• Korean Journal of Mathematics
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• v.28 no.4
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• pp.753-774
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• 2020

We introduce the notion of interval valued intuitionistic fuzzy hyperideals, bi-hyperideals and quasi-hyperideals of an ordered semihypergroup. We characterize an interval valued intuitionistic fuzzy hyperideal of an ordered semihypergroup in terms of its level subset. Moreover, we show that interval valued intuitionistic fuzzy bi-hyperideals and quasi-hyperideals coincide only in a particular class of ordered semihypergroups. Finally, we show that every interval valued intuitionistic fuzzy quasi-hyperideal is the intersection of an interval valued intuitionistic fuzzy left hyperideal and an interval valued intuitionistic fuzzy right hyperideal.

• The Korean Journal of Applied Statistics
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• v.18 no.3
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• pp.607-615
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• 2005

Recently the interval estimation of a binomial proportion is revisited in various literatures. This is mainly due to the erratic behavior of the coverage probability of the will-known Wald confidence interval. Various alternatives have been proposed. Among them, Agresti-Coull confidence interval has been recommended by Brown et al. (2001) with other confidence intervals for large sample, say n $\ge$ 40. On the other hand, a noninformative Bayesian approach called Polya posterior often produces statistics with good frequentist's properties. In this note, an interval estimator is developed using weighted Polya posterior. The resulting interval estimator is essentially the Agresti-Coull confidence interval with some improved features. It is shown that the weighted Polys posterior produce an effective interval estimator for small sample size and a severely skewed binomial distribution.

• Journal of Korean Physical Therapy Science
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• v.15 no.3
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• pp.31-41
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• 2008

Purpose : The purpose of this study is to examine the muscle activity of shoulder stabilization according to change of supporting base interval between push-up bend and push-up plus position and is to prevent or treat a shoulder injury by the most effective exercise for rehabilitation. Methods : This study analyzed the muscle activity according to change of supporting base interval between push-up bend and push-up plus movement. The participants without neuromuscular disease were 25 students - 12 males and 13 females - all twenty or over and the surface electrode of EMG attached on pectoralis major, triceps long head, middle trapezius, lower trapezius, serratus anterior and latissimus dorsi. The process has practiced 3 sessions of supporting base interval - narrowing interval, two shoulder interval, broad interval - by push-up bend and push-up plus movement. Result : 1. The muscle activity of pectoralis major was significantly increased according to narrow interval of supporting base on push-up plus movement and was significant difference(p<.05). 2. The muscle activity of biceps was significantly increased according to narrow interval of supporting base on push-up bend movement(p<.05). 3. The muscle activity of middle or lower trapezius was a difference according to change of supporting base on push-up bend and push-up plus movement but was not significant difference. 4. The muscle activity of serratus anterior was significantly increased according to broad interval of supporting base on push-up bend movement(p<.05). 5. The muscle activity of latissimus dorsi was significantly increased according to broad interval of supporting base on push-up bend movement(p<.05). Conclusion : These results lead us to the conclusion that push-up bend exercise have the effect of muscle strength of biceps on narrowing interval, of serratus anterior or latissimus dorsi on broad interval and push-up plus exercise have the effect of muscle strength of pectoralis major on narrowing interval of support base.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.529-535
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• 2014

In this paper, we propose a hybrid approach towards multiple kernels interval type-2 possibilistic fuzzy C-means(PFCM) based on interval type-2 possibilistic fuzzy c-means(IT2PFCM) and possibilistic fuzzy c-means using multiple kernels( PFCM-MK). In case of noisy data or overlapping cluster prototypes, fuzzy C-means gives poor performance in comparison to possibilistic fuzzy C-means(PFCM). Moreover, to address the uncertainty associated with fuzzifier parameter m, interval type-2 possibilistic fuzzy C-means(PFCM) is used. Most of the practical data available are complex and non-linearly separable. In such cases using Gaussian kernels proves helpful. Therefore, in order to overcome all these issues, we have integrated multiple kernels possibilistic fuzzy C-means(PFCM) into interval type-2 possibilistic fuzzy C-means(IT2PFCM) and propose the idea of multiple kernels based interval type-2 possibilistic fuzzy C-means(IT2PFCM-MK).

• Korean Journal of Mathematics
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• v.24 no.1
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• pp.27-40
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• 2016

In this paper, we introduce the concepts of interval-valued intuitionistic gradation of openness of fuzzy sets which is a generalization of intuitionistic gradation of openness of fuzzy sets and interval-valued intuitionistic gradation preserving mapping and then investigate their properties.

• The Korean Journal of Applied Statistics
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• v.19 no.1
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• pp.171-181
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• 2006

The Wald confidence interval has been considered as a standard method for the difference of proportions. However, the erratic behavior of the coverage probability of the Wald confidence interval is recognized in various literatures. Various alternatives have been proposed. Among them, Agresti-Caffo confidence interval has gained the reputation because of its simplicity and fairly good performance in terms of coverage probability. It is known however, that the Agresti-Caffo confidence interval is conservative. In this note, a confidence interval is developed using the weighted Polya posterior which was employed to obtain a confidence interval for the binomial proportion in Lee(2005). The resulting confidence interval is simple and effective in various respects such as the closeness of the average coverage probability to the nominal confidence level, the average expected length and the mean absolute error of the coverage probability. Practically it can be used for the interval estimation of the difference of proportions for any sample sizes and parameter values.

• Proceedings of the Korean Statistical Society Conference
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• 2004.11a
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• pp.67-72
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• 2004

Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate interval linear and nonlinear regression models combining the possibility and necessity estimation formulation with the principle of SVM. For data sets with crisp inputs and interval outputs, the possibility and necessity models have been recently utilized, which are based on quadratic programming approach giving more diverse spread coefficients than a linear programming one. SVM also uses quadratic programming approach whose another advantage in interval regression analysis is to be able to integrate both the property of central tendency in least squares and the possibilistic property In fuzzy regression. However this is not a computationally expensive way. SVM allows us to perform interval nonlinear regression analysis by constructing an interval linear regression function in a high dimensional feature space. In particular, SVM is a very attractive approach to model nonlinear interval data. The proposed algorithm here is model-free method in the sense that we do not have to assume the underlying model function for interval nonlinear regression model with crisp inputs and interval output. Experimental results are then presented which indicate the performance of this algorithm.

• Honam Mathematical Journal
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• v.30 no.2
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• pp.299-310
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• 2008

The notion of interval-valued fuzzy ${\alpha}$-continuous mappings and interval-valued fuzzy contra ${\alpha}$-continuous mappings is introduced, and their characterizations are investigated.

• Journal of applied mathematics & informatics
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• v.34 no.3_4
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• pp.179-192
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• 2016

In this paper, we introduce product interval-valued fuzzy graphs and prove several results which are analogous to interval-valued fuzzy graphs. We conclude by giving properties for a product interval-valued fuzzy graph.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.208-211
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• 2007

In a recently proposed method of model reduction for discrete interval systems, the denominator polynomial of a reduced model is computed by applying interval arithmetic to dominant poles of the original system. However, the denominator polynomial obtained via interval arithmetic usually has poles with larger intervals than desired ones. Hence an unstable polynomial can be derived from the stable polynomial. In this paper a simple technique is presented to partially overcome such a stability problem by accurately preserving desired real dominant poles.