Because of the difficulty to obtain the traffic flow information of lanes at non-detector intersections in most metropolises of the world,based on the relationships between the lanes of signal-controlled intersections...Because of the difficulty to obtain the traffic flow information of lanes at non-detector intersections in most metropolises of the world,based on the relationships between the lanes of signal-controlled intersections,cluster analysis and stepwise regression are integrated to predict the traffic volume of lanes at non-detector isolated controlled intersections.First cluster analysis is used to cluster the lanes of non-detector isolated signal-controlled intersections and the lanes of all signal-controlled intersections with detectors.Then, by the results of cluster analysis,the traffic volume samples are selected randomly and stepwise regression is used to predict the traffic volume of lanes at non-detector isolated signal-controlled intersections.The method is tested by the traffic volume data of lanes of the road network of Nanjing city.The problem of predicting the traffic volume of lanes at non-detector isolated signal-controlled intersections was resolved and can be widely used in urban traffic flow guidance and urban traffic control in cities without enough intersections equipped with detectors.展开更多
A significant portion of Landslide Early Warning Systems (LEWS) relies on the definition of operational thresholds and the monitoring of cumulative rainfall for alert issuance. These thresholds can be obtained in vari...A significant portion of Landslide Early Warning Systems (LEWS) relies on the definition of operational thresholds and the monitoring of cumulative rainfall for alert issuance. These thresholds can be obtained in various ways, but most often they are based on previous landslide data. This approach introduces several limitations. For instance, there is a requirement for the location to have been previously monitored in some way to have this type of information recorded. Another significant limitation is the need for information regarding the location and timing of incidents. Despite the current ease of obtaining location information (GPS, drone images, etc.), the timing of the event remains challenging to ascertain for a considerable portion of landslide data. Concerning rainfall monitoring, there are multiple ways to consider it, for instance, examining accumulations over various intervals (1 h, 6 h, 24 h, 72 h), as well as in the calculation of effective rainfall, which represents the precipitation that actually infiltrates the soil. However, in the vast majority of cases, both the thresholds and the rain monitoring approach are defined manually and subjectively, relying on the operators’ experience. This makes the process labor-intensive and time-consuming, hindering the establishment of a truly standardized and rapidly scalable methodology on a large scale. In this work, we propose a Landslides Early Warning System (LEWS) based on the concept of rainfall half-life and the determination of thresholds using Cluster Analysis and data inversion. The system is designed to be applied in extensive monitoring networks, such as the one utilized by Cemaden, Brazil’s National Center for Monitoring and Early Warning of Natural Disasters.展开更多
Total recoverable concentration of five elements of concern: Aluminum, Iron, Manganese, Arsenic and Lead (Al, Fe, Mn, As, Pb) were measured by inductively coupled plasma atomic emission spectrometry, and mass spectrom...Total recoverable concentration of five elements of concern: Aluminum, Iron, Manganese, Arsenic and Lead (Al, Fe, Mn, As, Pb) were measured by inductively coupled plasma atomic emission spectrometry, and mass spectrometry. The results show that sediment texture plays a controlling role in the concentrations and their spatial distribution. Principal Component Analysis and Cluster Analysis were used to analyze the grain sizes of the sediments. Result of texture analysis classified the samples into three main components in percentages: sand, silt, and clay. Significant differences among the element concentrations in the three groups were observed, and the concentrations of the elements in each group are reported in this study. Most of the elements have their highest concentrations in the fine-grained samples with clay playing an important role, in comparison with the sand component of the soil/sediment samples. There appears to be a strong correlation between samples with high silt, and clay content with the areas of elevated concentrations for Al, Fe, and Mn. There was a strong correlation between aluminum and lead with clay;lead with silt;and sand with manganese, aluminum, and lead. However, there was no strong relationship between the soil textures and iron or arsenic. All elements measured were statistically significant (at P ≤ 0.05) by watershed. The upland areas, and depositional areas’ spatial variation of element concentrations in the sediments were also observed, which was in line with the spatial distribution of the grain size and was thought to be related to the watersheds hydrological dynamics.展开更多
Purpose:This study analyzes the profiles of elite Brazilian researchers,recognized through the prestigious CNPq productivity scholarships.By identifying distinct researcher clusters,the study sheds light on different ...Purpose:This study analyzes the profiles of elite Brazilian researchers,recognized through the prestigious CNPq productivity scholarships.By identifying distinct researcher clusters,the study sheds light on different academic strategies,levels of productivity,and academic contributions within the Brazilian higher education system.Design/methodology/approach:The research analyzes a comprehensive dataset of 14,003 researchers,employing principal component analysis(PCA)followed by cluster analysis to group researchers based on their academic attributes.The clusters reflect diverse aspects of research productivity,graduate supervisions,and publication patterns.Findings:The analysis reveals the existence of three distinct researcher profiles(the Advanced Supervisors,the Book Publishers/Organizers,and the Generalists).The study also highlights the characteristics of highcaliber scientists,representing the upper echelon of Brazilian researchers in terms of productivity and impact.Research limitations:Although the study provides a robust analysis of the Brazilian system,the results reflect specific characteristics of the Brazilian academic context.Furthermore,the analysis was restricted to normalized annual data,which may overlook temporal variations in researcher productivity.Pratical implications:The findings provide valuable insights for policy makers,funding agencies(such as CNPq),and university administrators who aim to develop tailored support programs for different researcher profiles.Originality/value:The cluster-based profiling offers a novel perspective on how different academic trajectories coexist within a national science system,offering lessons for other emerging economies.展开更多
Traditional Chinese medicine(TCM)has played a significant role in the prevention and treatment of chronic heart failure(CHF).To study TCM diagnosis of CHF,a total of 278 Chinese clinical research articles on the study...Traditional Chinese medicine(TCM)has played a significant role in the prevention and treatment of chronic heart failure(CHF).To study TCM diagnosis of CHF,a total of 278 Chinese clinical research articles on the study of CHF syndromes in recent 40 years retrieved from Web of Science,Scopus,Pub Med,Embase,CNKI,Wanfang Data,Cq VIP,and Sino Med.According to cumulative frequency analysis,network analysis,and hierarchical cluster analysis,the study found the distribution of CHF syndromes was syndrome of qi deficiency with blood stasis,syndrome of qi and yin deficiency,syndrome of yang deficiency with water flooding,syndrome of heart blood stasis obstruction,syndrome of turbid phlegm,and syndrome of collapse due to primordial yang deficiency.The syndrome elements on location of illness were heart,kidney,lung,and spleen.The syndrome elements on nature of illness were qi deficiency,blood stasis,yang deficiency,yin deficiency,water retention,and turbid phlegm.These findings can provide reference to the research on diagnosis and treatment of CHF,and contribute to the study on syndrome standardization and objective research of TCM diagnosis.展开更多
With the continuous expansion of the power system scale and the increasing complexity of operational mode,the interaction between transmission and distribution systems is becoming more and more significant,placing hig...With the continuous expansion of the power system scale and the increasing complexity of operational mode,the interaction between transmission and distribution systems is becoming more and more significant,placing higher requirements on the accuracy and efficiency of the power system state estimation to address the challenge of balancing computational efficiency and estimation accuracy in traditional coupled transmission and distribution state estimation methods,this paper proposes a collaborative state estimation method based on distribution systems state clustering and load model parameter identification.To resolve the scalability issue of coupled transmission and distribution power systems,clustering is first carried out based on the distribution system states.As the data and models of the transmission system and distribution systems are not shared.For the transmission system,equating the power transmitted from the transmission system to the distribution system is the same as equating the distribution system.Further,the power transmitted from the transmission system to different types of distribution systems is equivalent to different polynomial equivalent load models.Then,a parameter identification method is proposed to obtain the parameters of the equivalent load model.Finally,a transmission and distribution collaborative state estimation model is constructed based on the equivalent load model.The results of the numerical analysis show that compared with the traditional master-slave splitting method,the proposed method significantly enhances computational efficiency while maintaining high estimation accuracy.展开更多
The issue of strong noise has increasingly become a bottleneck restricting the precision and application space of electromagnetic exploration methods.Noise suppression and extraction of effective electromagnetic respo...The issue of strong noise has increasingly become a bottleneck restricting the precision and application space of electromagnetic exploration methods.Noise suppression and extraction of effective electromagnetic response information under a strong noise background is a crucial scientific task to be addressed.To solve the noise suppression problem of the controlled-source electromagnetic method in strong interference areas,we propose an approach based on complex-plane 2D k-means clustering for data processing.Based on the stability of the controlled-source signal response,clustering analysis is applied to classify the spectra of different sources and noises in multiple time segments.By identifying the power spectra with controlled-source characteristics,it helps to improve the quality of the controlled-source response extraction.This paper presents the principle and workflow of the proposed algorithm,and demonstrates feasibility and effectiveness of the new algorithm through synthetic and real data examples.The results show that,compared with the conventional Robust denoising method,the clustering algorithm has a stronger suppression effect on common noise,can identify high-quality signals,and improve the preprocessing data quality of the controlledsource electromagnetic method.展开更多
Objective To explore the clinical characteristics and prognostic value in hereditary transthyretin amyloidosis cardiomyopathy(hATTR-CM)patients based on cluster analysis,and to explore the risk factors for cardiovascu...Objective To explore the clinical characteristics and prognostic value in hereditary transthyretin amyloidosis cardiomyopathy(hATTR-CM)patients based on cluster analysis,and to explore the risk factors for cardiovascular composite events.Methods This retrospective cohort study included hATTR-CM patients who were admitted to Peking Union Medical College Hospital from January 2000 to January 2024.These patients were divided into two clusters using cluster analysis,based on genetic information,ddemographic information and clinical information.During the follow-up period,cardiovascular composite events were defined as all-cause death and hospitalization for heart failure.Both cardiovascular composite events and all-cause death were the endpoints.Kaplan-Meier survival curves and log-rank method were used to compare the prognostic significance of cluster analysis subgroups.Univariate and multivariate Cox proportional hazardd regression mnodelswere used to analyze the risk factors affecting the incidence of cardiovascular composite events.Results A total of 43 patients were included in this study,30 were male(69.8%).In cluster 1(n=27),whose age of onset was(49.9±13.9)years old,24(88.9%)of them started with neuropathy or gastrointestinal symptoms,and all clinical phenotypes were mixed type(neurological and cardiac).In cluster 2(n=16),whose age of onset was(59.0±10.6)years old,15(93.8%)of them started with heart failure symptoms,and 13(81.3%)were pure cardiomyopathy.During the median follow-up time of 2.6 years,a total of 16 patients(37.2%)experienced composite cardiovascular events,and a total of 12 patients(27.9%)died.Kaplan-Meier survival curves showed a significantly lower cumulative survival rate for cardiovascular composite endpoint events(log-rank P=0.04)and all-cause death(log-rank P=0.04)in cluster 2 was than that in cluster 1.Univariate Cox proportional hazard regression model analysis showed that hATTR-CM patients with reduced estimated glomerular filtration rate,left ventricular ejection fraction≤40%,and moderate to severe mitral regurgitation were risk factors for vascular composite events(all P<0.05).Multivariate Cox proportional hazard regression analysis showed that left ventricular ejection fraction≤40%was an independent risk factor(P<0.O1).Conclusion Cluster analysis is a valuable prediction tool on the prognostic stratification of hATTR-CM.Cluster 2,which is late-onset with onset of heart failure symptoms has a worse prognosis during follow-up period.The occurrence of composite cardiovascular events in hATTR-CM is related to left ventricular ejection fraction≤40%.Cluster analysis is helpful for clinical identification of high-risk groups.展开更多
Cycle slip detection and repair is one of the key technologies for GNSS high-precision positioning.We introduce an enhanced methodology for detecting and repairing BDS four-frequency cycle slips,utilizing fuzzy cluste...Cycle slip detection and repair is one of the key technologies for GNSS high-precision positioning.We introduce an enhanced methodology for detecting and repairing BDS four-frequency cycle slips,utilizing fuzzy clustering analysis.Firstly,based on fuzzy clustering analysis,the optimal combinations for the BDS four-frequency,including extra-wide lane(EWL),wide lane(WL),and narrow lane(NL),were selected.Secondly,the feasibility of this method was verified using actual static and dynamic observation data,and different types of cycle slips were simulated for further validation.Meanwhile,the proposed method was compared with the classical Turbo-Edit method through experiments.Finally,cycle slips were repaired using the least squares method.According to the experimental results,the optimal geometry-free phase combinations(-2,2,1,-1),(1,-1,1,-1),(3,2,-2,-3),and the pseudo-range phase combination(-1,1,1,-1),selected based on fuzzy clustering analysis,were used for cycle slip detection.The proposed method accurately detected small,large,and specific cycle slips simulated in the actual data.Compared with the Turbo-Edit method,the proposed methodwas able to detect specific cycle slips that Turbo-Edit could not.It is worth noting that during the repair process,the coefficients of the combined observation values are integers,preserving the integer cycle characteristic of the observation values,which allows cycle slips to be fixed directly,eliminating the need for complex searching procedures.Consequently,by enhancing the precision and reliability of the detection of BDS four-frequency cycle slips,our proposed method provides the support for the high-precision localization of BDS multi-frequency observations.展开更多
[Objective] The aim was to study the variation of leaf characters from different provenance sources of Polygonum multiflorum Thunb,as well as to carry out cluster analysis on P.multiflorum from different provenance so...[Objective] The aim was to study the variation of leaf characters from different provenance sources of Polygonum multiflorum Thunb,as well as to carry out cluster analysis on P.multiflorum from different provenance sources to provide basis for the classification,identification,breeding and improved variety selection of P.multiflorum.[Method] Leaf shape characters of 31 copies of germplasm resources in the major distribution region of the whole country were determined,and the genetic variation of P.multiflorum leaves from different producing areas was analyzed.[Result] The leaf characters of single plant of the same experimental provenance source of P.multiflorum were relatively stable,the variation was mainly found on the single leaf area,1/2 leaf width,leaf width and other indicators;the variation of each leaf character among different provenance sources was obvious,and the variation was mainly found on the single leaf weight,leaf area,1/2 leaf width,leaf length and other indicators.The correlation analysis of each leaf character in P.multiflorum suggested that the single leaf area and single leaf weight showed extremely significant positive correlation with leaf length,1/2 leaf width,leaf width,leaf thickness and leaf stem length,while the single leaf area and single leaf weight showed significant negative correlation with WWR（leaf width/1/2 leaf width）and LWR（leaf length/1/2 leaf length）,in addition,several macroscopic leaf characters such as leaf length,1/2 leaf width,leaf width,leaf stem length showed extremely positive correlation.The main component analysis result suggested that the contribution rate of accumulation variance of the front three main components was up to 97.4%,which could better reflect the comprehensive performance of leaf characters of different provenance sources of P.multiflorum.The cluster analysis showed that the experimental 31 copies of P.multiflorum provenance sources should be divided into three classes,the first class was distributed in the Middle,Western of Guizhou,northwestern of Guangxi and western areas with higher altitude;the second class was distributed in Hunan,Hubei,Sichuan,Guangdong and the most area of Guangxi;the third class was distributed in Anhui,Jiangsu and Henan and Shandong.[Conclusion] Cluster analysis of leaf characters indicated that the kinds of provenance sources which the geographical position was closer could be got together.The study had provided a certain basis for the classification of P.multiflorum.展开更多
In order to analyze the heterogeneity in vehicular traffic speed, a new method that integrates cluster analysis and probability distribution function fitting is presented. First, for identifying the optimal number of ...In order to analyze the heterogeneity in vehicular traffic speed, a new method that integrates cluster analysis and probability distribution function fitting is presented. First, for identifying the optimal number of clusters, the two-step cluster method is applied to analyze actual speed data, which suggests that dividing speed data into two clusters can best reflect the intrinsic patterns of traffic flows. Such information is then taken as guidance in probability distribution function fitting. The normal, skew-normal and skew-t distribution functions are used to fit the probability distribution of each cluster respectively, which suggests that the skew-t distribution has the highest fitting accuracy; the second is skew-normal distribution; the worst is normal distribution. Model analysis results demonstrate that the proposed mixture model has a better fitting and generalization capability than the conventional single model. In addition, the new method is more flexible in terms of data fitting and can provide a more accurate model of speed distribution.展开更多
[ObJective] The research aimed to determine the geographic distribution map of system of Rana dybowskii. [Method] Four morphologic indices （body length, body weight, forelimb length, hindlimb length） of eight geogra...[ObJective] The research aimed to determine the geographic distribution map of system of Rana dybowskii. [Method] Four morphologic indices （body length, body weight, forelimb length, hindlimb length） of eight geographical populations of R.dybowskii which naturally distribute in Changhai Mountain and Xiaoxing＇an Mountain were measured. Measure results were variance analyzed and cluster analyzed. [Result] Variance analysis showed： the genetic branching among the Dongfanghong male population（ belongs to Wandashan） and Xiaoxing＇an Mountain male population and Changbai Mountain male population were significantly different （P〈0.05） ; the genetic branching between the Hebei female population （belongs to Xiaoxing＇an Mountain） and Changbai Mountain female population was significantly different （P〈0.05 ）. Cluster analysis showed ： male R.dybowskii can be divided into three groups ： the first group included Quanyang, Tianbei, Chaoyang and Ddkouqin, the second group included Tieli and Anshan, the third group included Dongfanghong; and the female R. dybowskii can be divided into three groups ： the first group included Quanyang and Chaoyang, the second group included Tianbei and Dakouqin, the third group included Hebei. [Condusion] The paper deduced that the Sanjiang Plain was the geographical origin center ofR. dybowskii which radiated to Changbai Mountain and Xiaoxing＇an Mountain along the adverse current of Songhua River basin, therefore, the current distribution pattern of R. dybowskii was formed.展开更多
Inter-simple sequence repeat（ISSR） molecular markers were applied to analyze the genetic diversity and clustering of 48 introduced and bred cultivars of Olea euyopaea L. Totally 106 DNA bands were amplified by 11 sc...Inter-simple sequence repeat（ISSR） molecular markers were applied to analyze the genetic diversity and clustering of 48 introduced and bred cultivars of Olea euyopaea L. Totally 106 DNA bands were amplified by 11 screened primers, including 99 polymorphic bands; the percentage of polymorphic loci was 93.40%, indicating a rich genetic diversity in Olea euyopaea L. germplasm resources. Based on Nei＇s genetic distances between various cultivars, a dendrogram of 48 cultivars of Olea euyopaea L. was constructed using unweighted pair-group（UPMGA）method,which showed that 48 cultivars were clustered into four main categories; 84.6% of native cultivars were clustered into two categories; most of introduced cultivars were clustered based on their sources and main usages but not on their geographic origins. This study will provide references for the utilization and further genetic improvement of Olea euyopaea L. germplasm resources.展开更多
In order to mine production and security information from security supervising data and to ensure security and safety involved in production and decision-making,a clustering analysis algorithm for security supervising...In order to mine production and security information from security supervising data and to ensure security and safety involved in production and decision-making,a clustering analysis algorithm for security supervising data based on a semantic description in coal mines is studied.First,the semantic and numerical-based hybrid description method of security supervising data in coal mines is described.Secondly,the similarity measurement method of semantic and numerical data are separately given and a weight-based hybrid similarity measurement method for the security supervising data based on a semantic description in coal mines is presented.Thirdly,taking the hybrid similarity measurement method as the distance criteria and using a grid methodology for reference,an improved CURE clustering algorithm based on the grid is presented.Finally,the simulation results of a security supervising data set in coal mines validate the efficiency of the algorithm.展开更多
In order to reveal the genetic differences and agronomic traits of Fagopy-rum tataricum_ varieties （lines） intuitively, explore good resources and avoid the blindness of parent selection during the breeding process,...In order to reveal the genetic differences and agronomic traits of Fagopy-rum tataricum_ varieties （lines） intuitively, explore good resources and avoid the blindness of parent selection during the breeding process, six primary agronomic traits of 45 F. tataricum_ varieties （lines） that came from the eleven buckwheat breeding departments across the country were analyzed with principal component analysis and cluster analysis. The results of principal component analysis showed that the six agronomic traits could be simplified into three principal components, and the cumulative contribution rate reached 83%. The results of cluster analysis showed that the 45 F. tataricum varieties （lines） were classified into four groups：high stalk, medium yield and smal grain type, medium stalk, high yield and large grain type, medium stalk, low yield and smal grain type and high stalk, medium yield and medium grain type. Among them, performance of comprehensive trait of the second type was better than that of the other types. Thus, the F. tataricum_va-rieties （lines） that were classified into the second type could be considered as good varieties （lines） or breeding materials. The genetic differences among F. tataricum_varieties （lines） had no necessary correlations with origin and geographical distance. ln addition to complementary traits and geographical distance, genetic distances （dif-ferent populations） should be taken into consideration during parent selection in cross breeding.展开更多
In order to compare the characteristics of different varieties of sweet cherry and to formulate corresponding pruning scheme, hierarchical cluster analysis was conducted for the 14 sweet cherry varieties that were mai...In order to compare the characteristics of different varieties of sweet cherry and to formulate corresponding pruning scheme, hierarchical cluster analysis was conducted for the 14 sweet cherry varieties that were mainly planted in Shanxi Province. The results showed that the 14 varieties of sweet cherry could be divided into two types, Hongmanao and Rainier. Fruit setting rate, branching rate, medium fruit shoot proportion, spur proportion and yield per plant were significantly different between these two types of sweet cherry. The key points of pruning management, to improve the yield of Rainier type, were to increase the fruit setting rate and spur proportion, and to control properly the long and medium fruit shoot proportion.展开更多
[Objective] This study aimed to develop ACGM markers for the clustering analysis of large grained Brassica napus materials. [Method] A total of 44 pairs of ACGM primers were designed according to 18 genes related to A...[Objective] This study aimed to develop ACGM markers for the clustering analysis of large grained Brassica napus materials. [Method] A total of 44 pairs of ACGM primers were designed according to 18 genes related to Arabidopsis grain development and their homologous rape EST sequences. After electrophoresis, 18 pairs of ACGM primers were selected for the clustering analysis of 16 larger grained samples and four fine grained samples of rapeseed. [Result] PCR result showed that 2-6 specific bands were respectively amplified by each pair of primes, and all the bands were polymorphic and repeatable, suggesting that the optimized ACGM markers were useful for clustering analysis of B. napus species. Clustering analysis revealed that the 20 rapeseed samples were divided into three clusters A, B, and C at similarity coefficient 0.6. Then, the clusters A and B were further divided into five sub clusters A1, A2, A3, B1 and B2 at similarity coefficient 0.67. [Conclusion] This study will provide theoretical and practical values for rape breeding.展开更多
[Objective] This research aimed to study the FTIR spectra of corn germs and endosperms so as to provide a scientific way for identifying corn of different types. [Method] The corn germs and endosperms of three types w...[Objective] This research aimed to study the FTIR spectra of corn germs and endosperms so as to provide a scientific way for identifying corn of different types. [Method] The corn germs and endosperms of three types were studied by using Fourier transform infrared spectroscopy（FTIR） technology, combined with cluster analysis. [Result] The overall characteristics of original FTIR spectra were basically similar within the range of 700-1 800 cm^-1. The FTIR spectra were mainly composed by the absorption peaks of polysaccharides, proteins and lipids. Within the wavelength range of 700-1 800 cm^-1, there were only tiny differences in original FTIR spectra among the corn germs and endosperms of three different types. The spectra were then processed by using first derivative and second derivative. The second derivative spectra were used for hierarchical cluster analysis（HCA）. The results showed that with the wavelength range of 700-1 800 cm^-1, the second derivative spectra of the 52 samples could be better clustered according to the tree types and corn germ and corn endosperm. The clustering correct rate reached 96.1%.[Conclusion] FTIR technology, combined with cluster analysis, can be used to identify different types of corn germs and endosperms, and it is characterized by convenience and rapidness.展开更多
[Objective] This study aimed to investigate the trace elements in Rehman- nia glutinosa Libosch. by using principal component analysis and clustering analysis. [Method] Principal component analysis and clustering anal...[Objective] This study aimed to investigate the trace elements in Rehman- nia glutinosa Libosch. by using principal component analysis and clustering analysis. [Method] Principal component analysis and clustering analysis of R. glutinosa medicinal materials from different sources were conducted with contents of six trace elements as indices. [Result] The principal component analysis could comprehen- sively evaluate the quality of R. glutinosa samples with objective results which was consistent with the results of clustering analysis. [Conclusion] Principal component analysis and clustering analysis methods can be used for the quality evaluation of Chinese medicinal materials with multiple indices.展开更多
基金The National Natural Science Foundation of China(No.50378016).
文摘Because of the difficulty to obtain the traffic flow information of lanes at non-detector intersections in most metropolises of the world,based on the relationships between the lanes of signal-controlled intersections,cluster analysis and stepwise regression are integrated to predict the traffic volume of lanes at non-detector isolated controlled intersections.First cluster analysis is used to cluster the lanes of non-detector isolated signal-controlled intersections and the lanes of all signal-controlled intersections with detectors.Then, by the results of cluster analysis,the traffic volume samples are selected randomly and stepwise regression is used to predict the traffic volume of lanes at non-detector isolated signal-controlled intersections.The method is tested by the traffic volume data of lanes of the road network of Nanjing city.The problem of predicting the traffic volume of lanes at non-detector isolated signal-controlled intersections was resolved and can be widely used in urban traffic flow guidance and urban traffic control in cities without enough intersections equipped with detectors.
文摘A significant portion of Landslide Early Warning Systems (LEWS) relies on the definition of operational thresholds and the monitoring of cumulative rainfall for alert issuance. These thresholds can be obtained in various ways, but most often they are based on previous landslide data. This approach introduces several limitations. For instance, there is a requirement for the location to have been previously monitored in some way to have this type of information recorded. Another significant limitation is the need for information regarding the location and timing of incidents. Despite the current ease of obtaining location information (GPS, drone images, etc.), the timing of the event remains challenging to ascertain for a considerable portion of landslide data. Concerning rainfall monitoring, there are multiple ways to consider it, for instance, examining accumulations over various intervals (1 h, 6 h, 24 h, 72 h), as well as in the calculation of effective rainfall, which represents the precipitation that actually infiltrates the soil. However, in the vast majority of cases, both the thresholds and the rain monitoring approach are defined manually and subjectively, relying on the operators’ experience. This makes the process labor-intensive and time-consuming, hindering the establishment of a truly standardized and rapidly scalable methodology on a large scale. In this work, we propose a Landslides Early Warning System (LEWS) based on the concept of rainfall half-life and the determination of thresholds using Cluster Analysis and data inversion. The system is designed to be applied in extensive monitoring networks, such as the one utilized by Cemaden, Brazil’s National Center for Monitoring and Early Warning of Natural Disasters.
文摘Total recoverable concentration of five elements of concern: Aluminum, Iron, Manganese, Arsenic and Lead (Al, Fe, Mn, As, Pb) were measured by inductively coupled plasma atomic emission spectrometry, and mass spectrometry. The results show that sediment texture plays a controlling role in the concentrations and their spatial distribution. Principal Component Analysis and Cluster Analysis were used to analyze the grain sizes of the sediments. Result of texture analysis classified the samples into three main components in percentages: sand, silt, and clay. Significant differences among the element concentrations in the three groups were observed, and the concentrations of the elements in each group are reported in this study. Most of the elements have their highest concentrations in the fine-grained samples with clay playing an important role, in comparison with the sand component of the soil/sediment samples. There appears to be a strong correlation between samples with high silt, and clay content with the areas of elevated concentrations for Al, Fe, and Mn. There was a strong correlation between aluminum and lead with clay;lead with silt;and sand with manganese, aluminum, and lead. However, there was no strong relationship between the soil textures and iron or arsenic. All elements measured were statistically significant (at P ≤ 0.05) by watershed. The upland areas, and depositional areas’ spatial variation of element concentrations in the sediments were also observed, which was in line with the spatial distribution of the grain size and was thought to be related to the watersheds hydrological dynamics.
文摘Purpose:This study analyzes the profiles of elite Brazilian researchers,recognized through the prestigious CNPq productivity scholarships.By identifying distinct researcher clusters,the study sheds light on different academic strategies,levels of productivity,and academic contributions within the Brazilian higher education system.Design/methodology/approach:The research analyzes a comprehensive dataset of 14,003 researchers,employing principal component analysis(PCA)followed by cluster analysis to group researchers based on their academic attributes.The clusters reflect diverse aspects of research productivity,graduate supervisions,and publication patterns.Findings:The analysis reveals the existence of three distinct researcher profiles(the Advanced Supervisors,the Book Publishers/Organizers,and the Generalists).The study also highlights the characteristics of highcaliber scientists,representing the upper echelon of Brazilian researchers in terms of productivity and impact.Research limitations:Although the study provides a robust analysis of the Brazilian system,the results reflect specific characteristics of the Brazilian academic context.Furthermore,the analysis was restricted to normalized annual data,which may overlook temporal variations in researcher productivity.Pratical implications:The findings provide valuable insights for policy makers,funding agencies(such as CNPq),and university administrators who aim to develop tailored support programs for different researcher profiles.Originality/value:The cluster-based profiling offers a novel perspective on how different academic trajectories coexist within a national science system,offering lessons for other emerging economies.
基金financed by the grants from the National Natural Science Foundation of China(No.81803996)Shanghai Key Laboratory of Health Identification and Assessment(No.21DZ2271000)。
文摘Traditional Chinese medicine(TCM)has played a significant role in the prevention and treatment of chronic heart failure(CHF).To study TCM diagnosis of CHF,a total of 278 Chinese clinical research articles on the study of CHF syndromes in recent 40 years retrieved from Web of Science,Scopus,Pub Med,Embase,CNKI,Wanfang Data,Cq VIP,and Sino Med.According to cumulative frequency analysis,network analysis,and hierarchical cluster analysis,the study found the distribution of CHF syndromes was syndrome of qi deficiency with blood stasis,syndrome of qi and yin deficiency,syndrome of yang deficiency with water flooding,syndrome of heart blood stasis obstruction,syndrome of turbid phlegm,and syndrome of collapse due to primordial yang deficiency.The syndrome elements on location of illness were heart,kidney,lung,and spleen.The syndrome elements on nature of illness were qi deficiency,blood stasis,yang deficiency,yin deficiency,water retention,and turbid phlegm.These findings can provide reference to the research on diagnosis and treatment of CHF,and contribute to the study on syndrome standardization and objective research of TCM diagnosis.
基金State Grid Jiangsu Electric Power Co.,Ltd.Technology Project(J2023121).
文摘With the continuous expansion of the power system scale and the increasing complexity of operational mode,the interaction between transmission and distribution systems is becoming more and more significant,placing higher requirements on the accuracy and efficiency of the power system state estimation to address the challenge of balancing computational efficiency and estimation accuracy in traditional coupled transmission and distribution state estimation methods,this paper proposes a collaborative state estimation method based on distribution systems state clustering and load model parameter identification.To resolve the scalability issue of coupled transmission and distribution power systems,clustering is first carried out based on the distribution system states.As the data and models of the transmission system and distribution systems are not shared.For the transmission system,equating the power transmitted from the transmission system to the distribution system is the same as equating the distribution system.Further,the power transmitted from the transmission system to different types of distribution systems is equivalent to different polynomial equivalent load models.Then,a parameter identification method is proposed to obtain the parameters of the equivalent load model.Finally,a transmission and distribution collaborative state estimation model is constructed based on the equivalent load model.The results of the numerical analysis show that compared with the traditional master-slave splitting method,the proposed method significantly enhances computational efficiency while maintaining high estimation accuracy.
基金supported by the National Key Research and Development Program Project of China(Grant No.2023YFF0718003)the key research and development plan project of Yunnan Province(Grant No.202303AA080006).
文摘The issue of strong noise has increasingly become a bottleneck restricting the precision and application space of electromagnetic exploration methods.Noise suppression and extraction of effective electromagnetic response information under a strong noise background is a crucial scientific task to be addressed.To solve the noise suppression problem of the controlled-source electromagnetic method in strong interference areas,we propose an approach based on complex-plane 2D k-means clustering for data processing.Based on the stability of the controlled-source signal response,clustering analysis is applied to classify the spectra of different sources and noises in multiple time segments.By identifying the power spectra with controlled-source characteristics,it helps to improve the quality of the controlled-source response extraction.This paper presents the principle and workflow of the proposed algorithm,and demonstrates feasibility and effectiveness of the new algorithm through synthetic and real data examples.The results show that,compared with the conventional Robust denoising method,the clustering algorithm has a stronger suppression effect on common noise,can identify high-quality signals,and improve the preprocessing data quality of the controlledsource electromagnetic method.
文摘Objective To explore the clinical characteristics and prognostic value in hereditary transthyretin amyloidosis cardiomyopathy(hATTR-CM)patients based on cluster analysis,and to explore the risk factors for cardiovascular composite events.Methods This retrospective cohort study included hATTR-CM patients who were admitted to Peking Union Medical College Hospital from January 2000 to January 2024.These patients were divided into two clusters using cluster analysis,based on genetic information,ddemographic information and clinical information.During the follow-up period,cardiovascular composite events were defined as all-cause death and hospitalization for heart failure.Both cardiovascular composite events and all-cause death were the endpoints.Kaplan-Meier survival curves and log-rank method were used to compare the prognostic significance of cluster analysis subgroups.Univariate and multivariate Cox proportional hazardd regression mnodelswere used to analyze the risk factors affecting the incidence of cardiovascular composite events.Results A total of 43 patients were included in this study,30 were male(69.8%).In cluster 1(n=27),whose age of onset was(49.9±13.9)years old,24(88.9%)of them started with neuropathy or gastrointestinal symptoms,and all clinical phenotypes were mixed type(neurological and cardiac).In cluster 2(n=16),whose age of onset was(59.0±10.6)years old,15(93.8%)of them started with heart failure symptoms,and 13(81.3%)were pure cardiomyopathy.During the median follow-up time of 2.6 years,a total of 16 patients(37.2%)experienced composite cardiovascular events,and a total of 12 patients(27.9%)died.Kaplan-Meier survival curves showed a significantly lower cumulative survival rate for cardiovascular composite endpoint events(log-rank P=0.04)and all-cause death(log-rank P=0.04)in cluster 2 was than that in cluster 1.Univariate Cox proportional hazard regression model analysis showed that hATTR-CM patients with reduced estimated glomerular filtration rate,left ventricular ejection fraction≤40%,and moderate to severe mitral regurgitation were risk factors for vascular composite events(all P<0.05).Multivariate Cox proportional hazard regression analysis showed that left ventricular ejection fraction≤40%was an independent risk factor(P<0.O1).Conclusion Cluster analysis is a valuable prediction tool on the prognostic stratification of hATTR-CM.Cluster 2,which is late-onset with onset of heart failure symptoms has a worse prognosis during follow-up period.The occurrence of composite cardiovascular events in hATTR-CM is related to left ventricular ejection fraction≤40%.Cluster analysis is helpful for clinical identification of high-risk groups.
基金supported by the National Natural Science Foundation of China(42174003)the Gansu Provincial Department of Education:Innovation Fund Project for College Teachers(2023A-035)+1 种基金Gansu Provincial Science and Technology Program(Joint Research Fund),24JRRA856the Lanzhou Talent Innovation Project,2023-RC-31.
文摘Cycle slip detection and repair is one of the key technologies for GNSS high-precision positioning.We introduce an enhanced methodology for detecting and repairing BDS four-frequency cycle slips,utilizing fuzzy clustering analysis.Firstly,based on fuzzy clustering analysis,the optimal combinations for the BDS four-frequency,including extra-wide lane(EWL),wide lane(WL),and narrow lane(NL),were selected.Secondly,the feasibility of this method was verified using actual static and dynamic observation data,and different types of cycle slips were simulated for further validation.Meanwhile,the proposed method was compared with the classical Turbo-Edit method through experiments.Finally,cycle slips were repaired using the least squares method.According to the experimental results,the optimal geometry-free phase combinations(-2,2,1,-1),(1,-1,1,-1),(3,2,-2,-3),and the pseudo-range phase combination(-1,1,1,-1),selected based on fuzzy clustering analysis,were used for cycle slip detection.The proposed method accurately detected small,large,and specific cycle slips simulated in the actual data.Compared with the Turbo-Edit method,the proposed methodwas able to detect specific cycle slips that Turbo-Edit could not.It is worth noting that during the repair process,the coefficients of the combined observation values are integers,preserving the integer cycle characteristic of the observation values,which allows cycle slips to be fixed directly,eliminating the need for complex searching procedures.Consequently,by enhancing the precision and reliability of the detection of BDS four-frequency cycle slips,our proposed method provides the support for the high-precision localization of BDS multi-frequency observations.
基金Supported by High-tech Research Project of Jiangsu Province(BG2004314)~~
文摘[Objective] The aim was to study the variation of leaf characters from different provenance sources of Polygonum multiflorum Thunb,as well as to carry out cluster analysis on P.multiflorum from different provenance sources to provide basis for the classification,identification,breeding and improved variety selection of P.multiflorum.[Method] Leaf shape characters of 31 copies of germplasm resources in the major distribution region of the whole country were determined,and the genetic variation of P.multiflorum leaves from different producing areas was analyzed.[Result] The leaf characters of single plant of the same experimental provenance source of P.multiflorum were relatively stable,the variation was mainly found on the single leaf area,1/2 leaf width,leaf width and other indicators;the variation of each leaf character among different provenance sources was obvious,and the variation was mainly found on the single leaf weight,leaf area,1/2 leaf width,leaf length and other indicators.The correlation analysis of each leaf character in P.multiflorum suggested that the single leaf area and single leaf weight showed extremely significant positive correlation with leaf length,1/2 leaf width,leaf width,leaf thickness and leaf stem length,while the single leaf area and single leaf weight showed significant negative correlation with WWR（leaf width/1/2 leaf width）and LWR（leaf length/1/2 leaf length）,in addition,several macroscopic leaf characters such as leaf length,1/2 leaf width,leaf width,leaf stem length showed extremely positive correlation.The main component analysis result suggested that the contribution rate of accumulation variance of the front three main components was up to 97.4%,which could better reflect the comprehensive performance of leaf characters of different provenance sources of P.multiflorum.The cluster analysis showed that the experimental 31 copies of P.multiflorum provenance sources should be divided into three classes,the first class was distributed in the Middle,Western of Guizhou,northwestern of Guangxi and western areas with higher altitude;the second class was distributed in Hunan,Hubei,Sichuan,Guangdong and the most area of Guangxi;the third class was distributed in Anhui,Jiangsu and Henan and Shandong.[Conclusion] Cluster analysis of leaf characters indicated that the kinds of provenance sources which the geographical position was closer could be got together.The study had provided a certain basis for the classification of P.multiflorum.
基金The National Science Foundation by Changjiang Scholarship of Ministry of Education of China(No.BCS-0527508)the Joint Research Fund for Overseas Natural Science of China(No.51250110075)+1 种基金the Natural Science Foundation of Jiangsu Province(No.BK200910046)the Postdoctoral Science Foundation of Jiangsu Province(No.0901005C)
文摘In order to analyze the heterogeneity in vehicular traffic speed, a new method that integrates cluster analysis and probability distribution function fitting is presented. First, for identifying the optimal number of clusters, the two-step cluster method is applied to analyze actual speed data, which suggests that dividing speed data into two clusters can best reflect the intrinsic patterns of traffic flows. Such information is then taken as guidance in probability distribution function fitting. The normal, skew-normal and skew-t distribution functions are used to fit the probability distribution of each cluster respectively, which suggests that the skew-t distribution has the highest fitting accuracy; the second is skew-normal distribution; the worst is normal distribution. Model analysis results demonstrate that the proposed mixture model has a better fitting and generalization capability than the conventional single model. In addition, the new method is more flexible in terms of data fitting and can provide a more accurate model of speed distribution.
文摘[ObJective] The research aimed to determine the geographic distribution map of system of Rana dybowskii. [Method] Four morphologic indices （body length, body weight, forelimb length, hindlimb length） of eight geographical populations of R.dybowskii which naturally distribute in Changhai Mountain and Xiaoxing＇an Mountain were measured. Measure results were variance analyzed and cluster analyzed. [Result] Variance analysis showed： the genetic branching among the Dongfanghong male population（ belongs to Wandashan） and Xiaoxing＇an Mountain male population and Changbai Mountain male population were significantly different （P〈0.05） ; the genetic branching between the Hebei female population （belongs to Xiaoxing＇an Mountain） and Changbai Mountain female population was significantly different （P〈0.05 ）. Cluster analysis showed ： male R.dybowskii can be divided into three groups ： the first group included Quanyang, Tianbei, Chaoyang and Ddkouqin, the second group included Tieli and Anshan, the third group included Dongfanghong; and the female R. dybowskii can be divided into three groups ： the first group included Quanyang and Chaoyang, the second group included Tianbei and Dakouqin, the third group included Hebei. [Condusion] The paper deduced that the Sanjiang Plain was the geographical origin center ofR. dybowskii which radiated to Changbai Mountain and Xiaoxing＇an Mountain along the adverse current of Songhua River basin, therefore, the current distribution pattern of R. dybowskii was formed.
基金Supported by Key Project of New Product Development in Yunnan Province(2009BB006)~~
文摘Inter-simple sequence repeat（ISSR） molecular markers were applied to analyze the genetic diversity and clustering of 48 introduced and bred cultivars of Olea euyopaea L. Totally 106 DNA bands were amplified by 11 screened primers, including 99 polymorphic bands; the percentage of polymorphic loci was 93.40%, indicating a rich genetic diversity in Olea euyopaea L. germplasm resources. Based on Nei＇s genetic distances between various cultivars, a dendrogram of 48 cultivars of Olea euyopaea L. was constructed using unweighted pair-group（UPMGA）method,which showed that 48 cultivars were clustered into four main categories; 84.6% of native cultivars were clustered into two categories; most of introduced cultivars were clustered based on their sources and main usages but not on their geographic origins. This study will provide references for the utilization and further genetic improvement of Olea euyopaea L. germplasm resources.
基金The National Natural Science Foundation of China(No.50674086)Specialized Research Fund for the Doctoral Program of Higher Education(No.20060290508)the Postdoctoral Scientific Program of Jiangsu Province(No.0701045B)
文摘In order to mine production and security information from security supervising data and to ensure security and safety involved in production and decision-making,a clustering analysis algorithm for security supervising data based on a semantic description in coal mines is studied.First,the semantic and numerical-based hybrid description method of security supervising data in coal mines is described.Secondly,the similarity measurement method of semantic and numerical data are separately given and a weight-based hybrid similarity measurement method for the security supervising data based on a semantic description in coal mines is presented.Thirdly,taking the hybrid similarity measurement method as the distance criteria and using a grid methodology for reference,an improved CURE clustering algorithm based on the grid is presented.Finally,the simulation results of a security supervising data set in coal mines validate the efficiency of the algorithm.
基金Supported by National Oat and Buckwheat Industrial Technology System(CARS-08-A-1-3)Breeding Project of Shanxi Academy of Agricultural Sciences during the Thirteenth Five-Year Plan Period(16yzgc035)~~
文摘In order to reveal the genetic differences and agronomic traits of Fagopy-rum tataricum_ varieties （lines） intuitively, explore good resources and avoid the blindness of parent selection during the breeding process, six primary agronomic traits of 45 F. tataricum_ varieties （lines） that came from the eleven buckwheat breeding departments across the country were analyzed with principal component analysis and cluster analysis. The results of principal component analysis showed that the six agronomic traits could be simplified into three principal components, and the cumulative contribution rate reached 83%. The results of cluster analysis showed that the 45 F. tataricum varieties （lines） were classified into four groups：high stalk, medium yield and smal grain type, medium stalk, high yield and large grain type, medium stalk, low yield and smal grain type and high stalk, medium yield and medium grain type. Among them, performance of comprehensive trait of the second type was better than that of the other types. Thus, the F. tataricum_va-rieties （lines） that were classified into the second type could be considered as good varieties （lines） or breeding materials. The genetic differences among F. tataricum_varieties （lines） had no necessary correlations with origin and geographical distance. ln addition to complementary traits and geographical distance, genetic distances （dif-ferent populations） should be taken into consideration during parent selection in cross breeding.
基金Supported by Spark Program of Science and Technology Department of Shanxi Province(20130511021)~~
文摘In order to compare the characteristics of different varieties of sweet cherry and to formulate corresponding pruning scheme, hierarchical cluster analysis was conducted for the 14 sweet cherry varieties that were mainly planted in Shanxi Province. The results showed that the 14 varieties of sweet cherry could be divided into two types, Hongmanao and Rainier. Fruit setting rate, branching rate, medium fruit shoot proportion, spur proportion and yield per plant were significantly different between these two types of sweet cherry. The key points of pruning management, to improve the yield of Rainier type, were to increase the fruit setting rate and spur proportion, and to control properly the long and medium fruit shoot proportion.
基金Supported by the National Natural Science Foundation of China(30860147)Open Funds of National Key Laboratory of Crop Genetic Improvement(ZK200902)Natural Science Foundation of Yunnan Province(2011FB117)~~
文摘[Objective] This study aimed to develop ACGM markers for the clustering analysis of large grained Brassica napus materials. [Method] A total of 44 pairs of ACGM primers were designed according to 18 genes related to Arabidopsis grain development and their homologous rape EST sequences. After electrophoresis, 18 pairs of ACGM primers were selected for the clustering analysis of 16 larger grained samples and four fine grained samples of rapeseed. [Result] PCR result showed that 2-6 specific bands were respectively amplified by each pair of primes, and all the bands were polymorphic and repeatable, suggesting that the optimized ACGM markers were useful for clustering analysis of B. napus species. Clustering analysis revealed that the 20 rapeseed samples were divided into three clusters A, B, and C at similarity coefficient 0.6. Then, the clusters A and B were further divided into five sub clusters A1, A2, A3, B1 and B2 at similarity coefficient 0.67. [Conclusion] This study will provide theoretical and practical values for rape breeding.
基金Supported by National Natural Science Foundation of China(30960179)Natural Science Foundation of Yunnan Province(2007A048M)~~
文摘[Objective] This research aimed to study the FTIR spectra of corn germs and endosperms so as to provide a scientific way for identifying corn of different types. [Method] The corn germs and endosperms of three types were studied by using Fourier transform infrared spectroscopy（FTIR） technology, combined with cluster analysis. [Result] The overall characteristics of original FTIR spectra were basically similar within the range of 700-1 800 cm^-1. The FTIR spectra were mainly composed by the absorption peaks of polysaccharides, proteins and lipids. Within the wavelength range of 700-1 800 cm^-1, there were only tiny differences in original FTIR spectra among the corn germs and endosperms of three different types. The spectra were then processed by using first derivative and second derivative. The second derivative spectra were used for hierarchical cluster analysis（HCA）. The results showed that with the wavelength range of 700-1 800 cm^-1, the second derivative spectra of the 52 samples could be better clustered according to the tree types and corn germ and corn endosperm. The clustering correct rate reached 96.1%.[Conclusion] FTIR technology, combined with cluster analysis, can be used to identify different types of corn germs and endosperms, and it is characterized by convenience and rapidness.
基金Supported by Fund of Sichuan Provincial Administration of traditional Chinese Medicine(2008-12)~~
文摘[Objective] This study aimed to investigate the trace elements in Rehman- nia glutinosa Libosch. by using principal component analysis and clustering analysis. [Method] Principal component analysis and clustering analysis of R. glutinosa medicinal materials from different sources were conducted with contents of six trace elements as indices. [Result] The principal component analysis could comprehen- sively evaluate the quality of R. glutinosa samples with objective results which was consistent with the results of clustering analysis. [Conclusion] Principal component analysis and clustering analysis methods can be used for the quality evaluation of Chinese medicinal materials with multiple indices.
