• Journal of the Korean School Mathematics Society
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• 제20권4호
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• pp.387-404
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• 2017

In this paper, in the last 4 years(2014~2017 school year), we classified the probability and statistical items based on the evaluation scope of the mathematics subject content knowledge which were presented by the Korea Institute for Curriculum and Evaluation, and the classified items were analyzed. As a result, First, in order to induce normalization of the probability and statistical curriculum, four assessment field should be evenly distributed. Second, integrated thinking and comprehensive analytical thinking assessment is required. Third, item an epilogue should be used to measure mathematical thinking and logical competence. Fourth, the ratio of the number of items in probability and statistics to the number of that was 7.7%~10.0%, and the ratio according to the item weighting was 5.0%~7.5%. Fifth, it maintains the policy of stabilizing a good the level of difficulty of the items. Finally, probability and statistical assessment should focus on measuring problem solving ability from an inductive point of view.

• Journal of the Korean Institute of Intelligent Systems
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• 제17권2호
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• pp.244-251
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• 2007

Intention reading technique is essential to provide personalized services toward more convenient and human-friendly services in complex ubiquitous environment such as a smart home. If a system has knowledge about an user's intention of his/her behavioral pattern, the system can provide mote qualified and satisfactory services automatically in advance to the user's explicit command. In this sense, learning capability is considered as a key function for the intention reading technique in view of knowledge discovery. In this paper, ore introduce a personalized media control method for a possible application iii a smart home. Note that data pattern such as human behavior contains lots of inconsistent data due to limitation of feature extraction and insufficiently available features, where separable data groups are intermingled with inseparable data groups. To deal with such a data pattern, we introduce an effective engineering approach with the combination of fuzzy logic and probabilistic reasoning. The proposed learning system, which is based on IFCS (Iterative Fuzzy Clustering with Supervision) algorithm, extract probabilistic fuzzy rules effectively from the given numerical training data pattern. Furthermore, an extended architectural design methodology of the learning system incorporating with the IFCS algorithm are introduced. Finally, experimental results of the media contents recommendation system are given to show the effectiveness of the proposed system.

• Transactions of the Korean Society of Mechanical Engineers
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• 제16권7호
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• pp.1234-1243
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• 1992

A systematic procedure to design fuzzy PID controllers is developed in this paper. The concept of local fuzzy control cell is proposed by introducing both an adequate global control rule and membership functions to simplify a fuzzy logic controller. Fuzzy decision is made by using algebraic product and parallel firing arithematic mean, and a defuzzification strategy is adopted for improving the computational efficiency based on nonfuzzy micro-processor. A direct method, transforming the typical output of quasi-linear fuzzy operator to the digital compensator of PID form, is also proposed. Finally, the proposed algorithm is applied to an DC-servo motor. It is found that this algorithm is systematic and robust through computer simulations and implementation of controller using Intel 8097 micro-processor.

• Nuclear Engineering and Technology
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• 제26권1호
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• pp.9-18
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• 1994

The engineered safeguards of Wolsung nuclear power plant unit 1 contain redundant systems of 2-out-of-3 logic which are not operating under normal conditions but are called upon to act when emergency conditions develop. To ensure their operability, the systems are periodically tested. In this work, we develop the unavailability formulae for 2-out-of-3 logic configurations which take into account the failure probability of the channels tested due to human error in the simultaneous testing scheme. We also develop the model for the probability that the reactor is tripped during the surveillance test due to either system failure or human error. We determined the optimal inspection periods of safety systems, taking into account both the unavailability of the safety system and the probability that the reactor is tripped during the surveillance test. We compared the results with the inspection periods currently used at Wolsung NPP Unit 1. As a result, the inspection periods obtained using a minimum human error (8.24 $\times$ 1$^{-6}$ ) are shorter than those currently used in Wolsung NPP unit 1 whereas the inspection periods obtained using a maximum human error are (4.44 $\times$ 10$^{-4}$ ) longer than those used in Wolsung NPP unit 1.

• Korean Journal of Logic
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• 제18권2호
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• pp.167-195
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• 2015

This paper aims to respond to Weisberg's claim that the standard Bayesian epistemology cannot model an agent's belief updating that is triggered by some undermining evidence. Our epistemological intuition seems to require that the undermining evidence decreases some particular relevant credences. According to Weisberg, however, such a belief change cannot result from the standard Bayesian belief updating rules-i.e., (Jeffrey) Conditionalization. This is because probabilistic independence between some propositions is preserved under (Jeffrey) Conditionalization on the relevant evidence. Yet I will show in this paper that this conclusion is somewhat hasty. In particular, I will show that there is another version of Conditionalization and that when one updates her credences by means of such a version, the belief updating originated in undermining evidence can be well modeled in the Bayesian framework. Some authors often call the version Higher Order Conditionalization.

• Korean Journal of Logic
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• 제15권1호
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• pp.107-154
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• 2012

In my previous paper (2009), I defended a solution of the Sleeping Beauty problem, according to which, on Monday, Sleeping Beauty assigns a lower credence to the coin's landing heads than 1/2. This conclusion was largely favorable to the Thirder view. However, even if my defense of the Thirder view was successful, it left one important question to be unanswered: Where did the Halfers go wrong? Their main argument was simple: Because Sleeping Beauty does not receive new and relevant evidence about how the coin lands, her credence in its landing heads should remain to be the same. But note that, if the Thirder view was right and Sleeping Beauty receives no new and relevant evidence, then this becomes a special case of the so-called old evidence problem (Glymour, 1980). In this paper, I will explain why it is rational for Sleeping Beauty to change her credence despite the lack of new evidence about the coin's landing heads. For this explanation, I will use Garber's well-known solution to the old evidence problem.

• Korean Journal of Logic
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• 제13권1호
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• pp.21-52
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• 2010

What van Fraassen calls 'Reflection Principle' is claimed to meet several counterexamples, one of which stands out in the form of the Sleeping Beauty problem. Adam Elga argues that what he believes is the correct answer to the Sleeping Beauty problem shows that Reflection is subject to counterexamples. David Lewis proposes a different answer which preserves Reflection intact. Recently, Nick Bostrom presents a hybrid view which is supposed to allow us to keep Reflection. In proposing his hybrid view Bostrom criticizes both Elga and Lewis while taking some 'good' parts from each. He claims that Elga's view is not entirely acceptable because it presupposes the 'Self-Indication Assumption'. I shall claim, however, that Elga could avoid Bostrom's criticisms by introducing Bostrom's notion of agent-part. I believe that several probability-related puzzles including the Sleeping Beauty problem indicate a promising view concerning the way we should regard our future selves' opinions. According to this view, whether one takes the outsider stance or insider stance makes a difference in an important way that one and the same proposition is associated with different degrees of belief by one agent.

• Journal of the Korea Society for Simulation
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• 제18권2호
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• pp.49-55
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• 2009

In this paper, we investigate an optimal allocation of constant service resources in stochastic system to optimize the expected performance of interest. For this purpose, we use the control variates to estimate the gradients of expected performance with respect to given resource parameters, and apply these estimated gradients in stochastic optimization algorithm to find the optimal allocation of resources. The proposed gradient estimation method is advantageous in that it uses simulation results of a single design point without increasing the number of design points in simulation experiments and does not need to describe the logical relationship among realized performance of interest and perturbations in input parameters. We consider the applications of this research to various models and extension of input parameter space as the future research.

• Journal of Educational Research in Mathematics
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• 제17권2호
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• pp.179-199
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• 2007

The purpose of this study was to discover differences between mathematically gifted students (MGS) and non-gifted students (NGS) when making probability judgments. For this purpose, the following research questions were selected: 1. How do MGS differ from NGS when making probability judgments(answer correctness, answer confidence)? 2. When tackling probability problems, what effect do differences in probability judgment factors have? To solve these research questions, this study employed a survey and interview type investigation. A probability test program was developed to investigate the first research question, and the second research question was addressed by interviews regarding the Program. Analysis of collected data revealed the following results. First, both MGS and NGS justified their answers using six probability judgment factors: mathematical knowledge, use of logical reasoning, experience, phenomenon of chance, intuition, and problem understanding ability. Second, MGS produced more correct answers than NGS, and MGS also had higher confidence that answers were right. Third, in case of MGS, mathematical knowledge and logical reasoning usage were the main factors of probability judgment, but the main factors for NGS were use of logical reasoning, phenomenon of chance and intuition. From findings the following conclusions were obtained. First, MGS employ different factors from NGS when making probability judgments. This suggests that MGS may be more intellectual than NGS, because MGS could easily adopt probability subject matter, something not learnt until later in school, into their mathematical schemata. Second, probability learning could be taught earlier than the current elementary curriculum requires. Lastly, NGS need reassurance from educators that they can understand and accumulate mathematical reasoning.

• The Korean Journal of Applied Statistics
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• 제10권2호
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• pp.261-274
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• 1997

Most of the data sets to which the conventional discriminant rules have been applied contain only those which belong to one and only one class among the classes of interest. However the extension of the bivalence to multivlaence like Fuzzy concepts strongly influence the traditional view that an object must belong to only class. Thus the goal of this paper is to develop new discriminant rules which can handle the data each object of which may belong to moer than two classes with certain degrees of belongings. A calibration model is used for the relationship between the feature vector of an object and the degree of belongings and a Bayesian inference is made with the Metropolis algorithm on the degree of belongings when a feature vector of an object whose membership is unknown is given. An evalution criterion is suggested for the rules developed in this paper and comparision study is carried using two training data sets.