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The processing parameters directly affect the polishing quality of planar optics in chemical mechanical polishing (CMP). In this paper, a novel multiparameter optimization method based on the fuzzy theory was proposed to evaluate the manufacturing efficiency and accuracy of flat optical elements with CMP. The evaluation criteria and optimized parameters for CMP optimization were selected. The optimized objective function—combined fuzzy index of CMP (CFICMP)—was introduced to combine different criteria. A L9(34) orthogonal experimental design was implemented to improve the efficiency of experiments and analyze the effect of three parameters (polishing pressure, rotational speed of polishing pad, and slurry flow rate) on CMP. A half-normal distribution was applied to fit the trend of CFICMP. To verify the validity and feasibility of CFICMP, the material removal rate and the material removal uniformity were set as the optimized functions in verification experiments. The experimental results demonstrated that the optimal parameters of CFICMP could achieve better manufacturing efficiency and accuracy of planar optics simultaneously. The proposed method provides a feasible and effective way to select optimized processing parameters for CMP.

In order to analyse the currency crises in Turkey over the period of January 1990 and October 2019, we first dated currency crises with meta-possibilistic fuzzy index functions. Then, we determined the significant predictors or leading indicators of currency crisis with logistic regression. Finally, we tried to measure and compare the in-sample and out-of-sample performances of our method with an index generated by principal component analysis (PCA). We found that the models using the currency crisis index generated by our method have higher in-sample and out-of-sample performances than the models using the currency crisis index generated by PCA. We concluded that the change in real exchange rate, bank loans over bank deposits, bank reserves over bank assets, growth in foreign reserves, growth in central bank foreign assets, M2 over foreign assets, change in exports, change in imports, industrial production index, M1 growth, M2 growth, foreign reserves over M1, central bank foreign assets over M1 and public sector credit growth are the leading indicators of currency crisis among 20 explanatory variables. As policy implications, we recommend that government and the monetary authority should strictly monitor the ratio of bank loans over bank deposits, public sector credit growth, the volatility of foreign trade, ratio of foreign reserves and central bank foreign assets over money supply among significant explanatory variables to avoid currency crisis as policy implications.

The phenomenon of drought has a lot of damage every year in different parts of human life. The drought is not specific to the region, and it affects different parts of the world. One of these areas is Northwest of Iran, which suffered from this phenomenon in recent years. The purpose of this study is to model, analyze, and predict the drought in Northwest of Iran. To do this, climatic parameters (precipitation, temperature, sunshine, minimum relative humidity, and wind speed) of 21 stations were used in the period of 32 years (1987–2018). For modeling of the TIBI fuzzy index, first, four indicators (SET, SPI, SEB, and MCZI) were been fuzzy in MATLAB software. Then, the indices were compared and the Topsis model was used for prioritizing areas involved with drought. Results showed that the new fuzzy index of T.I.B.I. for classifying drought reflected four above indicators with high accuracy. Of these five climatic parameters used in this study, the temperature parameter had the most effect on the fluctuation of drought severity. The severity of the drought was more based on a 12-month scale modeling than 6 months. The longest drought persistence in the study area occurred in Urmia Station in the 12-month period from July 2003 to December 2004. The highest percentage of drought occurrence was at Urmia station on a 12-month scale and the lowest was in Sanandaj station on a 6-month scale.

This paper introduces an intelligent index that numerically assesses high-heeled gait deviations. Experiments were conducted on 14 young female volunteers, and the spatial-temporal gait parameters were calculated at each heel height. A type-2 fuzzy system index was built using the baseline case (barefoot). The index showed sensitivity to heel height changes. Moreover, its values divided the heel heights used in this study into three groups, depending on their effect on the gait parameters. A high correlation between the proposed index and the gait profile score (GPS) was found, this supports the index validity to evaluate different human gait deviations.

Drought is one of the natural hazards that has hit Iran over the past decades with serious environmental hazards, including those in southern parts of Iran. Researches done in the southern region of Iran in the field of statistical modeling of drought are rare. Therefore, the aim of this study is to fuzzify the SMS index, modeling and forecasting droughts in the southern part of Iran. For this study, 29-year-old temperature and precipitation data were used in 28 synoptic stations in the southern part of Iran during the period 1908–2018. In this study, three drought indexes SPI, MCZI, SET were separately calculated and combined and the fuzzy index SMS was obtained. Then, in ANFIS and RBF neural network models were compared and modelled in MATLAB software and simulated for the next 16 years, and finally, using the TOPSIS multivariate decision-making model, the drought-affected areas for the coming years, 16 next years, they were prioritized. The findings of the study showed that the new fuzzy index of the three indicators reflected drought with acceptable accuracy. In assessing the two models of ANFIS and RBF, the RBF model with a RMSE value of 1.15 and R2 values of 0.9161 have the highest accuracy than the ANFIS model for prediction. According to the SMS fuzzy index, stations such as Kerman, Yasuj and Abadan with drought of 0.69, 0.97, and 0.89, respectively were exposed more to future drought. Also, based on Topsis model, central and northern stations such as Koohrang and Safashahr with drought of 0.19 and 0.21, respectively, were subjected lower to drought in the following years.

In this chapter, we used fuzzy entropy input–output model and DEMATEL method for analysis of intersectoral relation. As a result, we built fuzzy index of diversification level. Thus, by using fuzzy methods, the level of diversification of national economy of Azerbaijan Republic was defined.

Measuring and comparing levels of violence against women across individuals or countries are controversial exercises, and yet they remain essential to understanding the phenomenon. We develop a scale of severity of violence against women based on fuzzy set theory. The scale can be used to derive fuzzy indexes of violence which account for the prevalence, frequency and severity of violence. Unlike existing alternatives, however, the scale that we propose is based on objective information rather than subjective assessment; it is parsimonious in terms of the amount of information that it requires; and it is less vulnerable to risks of cultural bias. We exploit our scale to unravel a puzzle which arises from the largest survey of violence against women in Europe to date, namely that some of the more gender equal countries record higher prevalence rates for violence from intimate partners. We show that the puzzle is resolved once violence is weighted by severity using our scale instead of being measured by simple prevalence.

Sequence alignment is one of the most important problems in bioinformatics. However, the existing alignment tools may result in a large number of candidate locations which degradate alignment performance. Recent researches discard the high repetitive seeds for improving the alignment speed, which influences alignment accuracy. To this end, we propose a novel fuzzy index ( $fBWT$ ), which is available at https://github.com/weiquan/appr_bwt. It allows approximate search and extending the length of seeds to reduce the candidate locations and accelerate the sequence alignment. The performance of our tool was compared with BWA using 150bp and 250bp length datasets. The result shows the number of misaligned reads (the correct position is not included in the high-score candidate position set) of the current mainstream tool is 5-10 times higher than it. The efficiency between the presented and the existing tools are also compared. Under the above conditions, the alignment time of the presented tool is very close. However, the alignment speed of $fBWT$ is much faster than BWA under the requirement of similar alignment accuracy.

There are great interests of designing research metrics and indices to measure the research impacts in research institutes. Unfortunately, most of those indices ignore critical design issues, e.g. ...

espanolEste trabajo tuvo como objetivo desarrollar y evaluar un modelo matematico computacional, con base en la teoria de los conjuntos fuzzy, para predecir el confort termico a partir del comportamiento de lechones, en funcion de su edad y del indice de temperatura de globo y humedad, en dos tipologias de instalacion de preceba. La instalacion 1 estaba compuesta por corrales de mamposteria y piso de malla metalica, y la instalacion 2 tenia corrales construidos con tablilla de madera y piso en malla plastica. La instalacion 2 presento una mayor frecuencia comportamental en la condicion de confort que la instalacion 1, con 39,32% y 38,16% respectivamente. Los valores da tasa de confort termico estimados por el sistema fuzzy presentaron una desviacion estandar media de 3,58% y coeficiente de determinacion de 72,86%. El modelo fuzzy desarrollado mostro ser adecuado para la prediccion de la tasa de confort termico a partir del comportamiento de los animales. EnglishThis work aims to develop and test a computational mathematical model, based on the fuzzy set theory, to predict the rate of thermal comfort by means of the swine behavior in relation to their age and to the black globe humidity index for two nursery types. Nursery1 had brick stalls with fully slatted metal flooring, and nursery 2 had woodenstalls with fully slatted plastic flooring. Nursery style 2 presented a higher frequency of behavior in the condition comfort than nursery style 1, respectively 39,32% and 38,16%. The thermal comfort values for the fuzzysystem were 3,58% for the standarddeviation and 72,86% for the coefficient of determination. The developed fuzzymodel has proven adequate in predicting thermal comfort by means of the animal's behavior.

Resumo: O objetivo deste estudo é investigar e mensurar a intensidade da pobreza rural multidimensional por meio dos conjuntos Fuzzy, tendo como recorte geográfico as mesorregiões norte e Jequitinhonha do estado de Minas Gerais e seus agricultores familiares como público-alvo. A metodologia fundamenta-se na construção do Índice Fuzzy de Pobreza Rural multidimensional e no cálculo dos pesos de cada dimensão. Quanto aos resultados, estes se alinham com o que Amartya Sen defende na Abordagem das Capacitações, pois, apesar de a dimensão referente a renda e trabalho ter apresentado o maior peso na mensuração da pobreza, fatores como educação e saúde também merecem atenção devido à maior intensidade apresentada. Portanto, este segmento deveria ser assistido por políticas estruturantes com melhorias constantes na educação, na saúde e na infraestrutura, de modo a atender as particularidades de cada localidade, de acordo com as verdadeiras privações sofridas pelos agricultores familiares.

The aim of this paper is to investigate the potential of fuzzy regression methods for computing a measure of skewness for the market. A quadratic version of the Ishibuchi and Nii hybrid fuzzy regression method is used to estimate the third order moment. The obtained fuzzy estimates are compared with the one provided by standard market practice. The proposed approach allows us to cope with the limited availability of data and to use all the information that is present in the market.

The drought phenomenon is not specific to the region and it affects different parts of the world. One of these areas is Iran in Southwest Asia, which suffered from this phenomenon in recent years. The purpose of this study is to model, analyze and predict the drought in Iran. To do this, climatic parameters (precipitation, temperature, sunshine, minimum relative humidity and wind speed) were used at 30 stations in the period of 29 years (1990-2018). For modeling of TIBI fuzzy index, first, four indicators (SET, SPI, SEB, MCZI) were fuzzy in Matlab software. Then the indices were compared and Topsis model were used for prioritizing areas involved with drought. Finally, Anfis adaptive artificial neural network model was used to predict. Results showed that the new fuzzy index TIBI for classifying drought reflected four of the above indicators with high accuracy. Among these five climatic parameters used in this study, the temperature and precipitation parameters had the most influential effect on the fluctuation of drought severity. The severity of drought was more based on a 6-month scale modeling than 12 months. The highest percentage of drought occurrence was at Bandar Abbas station with a value of 24.3 on a 12-month scale and the lowest was in Shahrekord station with a percentage of 0.36% on a six-month scale. Based on Anfis model and TIBI fuzzy index, Bandar Abbas, Bushehr and Zahedan stations were more exposed to drought due to the TIBI index of 0.62, 0.96 and 0.97, respectively. According to the results in both 6 and 12 months scale, the southern regions of Iran were more severely affected by drought, which requires suitable water management in these areas.

Composite indicators should ideally identify multidimensional concepts that cannot be captured by a single variable. In this paper, we suggest a method based on fuzzy set theory for the construction of fuzzy synthetic indexes of dyslexia, using the set of manifest variables measured by means of reading tests. A few criteria for assigning values to the membership function are discussed, as well as criteria for defining the weights of the variables. An application regarding the diagnosis of dyslexia in primary and middle school in Italy is presented. In this application, the fuzzy approach is compared with the crisp approach actually used in Italy for detecting dyslexic children in compulsory school.

Floodwater spreading (FWS) is an important multi-objective technology in soil–water resources management, particularly to utilize excess runoff. More than 37 such schemes have been implemented in Iran. To measure the success of FWS projects, the factors influencing their performance is a prerequisite. Experienced professionals were asked to participate in a poll to identify the key factors that govern project success; a total of 50 researchers ultimately participated in the study. Seven factors were identified as key success factors governing the effectiveness of FWS in Iran. Fuzzy logic formalism was used to determine the success of FWS projects by integrating the factors into a single number that demonstrates the overall degree of success. Evaluation of the developed fuzzy index showed that the Tasuj FWS performed better than the other FWS projects investigated in 2009.

A mono-feature fuzzy index that evaluates the stress level from one feature extracted from ECG or GSR is presented. It is build using several measures of the feature recorded when the subject is at rest. The mono-feature fuzzy index can be merged in a multi-feature stress index without any tuning. It can be used to select relevant features and to detect stress. The performance of the stress index is analyzed on a data set made of 160 time periods of time when 20 subjects had to perform stressful tasks and corresponding control tasks. The stress was induced by 4 different tasks. The performances reached are 72% of correctly classified time periods in stress and no stress situations. Interesting conclusions could also be made on the tasks ability to induce stress.

To facilitate uncertain internet opinion emergency decision involved with multiple fuzzy index values, we de- sign a new prewarning decision system mechanism for uncertain internet opinion emergency based on case reasoning and grey relational analysis. Through the invented software in recent patents in data mining areas we first collect the internet opinion and detect the emergency data. Then by calculating the comprehensive grey relational coefficient between the un- known internet opinion emergency and each source emergency case, we can easily retrieve the optimal historical case for current emergency problem. And the related emergency managers may adopt or modify the corresponding warning deci- sion solution of the most matched source case to make urgent decision for the new occurred internet public opinion emer- gency with uncertain indexes and incomplete weight information.

Design evaluation is necessary and important for conceptual design because it is often a must for designers to select a design concept from a number of candidates for further development. Assembly devices are usually product specific and there need extensive efforts in developing a feasible conceptual design solution satisfying a number of design constraints. To get a suitable evaluation method for assembly devices in the conceptual design phase, it’s necessary to apply Fuzzy mathematics in the evaluation method and the corresponding algorithm. This paper proposes a fuzzy index evaluation method for the conceptual design of assembly devices, where a number of evaluation indexes specific for assembly devices are proposed and organized into various levels for the evaluation algorithm. Finally, an evaluation software platform is presented, together with a simple design case study to illustrate the application of the proposed evaluation methodology.

Breast Cancer involves the uncontrolled growth of abnormal cells that have mutated from normal tissues. A radiologist looks for certain signs and characteristics indicative of cancer when evaluating a mammogram. The main task is to obtain the locations of suspicious regions to assist radiologists in diagnosis. Image segmentation has been approached from a wide variety of perspectives: region-based approach, morphological operation, multi-scale analysis, fuzzy approaches and stochastic approaches have been used for mammogram image segmentation but with some limitations. In spite of the several methods available in the literature, image segmentation still a challenging problem in most of image processing applications. The challenge comes from the fuzziness of image objects and the overlapping of the different regions. In this paper we propose fast auto adaptive image segmentation algorithm for finding the optimal thresholds for segmenting gray scale images. The proposed method is based on fuzzy index which decreases the similarity between pixels increases. The system uses initial estimation of the parameters. The fuzzy subsets derived from the image histogram using weighted fuzzy entropy will shows the similar cost measure as in pixels of the same subset. Experimental results demonstrate the effectiveness of the proposed approach.

Support vector machine (SVM), a machine learning algorithm used extensively for pattern analysis and recognition, is found sensitive to outliers and noise. Fuzzy support vector machine (FSVM) has been used in many applications as a most prominent technique by researchers to overcome the sensitivity issue faced by SVM, and for its good generalisation performance. In this research, a method to justify the performance of FSVM classifier by showing the influence of fuzzy index m on membership function of the model has been proposed. In the first phase of the study, an algorithm to find the optimal fuzzy index using fuzzy C-means (FCM) and to avoid testing all fuzzy index values on the FSVM model has been proposed. The operational complexity of the model can be reduced by this process. In the second phase of this study a FSVM algorithm to incorporate new membership function is proposed. The model is tested on six different datasets and kernel functions and the kernel with the highest classification accuracy is identified as an efficient kernel for the applied dataset. The experimental results on the chosen fuzzy index have proven that the proposed alternate methodology enhances classifier accuracy compared to other research findings. Hence, the model could be applied to diverse fields of FSVM applications.

The paper presents a new approach to assessment of the power system security. Using fuzzy membership functions of power system elements, it continuously quantifies the security state of a power system, as opposed to conventional methods which use off-line screening for the most vulnerable system states. It introduces global fuzzy security index (GFSI) of the power system using system's variables characterized by fuzzy sets of a trapezoidal form. GFSI is calculated by multiplying the security membership grade (SMG) values of the power system's segments that exhibit the lowest SMG values. The power system security levels are traced continually through time using real data of power flow and state estimation calculations as well as measurements of variables inaccessible by the load flow analysis. The GFSI enables the system operator to identify the insecure state and then continuously monitor the distance of the power system's actual state and the insecure one. Application of the algorithm is illustrated using the data of Bosnian power system. Copyright © 2009 John Wiley & Sons, Ltd.

Nighttime driving behavior differs from that during the day because of differences in the driver's field of view. At night, drivers must rely on their vehicle headlamps to illuminate the roadway. It is essential then that the roadway delineation system provide the appropriate lane guidance to motorists when navigating a roadway, particularly one that is curvilinear. A nighttime driving experiment was conducted to collect user perception data of various pavement markings and markers applied to horizontal curves. The effectiveness of each pavement marking was rated using a subjective scale. A fuzzy inference system was used to analyze the subjective pavement marking and marker evaluation ratings provided by the research participants. Pavement marking effectiveness, horizontal curve sharpness, and driver age were used to develop a fuzzy index for nighttime driving condition (FIND). Based on the FIND, the results indicate that drivers prefer that a combination of treatments be applied to horizontal curves rather than only a single treatment. A bright centerline, bright edgeline, and bright retroreflective raised pavement maker combination treatment, and a bright centerline and bright edgeline combination treatment, resulted in the highest FIND score. A bright, 8-in. (20.3 cm) edgeline, applied alone to a horizontal curve, scored the lowest FIND.

Quality assessment can be performed with natural language (in descriptive form) or with numbers (in quantitative form). Such approach enables consideration of all the aspects and characteristics beyond quantification, difficult or impossible to assess with numbers, hence requiring linguistic representation. Application of fuzzy index to work conditions quality assessment provides objective identification of hazards and their influence on work conditions quality.

A hierarchical fuzzy index is proposed for comparing product and process toxicity. The comparison is based on the dose of toxin, time of exposure and method of absorption. The concept of a γ-coefficient is applied for handling the above-mentioned toxicity factors. An example is presented to illustrate the applicability of the method.

Previously, several attempts have been made to find a suitable way of measuring poverty. The current practice in measuring poverty is based on assumption that the poor can be identified by determining a poverty line. As pointed out by Cerioli and Zani (1990) and by Cheli et al. (1994), among others, the problem is due to the fact that a sharp division of the total population between poor and non-poor is unrealistic. The traditional approaches usually assess the poverty status of an individual based solely on a unique indicator of such income or expenditure. Thus there is a need for an efficient poverty measures to be developed. Due to the weaknesses of traditional poverty measurement, the research introduces a composite of multidimensional poverty indicators. Data collected from the questionnaire on Household Income Survey/ Basic Amenities (HIS/ BA) year 2004 and 2007 which was conducted by the Department of Statistics Malaysia, Terengganu (DOS) were used. Fuzzy set was used to calculate poverty index to assess the living condition of households in rural areas of Terengganu. The results show that the use of Fuzzy Index Poverty on several poverty indicators provides a more complete picture of poverty than the traditional approach that use common indicators such as disposable income or expenditure.