• Korean Journal of Child Studies
• /
• v.29 no.5
• /
• pp.113-131
• /
• 2008

This study examined mothers' ratings of everyday rules for their young children. Participants were 294 mothers of 2- to 5-year-old children attending kindergartens and nursery schools in Korea. Data were collected by questionnaire and were analyzed by $x^2$. Results indicated that the majority of mothers' rules for their children pertained to safety, interpersonal issues, and as children got older, social conventions. Mothers endorsed prudential justifications for safety and self-care, moral justifications for interpersonal rules, practical and moral justifications for safeguarding property, and conventional justifications for obedience/order and food/mealtime routines. Analyses of mothers' judgments of rule independence indicated that rules on interpersonal and safety issues were to be kept without exception.

• Journal of Arbitration Studies
• /
• v.24 no.3
• /
• pp.105-124
• /
• 2014

There is a growing interest in resolving intellectual property rights disputes through arbitration rather than in state courts. The internationalization of commercial relations, one of the most significant drivers of the growth of international arbitration in general, encompasses intellectual property relationships as well. In 2014, the World Intellectual Property Organization Arbitration and Mediation Center revised its arbitration rules. The revision is part of a wave of recent updates of institutional arbitral rules. After briefly introducing the WIPO Center as an arbitral institution, this article assesses the features of the WIPO Rules that make them suitable for the particular challenges of IP-related disputes. A second part reviews the salient new aspects of the WIPO Rules from a comparative perspective.

• Korean Journal of Child Studies
• /
• v.23 no.4
• /
• pp.35-51
• /
• 2002

This study investigated the expectations Of 186 Korean mothers regarding the self-regulatory behaviors of their l-to 5-year old child. A questionnaire for mothers was prepared which consists of nine categories identified in previous research : safety rules, personal property rules, interpersonal rules, food-related rules, independence requests, self-care rules, family routines, delay, manners, obedience rules, and academic skills and attitude. Data consisted of questionnaires completed by the mothers. Findings were that (1) mothers had high expectations regarding self-regulatory behaviors about safety and independence but low expectations regarding family routines and personal property self-regulation, (2) their expectations increased with age of child, (3) the pattern of expectations did not change with age, and (4) expectations were higher with lower educational background of the mother.

• Journal of Intelligence and Information Systems
• /
• v.14 no.1
• /
• pp.1-17
• /
• 2008

Data mining is defined as the process of discovering meaningful and useful pattern in large volumes of data. In particular, finding associations rules between items in a database of customer transactions has become an important thing. Some data structures and algorithms had been proposed for storing meaningful information compressed from an original database to find frequent itemsets since Apriori algorithm. Though existing method find all association rules, we must have a lot of process to analyze association rules because there are too many rules. In this paper, we propose a new data structure, called a Frequent Pattern Network (FPN), which represents items as vertices and 2-itemsets as edges of the network. In order to utilize FPN, We constitute FPN using item's frequency. And then we use a clustering method to group the vertices on the network into clusters so that the intracluster similarity is maximized and the intercluster similarity is minimized. We generate association rules based on clusters. Our experiments showed accuracy of clustering items on the network using confidence, correlation and edge weight similarity methods. And We generated association rules using clusters and compare traditional and our method. From the results, the confidence similarity had a strong influence than others on the frequent pattern network. And FPN had a flexibility to minimum support value.

• Journal of KIISE:Databases
• /
• v.32 no.6
• /
• pp.567-584
• /
• 2005

Temporal data mining, the incorporation of temporal semantics to existing data mining techniques, refers to a set of techniques for discovering implicit and useful temporal knowledge from temporal data. Association rules and classification are applied to various applications which are the typical data mining problems. However, these approaches do not consider temporal attribute and have been pursued for discovering knowledge from static data although a large proportion of data contains temporal dimension. Also, data mining researches from temporal data treat problems for discovering knowledge from data stamped with time point and adding time constraint. Therefore, these do not consider temporal semantics and temporal relationships containing data. This paper suggests that temporal associative classification technique based on temporal class association rules. This temporal classification applies rules discovered by temporal class association rules which extends existing associative classification by containing temporal dimension for generating temporal classification rules. Therefore, this technique can discover more useful knowledge in compared with typical classification techniques.

• International Commerce and Information Review
• /
• v.12 no.3
• /
• pp.361-387
• /
• 2010

China has been the number one target of anti-dumping cases. In the middle of 1990s, China began to make anti-dumping rules to protect its domestic markets. The first anti-dumping regulation was mentioned in 1994 and the anti-dumping and anti-subsidy regulation was published in 1997. In 2001, China entered into the WTO and as a member of WTO, China is obliged to revise its anti-dumping rules in accordance with WTO's requirements. After that China amended anti-dumping rules in 2004 and it is still valid. Even though China makes considerable efforts to make the rules to be consistent with WTO Rules, China is still facing various difficulties such as lack of transparency, absence of definite deadlines, mismatch between rules, lack of clear interest criteria, overly hard questionnaires and inadequacy of judicial review and non-market economy. This paper deals with the current situation of anti-dumping system in China and the scheme of antidumping law and regulations and the main contents of that law and regulations. The purpose of this paper is to contribute to the enhancement of China's anti-dumping rules by studying the problems and solutions of the anti-dumping rules in China.

• Journal of information and communication convergence engineering
• /
• v.1 no.3
• /
• pp.150-156
• /
• 2003

This paper explored the use of an algorithm for the data mining and method in handling missing data which had generated enhanced association patterns observed using the data illustrated here. The evaluations showed that more association patterns are generated in the second analysis which suggests more meaningful rules than in the first situation. It showed that the model offer more precise and important association rules that is more valuable when applied for business decision making. With the discovery of accurate association rules or business patterns, strategies could be efficiently planned out and implemented to improve marketing schemes. This investigation gives rise to a number of interesting issues that could be explored further like the effect of outliers and missing data for detecting fraud and devious database entries.

• 한국데이터정보과학회:학술대회논문집
• /
• 2005.04a
• /
• pp.18-24
• /
• 2005

The methods of data mining are decision tree, association rules, clustering, neural network and so on. Data mining is the method to find useful information for large amounts of data in database. It is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. We analyze Gyeongnam social indicator survey data by 2003 using association rule technique for environment information. Association rules are useful for determining correlations between attributes of a relation and have applications in marketing, financial and retail sectors. We can use association rule outputs in environmental preservation and environmental improvement.

• Journal of the Korean Data and Information Science Society
• /
• v.19 no.4
• /
• pp.1141-1151
• /
• 2008

Data mining is the process of sorting through large amounts of data and picking out useful information. One of the well-studied problems in data mining is the exploration of association rules. An association rule technique finds the relation among each items in massive volume database. Some interestingness measures have been developed in association rule mining. Interestingness measures are useful in that it shows the causes for pruning uninteresting rules statistically or logically. This paper propose a conditional pure confidence to evaluate association rules and then describe some properties for a proposed measure. The comparative studies with confidence and pure confidence are shown by numerical example. The results show that the conditional pure confidence is better than confidence or pure confidence.

• Journal of The Korean Association For Science Education
• /
• v.37 no.4
• /
• pp.705-717
• /
• 2017

The purpose of the study is to explore secondary science teachers' emotional display rules, types of emotional labor, science-specific emotional display rules and the episodes of emotional labor. For this purpose, the survey to measure emotional labor of science teachers (The Emotional Labor of Science Teaching Scale: TELSTS) was developed and the participants were 145 secondary science teachers in Korea. Results showed that first, secondary science teachers recognized the emotional display rules defined by their schools, especially, positive display rules. Second, secondary science teachers showed that they were carrying out emotional labor in order to keep their emotional display rules in check. The mean value of responses to deep acting was high. Also, there were statistically significant differences in emotional labor depending on whether they were full-time or part-time teachers and their teaching career. Third, as a result of analyzing the specificity of science teachers, it was mainly related to the objective and logical image of science, and experimental instruction. Seventy-four percent (74%) of responses were negative or neutral emotional display rules. Finally, implications for science education are discussed.