With the rapid development of digital culture,a large number of cultural texts are presented in the form of digital and network.These texts have significant characteristics such as sparsity,real-time and non-standard ...With the rapid development of digital culture,a large number of cultural texts are presented in the form of digital and network.These texts have significant characteristics such as sparsity,real-time and non-standard expression,which bring serious challenges to traditional classification methods.In order to cope with the above problems,this paper proposes a new ASSC(ALBERT,SVD,Self-Attention and Cross-Entropy)-TextRCNN digital cultural text classification model.Based on the framework of TextRCNN,the Albert pre-training language model is introduced to improve the depth and accuracy of semantic embedding.Combined with the dual attention mechanism,the model’s ability to capture and model potential key information in short texts is strengthened.The Singular Value Decomposition(SVD)was used to replace the traditional Max pooling operation,which effectively reduced the feature loss rate and retained more key semantic information.The cross-entropy loss function was used to optimize the prediction results,making the model more robust in class distribution learning.The experimental results indicate that,in the digital cultural text classification task,as compared to the baseline model,the proposed ASSC-TextRCNN method achieves an 11.85%relative improvement in accuracy and an 11.97%relative increase in the F1 score.Meanwhile,the relative error rate decreases by 53.18%.This achievement not only validates the effectiveness and advanced nature of the proposed approach but also offers a novel technical route and methodological underpinnings for the intelligent analysis and dissemination of digital cultural texts.It holds great significance for promoting the in-depth exploration and value realization of digital culture.展开更多
An online algorithm for training LS-SVM (Least Square Support VectorMachines) was proposed for the application of function estimation and classification. Online LS-SVMmeans that LS-SVM can be trained in an incremental...An online algorithm for training LS-SVM (Least Square Support VectorMachines) was proposed for the application of function estimation and classification. Online LS-SVMmeans that LS-SVM can be trained in an incremental way, and can be pruned to get sparseapproximation in a decremental way. When a SV (Support Vector) is added or removed, the onlinealgorithm avoids computing large-scale matrix inverse. Thus the computation cost is reduced. Onlinealgorithm is especially useful to realistic function estimation problem such as systemidentification. The experiments with benchmark function estimation problem and classificationproblem show the validity of this online algorithm.展开更多
A method for data classification will influence the efficiency of classification. Attributes reduction based on discernibility matrix and discernibility function in rough sets can use in data classification, so we put...A method for data classification will influence the efficiency of classification. Attributes reduction based on discernibility matrix and discernibility function in rough sets can use in data classification, so we put forward a method for data classification. Namely, firstly, we use discernibility matrix and discernibility function to delete superfluous attributes in formation system and get a necessary attribute set. Secondly, we delete superfluous attribute values and get decision rules. Finally, we classify data by means of decision rules. The experiments show that data classification using this method is simpler in the structure, and can improve the efficiency of classification.展开更多
The relationship between the importance of criterion and the criterion aggregation function is discussed, criterion＇s weight and combinational weights between some criteria are defined, and a multi-criteria classific...The relationship between the importance of criterion and the criterion aggregation function is discussed, criterion＇s weight and combinational weights between some criteria are defined, and a multi-criteria classification method with incomplete certain information and polynomial aggregation function is proposed. First, linear programming is constructed by classification to reference alternative set （assignment examples） and incomplete certain information on criterion＇s weights. Then the coefficient of the polynomial aggregation function and thresholds of categories are gained by solving the linear programming. And the consistency index of alternatives is obtained, the classification of the alternatives is achieved. The certain criteria＇s values of categories and uncertain criteria＇s values of categories are discussed in the method. Finally, an example shows the feasibility and availability of this method.展开更多
Multi-Valued Neuron (MVN) was proposed for pattern classification. It operates with complex-valued inputs, outputs, and weights, and its learning algorithm is based on error-correcting rule. The activation function of...Multi-Valued Neuron (MVN) was proposed for pattern classification. It operates with complex-valued inputs, outputs, and weights, and its learning algorithm is based on error-correcting rule. The activation function of MVN is not differentiable. Therefore, we can not apply backpropagation when constructing multilayer structures. In this paper, we propose a new neuron model, MVN-sig, to simulate the mechanism of MVN with differentiable activation function. We expect MVN-sig to achieve higher performance than MVN. We run several classification benchmark datasets to compare the performance of MVN-sig with that of MVN. The experimental results show a good potential to develop a multilayer networks based on MVN-sig.展开更多
We describe the case of a 73-year-old man with left shoulder paresis caused by a herpes zoster infection of the left C5 dermatomes. The patient had been affected by pain for 10 days, a skin rash on his left shoulder a...We describe the case of a 73-year-old man with left shoulder paresis caused by a herpes zoster infection of the left C5 dermatomes. The patient had been affected by pain for 10 days, a skin rash on his left shoulder and back for 5 days, and weakness of his left shoulder for 2 days before admission. Eiectromyography revealed denervation discharges from the left supraspinatus, infraspinatus and deltoid muscles, which was compatible with radiculopathy showing after zoster infection. The patient was examined in accordance with the International Classification of Functioning, Disability and Health, and treated with range-of-movement and strengthening exercises as well as activities of daily living and social participation. At 14 months after the onset of the condition, muscle strength had returned to normal. Electromyography revealed that motor unit action potentials were largely normal. These results indicate that the rehabilitation of paresis caused by herpes zoster can obtain positive results with suitable movement training.展开更多
The functional differentiations of stomach cancer specimens from 121 patients were investigated by enzyme-,mucin-,affinity-and immunohistochemical methods, and the stomach cancers were divided into five functionally d...The functional differentiations of stomach cancer specimens from 121 patients were investigated by enzyme-,mucin-,affinity-and immunohistochemical methods, and the stomach cancers were divided into five functionally differentiated types : 1 ) Absorptive Function Differentiation Type (AFDT), 19. 8% ; 2) Mucin Secreting Function Differentiation Type(MSFDT) , 24. 0% ; 3) Absorptive and Mucin-Producing Function Differentiation Type(AMPFDT) , 47. 1%; 4 ) Special Function Differentiation Type(SFDT) , 0. 8 %; and 5) Non-Function Differentiation Type(NFDT) , 8. 3%. The results indicate that stomach cancer tissues of the same histological type often display differing functional differentiation, and these functionally differentiated types have different invasive and metastatic characteristics. In addition, the functionally differentiated types have particular organic affinities of metastasis and different clinical prognoses. This study suggests that this new functional classification may supplement histological classification. The mechanisms of liver and ovary metastases of stomach cancer are also dis-cussed.展开更多
In this paper, a new hybrid model of amino acid substitution is developed and compared with the others in previous works. The results show that the new hybrid model can characterize the protein sequences very well by ...In this paper, a new hybrid model of amino acid substitution is developed and compared with the others in previous works. The results show that the new hybrid model can characterize the protein sequences very well by calculating Fisher weights, which can denote how much the variants contribute to the classification.展开更多
The classification of urban functional areas plays an important role in urban planning and resource management.Although previous studies have confirmed that different urban func-tional areas have different morphologic...The classification of urban functional areas plays an important role in urban planning and resource management.Although previous studies have confirmed that different urban func-tional areas have different morphological structures and Land Surface Temperature(LST)characteristics,these two types of characteristics have rarely been fully integrated and used for functional area classification.In this paper,a new framework for classifying urban functional areas is proposed by combining urban morphological features and LST features.First,metrics are constructed from three levels,namely,building,road and region,which are used to portray urban morphology;LST is retrieved using thermal infrared remote sensing to reflect LST features with four metrics:the average temperature,maximum temperature,temperature difference and standard deviation of temperature.Then,the functional areas are classified into four categories:service/public land,commercial land,residential land and industrial land.A random forest algorithm is used to effectively fuse the features of these two categories and classify the functional areas.The effectiveness of the proposed framework is tested in the study area of Shenzhen City,Guangdong Province.The results show that the combined classification accuracy of the proposed classification method is 0.85,which is 0.26 higher than that of the classification model based on urban morphology and 0.1 higher than that of the classification model based on LST features.The proposed framework verifies that the integration of LST features into urban functional area classification is reliable and effectively combines urban morphology and LST features for functional area classification.展开更多
The maximum of k numerical functions defined on , , by , ??is used here in Statistical classification. Previously, it has been used in Statistical Discrimination [1] and in Clustering [2]. We present first some theore...The maximum of k numerical functions defined on , , by , ??is used here in Statistical classification. Previously, it has been used in Statistical Discrimination [1] and in Clustering [2]. We present first some theoretical results on this function, and then its application in classification using a computer program we have developed. This approach leads to clear decisions, even in cases where the extension to several classes of Fisher’s linear discriminant function fails to be effective.展开更多
Represents the first attempt to classify all of China’s295 cities in terms of industrial functions,using 1984 data.Within the framework of economic base theory of urban development,three elements are defined as speci...Represents the first attempt to classify all of China’s295 cities in terms of industrial functions,using 1984 data.Within the framework of economic base theory of urban development,three elements are defined as specialized branch,functional intensity and functional scale.The method used here is based on a combination of the three elements.A number of techniques tried made it possible to base the classification on a composite measure,consisting of the Ward’s Error Method of hierarchical cluster analysis and a supplementary application of Nelson measure.The 295 cities have been grouped into three categories with 19 subcategories and 54 functional groups.The distribution of cities in most of the subcategories are displayed on 8 maps.展开更多
The radial basis function networks were applied to bacterial classification based on the matrix-assisted laser desorption/ionization time-of-flight mass spectrometric (MALDI-TOF-MS) data. The classification of bacteri...The radial basis function networks were applied to bacterial classification based on the matrix-assisted laser desorption/ionization time-of-flight mass spectrometric (MALDI-TOF-MS) data. The classification of bacteria cultured at different time was discussed and the effect of the network parameters on the classification was investigated. The cross-validation method was used to test the trained networks. The correctness of the classification of different bacteria investigated changes in a wide range from 61.5% to 92.8%. Owing to the complexity of biological effects in bacterial growth, the more rigid control of bacterial culture conditions seems to be a critical factor for improving the rate of correctness for bacterial classification.展开更多
Pituitary adenoma may be calssifded in light of the hormones produced. 225 surgical specimens were labeled with anti-sear of GH, PRL. ACTH, TSH, FSH and LH by immunohistochemical technique (ABC method). Data indicated...Pituitary adenoma may be calssifded in light of the hormones produced. 225 surgical specimens were labeled with anti-sear of GH, PRL. ACTH, TSH, FSH and LH by immunohistochemical technique (ABC method). Data indicated that 100 out of 225 cases (44.5%) were monohormonal adenomas, including 24 GH, 39 PRL, 1 FSH and 9 LH, 77 (34.2%) were multi-hormonal adenomas, including 28 positive for 2 hormones, 30 positive for 3 hormones, 19 positive for 4 or more different hormones, and the remaining 48 (21.3%) were nonfunctional adenomas. In comparison with Kovacs series, factors which might participate in the mechanism of developing monohormonal or multi-hormonal adenomas are discussed.展开更多
The increase in chronic diseases in childhood highlights the need for a biopsychosocial approach to deal with the complexity of these health conditions. The International Classification of Functioning, Disability, and...The increase in chronic diseases in childhood highlights the need for a biopsychosocial approach to deal with the complexity of these health conditions. The International Classification of Functioning, Disability, and Health (ICF) results from the need to implement new explanatory evaluative and therapeutic models. Thus, the present systematic review aims to identify published studies on the use of the ICF in chronic childhood diseases. As a secondary objective, to map the themes that have already been studied in the area to support the discussion on the expansion of the use of this classification in health services. The systematic review followed the PRISMA protocol, and the model was the PICO acronym, where Population was children and adolescents with chronic diseases, Intervention/Exposure was evaluation based on ICF concepts, Comparator was any tool, instrument, or intervention, and outcome was direct or indirect use of the ICF. We selected eight articles, five of which used the ICF as a conceptual tool and three as a classification system, divided into the following themes: quality of life, evaluation of patients (without using coding) and mapping the inclusion of the activity’s results and participation in clinical trials. Thus, use of the ICF in clinical practice is still incipient, although it has been recommended in guidelines. Further studies are necessary to expand the number of contributions by the ICF and to develop the necessary approaches for understanding the classification’s use.展开更多
The ocean plays an important role in maintaining the equilibrium of Earth’s ecology and providing humans access to a wealth of resources.To obtain a high-precision underwater image classification model,we propose a c...The ocean plays an important role in maintaining the equilibrium of Earth’s ecology and providing humans access to a wealth of resources.To obtain a high-precision underwater image classification model,we propose a classification model that combines an EfficientnetB0 neural network and a two-hidden-layer random vector functional link network(EfficientnetB0-TRVFL).The features of underwater images were extracted using the EfficientnetB0 neural network pretrained via ImageNet,and a new fully connected layer was trained on the underwater image dataset using the transfer learning method.Transfer learning ensures the initial performance of the network and helps in the development of a high-precision classification model.Subsequently,a TRVFL was proposed to improve the classification property of the model.Net construction of the two hidden layers exhibited a high accuracy when the same hidden layer nodes were used.The parameters of the second hidden layer were obtained using a novel calculation method,which reduced the outcome error to improve the performance instability caused by the random generation of parameters of RVFL.Finally,the TRVFL classifier was used to classify features and obtain classification results.The proposed EfficientnetB0-TRVFL classification model achieved 87.28%,74.06%,and 99.59%accuracy on the MLC2008,MLC2009,and Fish-gres datasets,respectively.The best convolutional neural networks and existing methods were stacked up through box plots and Kolmogorov-Smirnov tests,respectively.The increases imply improved systematization properties in underwater image classification tasks.The image classification model offers important performance advantages and better stability compared with existing methods.展开更多
The structure and function of brain networks have been altered in patients with end-stage renal disease(ESRD).Manifold regularization(MR)only considers the pairing relationship between two brain regions and cannot rep...The structure and function of brain networks have been altered in patients with end-stage renal disease(ESRD).Manifold regularization(MR)only considers the pairing relationship between two brain regions and cannot represent functional interactions or higher-order relationships between multiple brain regions.To solve this issue,we developed a method to construct a dynamic brain functional network(DBFN)based on dynamic hypergraph MR(DHMR)and applied it to the classification of ESRD associated with mild cognitive impairment(ESRDaMCI).The construction of DBFN with Pearson’s correlation(PC)was transformed into an optimization model.Node convolution and hyperedge convolution superposition were adopted to dynamically modify the hypergraph structure,and then got the dynamic hypergraph to form the manifold regular terms of the dynamic hypergraph.The DHMR and L_(1) norm regularization were introduced into the PC-based optimization model to obtain the final DHMR-based DBFN(DDBFN).Experiment results demonstrated the validity of the DDBFN method by comparing the classification results with several related brain functional network construction methods.Our work not only improves better classification performance but also reveals the discriminative regions of ESRDaMCI,providing a reference for clinical research and auxiliary diagnosis of concomitant cognitive impairments.展开更多
Purpose: Brain functional networks (BFNs) has become important approach for diagnosis of some neurological or psychological disorders. Before estimating BFN, obtaining blood oxygen level dependent (BOLD) representativ...Purpose: Brain functional networks (BFNs) has become important approach for diagnosis of some neurological or psychological disorders. Before estimating BFN, obtaining blood oxygen level dependent (BOLD) representative signals from brain regions of interest (ROIs) is important. In the past decades, the common method is generally to take a ROI as a node, averaging all the voxel time series inside it to extract a representative signal. However, one node does not represent the entire information of this ROI, and averaging method often leads to signal cancellation and information loss. Inspired by this, we propose a novel model extraction method based on an assumption that a ROI can be represented by multiple nodes. Methods: In this paper, we first extract multiple nodes (the number is user-defined) from the ROI based on two traditional methods, including principal component analysis (PCA), and K-means (Clustering according to the spatial position of voxels). Then, canonical correlation analysis (CCA) was issued to construct BFNs by maximizing the correlation between the representative signals corresponding to the nodes in any two ROIs. Finally, to further verify the effectiveness of the proposed method, the estimated BFNs are applied to identify subjects with autism spectrum disorder (ASD) and mild cognitive impairment (MCI) from health controls (HCs). Results: Experimental results on two benchmark databases demonstrate that the proposed method outperforms the baseline method in the sense of classification performance. Conclusions: We propose a novel method for obtaining nodes of ROId based on the hypothesis that a ROI can be represented by multiple nodes, that is, to extract the node signals of ROIs with K-means or PCA. Then, CCA is used to construct BFNs.展开更多
Designing appropriate loss functions is critical to the success of supervised learning models.However,most conventional losses are fixed and manually designed,making them suboptimal for diverse and dynamic learning sc...Designing appropriate loss functions is critical to the success of supervised learning models.However,most conventional losses are fixed and manually designed,making them suboptimal for diverse and dynamic learning scenarios.In this work,we propose an Adaptive Meta-Loss Network(Adaptive-MLN)that learns to generate taskagnostic loss functions tailored to evolving classification problems.Unlike traditional methods that rely on static objectives,Adaptive-MLN treats the loss function itself as a trainable component,parameterized by a shallow neural network.To enable flexible,gradient-free optimization,we introduce a hybrid evolutionary approach that combines GeneticAlgorithms(GA)for global exploration and Evolution Strategies(ES)for local refinement.This co-evolutionary process dynamically adjusts the loss landscape,improvingmodel generalization without relying on analytic gradients or handcrafted heuristics.Experimental evaluations on synthetic tasks and the CIFAR-10 andMNIST datasets demonstrate that our approach consistently outperforms standard losses such as Cross-Entropy and Mean Squared Error in terms of accuracy,convergence,and adaptability.展开更多
This paper attempts to provide a brief but systematic survey of nonverbal communication in terms of its characteristics, functions, and classification. Nonverbal communication involves all those nonverbal stimuli in a...This paper attempts to provide a brief but systematic survey of nonverbal communication in terms of its characteristics, functions, and classification. Nonverbal communication involves all those nonverbal stimuli in a communication setting that are generated by both the source and the receiver. First, unlike verbal communication, it does not have a fixed set of signs, and formal rules and structures; it is innate and continuous. Second, it performs such functions as repeating, complementing, substituting, regulating, and contradicting. Finally, nonverbal communication may be classified into two major types: those produced by the body (including physical appearance, body movements, physical contact, facial expressions, eye contact, and paralanguage); and those associated with the setting (including space, time, and silence).展开更多
The different land use surrounding parking facility has significant impact on parking behavior. This paper studies the functional classification of land use surrounding parking facility, which is fundamentally importa...The different land use surrounding parking facility has significant impact on parking behavior. This paper studies the functional classification of land use surrounding parking facility, which is fundamentally important for indepth research on parking behavior. 37 parking facilities located between the second and sixth ring roadway in Beijing were selected for this study. Based on the surveys conducted at these parking facilities, various parking behavior were analyzed, based on which the scope of the different parking was determined. The information on location, land use characteristics, public transport, the surrounding parking situations are collected for each investigated parking facility. Applying the SPSS clustering method, the threshold was developed for the classification. Totally, five categories are proposed for the land use functionality surrounding parking facility as the results of this study.展开更多
基金funded by China National Innovation and Entrepreneurship Project Fund Innovation Training Program(202410451009).
文摘With the rapid development of digital culture,a large number of cultural texts are presented in the form of digital and network.These texts have significant characteristics such as sparsity,real-time and non-standard expression,which bring serious challenges to traditional classification methods.In order to cope with the above problems,this paper proposes a new ASSC(ALBERT,SVD,Self-Attention and Cross-Entropy)-TextRCNN digital cultural text classification model.Based on the framework of TextRCNN,the Albert pre-training language model is introduced to improve the depth and accuracy of semantic embedding.Combined with the dual attention mechanism,the model’s ability to capture and model potential key information in short texts is strengthened.The Singular Value Decomposition(SVD)was used to replace the traditional Max pooling operation,which effectively reduced the feature loss rate and retained more key semantic information.The cross-entropy loss function was used to optimize the prediction results,making the model more robust in class distribution learning.The experimental results indicate that,in the digital cultural text classification task,as compared to the baseline model,the proposed ASSC-TextRCNN method achieves an 11.85%relative improvement in accuracy and an 11.97%relative increase in the F1 score.Meanwhile,the relative error rate decreases by 53.18%.This achievement not only validates the effectiveness and advanced nature of the proposed approach but also offers a novel technical route and methodological underpinnings for the intelligent analysis and dissemination of digital cultural texts.It holds great significance for promoting the in-depth exploration and value realization of digital culture.
基金This project was financially supported by the National Natural Science Foundation of China (No. 69889050)
文摘An online algorithm for training LS-SVM (Least Square Support VectorMachines) was proposed for the application of function estimation and classification. Online LS-SVMmeans that LS-SVM can be trained in an incremental way, and can be pruned to get sparseapproximation in a decremental way. When a SV (Support Vector) is added or removed, the onlinealgorithm avoids computing large-scale matrix inverse. Thus the computation cost is reduced. Onlinealgorithm is especially useful to realistic function estimation problem such as systemidentification. The experiments with benchmark function estimation problem and classificationproblem show the validity of this online algorithm.
基金Supported by the National Natural Science Foun-dation of China(60474022)
文摘A method for data classification will influence the efficiency of classification. Attributes reduction based on discernibility matrix and discernibility function in rough sets can use in data classification, so we put forward a method for data classification. Namely, firstly, we use discernibility matrix and discernibility function to delete superfluous attributes in formation system and get a necessary attribute set. Secondly, we delete superfluous attribute values and get decision rules. Finally, we classify data by means of decision rules. The experiments show that data classification using this method is simpler in the structure, and can improve the efficiency of classification.
基金This project was supported by the Social Science Foundation of Hunan(05YB74)
文摘The relationship between the importance of criterion and the criterion aggregation function is discussed, criterion＇s weight and combinational weights between some criteria are defined, and a multi-criteria classification method with incomplete certain information and polynomial aggregation function is proposed. First, linear programming is constructed by classification to reference alternative set （assignment examples） and incomplete certain information on criterion＇s weights. Then the coefficient of the polynomial aggregation function and thresholds of categories are gained by solving the linear programming. And the consistency index of alternatives is obtained, the classification of the alternatives is achieved. The certain criteria＇s values of categories and uncertain criteria＇s values of categories are discussed in the method. Finally, an example shows the feasibility and availability of this method.
文摘Multi-Valued Neuron (MVN) was proposed for pattern classification. It operates with complex-valued inputs, outputs, and weights, and its learning algorithm is based on error-correcting rule. The activation function of MVN is not differentiable. Therefore, we can not apply backpropagation when constructing multilayer structures. In this paper, we propose a new neuron model, MVN-sig, to simulate the mechanism of MVN with differentiable activation function. We expect MVN-sig to achieve higher performance than MVN. We run several classification benchmark datasets to compare the performance of MVN-sig with that of MVN. The experimental results show a good potential to develop a multilayer networks based on MVN-sig.
文摘We describe the case of a 73-year-old man with left shoulder paresis caused by a herpes zoster infection of the left C5 dermatomes. The patient had been affected by pain for 10 days, a skin rash on his left shoulder and back for 5 days, and weakness of his left shoulder for 2 days before admission. Eiectromyography revealed denervation discharges from the left supraspinatus, infraspinatus and deltoid muscles, which was compatible with radiculopathy showing after zoster infection. The patient was examined in accordance with the International Classification of Functioning, Disability and Health, and treated with range-of-movement and strengthening exercises as well as activities of daily living and social participation. At 14 months after the onset of the condition, muscle strength had returned to normal. Electromyography revealed that motor unit action potentials were largely normal. These results indicate that the rehabilitation of paresis caused by herpes zoster can obtain positive results with suitable movement training.
文摘The functional differentiations of stomach cancer specimens from 121 patients were investigated by enzyme-,mucin-,affinity-and immunohistochemical methods, and the stomach cancers were divided into five functionally differentiated types : 1 ) Absorptive Function Differentiation Type (AFDT), 19. 8% ; 2) Mucin Secreting Function Differentiation Type(MSFDT) , 24. 0% ; 3) Absorptive and Mucin-Producing Function Differentiation Type(AMPFDT) , 47. 1%; 4 ) Special Function Differentiation Type(SFDT) , 0. 8 %; and 5) Non-Function Differentiation Type(NFDT) , 8. 3%. The results indicate that stomach cancer tissues of the same histological type often display differing functional differentiation, and these functionally differentiated types have different invasive and metastatic characteristics. In addition, the functionally differentiated types have particular organic affinities of metastasis and different clinical prognoses. This study suggests that this new functional classification may supplement histological classification. The mechanisms of liver and ovary metastases of stomach cancer are also dis-cussed.
基金supported by the National Natural Science Foundation of China(No 29877016).
文摘In this paper, a new hybrid model of amino acid substitution is developed and compared with the others in previous works. The results show that the new hybrid model can characterize the protein sequences very well by calculating Fisher weights, which can denote how much the variants contribute to the classification.
基金supported by the National Natural Science Foundation of China[grant Nos 41971406,41871292]the Science and Technology Program of Guangdong Province[grant number 2018B020207002]the Science and Technology Program of Guangzhou,China[grant number 201803030034].
文摘The classification of urban functional areas plays an important role in urban planning and resource management.Although previous studies have confirmed that different urban func-tional areas have different morphological structures and Land Surface Temperature(LST)characteristics,these two types of characteristics have rarely been fully integrated and used for functional area classification.In this paper,a new framework for classifying urban functional areas is proposed by combining urban morphological features and LST features.First,metrics are constructed from three levels,namely,building,road and region,which are used to portray urban morphology;LST is retrieved using thermal infrared remote sensing to reflect LST features with four metrics:the average temperature,maximum temperature,temperature difference and standard deviation of temperature.Then,the functional areas are classified into four categories:service/public land,commercial land,residential land and industrial land.A random forest algorithm is used to effectively fuse the features of these two categories and classify the functional areas.The effectiveness of the proposed framework is tested in the study area of Shenzhen City,Guangdong Province.The results show that the combined classification accuracy of the proposed classification method is 0.85,which is 0.26 higher than that of the classification model based on urban morphology and 0.1 higher than that of the classification model based on LST features.The proposed framework verifies that the integration of LST features into urban functional area classification is reliable and effectively combines urban morphology and LST features for functional area classification.
文摘The maximum of k numerical functions defined on , , by , ??is used here in Statistical classification. Previously, it has been used in Statistical Discrimination [1] and in Clustering [2]. We present first some theoretical results on this function, and then its application in classification using a computer program we have developed. This approach leads to clear decisions, even in cases where the extension to several classes of Fisher’s linear discriminant function fails to be effective.
文摘Represents the first attempt to classify all of China’s295 cities in terms of industrial functions,using 1984 data.Within the framework of economic base theory of urban development,three elements are defined as specialized branch,functional intensity and functional scale.The method used here is based on a combination of the three elements.A number of techniques tried made it possible to base the classification on a composite measure,consisting of the Ward’s Error Method of hierarchical cluster analysis and a supplementary application of Nelson measure.The 295 cities have been grouped into three categories with 19 subcategories and 54 functional groups.The distribution of cities in most of the subcategories are displayed on 8 maps.
基金Supported by Foundation for Young Mainstay TeachersEducation Ministry of China.
文摘The radial basis function networks were applied to bacterial classification based on the matrix-assisted laser desorption/ionization time-of-flight mass spectrometric (MALDI-TOF-MS) data. The classification of bacteria cultured at different time was discussed and the effect of the network parameters on the classification was investigated. The cross-validation method was used to test the trained networks. The correctness of the classification of different bacteria investigated changes in a wide range from 61.5% to 92.8%. Owing to the complexity of biological effects in bacterial growth, the more rigid control of bacterial culture conditions seems to be a critical factor for improving the rate of correctness for bacterial classification.
文摘Pituitary adenoma may be calssifded in light of the hormones produced. 225 surgical specimens were labeled with anti-sear of GH, PRL. ACTH, TSH, FSH and LH by immunohistochemical technique (ABC method). Data indicated that 100 out of 225 cases (44.5%) were monohormonal adenomas, including 24 GH, 39 PRL, 1 FSH and 9 LH, 77 (34.2%) were multi-hormonal adenomas, including 28 positive for 2 hormones, 30 positive for 3 hormones, 19 positive for 4 or more different hormones, and the remaining 48 (21.3%) were nonfunctional adenomas. In comparison with Kovacs series, factors which might participate in the mechanism of developing monohormonal or multi-hormonal adenomas are discussed.
文摘The increase in chronic diseases in childhood highlights the need for a biopsychosocial approach to deal with the complexity of these health conditions. The International Classification of Functioning, Disability, and Health (ICF) results from the need to implement new explanatory evaluative and therapeutic models. Thus, the present systematic review aims to identify published studies on the use of the ICF in chronic childhood diseases. As a secondary objective, to map the themes that have already been studied in the area to support the discussion on the expansion of the use of this classification in health services. The systematic review followed the PRISMA protocol, and the model was the PICO acronym, where Population was children and adolescents with chronic diseases, Intervention/Exposure was evaluation based on ICF concepts, Comparator was any tool, instrument, or intervention, and outcome was direct or indirect use of the ICF. We selected eight articles, five of which used the ICF as a conceptual tool and three as a classification system, divided into the following themes: quality of life, evaluation of patients (without using coding) and mapping the inclusion of the activity’s results and participation in clinical trials. Thus, use of the ICF in clinical practice is still incipient, although it has been recommended in guidelines. Further studies are necessary to expand the number of contributions by the ICF and to develop the necessary approaches for understanding the classification’s use.
基金support of the National Key R&D Program of China(No.2022YFC2803903)the Key R&D Program of Zhejiang Province(No.2021C03013)the Zhejiang Provincial Natural Science Foundation of China(No.LZ20F020003).
文摘The ocean plays an important role in maintaining the equilibrium of Earth’s ecology and providing humans access to a wealth of resources.To obtain a high-precision underwater image classification model,we propose a classification model that combines an EfficientnetB0 neural network and a two-hidden-layer random vector functional link network(EfficientnetB0-TRVFL).The features of underwater images were extracted using the EfficientnetB0 neural network pretrained via ImageNet,and a new fully connected layer was trained on the underwater image dataset using the transfer learning method.Transfer learning ensures the initial performance of the network and helps in the development of a high-precision classification model.Subsequently,a TRVFL was proposed to improve the classification property of the model.Net construction of the two hidden layers exhibited a high accuracy when the same hidden layer nodes were used.The parameters of the second hidden layer were obtained using a novel calculation method,which reduced the outcome error to improve the performance instability caused by the random generation of parameters of RVFL.Finally,the TRVFL classifier was used to classify features and obtain classification results.The proposed EfficientnetB0-TRVFL classification model achieved 87.28%,74.06%,and 99.59%accuracy on the MLC2008,MLC2009,and Fish-gres datasets,respectively.The best convolutional neural networks and existing methods were stacked up through box plots and Kolmogorov-Smirnov tests,respectively.The increases imply improved systematization properties in underwater image classification tasks.The image classification model offers important performance advantages and better stability compared with existing methods.
基金supported by the National Natural Science Foundation of China (No.51877013),(ZJ),(http://www.nsfc.gov.cn/)the Jiangsu Provincial Key Research and Development Program (No.BE2021636),(ZJ),(http://kxjst.jiangsu.gov.cn/)+1 种基金the Science and Technology Project of Changzhou City (No.CE20205056),(ZJ),(http://kjj.changzhou.gov.cn/)by Qing Lan Project of Jiangsu Province (no specific grant number),(ZJ),(http://jyt.jiangsu.gov.cn/).
文摘The structure and function of brain networks have been altered in patients with end-stage renal disease(ESRD).Manifold regularization(MR)only considers the pairing relationship between two brain regions and cannot represent functional interactions or higher-order relationships between multiple brain regions.To solve this issue,we developed a method to construct a dynamic brain functional network(DBFN)based on dynamic hypergraph MR(DHMR)and applied it to the classification of ESRD associated with mild cognitive impairment(ESRDaMCI).The construction of DBFN with Pearson’s correlation(PC)was transformed into an optimization model.Node convolution and hyperedge convolution superposition were adopted to dynamically modify the hypergraph structure,and then got the dynamic hypergraph to form the manifold regular terms of the dynamic hypergraph.The DHMR and L_(1) norm regularization were introduced into the PC-based optimization model to obtain the final DHMR-based DBFN(DDBFN).Experiment results demonstrated the validity of the DDBFN method by comparing the classification results with several related brain functional network construction methods.Our work not only improves better classification performance but also reveals the discriminative regions of ESRDaMCI,providing a reference for clinical research and auxiliary diagnosis of concomitant cognitive impairments.
文摘Purpose: Brain functional networks (BFNs) has become important approach for diagnosis of some neurological or psychological disorders. Before estimating BFN, obtaining blood oxygen level dependent (BOLD) representative signals from brain regions of interest (ROIs) is important. In the past decades, the common method is generally to take a ROI as a node, averaging all the voxel time series inside it to extract a representative signal. However, one node does not represent the entire information of this ROI, and averaging method often leads to signal cancellation and information loss. Inspired by this, we propose a novel model extraction method based on an assumption that a ROI can be represented by multiple nodes. Methods: In this paper, we first extract multiple nodes (the number is user-defined) from the ROI based on two traditional methods, including principal component analysis (PCA), and K-means (Clustering according to the spatial position of voxels). Then, canonical correlation analysis (CCA) was issued to construct BFNs by maximizing the correlation between the representative signals corresponding to the nodes in any two ROIs. Finally, to further verify the effectiveness of the proposed method, the estimated BFNs are applied to identify subjects with autism spectrum disorder (ASD) and mild cognitive impairment (MCI) from health controls (HCs). Results: Experimental results on two benchmark databases demonstrate that the proposed method outperforms the baseline method in the sense of classification performance. Conclusions: We propose a novel method for obtaining nodes of ROId based on the hypothesis that a ROI can be represented by multiple nodes, that is, to extract the node signals of ROIs with K-means or PCA. Then, CCA is used to construct BFNs.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant number:82171965.
文摘Designing appropriate loss functions is critical to the success of supervised learning models.However,most conventional losses are fixed and manually designed,making them suboptimal for diverse and dynamic learning scenarios.In this work,we propose an Adaptive Meta-Loss Network(Adaptive-MLN)that learns to generate taskagnostic loss functions tailored to evolving classification problems.Unlike traditional methods that rely on static objectives,Adaptive-MLN treats the loss function itself as a trainable component,parameterized by a shallow neural network.To enable flexible,gradient-free optimization,we introduce a hybrid evolutionary approach that combines GeneticAlgorithms(GA)for global exploration and Evolution Strategies(ES)for local refinement.This co-evolutionary process dynamically adjusts the loss landscape,improvingmodel generalization without relying on analytic gradients or handcrafted heuristics.Experimental evaluations on synthetic tasks and the CIFAR-10 andMNIST datasets demonstrate that our approach consistently outperforms standard losses such as Cross-Entropy and Mean Squared Error in terms of accuracy,convergence,and adaptability.
文摘This paper attempts to provide a brief but systematic survey of nonverbal communication in terms of its characteristics, functions, and classification. Nonverbal communication involves all those nonverbal stimuli in a communication setting that are generated by both the source and the receiver. First, unlike verbal communication, it does not have a fixed set of signs, and formal rules and structures; it is innate and continuous. Second, it performs such functions as repeating, complementing, substituting, regulating, and contradicting. Finally, nonverbal communication may be classified into two major types: those produced by the body (including physical appearance, body movements, physical contact, facial expressions, eye contact, and paralanguage); and those associated with the setting (including space, time, and silence).
文摘The different land use surrounding parking facility has significant impact on parking behavior. This paper studies the functional classification of land use surrounding parking facility, which is fundamentally important for indepth research on parking behavior. 37 parking facilities located between the second and sixth ring roadway in Beijing were selected for this study. Based on the surveys conducted at these parking facilities, various parking behavior were analyzed, based on which the scope of the different parking was determined. The information on location, land use characteristics, public transport, the surrounding parking situations are collected for each investigated parking facility. Applying the SPSS clustering method, the threshold was developed for the classification. Totally, five categories are proposed for the land use functionality surrounding parking facility as the results of this study.
