latest developments in the application of presynaptic dopaminergic positron emission tomography imaging in disorders that manifest parkinsonism.We conducted a thorough literature search using reputable databases such as PubMed and Web of Science.Selection criteria involved identifying peer-reviewed articles published within the last 5 years,with emphasis on their relevance to clinical applications.The findings from these studies highlight that presynaptic dopaminergic positron emission tomography has demonstrated potential not only in diagnosing and differentiating various Parkinsonian conditions but also in assessing disease severity and predicting prognosis.Moreover,when employed in conjunction with other imaging modalities and advanced analytical methods,presynaptic dopaminergic positron emission tomography has been validated as a reliable in vivo biomarker.This validation extends to screening and exploring potential neuropathological mechanisms associated with dopaminergic depletion.In summary,the insights gained from interpreting these studies are crucial for enhancing the effectiveness of preclinical investigations and clinical trials,ultimately advancing toward the goals of neuroregeneration in parkinsonian disorders.展开更多
Titled as the name of the main characters,the seven parts in The Thorn Birds together tell the story of the three generations of the Cleary family from 1915 to 1969.Fiona and Paddy are the first generation,Meggie and ...Titled as the name of the main characters,the seven parts in The Thorn Birds together tell the story of the three generations of the Cleary family from 1915 to 1969.Fiona and Paddy are the first generation,Meggie and Ralph are the second generation,and Justine and Dane are the third generation.Although they are both thorny birds,they have different personal characteristics and life pursuits.Fiona,Meggie,and Justine,as women,are more and more rebellious from generation to generation.They are more and more daring to fight against the Almighty God and their cruel fates.But at the same time,in the process of pursuing self-happiness,there are also dislocations of ethical identity of these women who inevitably make wrong ethical choices.The author of this thesis tries to analyze the ethical identity of the three generations of women in The Thorn Birds from a relatively comprehensive perspective based on literary ethics,and then analyzes the round ethical image of these female characters.展开更多
BACKGROUND： Diffusion tensor imaging （DTI） is one of the noninvasive methods to study the morphological structure of brain white matter fibrous bands in vivo, and it has been applied primarily in clinic. DTI is ack...BACKGROUND： Diffusion tensor imaging （DTI） is one of the noninvasive methods to study the morphological structure of brain white matter fibrous bands in vivo, and it has been applied primarily in clinic. DTI is acknowledged as the more effective imaging method to diagnose ultra-acute and/or acute cerebral infarction.OB_3ECTIVE： To observe the anisotropic characters of cerebral white matter fibrous bands in patients with ischemic stroke by using DTI, and investigate the correlation between the damage of corticospinal tract and muscle strength in patients with ischemic stroke at acute period.DESIGN： A case-control observationSEFIING： Department of Medical Imaging, Fuzhou General Hospital of Nanjing Military Area Command of Chinese PLA.PARTICIPANTS： Nine inpatients with injury of motor function induced by acute ischemic stroke （patient group） at 6 hours to 2 weeks after the attack were selected from the Department of Neurology, Fuzhou General Hospital of Nanjing Military Area Command of Chinese PLA from September 2005 to March 2006, and they all accorded with the present diagnostic standard for cerebrovascular disease in China. There were 5 males and 4 females, aged 16-87 years. At the same time, nine healthy right-handed physical examinees matched by age and sex with the patients were taken as the control group, and they all had no nervous disease, mental diseases, cerebrovascular abnormalities and injury history, etc. All the subjects were informed with the detected items and agreed to participate in the study.METHODS： All the 9 patients with ischemic stroke at acute period and 9 healthy subjects were examined with MRI, T1 weighted imaging, T2 weighted imaging and DTI. And the data were processed offline with dTV.II software, the images of fractional anisotropy and directional encoded color （DEC） were obtained, and the three-dimensional fibrous band images of bilateral corticospinal tracts were reconstructed. In the control group, the values of fractional anisotropy of main white matter fibrous bands were measured in the region of interest （ROI） of the anterior limb, knee and posterior limb of internal capsule. In the patient group, the values of fractional anisotropy of white matter were measured in the infarcted sites and corresponding contralateral sites of the patients. The ROI was set in bilateral cerebral peduncles to reconstruct three-dimensionally the bilateral corticospinal tracts. The muscle strength of the affected hand was assessed with Brunnstorm standard in the stroke patients.MAIN OUTCOME MEASURES ： The characters of DTI and images of the value of fractional anisotropy, and the manifestations of three-dimensional corticospinal tracts were observed in the two groups.RESULTS： All the data from the 9 patients and 9 healthy volunteers were involved in the analysis of results. In the control group, the white matter and gray matter could be distinguished clearly in the image of fractional anisotropic values, the fibers of different directions were shown by different colors in DEC picture, which clearly demonstrated the normal anatomic structure and direction of white matter fibers. In the patient group, the infarctions occurred in the gray matter or white matter could be distinguished in the images of fractional anisotropic values, DEC picture could clearly show the direct influence of the infarcted site on the white matter fibers. The fractional anisotropic values in different white matter structure of the same side were significantly different in the control group （t=-3.12, P 〈 0.05）, and the reconstructed images fractional anisotropic values and DEC picture could show most of the main white matter fibrous bands. The fractional anisotropic values of the infarcted sites were significantly lower than the contralateral ones in the patient group （t=-5.570, P 〈 0.01）. ② The reconstructed bilateral corticospinal tracts showed that the anatomic forms of the contralateral corticospinal tract of the patients were almost identical to those of normal people, it started from precentral gyrus, downward to the nternal capsule, and extended to pontine and medulla oblongata, each fibrous band was continuous, and the form had good consistency. Because of the involvement of infarction of different severity, the ipsilateral corticospinal tract manifested as continuous interruption and the loss of consistent anatomic structural form. The involved severity of corticospinal tract had significant correlation with that of muscle strength of the ipsilateral hand （r=-1.30, P 〈 0.01）.CONCLUSION： ① DTI can display the direction and distribution of cerebral white matter fibrous bands.② DTI images of fractional anisotropic values and DEC can show the directions and anisotropic degree of white matter fibers in the infarcted sites of stroke patients. ③ The three-dimensional images of fibrous bands can show the conditions of pyramidal tracts more directly. ④ The damaged severity of corticospinal tracts is correlated with that of muscle strength.展开更多
Ruth and Mary are two heroines in Eugene O'Neill's plays Beyond the Horizon, and Long Day's Journey into Night. They have some similarities: when they are young, they are beautiful, native and full of hope...Ruth and Mary are two heroines in Eugene O'Neill's plays Beyond the Horizon, and Long Day's Journey into Night. They have some similarities: when they are young, they are beautiful, native and full of hope towards the future life, but both make wrong choices; in the following years, both suffer a lot from these wrong choices, and feel regretful. This paper tries to explore these two tragic female images.展开更多
After the introduction of tourist resources in Wunvfeng National Forest Park, the paper had planed its overall image from the perspectives of concept design, visual identity, behavioral norms and audio identity. The s...After the introduction of tourist resources in Wunvfeng National Forest Park, the paper had planed its overall image from the perspectives of concept design, visual identity, behavioral norms and audio identity. The slogan of Wunvfeng National Forest Park had been identified as "tour of nature and mythology-Wunvfeng", and the park's emblem, symbolic mascots, spokesman of tourism image and tourist souvenirs had been set, so as to better display tourist advantages of Wunvfeng National Forest Park and create more economic and social benefits.展开更多
The women of the 1930s in the Chinese TV serials deduct inspiring stories.They play different roles in the big wealthy families such as mothers-in-law,daughters-in-law,and maidservants.There are unceasing conflicts be...The women of the 1930s in the Chinese TV serials deduct inspiring stories.They play different roles in the big wealthy families such as mothers-in-law,daughters-in-law,and maidservants.There are unceasing conflicts between these women,because of their struggle for men's love,wealth or social position.The theme of their stories is always about fertility,love,kindness and evil,with the ending being either comic or tragic.The stories of various kinds of women of the 1930s in the Chinese TV serials decorate and enrich the lives of many of us latecomers and their names are passed on from generation to generation.展开更多
Due to nutrient stress,which is an important constraint to the development of the global agricultural sector,it is now vital to timely evaluate plant health.Remote sensing technology,especially hyperspectral imaging t...Due to nutrient stress,which is an important constraint to the development of the global agricultural sector,it is now vital to timely evaluate plant health.Remote sensing technology,especially hyperspectral imaging technology,has evolved from spectral response modes to pattern recognition and vegetation monitoring.This study established a hyperspectral library of 14 NPK(nitrogen,phosphorus,potassium)nutrient stress conditions in rice.The terrestrial hyperspectral camera(SPECIM-IQ)collected 420 rice stress images and extracted as well as analyzed representative spectral reflectance curves under 14 stress modes.The canopy spectral profile characteristics,vegetation index,and principal component analysis demonstrated the differences in rice under different nutrient stresses.A transformer-based deep learning network SHCFTT(SuperPCA-HybridSN-CBAM-Feature tokenization transformer)was established for identifying nutrient stress patterns from hyperspectral images while being compared with classic support vector machines,1D-CNN(1D-Convolutional Neural Network),and 3D-CNN.The total accuracy of the SHCFTT model under different modeling strategies and different years ranged from 93.92%to 100%,indicating the positive effect of the proposed method on improving the accuracy of identifying nutrient stress in rice.展开更多
The scientists are dedicated to studying the detection of Alzheimer’s disease onset to find a cure, or at the very least, medication that can slow the progression of the disease. This article explores the effectivene...The scientists are dedicated to studying the detection of Alzheimer’s disease onset to find a cure, or at the very least, medication that can slow the progression of the disease. This article explores the effectiveness of longitudinal data analysis, artificial intelligence, and machine learning approaches based on magnetic resonance imaging and positron emission tomography neuroimaging modalities for progression estimation and the detection of Alzheimer’s disease onset. The significance of feature extraction in highly complex neuroimaging data, identification of vulnerable brain regions, and the determination of the threshold values for plaques, tangles, and neurodegeneration of these regions will extensively be evaluated. Developing automated methods to improve the aforementioned research areas would enable specialists to determine the progression of the disease and find the link between the biomarkers and more accurate detection of Alzheimer’s disease onset.展开更多
All previously reported bacterial species which are capable of lysing harmful algae have been isolated from coastal environments in which harmful algae blooms have occurred. Due to the low concentration of alga-lysing...All previously reported bacterial species which are capable of lysing harmful algae have been isolated from coastal environments in which harmful algae blooms have occurred. Due to the low concentration of alga-lysing bacteria in an algal bloom, it is difficult to isolate the alga-lysing bacteria by existing methods. In this paper, two algae-lysing bacterial strains, P01 and P03, have been isolated from a biosystem immobilized on a sponge that was highly effective in removing algae and microcystins. Their lysing modes and effects on Microcystis aeruginosa have been studied. The results show that the degradation processes of these two strains for M. aeruginosa accorded with a first-order reaction model when the chlorophylla concentration was in the range from 0 to 1000 μgL-1. The degradation rate constants were 0.1067, 0.1274 and 0.2792 for P01 and0.0683, 0.0744 and 0.028 97 for P03, when the bacterial densities were 8.6 × 105, 8.6 × 106 and 8.6 × 107cells mL-1 respectively. Moreover, the two bacterial strains had favourable lytic effects not only on M. aeruginosa , but also on Chlorella and Scene-desmus. Their lytic effect on M. aeruginosa did not require physical cell to cell contact, but proceeded by the production of an extracellular product. The bacterial strains were identified as Bacillus species by PCR amplification of the 16S rRNA gene, BLAST analysis, and comparison with sequences in the GenBank nucleotide database.展开更多
基金supported by science and technology projects of Gansu State Grid Corporation of China(52272220002U).
文摘Optical Character Recognition(OCR)refers to a technology that uses image processing technology and character recognition algorithms to identify characters on an image.This paper is a deep study on the recognition effect of OCR based on Artificial Intelligence(AI)algorithms,in which the different AI algorithms for OCR analysis are classified and reviewed.Firstly,the mechanisms and characteristics of artificial neural network-based OCR are summarized.Secondly,this paper explores machine learning-based OCR,and draws the conclusion that the algorithms available for this form of OCR are still in their infancy,with low generalization and fixed recognition errors,albeit with better recognition effect and higher recognition accuracy.Finally,this paper explores several of the latest algorithms such as deep learning and pattern recognition algorithms.This paper concludes that OCR requires algorithms with higher recognition accuracy.
基金Institutional Fund Projects under Grant No.(IFPIP:638-830-1443).
文摘The utilization of visual attention enhances the performance of image classification tasks.Previous attentionbased models have demonstrated notable performance,but many of these models exhibit reduced accuracy when confronted with inter-class and intra-class similarities and differences.Neural-Controlled Differential Equations(N-CDE’s)and Neural Ordinary Differential Equations(NODE’s)are extensively utilized within this context.NCDE’s possesses the capacity to effectively illustrate both inter-class and intra-class similarities and differences with enhanced clarity.To this end,an attentive neural network has been proposed to generate attention maps,which uses two different types of N-CDE’s,one for adopting hidden layers and the other to generate attention values.Two distinct attention techniques are implemented including time-wise attention,also referred to as bottom N-CDE’s;and element-wise attention,called topN-CDE’s.Additionally,a trainingmethodology is proposed to guarantee that the training problem is sufficiently presented.Two classification tasks including fine-grained visual classification andmulti-label classification,are utilized to evaluate the proposedmodel.The proposedmethodology is employed on five publicly available datasets,including CUB-200-2011,ImageNet-1K,PASCAL VOC 2007,PASCAL VOC 2012,and MS COCO.The obtained visualizations have demonstrated that N-CDE’s are better appropriate for attention-based activities in comparison to conventional NODE’s.
文摘Multi-modal histological image registration tasks pose significant challenges due to tissue staining operations causing partial loss and folding of tissue.Convolutional neural network(CNN)and generative adversarial network(GAN)are pivotal inmedical image registration.However,existing methods often struggle with severe interference and deformation,as seen in histological images of conditions like Cushing’s disease.We argue that the failure of current approaches lies in underutilizing the feature extraction capability of the discriminator inGAN.In this study,we propose a novel multi-modal registration approach GAN-DIRNet based on GAN for deformable histological image registration.To begin with,the discriminators of two GANs are embedded as a new dual parallel feature extraction module into the unsupervised registration networks,characterized by implicitly extracting feature descriptors of specific modalities.Additionally,modal feature description layers and registration layers collaborate in unsupervised optimization,facilitating faster convergence and more precise results.Lastly,experiments and evaluations were conducted on the registration of the Mixed National Institute of Standards and Technology database(MNIST),eight publicly available datasets of histological sections and the Clustering-Registration-Classification-Segmentation(CRCS)dataset on the Cushing’s disease.Experimental results demonstrate that our proposed GAN-DIRNet method surpasses existing approaches like DIRNet in terms of both registration accuracy and time efficiency,while also exhibiting robustness across different image types.
基金Natural Science Foundation of Shandong Province,China(Grant No.ZR202111230202).
文摘Hyperspectral image classification stands as a pivotal task within the field of remote sensing,yet achieving highprecision classification remains a significant challenge.In response to this challenge,a Spectral Convolutional Neural Network model based on Adaptive Fick’s Law Algorithm(AFLA-SCNN)is proposed.The Adaptive Fick’s Law Algorithm(AFLA)constitutes a novel metaheuristic algorithm introduced herein,encompassing three new strategies:Adaptive weight factor,Gaussian mutation,and probability update policy.With adaptive weight factor,the algorithmcan adjust theweights according to the change in the number of iterations to improve the performance of the algorithm.Gaussianmutation helps the algorithm avoid falling into local optimal solutions and improves the searchability of the algorithm.The probability update strategy helps to improve the exploitability and adaptability of the algorithm.Within the AFLA-SCNN model,AFLA is employed to optimize two hyperparameters in the SCNN model,namely,“numEpochs”and“miniBatchSize”,to attain their optimal values.AFLA’s performance is initially validated across 28 functions in 10D,30D,and 50D for CEC2013 and 29 functions in 10D,30D,and 50D for CEC2017.Experimental results indicate AFLA’s marked performance superiority over nine other prominent optimization algorithms.Subsequently,the AFLA-SCNN model was compared with the Spectral Convolutional Neural Network model based on Fick’s Law Algorithm(FLA-SCNN),Spectral Convolutional Neural Network model based on Harris Hawks Optimization(HHO-SCNN),Spectral Convolutional Neural Network model based onDifferential Evolution(DE-SCNN),SpectralConvolutionalNeuralNetwork(SCNN)model,and SupportVector Machines(SVM)model using the Indian Pines dataset and PaviaUniversity dataset.The experimental results show that the AFLA-SCNN model outperforms other models in terms of Accuracy,Precision,Recall,and F1-score on Indian Pines and Pavia University.Among them,the Accuracy of the AFLA-SCNN model on Indian Pines reached 99.875%,and the Accuracy on PaviaUniversity reached 98.022%.In conclusion,our proposed AFLA-SCNN model is deemed to significantly enhance the precision of hyperspectral image classification.
文摘Health care is an important part of human life and is a right for everyone. One of the most basic human rights is to receive health care whenever they need it. However, this is simply not an option for everyone due to the social conditions in which some communities live and not everyone has access to it. This paper aims to serve as a reference point and guide for users who are interested in monitoring their health, particularly their blood analysis to be aware of their health condition in an easy way. This study introduces an algorithmic approach for extracting and analyzing Complete Blood Count (CBC) parameters from scanned images. The algorithm employs Optical Character Recognition (OCR) technology to process images containing tabular data, specifically targeting CBC parameter tables. Upon image processing, the algorithm extracts data and identifies CBC parameters and their corresponding values. It evaluates the status (High, Low, or Normal) of each parameter and subsequently presents evaluations, and any potential diagnoses. The primary objective is to automate the extraction and evaluation of CBC parameters, aiding healthcare professionals in swiftly assessing blood analysis results. The algorithmic framework aims to streamline the interpretation of CBC tests, potentially improving efficiency and accuracy in clinical diagnostics.
基金Project supported by the National Basic Research Program (973) of China (No. 2002-CB-312101) and the National Natural Science Foundation of China (No. 60773037)
文摘In this paper, a novel approach is proposed for denoising of Chinese calligraphy tablet documents. The method includes two phases: First, a partial differential equations (PDE) based the total variation model and Otsu thresholding method are used to preprocess the calligraphy document image. Second, a new method based on run-length statistics and structure charac- teristics of Chinese characters is proposed to remove some random and ant-like noises. This includes the optimal threshold se- lection from histogram of run-length probability density, and improved Hough transform algorithm for line shape noise detection and removal. Examples are given in the paper to demonstrate the proposed method.
基金supported by the National Natural Science Foundation of China(61073106)the Aerospace Science and Technology Innovation Fund(CASC201105)
文摘An image segmentation algorithm of the restrained fuzzy Kohonen clustering network （RFKCN） based on high- dimension fuzzy character is proposed. The algorithm includes two steps. The first step is the fuzzification of pixels in which two redundant images are built by fuzzy mean value and fuzzy median value. The second step is to construct a three-dimensional （3-D） feature vector of redundant images and their original images and cluster the feature vector through RFKCN, to realize image seg- mentation. The proposed algorithm fully takes into account not only gray distribution information of pixels, but also relevant information and fuzzy information among neighboring pixels in constructing 3- D character space. Based on the combination of competitiveness, redundancy and complementary of the information, the proposed algorithm improves the accuracy of clustering. Theoretical anal- yses and experimental results demonstrate that the proposed algorithm has a good segmentation performance.
文摘As the typical representative of love and marriage drama in Yuan variety play,Qiuhu philander his wife plays a relatively important role in it.This paper carries on the analysis in a few typical character image,which are Luo Meiying who has the courage to fight,the hypocritical and insidious Qiu Hu,the ugly and vicious Li Dahu,the greedy and hard-hearted Luo Dahu,the kind and helpless mother-in-law Mei Ying,these five different images apparently jumping on the paper.
文摘Image is a term that mainly embodies in the composition of classical Chinese poetry(CCP). Effective translation of images is crucial to the grasp of original meanings in a poem. As aesthetic beauty is the primary concern in poetry,the conveyance of beauty in image has a direct impact in translation. To analyze translation strategies of imagery beauty,the theory of"translation levels"by Xu Jun is adopted as a criterion in comparing variant English versions of CCP in the aesthetic level. Images are selected from Seven-character quatrains typified for abundant sources of images,and features of images are put forward at the aesthetic level. Through the analysis,images are rendered by recreation of the sensuous and emotional beauty.
基金supported by the Research Project of the Shanghai Health Commission,No.2020YJZX0111(to CZ)the National Natural Science Foundation of China,Nos.82021002(to CZ),82272039(to CZ),82171252(to FL)+1 种基金a grant from the National Health Commission of People’s Republic of China(PRC),No.Pro20211231084249000238(to JW)Medical Innovation Research Project of Shanghai Science and Technology Commission,No.21Y11903300(to JG).
文摘Nowadays,presynaptic dopaminergic positron emission tomography,which assesses deficiencies in dopamine synthesis,storage,and transport,is widely utilized for early diagnosis and differential diagnosis of parkinsonism.This review provides a comprehensive summary of the latest developments in the application of presynaptic dopaminergic positron emission tomography imaging in disorders that manifest parkinsonism.We conducted a thorough literature search using reputable databases such as PubMed and Web of Science.Selection criteria involved identifying peer-reviewed articles published within the last 5 years,with emphasis on their relevance to clinical applications.The findings from these studies highlight that presynaptic dopaminergic positron emission tomography has demonstrated potential not only in diagnosing and differentiating various Parkinsonian conditions but also in assessing disease severity and predicting prognosis.Moreover,when employed in conjunction with other imaging modalities and advanced analytical methods,presynaptic dopaminergic positron emission tomography has been validated as a reliable in vivo biomarker.This validation extends to screening and exploring potential neuropathological mechanisms associated with dopaminergic depletion.In summary,the insights gained from interpreting these studies are crucial for enhancing the effectiveness of preclinical investigations and clinical trials,ultimately advancing toward the goals of neuroregeneration in parkinsonian disorders.
文摘Titled as the name of the main characters,the seven parts in The Thorn Birds together tell the story of the three generations of the Cleary family from 1915 to 1969.Fiona and Paddy are the first generation,Meggie and Ralph are the second generation,and Justine and Dane are the third generation.Although they are both thorny birds,they have different personal characteristics and life pursuits.Fiona,Meggie,and Justine,as women,are more and more rebellious from generation to generation.They are more and more daring to fight against the Almighty God and their cruel fates.But at the same time,in the process of pursuing self-happiness,there are also dislocations of ethical identity of these women who inevitably make wrong ethical choices.The author of this thesis tries to analyze the ethical identity of the three generations of women in The Thorn Birds from a relatively comprehensive perspective based on literary ethics,and then analyzes the round ethical image of these female characters.
文摘BACKGROUND： Diffusion tensor imaging （DTI） is one of the noninvasive methods to study the morphological structure of brain white matter fibrous bands in vivo, and it has been applied primarily in clinic. DTI is acknowledged as the more effective imaging method to diagnose ultra-acute and/or acute cerebral infarction.OB_3ECTIVE： To observe the anisotropic characters of cerebral white matter fibrous bands in patients with ischemic stroke by using DTI, and investigate the correlation between the damage of corticospinal tract and muscle strength in patients with ischemic stroke at acute period.DESIGN： A case-control observationSEFIING： Department of Medical Imaging, Fuzhou General Hospital of Nanjing Military Area Command of Chinese PLA.PARTICIPANTS： Nine inpatients with injury of motor function induced by acute ischemic stroke （patient group） at 6 hours to 2 weeks after the attack were selected from the Department of Neurology, Fuzhou General Hospital of Nanjing Military Area Command of Chinese PLA from September 2005 to March 2006, and they all accorded with the present diagnostic standard for cerebrovascular disease in China. There were 5 males and 4 females, aged 16-87 years. At the same time, nine healthy right-handed physical examinees matched by age and sex with the patients were taken as the control group, and they all had no nervous disease, mental diseases, cerebrovascular abnormalities and injury history, etc. All the subjects were informed with the detected items and agreed to participate in the study.METHODS： All the 9 patients with ischemic stroke at acute period and 9 healthy subjects were examined with MRI, T1 weighted imaging, T2 weighted imaging and DTI. And the data were processed offline with dTV.II software, the images of fractional anisotropy and directional encoded color （DEC） were obtained, and the three-dimensional fibrous band images of bilateral corticospinal tracts were reconstructed. In the control group, the values of fractional anisotropy of main white matter fibrous bands were measured in the region of interest （ROI） of the anterior limb, knee and posterior limb of internal capsule. In the patient group, the values of fractional anisotropy of white matter were measured in the infarcted sites and corresponding contralateral sites of the patients. The ROI was set in bilateral cerebral peduncles to reconstruct three-dimensionally the bilateral corticospinal tracts. The muscle strength of the affected hand was assessed with Brunnstorm standard in the stroke patients.MAIN OUTCOME MEASURES ： The characters of DTI and images of the value of fractional anisotropy, and the manifestations of three-dimensional corticospinal tracts were observed in the two groups.RESULTS： All the data from the 9 patients and 9 healthy volunteers were involved in the analysis of results. In the control group, the white matter and gray matter could be distinguished clearly in the image of fractional anisotropic values, the fibers of different directions were shown by different colors in DEC picture, which clearly demonstrated the normal anatomic structure and direction of white matter fibers. In the patient group, the infarctions occurred in the gray matter or white matter could be distinguished in the images of fractional anisotropic values, DEC picture could clearly show the direct influence of the infarcted site on the white matter fibers. The fractional anisotropic values in different white matter structure of the same side were significantly different in the control group （t=-3.12, P 〈 0.05）, and the reconstructed images fractional anisotropic values and DEC picture could show most of the main white matter fibrous bands. The fractional anisotropic values of the infarcted sites were significantly lower than the contralateral ones in the patient group （t=-5.570, P 〈 0.01）. ② The reconstructed bilateral corticospinal tracts showed that the anatomic forms of the contralateral corticospinal tract of the patients were almost identical to those of normal people, it started from precentral gyrus, downward to the nternal capsule, and extended to pontine and medulla oblongata, each fibrous band was continuous, and the form had good consistency. Because of the involvement of infarction of different severity, the ipsilateral corticospinal tract manifested as continuous interruption and the loss of consistent anatomic structural form. The involved severity of corticospinal tract had significant correlation with that of muscle strength of the ipsilateral hand （r=-1.30, P 〈 0.01）.CONCLUSION： ① DTI can display the direction and distribution of cerebral white matter fibrous bands.② DTI images of fractional anisotropic values and DEC can show the directions and anisotropic degree of white matter fibers in the infarcted sites of stroke patients. ③ The three-dimensional images of fibrous bands can show the conditions of pyramidal tracts more directly. ④ The damaged severity of corticospinal tracts is correlated with that of muscle strength.
文摘Ruth and Mary are two heroines in Eugene O'Neill's plays Beyond the Horizon, and Long Day's Journey into Night. They have some similarities: when they are young, they are beautiful, native and full of hope towards the future life, but both make wrong choices; in the following years, both suffer a lot from these wrong choices, and feel regretful. This paper tries to explore these two tragic female images.
文摘After the introduction of tourist resources in Wunvfeng National Forest Park, the paper had planed its overall image from the perspectives of concept design, visual identity, behavioral norms and audio identity. The slogan of Wunvfeng National Forest Park had been identified as "tour of nature and mythology-Wunvfeng", and the park's emblem, symbolic mascots, spokesman of tourism image and tourist souvenirs had been set, so as to better display tourist advantages of Wunvfeng National Forest Park and create more economic and social benefits.
文摘The women of the 1930s in the Chinese TV serials deduct inspiring stories.They play different roles in the big wealthy families such as mothers-in-law,daughters-in-law,and maidservants.There are unceasing conflicts between these women,because of their struggle for men's love,wealth or social position.The theme of their stories is always about fertility,love,kindness and evil,with the ending being either comic or tragic.The stories of various kinds of women of the 1930s in the Chinese TV serials decorate and enrich the lives of many of us latecomers and their names are passed on from generation to generation.
基金supported by China's National Key R&D Plan(2021YFD200060502)China's National Key R&D Plan(2018YFD0300105)China's National Key R&D Plan(2016YFD0300909).
文摘Due to nutrient stress,which is an important constraint to the development of the global agricultural sector,it is now vital to timely evaluate plant health.Remote sensing technology,especially hyperspectral imaging technology,has evolved from spectral response modes to pattern recognition and vegetation monitoring.This study established a hyperspectral library of 14 NPK(nitrogen,phosphorus,potassium)nutrient stress conditions in rice.The terrestrial hyperspectral camera(SPECIM-IQ)collected 420 rice stress images and extracted as well as analyzed representative spectral reflectance curves under 14 stress modes.The canopy spectral profile characteristics,vegetation index,and principal component analysis demonstrated the differences in rice under different nutrient stresses.A transformer-based deep learning network SHCFTT(SuperPCA-HybridSN-CBAM-Feature tokenization transformer)was established for identifying nutrient stress patterns from hyperspectral images while being compared with classic support vector machines,1D-CNN(1D-Convolutional Neural Network),and 3D-CNN.The total accuracy of the SHCFTT model under different modeling strategies and different years ranged from 93.92%to 100%,indicating the positive effect of the proposed method on improving the accuracy of identifying nutrient stress in rice.
文摘The scientists are dedicated to studying the detection of Alzheimer’s disease onset to find a cure, or at the very least, medication that can slow the progression of the disease. This article explores the effectiveness of longitudinal data analysis, artificial intelligence, and machine learning approaches based on magnetic resonance imaging and positron emission tomography neuroimaging modalities for progression estimation and the detection of Alzheimer’s disease onset. The significance of feature extraction in highly complex neuroimaging data, identification of vulnerable brain regions, and the determination of the threshold values for plaques, tangles, and neurodegeneration of these regions will extensively be evaluated. Developing automated methods to improve the aforementioned research areas would enable specialists to determine the progression of the disease and find the link between the biomarkers and more accurate detection of Alzheimer’s disease onset.
基金This study was supported by the Sino Japan Science Cooperative Program （Grant No.003250103） Special Funds for PhD Research Station of University （Grant No. 20020422045）Science Foundation of Shandong Province （Grant No. Z2003B01 ）.
文摘All previously reported bacterial species which are capable of lysing harmful algae have been isolated from coastal environments in which harmful algae blooms have occurred. Due to the low concentration of alga-lysing bacteria in an algal bloom, it is difficult to isolate the alga-lysing bacteria by existing methods. In this paper, two algae-lysing bacterial strains, P01 and P03, have been isolated from a biosystem immobilized on a sponge that was highly effective in removing algae and microcystins. Their lysing modes and effects on Microcystis aeruginosa have been studied. The results show that the degradation processes of these two strains for M. aeruginosa accorded with a first-order reaction model when the chlorophylla concentration was in the range from 0 to 1000 μgL-1. The degradation rate constants were 0.1067, 0.1274 and 0.2792 for P01 and0.0683, 0.0744 and 0.028 97 for P03, when the bacterial densities were 8.6 × 105, 8.6 × 106 and 8.6 × 107cells mL-1 respectively. Moreover, the two bacterial strains had favourable lytic effects not only on M. aeruginosa , but also on Chlorella and Scene-desmus. Their lytic effect on M. aeruginosa did not require physical cell to cell contact, but proceeded by the production of an extracellular product. The bacterial strains were identified as Bacillus species by PCR amplification of the 16S rRNA gene, BLAST analysis, and comparison with sequences in the GenBank nucleotide database.
