• Journal of Korea Water Resources Association
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• v.52 no.3
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• pp.195-206
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• 2019

In this study, the vulnerable period assessment method for weekly groundwater resources management was developed considering correlation between data of groundwater level, river level, precipitation applying critical infiltration concept. The vulnerable periods of 3 case study were assessed using data of groundwater, precipitation, river level, and results were compared. The weights for between observation stations were calculated using correlation of groundwater, precipitation, river level data, and weights that could be considered recently trend of data for each observation station. The vulnerable period was assessed using final calculated weights and multi criteria decision method, compared result for each case study. The developed method can be a quantitative basis for the establishment of efficient groundwater resources management and the decision of specific countermeasure applyment.

• Korean Journal of Applied Biomechanics
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• v.24 no.1
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• pp.43-50
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• 2014

The purpose of this study was to analyze of the GRF (ground reaction force) parameters according to the change of positions and weights of bag during downward stairs between dominant and non-dominant in upper & lower limbs. To perform this study, participants were selected 9 healthy women (age: $21.40{\pm}0.94yrs$, height: $166.50{\pm}2.68cm$, body mass: $57.00{\pm}3.61kg$, BMI: $20.53{\pm}1.03kg/m^2$), divided into 2 carrying bag positions (dominant arm/R, non-dominant arm/L) and walked with 3 type of bag weights (0, 3, 5 kg) respectively. One force-plate was used to collect GRF (AMTI OR6-7) data at a sample rate of 1000 Hz. The variables analyzed were consisted of the medial-lateral GRF (Fx), anterior-posterior GRF (Fy), vertical GRF (Fz), impact loading rate and center of pressure (COPx, COPy, COP area, COPy posterior peak time) during downward stairs. 1) The Fx, Fy, Fz, COPx, and COP area of GRF were not statistically significant between dominant leg and non-dominant leg, but non-dominant leg, that is, showed the higher COPy, and showed higher impact loading rate than that dominant leg during downward stairs. 2) In bag wearing to non-dominant arm, Fx, Fz, COPx, COPy, impact loading rate and COP area showed increase tendency according to increase of bag weights. Also, against bag wearing to dominant arm, non-dominant showed different mechanism according to increase of bag weights. The Ground Reaction Force parameters showed different characteristics according to the positions and weights of bag during downward stairs between dominant and non-dominant arm.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.8
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• pp.1041-1047
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• 2011

Data on 2,365 Mecheri sheep (1,201 males and 1,164 females), maintained at the Mecheri Sheep Research Station, Pottaneri, India, and recorded between 1979 and 2006, were analysed to study the growth related traits and their genetic control. The body weights at different ages (i.e. at birth, weaning (3 months), 6, 9 and 12 months) were recorded and collected from the birth and growth registers maintained in the farm. The average weights of Mecheri sheep at birth, and at 12 months of age were $2.24{\pm}0.01$ and $16.81{\pm}0.15$ kg respectively. The pre- and post-weaning average daily weight gains were $63.84{\pm}0.75$ and $29.52{\pm}0.43$ g respectively. Study revealed a significant difference with the period of lambing on body weight, weight gain and efficiency in weight gain at different stages of growth. Males were heavier and had a higher weight gain than females at almost all stages of growth and the differences tended to increase with age. The direct heritability estimates increased from birth to six months of age and then decreased. The direct heritabilities of all body weights at different stages of growth were low to moderate in magnitude and the values at birth, weaning, six, nine and 12 months of age were 0.08, 0.17, 0.21, 0.13 and 0.10 respectively. For the estimation of heritability at birth and three months body weights, the direct additive genetic and maternal additive genetic effects have to be taken into account and for the estimation of six months weight, the direct additive genetic and maternal permanent environmental effects have to be included in the model. The estimates of heritability, phenotypic and genetic correlations among the different body weights indicated that the selection for improving the body weights at different traits should be done on the basis of three or six months weight because of higher heritability estimates and having higher genetic correlations with other traits.

• Journal of the Korean Institute of Intelligent Systems
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• v.1 no.1
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• pp.9-25
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• 1991

This tutorial paper has been written for biologists, physicians or beginners in fuzzy sets theory and applications. This field is introduced in the framework of medical diagnosis problems. The paper describes and illustrates with practical examples, a general methodology of special interest in the processing of borderline cases, that allows a graded assignment of diagnoses to patients. A pattern of medical knowledge consists of a tableau with linguistic entries or of fuzzy propositions. Relationships between symptoms and diagnoses are interpreted as labels of fuzzy sets. It is shown how possibility measures (soft matching) can be used and combined to derive diagnoses after measurements on collected data. The concepts and methods are illustrated in a biomedical application on inflammatory protein variations. In the case of poor diagnostic classifications, it is introduced appropriate ponderations, acting on the characterizations of proteins, in order to decrease their relative influence. As a consequence, when pattern matching is achieved, the final ranking of inflammatory syndromes assigned to a given patient might change to better fit the actual classification. Defuzzification of results (i.e. diagnostic groups assigned to patients) is performed as a non fuzzy sets partition issued from a "separating power", and not as the center of gravity method commonly employed in fuzzy control. It is then introduced a model of fuzzy connectionist expert system, in which an artificial neural network is designed to build the knowledge base of an expert system, from training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the connections: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through MIN-MAX fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feed forward network is described and illustrated in the same biomedical domain as in the first part.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.645-651
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• 2021

With the advent of the Fourth Industrial Revolution, modern society uses a diverse pool of devices. In this context, there is increasing interest in removing various kinds of noise arising in data transmission. However, it is difficult to restore image that damaged by mixed noise, and a digital filter that effectively restores an image according to the characteristics of the noise is required. In this paper, we propose a digital switching filter algorithm to remove mixed noise generated during digital image transmission. The proposed algorithm switches the filtering process through noise judgment and reconstructs the image using fuzzy weights and combined weights based on the pixel values inside the mask. To evaluate the proposed algorithm, we compared it with existing filter algorithms through simulation. Filtering results were expanded and compared for visual evaluation, and PSNR comparison was used for quantitative evaluation.

• Journal of the Korea Society of Computer and Information
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• v.18 no.1
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• pp.177-183
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• 2013

In this paper, Cohen's kappa and weighted kappa are applied to measuring classification accuracy when performing classification in data minig. Cohen's kappa compensates for classifications that may be due to chance and is used for the data with nominal or ordinal scales. Especially, for the ordinal data, weighted kappa which measures the classification accuracy by quantifying the classification errors as weights is used. We used two weights (linear weight, quadratic weight) for calculations of weighted kappa. Also for the calculation and comparison of kappa and weighted kappa we used a real data set, fat-liver data.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.515-520
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• 2022

In context awareness using multiple sensors, when using sensor data detected and sent by each sensor, it is necessary to give different weights for each sensor. Even if the same type of sensor is configured for the same situation, sometimes it is necessary to assign different weights due to other secondary factors. It is inevitable to assign weights to events in the real world, and it can be said that a weighting method that can be used in a context awareness system using multiple sensors is necessary. In this study, we propose a weighting method for each sensor that reports to the host while the sensors continue to detect over time. In most IoT environments, the sensor continues the detection activity, and when the detected value shows a change pattern beyond a predetermined range, it is basically reported to the host. This can be called a kind of data stream environment. A weighting method was proposed for sensing data from multiple sensors in a data stream environment, and the new weighting method was to select and assign weights to data that indicates a context change in the stream.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.2
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• pp.123-140
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• 2007

This study focuses on establishing theoretically-reasonable framework of evaluation areas and items for the informatization program and analyzing the weights for each area and item by means of the AHP. To obtain the goal of this research, firstly, based on broadly reviewing previous literature and logical reasoning, the evaluation criteria were Identified and conceptualized, which were 3 evaluation phases, 5 evaluation areas, and 22 evaluation items. Secondly, The data used for calculating the weight values for the evaluation criteria were collected from 48 academic and practical experts in the field of the informatization program promotion using internet survey. Thirdly, the relative weights among evaluation phases, evaluation areas, and its items were derived by AHP analysis. The findings of this study are thought not only to be useful as a practical guideline in performing evaluating the informatization program but also to provide significant basis for constructing the theoretical framework of evaluating method and management of the informatization program.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.1
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• pp.113-127
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• 2014

The stochastic dominance approach is to form a portfolio that stochastically dominates a predetermined benchmark portfolio such as KOSPI. This study is to search a set of portfolio weights for the first-order stochastic dominance with maximum utility defined in terms of mean and variance by managing the constraint set and the objective function in an iterative manner. A nonlinear programming algorithm was developed and tested with promising results against Korean stock market data sets.

• Communications for Statistical Applications and Methods
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• v.22 no.2
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• pp.137-146
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• 2015

Singh (2013) considered the dual problem to the calibration of design weights to obtain a new generalized linear regression estimator (GREG) for the finite population total. In this work, we have made an attempt to suggest a way to use the dual calibration of the design weights in case of multi-auxiliary variables; in other words, we have made an attempt to give an answer to the concern in Remark 2 of Singh (2013) work. The same idea is also used to generalize the GREG estimator proposed by Deville and S$\ddot{a}$rndal (1992). It is not an easy task to find the optimum values of the parameters appear in our approach; therefore, few suggestions are mentioned to select values for such parameters based on a random sample. Based on real data set and under simple random sampling without replacement design, our approach is compared with other approaches mentioned in this paper and for different sample sizes. Simulation results show that all estimators have negligible relative bias, and the multivariate case of Singh (2013) estimator is more efficient than other estimators.