CORRESPONDENCE ANALYSIS ON IMAGES OF JIANGXI PROVINCE AS A TOURIST DESTINATION

This paper delineates the images of Jiangxi Province as tourist destination perceived by about 2000 sample visitors at Lushan Mountain and other 3 famous resorts (Jinggangshan Mountains, Longhushan Mountain, and Sanqingshan Mountain), with a result that the most common image is the famous scenic mountain image with partial attribute of image of religious culture destination. In order to reveal the similarities and dissimilarities of images among the four destinations, a correspondence analysis on 16 image attributes was employed. The results indicate that the tourists’ images on Longhushan Mountain, Sanqingshan Mountain and Lushan Mountain are very similar: having a lot of good tourist sites, famous mountain scenery, being close to nature and having good guide service, and others, but religious culture and good shopping facilities having not made deep impression on tourist, while Jinggangshan Mountains is famous for its red culture. The correspondence analysis visualizes the strengths and weaknesses of the destinations, which is useful for market positioning among the competitive places. Finally, some marketing suggestions for the four destinations were provided.

Study on the Characteristics of Urban Air Pollution Based on Correspondence Analysis--A Case Study of Six Provincial Capitals in Central-south China

[Objective] The aim was to study the characteristics of urban air pollution on the basis of correspondence analysis.[Method] By using the correlated data from China Statistical Yearbook in 2010,a correspondence analysis on the air pollution indicators(like respirable particles,SO2 and NO2) of six provincial capitals in central-south China was carried out by means of SPSS software,and the characteristics of air pollution in the cities of China during different industrialization stages were summarized further.[Result] In the cities during early industrialization(like Nanning City and Guiyang City) and mineral resource-based cities(like Taiyuan City),the air was mainly polluted by SO2;for the cities in the middle industrialization(such as Changsha City,Wuhan City,Zhengzhou City and Chengdu City),the air was polluted by respirable particles chiefly;in the cities in late industrialization(like Guangzhou City and Shenzhen City) or completing industrialization(like Shanghai City),the air was mainly polluted by NO2;for the cities in pre-industrial stage(like Haikou City and Lhasa City),the characteristic of air pollution wasn’t obvious.[Conclusion] The study could provide references for the control of urban air pollution in China in the further.

Usage as Complementary Correspondence Analysis and Logistic Regression in a Scientific Survey on Self Healing Methods

The aim of this study is to show complementary usage of logistic and correspondence analysis in a research subject to self-healing methodologies. Firstly, the number of the variables is reduced by logistic regression according to relationship between dependent and independent variables and then research carries on searching variables. The relationship among the behaviours of individuals and their demographic characteristics is modelled by logistic regression and shown graphically by correspondence analysis. In application, first of all, the effect of age, sex, marital status, education level, occupation and income level and present health condition, on appreciating self-health, is explained by a model. As a result of that model, it can be said that the effect of age, occupation and present health condition is reasonable. After analysing that model, the relationship between categorical variables (age, sex, occupation, preferred precautions, and worth of personal health) is shown graphically by multiple correspondence analysis.

Stock Pattern Mining and Correspondence Analysis Based on Association Rules

In this paper, association rules were applied to mining patterns in stock K-line trend. The pattern which ordinary investors interested in is defined as T-RG (Three-Red Guards). In the mining process, we take the K-line in A-share markets as objects. Through the analysis, investors can select the appropriate point of purchase and selling point. With the help of T-RG, investors can better improve the chance of short-term investment success in A-share markets. In order to explore and validate the T-RG, the main contents of this paper include the following aspects: putting forward a method that judge the validity of rules based on confidence-lift;proposing the meta rule that corresponds to the pattern of T-RG;developing a computer program to extract the T-RG using MATLAB, which supports batch mining;leading fundamental factors into correspondence analysis with identification indexes;reminding the selected stocks, so as to verify the reliability of the identification indexes. According to the above research, something can be learned: In A-share markets, the higher the discriminant index value is, the less number of shares meeting the requirements is;the same discriminant index value, the stock proportion has difference among plates. Confidence P1, P2 and Lift are extremely related to the GC (General Capital), and Lift is extremely related to the Ind (Industry). In the GEM, confidence P1 of mid-cap is near [0.7,1], Lift is near (1,3), confidence P1 of the manufacturing industry is near [0.7,1].

Correspondence Analysis on a Space-Time Data Set for Multiple Environmental Variables

Applications of the multivariate technique called correspondence analysis for environmental studies are relatively new and are limited to spatial multivariate data set. In this paper, a procedure of applying correspondence analysis to a large space-time data set for multiple environmental variables is shown. In particular, nitrogen dioxide and carbon monoxide hourly concentrations measured during January 1999 at several monitored stations in a district of Northern Italy are analyzed. The procedure consists in transforming the continuous variables into categorical ones by the means of appropriate indicator variables, generating special contingency tables and applying correspondence analysis. The use of this classical multivariate technique allows the identification of important relationships among pollution levels and monitoring stations and/or relationships among pollution levels and observation times.

Visualization of Special Features in “The Tale of Genji” by Text Mining and Correspondence Analysis with Clustering

In this paper, visualization of special features in “The Tale of Genji”, which is a typical Japanese classical literature, is studied by text mining the auxiliary verbs and examining the similarity in the sentence style by the correspondence analysis with clustering. The result shows that the text mining error in the number of auxiliary verbs can be as small as 15%. The extracted feature in this study supports the multiple authors of “The Tale of Genji”, which agrees well with the result by Murakami and Imanishi [1]. It is also found that extracted features are robust to the text mining error, which suggests that the classification error is less affected by the text mining error and the possible use of this technique for further statistical study in classical literatures.

Canonical Correspondence Analysis of Phytoplankton Community and Environmental Factors in Genhe River

To understand the status of phytoplankton community of the Genhe River in the summer of 2015,we investigated the phytoplankton in Genhe River. We identified 5 phyla and 36 species,among which Bacillariophyta(23) were the most,followed by Chlorophyta(10),Cyanophyta(1),Chrysophyta(1),Pyrrophyta(1). The phytoplankton abundance was(15. 6-810) × 104 ind·L^(-1); the biomass was(0. 07-2. 876) mg·L-1; Shannon-wiener index was 1. 05-3. 24; Pielou evenness index was 0. 27-0. 96. Using Shannon-wiener index and Pielou index,the water quality of Genhe River was assessed,and the results showed that the water quality was the best at 5# sampling point,the water quality was good in 3#,4#,7#,8#,9# sampling points,and there was a state of pollution at other sampling points. Canonical correspondence analysis and Pearson correlation analysis showed that iron ion,transparency,p H value,water depth and water temperature were important environmental factors that affect the distribution of phytoplankton,and copper ion,nitrite ion and COD also significantly affected the distribution of phytoplankton.

Elaboration of Explanatory Factors of Accidents in Cameroon by Factorial Correspondence Analysis

The aim of this paper is to examine the causes of road accidents in Cameroon. The Douala-Yaoundé highway was chosen as the case of study. Available field data recorded from the year 2006 to 2011, have enabled the analysis of each accident. The method used here is the factorial correspondence analysis;which aims to bring in a small number of dimensions, most of the initial information, focusing not on the absolute values, but the correspondence between the variables, that is to say the relative values. From this analysis, it appears that, of the 906 accidents recorded during this period, top five causes account for nearly 83% of the information provided by the set of variables on the occurrence of road accidents. These causes are: driver inattention, lack of control, over speeding, improper overtaking and tire puncture. These results require involvement in the construction of road safety policies through training, sensitization and adequate repressions as well as administrative reforms and research policy in road safety.

Applied research of correspondence analysis method in waste tailings reservoir heavy metal pollution monitoring points optimization

In order to optimize monitoring points and monitoring factor, the relationshipbetween pollutants and soil sample were established by correspondence analysis.Thestudy results show that the reflecting monitoring points and monitoring factors in thegraphic on the same factor axis can clearly express the intrinsic link between pollutantsand monitoring points and distribution characteristics.To determine the main monitoringpoint and the main monitoring indicators can reduce and optimize the number of monitoringpoints under the premise of ensuring the typical and representative of monitoring data.Using the correlation of pollutants can reduce the number of monitoring indicators and improvethe effectiveness of data collection.

Using Multiple Correspondence Analysis to Measure Multidimensional Poverty in Congo

The following analysis is based on a multidimensional understanding of poverty using a nonmonetary basic needs approach. It is ground on data from the first survey on household living conditions for poverty assessment, conducted by the National Institute of Statistics of Congo in 2005. Multiple Correspondence Analysis is applied to construct a composite indicator by aggregating several attributes likely to reflect the poverty of individuals or households. The application shows that Congolese households are not affected by the same type of poverty. Three types of non-monetary poverty are identified: infrastructure poverty, vulnerability of human existence and poverty of comfort. These households were then classified according to the composite indicator of Poverty. The results show that the incidence of poverty corresponds to the weight of poor class of about 70.67%.

Classification of subtypes of patients with eating disorders by correspondence analysis

BACKGROUND Grouping eating disorders(ED)patients into subtypes could help improve the establishment of more effective diagnostic and treatment strategies.AIM To identify clinically meaningful subgroups among subjects with ED using multiple correspondence analysis(MCA).METHODS A prospective cohort study was conducted of all outpatients diagnosed for an ED at an Eating Disorders Outpatient Clinic to characterize groups of patients with ED into subtypes according to sociodemographic and psychosocial impairment data,and to validate the results using several illustrative variables.In all,176(72.13%)patients completed five questionnaires(clinical impairment assessment,eating attitudes test-12,ED-short form health-related quality of life,metacognitions questionnaire,Penn State Worry Questionnaire)and sociodemographic data.ED patient groups were defined using MCA and cluster analysis.Results were validated using key outcomes of subtypes of ED.RESULTS Four ED subgroups were identified based on the sociodemographic and psychosocial impairment data.CONCLUSION ED patients were differentiated into well-defined outcome groups according to specific clusters of compensating behaviours.

Rules of Pesticide Use for Food Crop Diseases and Pests: A Concise Diagram Based on Correspondence Analysis

In order to ensure food security, the selection of pesticide must take into account the controlling effect and economy in the chemical control of food crop diseases and pests. Although China has registered a large number of pesticides and fungicides on food crops, traditional statistical methods cannot treat the complex relationships between crops, pests and diseases, as well as pesticides. To this end, the correspondence analysis was used to mine the data of pesticides being registered after January 1, 2010 for the prevention and control of pests and diseases on wheat, corn, and rice in China, in order to reveal the general rules of pesticide use for the prevention and control of grain crop pests and diseases and to provide scientifically recommended pesticide regimens.(1) Recommended pesticides for wheat diseases and pests: For underground pest control, phoxim, diazinon or clothianidin is recommended;imidacloprid is recommended for aphid control;avermectin is recommended for mite control;chlorpyrifos is recommended for midge control;the pesticides for rust control could be selected according to the order of epoxiconazole>flutriafol>kresoxim-methyl>cyproconazole≈hexaconazole;tebuconazole is recommended for the prevention and control of smut;difenoconazole is recommended for the simultaneous occurrence of take-all, smut and sheath blight;it is recommended to use carbendazim or thiophanate-methyl for the control of scab;and triazolone or pyraclostrobin is recommended for the control of powdery mildew.(2) Recommended pesticides for corn diseases and pests: For the control of underground pests, fipronil, carbosulfan or chlorpyrifos are recommended;thiamethoxam is recommended for control of planthoppers and corn aphids;Bacillus thuringiensis or phoxim is recommended for control of corn borers;pyraclostrobin is recommended for the control of northern leaf blight;tebuconazole is recommended for the control of head smut;and fludioxonil+metalaxyl-M is recommended for the control of corn stalk rot.(3) Recommended pesticides for rice diseases and pests: It is recommended to use triazophos, avermectin analogs or methoxyfenozide for the control of borers;for rice planthoppers, the pesticides could be selected in order of pymetrozine>imidacloprid>thiamethoxam>thiazide>nitenpyram;avermectin analogs are recommended for the control of rice leaf rollers;tebuconazole is recommended for the control of rice false smut;prochloraz and its manganese salts are recommended for the control of bakanae disease;hymexazol is recommended for the control of wilt disease;thifluzamide or hexaconazole is recommended for the control of sheath blight;and the pesticides for the control of rice blast are in order of tricyclazole>kasugamycin>fenoxanil>isoprothiolane>Bacillus subtilis. In addition, potential applications of correspondence analysis in other fields of plant protection are discussed.

Subset Multiple Correspondence Analysis as a Tool for Visualizing Affiliation Networks

In this paper we investigate the potential of Subset Multiple Correspondence Analysis (s-MCA), a variant of MCA, to visually explore two-mode networks. We discuss how s-MCA can be useful to focus the analysis on interesting subsets of events in an affiliation network while preserving the properties of the analysis of the complete network. This unique characteristic of the method is also particularly relevant to address the problem of missing data, where it can be used to partial out their influence and reveal the more substantive relational patterns. Similar to ordinary MCA, s- MCA can also alleviate the problem of overcrowded visualizations and can effectively identify associations between observed relational patterns and exogenous variables. All of these properties are illustrated on a student course-taking affiliation network.

Interpretation of Water Samples by Correspondence Analysis for Radioactive Elements in the Northern Coast of Oman Sea

Oman Sea is connecting belt between the Indian Ocean and Persian Gulf.Because it strategic and environmental aim,presence of natural radionuclide ^(226)Ra,^(232)Th,^(40)K and ^(137)Cs as man-made element is considered.Water samples were taken from 36 marine spots at the coastal strip from Hormoz canyon to Goatr seaport in the northern coast of Oman Sea.Correspondence analysis is used to identify variation and relationship between samples(Q-mood analysis)and variable(R-mood analysis)based on approximate χ^(2)distances.Radioactive elements(^(226)Ra,^(232)Th and^( 40)K),physical(temperature,pH,turbidity,conductivity,special density)and chemical(salinity,oxygen and chlorophyll)parameters of water for 36 samples handled by correspondence analysis,there are two outstanding result,(1)Radioactive elements show high correlation in factors by greater eigenvalue,and (2)some of the samples such as W13,W24 and rather W02,W05 and W12 show highest activity from Radioactive elements and also temperature and conductivity show nearest relation with them in many factors.

THE CORRESPONDING ANALYSIS OF HEAVY-METAL POLLUTION OF SOIL IN ZHUZHOU CITY

ＴＨＥ ＣＯＲＲＥＳＰＯＮＤＩＮＧ ＡＮＡＬＹＳＩＳ ＯＦ ＨＥＡＶＹ－ＭＥＴＡＬ ＰＯＬＬＵＴＩＯＮ ＯＦ ＳＯＩＬ ＩＮ ＺＨＵＺＨＯＵ ＣＩＴＹ ＳｈａｎｇＪｉｎｃｈｅｎｇ（尚金城）；ＬｏｎｇＡｉｍｉｎ（龙爱民）ＬｉＢｉｎ（李斌）；ＪｉａｎｇＪ...

Analysis on Chemical Compositions in Chinese Wolfberry from Different Producing Areas

[Objective] This study aimed to conduct correspondence cluster analysis of the trace elements in Chinese wolfberry from Qinghai and Ningxia regions, and to investigate the relationship among the quality of the wolfberry samples, the composition of trace elements and the sample sources. [Method] The determined contents of trace elements and ratios of zinc to copper （Zn/Cu） of wolfberry from 11 different producing areas of Qinghai and Ningxia regions were adopted to construct the raw measurement data matrix, to analyze the distribution characteristics of the trace ele- ments in wolfberry from Qinghai and Ningxia by using the corresponding cluster analysis method. [Result] The quality of wolfberry samples in 7hongning County, Zhongwei City, Pingluo County, Shizuishan City, Heicheng Town of Ningxia Hui Au-tonomous Region and Hehuang Valley, Golmud City of Qinghai Province is mainly related to the contents of Zn and Mn; Zn/Cu greatly affects the quality of Chinese wolfberry in Dulan County of Qinghai Province; Fe has great effect on the quality of Chinese wolfberry in Yinchuan City of Ningxia Hui Autonomous Region; Cu greatly affects the quality of Chinese wolfberry in Nuomuhong Village of Qinghai Province and a wolfberry research institute in Ningxia. [Conclusion] The relationship between the quality of wolfberry from different producing areas and the trace elements was investigated, which provides theoretical and practical basis for the cultivation, har- vesting, processing, and further development and utilization of Chinese wolfberry resources from different producing areas.

Analysis of Synonymous Codon Usage Bias in 09H1N1

A novel subtype of influenza A virus 09H1N1 has rapidly spread across the world. Evolutionary analyses of this virus have revealed that 09H1N1 is a triple reassortant of segments from swine, avian and human influenza viruses. In this study, we investigated factors shaping the codon usage bias of 09H1N1 and carried out cluster analysis of 60 strains of influenza A virus from different subtypes based on their codon usage bias. We discovered that more preferentially used codons of 09H1N1 are A-ended or U-ended, and the intra-genomic codon usage bias of 09H1N1 is quite low. Base composition constraint, dinucleotide biases and translational selection are the main factors influencing the codon usage bias of 09H1N1. At the genome level, we find that the codon usage bias of 09H1N1 is similar to H1N1 (A/swine/Kansas/77778/2007H1N1), H9N2 from Asia, H1N2 from Asia and North America and H3N2 from North America. Our results provide insight for understanding the processes governing evolution, regulation of gene expression, and revealing the evolution of 09H1N1.

A Unified Approach for the Multivariate Analysis of Contingency Tables

We present a unified approach to describing and linking several methods for representing categorical data in a contingency table. These methods include: correspondence analysis, Hellinger distance analysis, the log-ratio alternative, which is appropriate for compositional data, and the non-symmetrical correspondence analysis. We also present two solutions working with cummulative frequencies.

Association analysis datamining the compatibility regulations of Li Dong Yuan's formula of spleen and stomach

Analyzing systemically more than 550 Li Dong Y uan’s formula of spleen and stomach by using the association rule to mine the in formation relativity between formula, herbal medicine and syndrome.From this we can study better the compatibility regulations of the

Boundary Correspondence for Iso-Geometric Analysis Based on Deep Learning

One of the key problems in isogeometric analysis(IGA)is domain parameterization,i.e.,constructing a map between a parametric domain and a computational domain.As a preliminary step of domain parameterization,the mapping between the boundaries of the parametric domain and the computational domain should be established.The boundary correspondence strongly affects the quality of domain parameterization and thus subsequent numerical analysis.Currently,boundary correspondence is generally determined manually and only one approach based on optimal mass transport discusses automatic generation of boundary correspondence.In this article,we propose a deep neural network based approach to generate boundary correspondence for 2D simply connected computational domains.Given the boundary polygon of a planar computational domain,the main problem is to pick four corner vertices on the input boundary in order to subdivide the boundary into four segments which correspond to the four sides of the parametric domain.We synthesize a dataset with corner correspondence and train a fully convolutional network to predict the likelihood of each boundary vertex to be one of the corner vertices,and thus to locate four corner vertices with locally maximum likelihood.We evaluate our method on two types of datasets:MPEG-7 dataset and CAD model dataset.The experiment results demonstrate that our algorithm is faster by several orders of magnitude,and at the same time achieves smaller average angular distortion,more uniform area distortion and higher success rate,compared to the traditional optimization-based method.Furthermore,our neural network exhibits good generalization ability on new datasets.