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GIS based Landslide Susceptibility Mapping of Tevankarai Ar Sub-watershed,Kodaikkanal,India using binary logistic regression Analysis

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Journal of Mountain Science 2011年第4期8卷 505-517页

作者： Sujatha E RAMANI Kumarvel PITCHAIMANI Victor Rajamanickam GNANAMANICKAM School of Civil Engineering SASTRA University Indian Institute of Astrophysics Sairam Group of Institutions West Tambaram ChennaiTamilnaduIndia

Landslide susceptibility mapping is the first step in regional hazard management as it helps to understand the spatial distribution of the probability of slope failure in an *** attempt is made to map the landslide susceptibility in Tevankarai Ar subwatershed,Kodaikkanal,India using binary logistic regression *** Information System is used to prepare the database of the predictor variables and landslide inventory map,which is used to build the spatial model of landslide *** model describes the relationship between the dependent variable(presence and absence of landslide) and the independent variables selected for study(predictor variables) by the best fitting function.A forward stepwise logistic regression model using maximum likelihood estimation is used in the regression *** inventory of 84 landslides and cells within a buffer distance of 10m around the landslide is used as the dependent ***,slope,aspect,plan curvature,profile curvature,land use,soil,topographic wetness index,proximity to roads and proximity to lineaments are taken as independent *** constant and the coefficient of the predictor variable retained by the regression model are used to calculate the probability of slope failure and analyze the effect of each predictor variable on landslide occurrence in thestudy *** model shows that the most significant parameter contributing to landslides is *** other significant parameters are profile curvature,soil,road,wetness index and *** predictive logistic regression model is validated using temporal validation data-set of known landslide locations and shows an accuracy of 85.29 %.

关键词： Landslide Susceptibility binary logistic regression GIS Kodaikkanal India

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A binary logistic regression model for discriminating real protein-protein interface

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Progress in Natural Science:Materials International 2003年第6期 14-20页

作者： LIN Wei, SUN Ping and LIU Xiangjun(Bioinformatics Laboratory, School of Medicine, Tsinghua University, Beijing 100084, China)

The selection and study of descriptive variables of protein-protein complex interface is a major question that many biologists come across when the research of protein-protein recognition is concerned. Several variables have been proposed to understand the structural or energetic features of complex interfaces. Here a systematic study of some of these "traditional" variables, as well as a few new ones, is introduced. With the values of these variables extracted from 42 PDB samples with real or false complex interfaces, a binary logistic regression analysis is performed, which results in an effective empirical model for the evaluation of binding probabilities of protein-protein interfaces. The model is validated with 12 samples, and satisfactory results are obtained for both the training and validation sets. Meanwhile, three potential dimeric interfaces of staphylokinase have been investigated and one with the best suitability to our model is proposed .

关键词： protein-protein recognition binary logistic regression interfacial descriptive variable.

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Residents'satisfaction of Beijing new regulations for domestic waste classification based on binary logistic regression:A case study of Daxing District

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Ecological Economy 2022年第3期18卷 190-204页

作者： GU Yue-qi HOU Xiao-yu LI Si-tong TIAN Li ZHOU Yan-fang Sustainable Developing Center of Tourism Beijing Institute of Petrochemical TechnologyBeijing 102617CHINA

On the first anniversary of the implementation of the new regulations of Beijing Municipality on the management of domestic waste,to understand residents’views on the waste classification policy,the project conducted relevant investigation of the satisfaction of residents with the domestic waste classification policy in Daxing District of Beijing,*** on the analysis of the survey,this study uses the binary logistic regression model to explore the residents’satisfaction with the new domestic waste classification policy in Beijing and its influencing *** data from 398 valid questionnaires involve the demographic characteristics of residents,residents’cognition and views on Beijing municipal solid waste classification policy,and residents’satisfaction with Beijing domestic waste classification *** data show that the comprehensive satisfaction level of residents with the domestic waste classification policy in Beijing is quite high,up to 84.7%.Among them,the satisfaction level of residents with the details of the classification standards,the allocation of garbage cans,the publicity and supervision of the policy,incentive measures and the implementation process and effect of the policy is very high,exceeding 80%or even more than 90%.Through binary logistic regression analysis,we come to the conclusion that six factors significantly affect residents’satisfaction with Beijing municipal solid waste classification policy,such as residents’monthly income,household daily average domestic waste production,publicity of waste classification policy,supervisors’better understanding of waste classification standards,guidance of waste delivery by community classification supervisors,and convenience of waste classification process.

关键词： domestic waste classification policy residents’satisfaction binary logistic regression influencing factors

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Selection for high quality pepper seeds by machine vision and classifiers

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Journal of Integrative Agriculture 2018年第9期17卷 1999-2006页

作者： TU Ke-ling LI Lin-juan YANG Li-ming WANG Jian-hua SUN Qun Key Laboratory of Crop Genetic Improvement Department of Plant Genetics and Breeding College of Agriculture and Biotechnology China Agricultural University College of Science China Agricultural University

This research aimed to improve selection of pepper seeds for separating high-quality seeds from low-quality seeds. Past research has shown that seed vigor is significantly related to the seed color and size, thus several physical features were identified as candidate predictors of high seed quality. Image recognition software was used to automate recognition of seed feature quality using 400 kernels of pepper cultivar 101. In addition, binary logistic regression and a neural network were applied to determine models with high predictive value of seed germination. Single-kernel germination tests were conducted to validate the predictive value of the identified features. The best predictors of seed vigor were determined by the highest correlation observed between the physical features and the subsequent fresh weight of seedlings that germinated from the 400 seeds. Correlation analysis showed that fresh weight was significantly positively correlated with eight physical features： three color features （R, a＊, brightness）, width, length, projected area, and single-kernel density, and weight. In contrast, fresh weight significantly negatively correlated with the feature of hue. In analyses of two of the highest correlating single features,＇ germination percentage increased from 59.3 to 71.8% when a＊〉3, and selection rate peaked at 57.8%. Germination percentage increased from 59.3 to 79.4%, and the selection rate reached 76.8%, when single-kernel weight 〉0.0064 g. The most effective model was based on a multilayer perceptron （MLP） neural network, consisting of 15 physical traits as variables, and a stability calculated as 99.4%. Germination percentage in a calibration set of seeds was 79.1% and the selection rate was 90.0%. These results indicated that the model was effective in predicting seed germination based on physical features and could be used as a guide for quality control in seed selection. Automated systems based on machine vision and model classifiers can contribu

关键词： pepper seed image processing machine vision seed vigor binary logistic regression multilayer perceptron neural network

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Evaluation of Inference Adequacy in Cumulative logistic regression Models:An Empirical Validation of ISW-Ridge Relationships

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China Ocean Engineering 2008年第1期22卷 43-56页

作者： Cheng-Wu CHEN Hsien-Chueh Peter YANG Chen-Yuan CHEN Alex Kung-Hsiung CHANG Tsung-Hao CHEN Department of logistics Management Shu-Te University Kaohsiung 82445 China Department of Risk Management and Insurance National Knohsiung First Univershy of Scierwe and Technology Kaohsiung 811 China Department of Management Information System Yung- Ta Institute of Technology and Commerce Pingtung County 90941 China Department of Business Administration National Pingtung University of Science and Technology Pingtung China Department of Business Adrninistration MingDao University ChangHua 52345 China

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p 〈0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to cheek the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height （X1 ） and potential energy （X2 ） significantly impact （p 〈 0. 0001 ） the amplitude-based refleeted rate; the P-values for the deviance and Pearson are all 〉 0.05 （0.2839, 0.3438, respectively）. That is, the goodness-of-fit between ridge height （ X1 ） and potential energy （X2） can further predict parameters under the scenario of the best parsimonious model. Investigation of 6 predictive powers （ R2, Max-rescaled R^2, Sorners＇ D, Gamma, Tau-a, and c, respectively） indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.

关键词： binary logistic regression cumulative logistic regression model goodness-of-fit internal solitary wave amplitude-based transmission rate

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A Time-dependent Stochastic Grassland Fire Ignition Probability Model for Hulun Buir Grassland of China

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Chinese Geographical Science 2013年第4期23卷 445-459页

作者： GUO Zhixing FANG Weihua TAN Jun SHI Xianwu Academy of Disaster Reduction and Emergency Management Ministry of Civil Affairs & Ministry of Education National Marine Hazard Mitigation Service State Oceanic Administration State Key Laboratory of Earth Surface Processes and Resource Ecology Key Laboratory of Environmental Change and Natural Disaster Ministry of Education

Grassland fire is one of the most important disturbance factors in the natural *** paper focuses on the spatial distribution of long-term grassland fire patterns in the Hulun Buir Grassland located in the northeast of Inner Mongolia Autonomous Region in *** density or ratio of ignition can reflect the relationship between grassland fire and different ignition *** on the relationship between the density or ratio of ignition in different range of each ignition factor and grassland fire events,an ignition probability model was developed by using binary logistic regression function and its overall accuracy averaged up to 81.7%.Meanwhile it was found that daily relative humidity,daily temperature,elevation,vegetation type,distance to county-level road,distance to town are more important determinants of spatial distribution of fire *** Monte Carlo method,we developed a time-dependent stochastic ignition probability model based on the distribution of inter-annual daily relative humidity and daily *** this model,it is possible to estimate the spatial patterns of ignition probability for grassland fire,which will be helpful to the quantitative evaluation of grassland fire risk and its management in the future.

关键词： grassland fire binary logistic regression GIS spatial analysis ignition probability Monte Carlo method

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Association between people’s attitudes towards human-elephant conflict and their locational,demographic,and socio-economic characteristics in Buxa Tiger Reserve and its adjoining area,India

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Regional Sustainability 2024年第1期5卷 11-25页

作者： Chiranjib NAD Tamal BASU-ROY Department of Geography Raiganj UniversityRaiganj733134India

“Human-elephant conflict(HEC)”,the alarming issue,in present day context has attracted the attention of environmentalists and policy *** rising conflict between human beings and wild elephants is common in Buxa Tiger Reserve(BTR)and its adjoining area in West Bengal State,India,making the area ***’s attitudes towards elephant conservation activity are very crucial to get rid of HEC,because people’s proximity with wild elephants’habitat can trigger the occurrence of *** aim of this study is to conduct an in-depth investigation about the association of people’s attitudes towards HEC with their locational,demographic,and socio-economic characteristics in BTR and its adjoining area by using Pearson’s bivariate chi-square test and binary logistic regression *** is one of the constituent parts of Eastern Doors Elephant Reserve(EDER).We interviewed 500 respondents to understand their perceptions to HEC and investigated their locational,demographic,and socio-economic characteristics including location of village,gender,age,ethnicity,religion,caste,poverty level,education level,primary occupation,secondary occupation,household type,and source of *** results indicate that respondents who are living in enclave forest villages(EFVs),peripheral forest villages(PFVs),corridor village(CVs),or forest and corridor villages(FCVs),mainly males,at the age of 18–48 years old,engaged with agriculture occupation,and living in kancha and mixed houses,have more likelihood to witness ***,respondents who are illiterate or at primary education level are more likely to regard elephant as a main problematic animal around their villages and refuse to participate in elephant conservation *** the sake of a sustainable environment for both human beings and wildlife,people’s attitudes towards elephants must be friendly in a more prudent way,so that the two communities can live in harmony.

关键词： Human-elephant conflict Elephant conservation Chi-square test statistics binary logistic regression Demographic and socioeconomic characteristics Buxa Tiger Reserve

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Households’ Willingness-to-Pay to Reduce the Use of Plastic Bags: Case Study in Viet Nam

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Journal of Environmental Protection 2022年第3期13卷 289-298页

作者： Nguyen Van Song Nguyen Minh Hieu Vu Ngoc Huyen Nguyen Dang Que Nguyen Van Huong Bui Thi Minh Nguyet Viet Nam National University of Agriculture (VNUA) Ha Noi Viet Nam National Academy of Public Administration (NAPA) Ha Noi Viet Nam Hung Yen University of Technology and Education (UTEHY) Hung Yen Viet Nam Vietnam National University of Forestry Xuan Mai Ha Noi Vietnam

This study used the binary logistic regression model to estimate the willingness to pay (WTP) to reduce the use of plastic bags in the daily life of people in the Linh Nam ward. This study notes that households with higher incomes and higher levels of education tend to be more willing to pay. In addition, those who do not have access to information about the harmful effects of plastic bags and receive a higher proposed price often refuse to pay.

关键词： binary logistic regression Willingness to Pay Plastic Bags

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Sustainable House Principle in Affordable House

Sustainable House Principle in Affordable House

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2012 International Conference on Innovation,Trade and Economics(ICITE 2012)

作者： Norazmawati Md. Sani Abd. Rahim Muhammad Arkam Che Munaaim Universiti Sains Malaysia

Sustainable housing must not excluded low income *** affordability is an important matter in the housing market to ensure that each group such as high-income,middle income or lower income group are afford to own a ***,a home provided benefits for individuals,government and *** objective of this research is to examine the sustainable housing principle in affordable house and to examine attracted factors that affected low income people to own a *** sample for this research comprises individuals who own a low-cost house at *** double sampling technique was utilized to generate this *** research utilizes binary logistic regression as its analytical *** findings indicate that Malaysia have applied the principle of sustainable house in housing affordability for low income *** main attracted factors that affected low income people to own a house include household income,household expenditures,type of occupation,education level,working household members and monthly payment for housing.

关键词： Sustainable housing Housing affordability Low income people binary logistic regression

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Combination usage of tumor markers and cytokines improve the differential diagnosis of cervical diseases

Combination usage of tumor markers and cytokines improve the...

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2012全国临床微生物与感染免疫学术研讨会

作者： Li Juan,Tong Hongli,Tian Yaping Department of Clinical Biochemistry,Chinese PLA General Hospital

Background Cytokines are involved in the development of cancer and may be useful to diagnoze cervical diseases as *** analyzed pretreatment serum levels of 10 cytokines in patients with cervical diseases. Methods We investigated serum levels of 10 cytokines in 77 cervical cancer,61 CIN and 84 healthy subjects by Luminex *** classical tumor markers,such as squamous cell carcinoma(SCC) antigen,carbohydrate antigen 125(CA125) and cytokeratin 19 fragment antigen 21-1(CYFRA21-1) were also detected in our study. Results Serum levels of interleukin-8 and monocyte chemoattractant protein 1(MCP-1) were both significantly higher in cervical diseases patients(CIN and cervical cancer patients) than in healthy control(PSerum IL-6 and IL-10 concentrations were significantly elevated from healthy control group to CIN group and cervical cancer group(Pbinary logistic regression yield AUC of 0.939(95%CI:0.909-0.969) in multi-parameter *** discriminated cervical cancer from CIN patients,cytokines didn’t show better diagnosis value in single parameter *** analysis of classification and regression tree built a model in which SCC and IL-10 were *** model had significantly improved the diagnosis value. Conclusions Serum levels of IL-6,IL-8 and IL-10 could have great promising to help assist diagnosing cervical diseases in combined usage of tumor markers.

关键词： Cervical cancer Cervical intraepithelial neoplasm Cytokine Classification and regression tree(CART) binary logistic regression

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