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Open Journal of Statistics 2015年第2期5卷 127-139页

作者： Solaiman Afroughi Department of Biostatistics and Epidemiology Social Determinants of Health Research Centre Yasuj University of Medical Sciences Yasuj Iran

The analysis of spatially correlated binary data observed on lattices is an interesting topic that catches the attention of many scholars of different scientific fields like epidemiology, medicine, agriculture, biology, geology and geography. To overcome the encountered difficulties upon fitting the autologistic regression model to analyze such data via Bayesian and/or Markov chain Monte Carlo (MCMC) techniques, the Gaussian latent variable model has been enrolled in the methodology. Assuming a normal distribution for the latent random variable may not be realistic and wrong, normal assumptions might cause bias in parameter estimates and affect the accuracy of results and inferences. Thus, it entails more flexible prior distributions for the latent variable in the spatial models. A review of the recent literature in spatial statistics shows that there is an increasing tendency in presenting models that are involving skew distributions, especially skew-normal ones. In this study, a skew-normal latent variable modeling was developed in Bayesian analysis of the spatially correlated binary data that were acquired on uncorrelated lattices. The proposed methodology was applied in inspecting spatial dependency and related factors of tooth caries occurrences in a sample of students of Yasuj University of Medical Sciences, Yasuj, Iran. The results indicated that the skew-normal latent variable model had validity and it made a decent criterion that fitted caries data.

关键词： Spatial Data Latent Variable Autologistic Model Skew-Normal Distribution Bayesian inference Tooth Caries

Application of the Adaptive Neuro-Fuzzy inference System for Optimal Design of Reinforced Concrete Beams

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Journal of Intelligent Learning Systems and Applications 2014年第4期6卷 162-175页

作者： Jiin-Po Yeh Ren-Pei Yang Department of Civil and Ecological Engineering I-Shou University Kaohsiung Taiwan

Using a genetic algorithm owing to high nonlinearity of constraints, this paper first works on the optimal design of two-span continuous singly reinforced concrete beams. Given conditions are the span, dead and live loads, compressive strength of concrete and yield strength of steel;design variables are the width and effective depth of the continuous beam and steel ratios for positive and negative moments. The constraints are built based on the ACI Building Code by considering the strength requirements of shear and the maximum positive and negative moments, the development length of flexural reinforcement, and the serviceability requirement of deflection. The objective function is to minimize the total cost of steel and concrete. The optimal data found from the genetic algorithm are divided into three groups: the training set, the checking set and the testing set for the use of the adaptive neuro-fuzzy inference system (ANFIS). The input vector of ANFIS consists of the yield strength of steel, compressive strength of concrete, dead load, span, width and effective depth of the beam;its outputs are the minimum total cost and optimal steel ratios for positive and negative moments. To make ANFIS more efficient, the technique of Subtractive Clustering is applied to group the data to help streamline the fuzzy rules. Numerical results show that the performance of ANFIS is excellent, with correlation coefficients between the three targets and outputs of the testing data being greater than 0.99.

关键词： Continuous Reinforced Concrete Beams Genetic Algorithm Adaptive Neuro-Fuzzy inference System Correlation Coefficients

Segmentation and texture analysis with multimodel inference for the automatic detection of exudates in early diabetic retinopathy

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Journal of Biomedical Science and Engineering 2013年第3期6卷 298-307页

作者： Jack Lee Benny Zee Qing Li Division of Biostatistics JC School of Public Health and Primary Care The Chinese University of Hong Kong Hong Kong China

Diabetic retinopathy (DR) is an eye disease caused by the increase of insulin in blood and may cause blindness if not treated at an early stage. Exudates are the primary sign of DR. Currently there is no fully automated method to detect exudates in the literature and it would be useful in large scale screening if fully automatic method is available. In this paper we developed a novel method to detect exudates that based on interactions between texture analysis and segmentation with mathematical morphological technique by using multimodel inference. The texture analysis involves three components: they are statistical texture analysis, high order spectra analysis, and fractal analysis. The performance of the proposed method is assessed by the sensitivity, specificity and accuracy using the public data DIARETDB1. Our results show that the sensitivity, specificity and accuracy are 95.7%, 97.6% and 98.7% (SE = 0.01), respectively. It is shown that the proposed method can be run automatically and also improve the accuracy of exudates detection significantly over most of the previous methods.

关键词： Texture Analysis Multimodel inference Morphological Technique Exudates Diabetic Retinopathy

Fisher’s Fiducial inference for Parameters of Uniform Distribution

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Applied Mathematics 2013年第4期4卷 589-594页

作者： Kefa Wu Peiju Chang Yaolan Ma Tianxin Dong College of Information and Computation National University in the North Yinchuan China Office of Financial Affairs Xi’an Jiaotong University Xi’an China Society of Old Scientist & Technicians Xi’an Jiaotong University Xi’an China

Fisher’s Fiducial inference for the parameters of a totality uniformly distributed on [α, β] is discussed. The corresponding fiducial distributions are derived. The maximum fiducial estimators, fiducial median estimators and fiducial expect estimators of α and β are got. The problems about the fiducial interval, fiducial region and hypothesis testing are discussed. An example which showed that Neyman-Pearson’s confidence interval has some place to be improved is illustrated. An idea about deriving fiducial distribution is proposed.

关键词： Fiducial inference Uniformly Distribution Parameters Fiducial Interval Hypothesis Testing

Assessing Watershed Vulnerability in Bernalillo County, New Mexico Using GIS-Based Fuzzy inference

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Journal of Water Resource and Protection 2019年第2期11卷 99-121页

作者： Clinton P. Richardson Kofi Amankwatia Department of Civil and Environmental Engineering New Mexico Tech Socorro NM USA Application Systems Analyst City of Eugene Eugene

Watershed vulnerability was assessed for Bernalillo County, New Mexico using a multi-criteria Fuzzy inference System (FIS) implemented in a Geographic Information System (GIS). A vulnerability map was produced by means of a weighted overlay analysis that combined soil erosion and infiltration maps derived from the FIS methodology. Five vulnerability classes were stipulated in the model: not vulnerable (N), slightly vulnerable (SV), moderately vulnerable (MV), highly vulnerable (HV), and extremely vulnerable (EV). The results indicate that about 88% of the study area is susceptible to slight (SV) to moderate vulnerability (MV), with 11% of the area subject to experience high or extreme vulnerability (HV/EV). For land use and land cover (LULC) classifications, shrub land was identified to experience the most vulnerability. Weighted overlay output compared similarly with the results predicted by Revised Universal Soil Loss Equation (RUSLE) model with the exception of the not vulnerable (N) class. The eastern portion of the county was identified as most vulnerable due to its high slope and high precipitation. Herein, structural stormwater control measures (SCMs) may be viable for managing runoff and sediment transport offsite. This multi-criteria FIS/GIS approach can provide useful information to guide decision makers in selection of suitable structural and non-structural SCMs for the arid Southwest.

关键词： Stormwater Control Measures Fuzzy inference System Multi-Criteria Decision Support Systems Geographic Information System

Fuzzy Logic inference Applications in Road Traffic and Parking Space Management

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Journal of Software Engineering and Applications 2015年第7期8卷 339-345页

作者： Ahmed Tijjani Dahiru Department of Electrical/Electronics Technology School of Technical Education Federal College of Education (Technical) Bichi Kano Nigeria

In modern motoring, many factors are considered to realize driving convenience and achieving safety at a reasonable cost. A drive towards effective management of traffic and parking space allocation in urban centres using intelligent software applications is currently being developed and deployed as GPS enabled service to consumers in automobiles or smartphone applications for convenience, safety and economic benefits. Building a fuzzy logic inference for such applications may have numerous approaches such as algorithms in Pascal or C-languages and of course using an effective fuzzy logic toolbox. Referring to a case report based on IrisNet project analysis, in this paper Matlab fuzzy logic toolbox is used in developing an inference for managing traffic flow and parking allocation with generalized feature that is open for modification. Being that modifications can be done within any or all among the tool’s universe of discourse, increment in the number of membership functions and changing input and output variables etc, the work here is limited within changes at input and output variables and bases of universe of discourse. The process implications is shown as plotted by the toolbox in surface and rule views, implying that the inference is flexibly open for modifications to suit area of application within reasonable time frame no matter how complex. The travel time to the parking space being an output variable in the current inference is recommended to be substituted with distance to parking space as the former is believed to affect driving habits among motorist, whom may require the inference to as well cover other important locations such as nearest or cheapest gas station, hotels, hospitals etc.

关键词： Fuzzy Logic inference Universe of Discourse Membership Functions Parking Space Traffic Simulations Surface Views Rule Views

Empirical Likelihood inference for Generalized Partially Linear Models with Longitudinal Data

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Open Journal of Statistics 2020年第2期10卷 188-202页

作者： Jinghua Zhang Liugen Xue College of Applied Sciences Beijing University of Technology Beijing China Department of Information Engineering Jingdezhen Ceramic Institute Jiangxi China

In this article, we propose a generalized empirical likelihood inference for the parametric component in semiparametric generalized partially linear models with longitudinal data. Based on the extended score vector, a generalized empirical likelihood ratios function is defined, which integrates the within-cluster?correlation meanwhile avoids direct estimating the nuisance parameters in the correlation matrix. We show that the proposed statistics are asymptotically?Chi-squared under some suitable conditions, and hence it can be used to construct the confidence region of parameters. In addition, the maximum empirical likelihood estimates of parameters and the corresponding asymptotic normality are obtained. Simulation studies demonstrate the performance of the proposed method.

关键词： Longitudinal Data Generalized Partially Linear Models Empirical Likelihood Quadratic inference Function

Identification of inference Genes in Breast Cancer Network

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Journal of Biosciences and Medicines 2017年第9期5卷 29-42页

作者： Keilash Chirom Shahnawaz Ali Md. Zubbair Malik Romana Ishrat R. K. Brojen Singh School of Computational & Integrative Sciences Jawaharlal Nehru University New Delhi India Centre for Interdisciplinary Research in Basic Sciences Jamia Millia Islamia New Delhi India

Complex breast cancer network constructed from experimentally verified seventy genes, by coordinating standard seven human protein and genome databases, follows hierarchical scale free features. Centrality based method of identification of inferred genes is implemented to this network and has predicted forty nine breast cancer genes, and nineteen non-breast cancer genes. As predicting good candidate genes before experimental analysis will save time and effort both. Fourteen genes out of nineteen are found to involve in various types of cancer and diseases, and five genes are engaged in non-cancer diseases. Some of the inferred genes need proper experimental investigation to understand fundamental roles of these genes in regulating breast cancer network.

关键词： Breast Cancer Network Theory inference Genes Topological Propreties Centrality

Philosophical Research and General Education

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Frontiers of Philosophy in China 2013年第2期8卷 240-246页

作者： Jaakko Hintikka Department of Philosophy Boston University Boston MA 02215 USA

What can philosophical research do today to improve the lot of contemporary societies globally？ What can anyone do for the purpose？ To take the most urgent international problems as an example, what kind of person should the Secretary-General of the UN send to disarm a conflict situation？ Perhaps a religious leader, a priest, an imam or a guru？ But a leader of which religion？ Perhaps a lawyer？ But a lawyer is by definition some particular client＇s advocate. I submit that the best background of such a negotiator would be that of a labor arbitrator. Such a professional is trained to take into account the interest of different and conflicting parties. The success of a persuasive arbitrator presupposes a capacity to analyze objectively and realistically not only the professed goals of different parties, but the actual consequences of the realization of those goals. It presupposes objective knowledge of the consequences of different courses of action and the ability to explain them to the different parties. Above all, it presupposes a skill in finding possibilities of synthesizing apparently conflicting points of view.

关键词： Deductive reasoning Critical thinking Mathematical logic Thinking skills Epistemology inference Mathematics Educational philosophies

THE FEATURES OF A PARALLEL inference MACHINE EPIM

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Chinese Science Bulletin 1987年第23期32卷 1585-1589页

作者：谭小南张祥高庆狮 Institute of Computing Technology Academia Sinica Beijing

The paralld inference machine which supports the parallel execution of logic programs is one of the components forming the kernel of the fifth generation computer systems. The design of the architecture of parallel in... 详细信息

关键词： execution kernel locality processors inference programs overhead performing structured hardware