• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.4
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• pp.557-562
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• 2007

This paper extends the work of Maji et al. (2001) to present the concept of interval-valued fuzzy soft sets and to present an algorithm for finding where the degree of membership are represented by interval values in [0, 1]. The proposed method is more flexible than the one presented in Maji et at. (2001) due to the fact that it allows the degrees of membership of object for parameters to be represented by interval-values rather than crisp real values between zero and one.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.2
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• pp.99-105
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• 2017

Type-2 fuzzy sets are preferred over type-1 sets as they are capable of addressing uncertainty more efficiently. The fuzzifier values play pivotal role in managing these uncertainties; still selecting appropriate value of fuzzifiers has been a tedious task. Generally, based on observation particular value of fuzzifier is chosen from a given range of values. In this paper we have tried to adaptively compute suitable fuzzifier values of interval type-2 possibilistic fuzzy c-means (IT2 PFCM) for a given data. Information is extracted from individual data points using histogram approach and this information is further processed to give us the two fuzzifier values $m_1$, $m_2$. These obtained values are bounded within some upper and lower bounds based on interval type-2 fuzzy sets.

• Journal of applied mathematics & informatics
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• v.35 no.1_2
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• pp.95-111
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• 2017

Recently, interval-valued fuzzy graph is a growing research topic as it is the generalization of fuzzy graphs. The interval-valued fuzzy graphs are more flexible and compatible than fuzzy graphs due to the fact that they allowed the degree of membership of a vertex to an edge to be represented by interval values in [0.1] rather than the crisp values between 0 and 1. In this paper, we introduce the concepts of regular and totally regular interval-valued fuzzy graphs and discusses some properties of the ${\mu}$-complement of interval-valued fuzzy graph. Self ${\mu}$-complementary interval-valued fuzzy graphs and self-weak ${\mu}$-complementary interval-valued fuzzy graphs are defined and a necessary condition for an interval valued fuzzy graph to be self ${\mu}$-complementary is discussed. We define busy vertices and free vertices in interval valued fuzzy graph and study their image under an isomorphism.

• Journal of Internet Computing and Services
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• v.4 no.4
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• pp.45-51
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• 2003

In general, the values for attribute appearing in fuzzy object-oriented data models are represented by the fuzzy sets. If it can allow the attribute values in the fuzzy object-oriented data models to be represented by the interval-valued fuzzy sets, then it can allow the fuzzy object-oriented data models to represent the attribute values in more flexible manner. The attribute values of frames appearing in the inheritance structure of the fuzzy object-oriented data models are calculated by a prloritized conjunction operation using interval-valued fuzzy sets. This approach can be applied to knowledge and information processing in which degree of membership is represented as not the conventional fuzzy sets but the interval-valued fuzzy sets.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.2
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• pp.30-34
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• 2011

Variable precision rough set models have been successfully applied to problems whose domains are discrete values. However, there are many situations where discrete data is not available. When it comes to the problems with interval values, no variable precision rough set model has been proposed. In this paper, we propose a variable precision rough set model for interval values in which classification errors are allowed in determining if two intervals are same. To build the model, we define equivalence class, upper approximation, lower approximation, and boundary region. Then, we check if each of 11 characteristics on approximation that works in Pawlak's rough set model is valid for the proposed model or not.

• Journal of Medicine and Life Science
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• v.20 no.3
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• pp.107-114
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• 2023

Epidemiological control of coronavirus disease 2019 (COVID-19) is needed to estimate the infection period of confirmed cases and identify potential cases. The present study, targeting confirmed cases for which the time of COVID-19 symptom onset was disclosed, aimed to investigate the relationship between intervals (day) from symptom onset to testing the cycle threshold (CT) values of real-time reverse transcription-polymerase chain reaction. Of the COVID-19 confirmed cases, those for which the date of suspected symptom onset in the epidemiological investigation was specifically disclosed were included in this study. Interval was defined as the number of days from symptom onset (as disclosed by the patient) to specimen collection for testing. A locally weighted regression smoothing (LOWESS) curve was applied, with intervals as explanatory variables and CT values (CTR for RdRp gene and CTE for E gene) as outcome variables. After finding its non-linear relationship, a polynomial regression model was applied to estimate the 95% confidence interval values of CTR and CTE by interval. The application of LOWESS in 331 patients identified a U-shaped curve relationship between the CTR and CTE values according to the number of interval days, and both CTR and CTE satisfied the quadratic model for interval days. Active application of these results to epidemiological investigations would minimize the chance of failing to identify individuals who are in contact with COVID-19 confirmed cases, thereby reducing the potential transmission of the virus to local communities.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1663-1670
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• 2007

One-way hash chains are important cryptographic primitives and have been used as building blocks of various cryptographic applications. Advantages of one-way hash chains are their simplicity and efficiency for generation based on low-powered processors with short time. However, a drawback of one-way hash chains is their difficulty of control to compute interval values of one-way hash chains. That is, when hash values in one-way hash chain are used as encryption keys, if one hash value is compromised, then the attacker can compute other encryption keys from the compromised hash value. Therefore, direct use of one-way hash chains as encryption keys is limited to many cryptographic applications, such as pay per view system and DRM system. In this paper, we propose a new concept which is called interval hash chain using a hash function. In particular, proposed hash chains are made for only computing interval hash values by using two different one-way hash chains. The proposed scheme can be applied to contents encryption scheme for grading and partially usable contents in DRM system.

• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.325-333
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• 2010

Protection against disclosure of survey respondents' identifiable and/or sensitive information is a prerequisite for statistical agencies that release microdata files from their sample surveys. Coarsening is one of popular methods for protecting the confidentiality of the data. Grouped data can be released in the form of microdata or tabular data. Instead of releasing the data in a tabular form only, having microdata available to the public with interval codes with their representative values greatly enhances the utility of the data. It allows the researchers to compute covariance between the variables and build statistical models or to run a variety of statistical tests on the data. It may be conjectured that the variance of the interval data is lower that of the ungrouped data in the sense that the coarsened data do not have the within interval variance. This conjecture will be investigated using the uniform and triangular distributions. Traditionally, midpoint is used to represent all the values in an interval. This approach implicitly assumes that the data is uniformly distributed within each interval. However, this assumption may not hold, especially in the last interval of the economic data. In this paper, we will use three distributional assumptions - uniform, Pareto and lognormal distribution - in the last interval and use either midpoint or median for other intervals for wage and food costs of the Statistics Korea's 2006 Household Income and Expenditure Survey(HIES) data and compare these approaches in terms of the first two moments.

• Journal of Technologic Dentistry
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• v.33 no.2
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• pp.137-145
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• 2011

Purpose: To evaluate the accuracy of zirconia copings in terms of clinical verified for the clinical application of CAD/CAM. Methods: Zirconia copings (n=5) were prepared using CAD/CAM system and were sintered using the relevant electrical induction furnace, which uses a 2h sintering program with a maximum temperature of $1500^{\circ}C$. The copings placed at the models and the interval values were measured. Results: The meas interval values between the die and the zirconia copings were $44.14{\mu}m$(A), $44.57{\mu}m$(B), $44.72{\mu}m$(C). 51.05 ${\mu}m$(D). Conclusion: The maximum interval values between the die and the zirconia copings were $51.3{\mu}m$ which is acceptable for clinical use. ${\mu}m$ Proper understanding of the test conditions will help enhancing the accuracy of zirconia coping.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.2
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• pp.1-6
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• 2001

This paper proposes a pattern classification method of interval vectors by interval neural networks. The proposed method can be applied to pattern classification where attribute values of each sample are given as interval numbers. First, an architecture of interval neural networks is proposed for dealing with interval input vectors. Next, a learning algorithm is derived from the cost function. a cost function is defined using the interval output from the interval neural network and the corresponding target output. Last, using numerical examples, the proposed approach is illustrated and compared with other approach based on the standard back-propagation neural networks.