• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.7
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• pp.715-725
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• 2010

Orthgonal Frequency Division Multiplexing(OFDM) system is effective for the high data rate transmission in the frequency selective fading channel. In this paper we propose PAPR(Peak to Average Power Ratio) reduction method of problem in OFDM system used Fuzzy theory that often control machine. This thesis proposes PAPR reducing method of OFDM system using Fuzzy theory. The advantages for using Fuzzy theory to reduce PAPR are that it is easy to manage the data and embody the hardware, and required smaller amount of operation. Firstly, we proposed simple algorithm that is reconstructed at receiver with transmitted overall PAPR which is reduced PAPR of sub-block using Fuzzy. Although there are some drawbacks that the operation of the system is increased comparing conventional OFDM system and it is needed to send the information about Fuzzy indivisually, it is assured that the performance of the system is enhanced for PAPR reducing. To evaluate the perfomance, the proposed search algorithm is compared with the proposed algorithm in terms of the complementary cumulative distribution function(CCDF) of the PAPR and the computational complexity. As a result of using the QPSK and 16QAM modulation, Fuzzy theory method is more an effective method of reducing 2.3 dB and 3.1 dB PAPR than exiting OFDM system when FFT size(N)=512, and oversampling=4 in the base PR of $10^{-5}$.

• The Journal of Korean Academy of Sensory Integration
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• v.18 no.2
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• pp.55-68
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• 2020

Objective : The purpose of this study is to summarize the best-available intervention evidence for children's sensory integration therapy, drawn from studies published domestically in Korea over the last 10 years. Methods : The articles evaluated in this study were collected from the RISS and DBpia databases using the search terms "sensory integration," "sensory processing," and "Ayres Sensory Integration (ASI)". A total of 19 papers were analyzed. The selected studies were then assessed using the Population, Intervention, Outcomes, and Comparison method, the International Classification of Functioning, Disability and Health (ICF) method, and the modified Evidence Alert Traffic Light Grading System. Results : Development delay was the most commonly applied diagnosis for children's sensory integration therapy and individual sensory integration therapy was the most frequently used intervention method. The intervention effect was 91 percent in the body structure and function of ICF. The areas concentrated on were sensory modulation, sensory processing, fine and gross motor, body scheme, body-self concept, balance, basic movement, postural control and hand function, attention, and self-esteem. Conclusion : This simple overview of the efficacy of children's sensory integration therapy provides a basis for easy understanding and use by therapists, researchers and families with children.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.155-175
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• 2003

In context of e-commerce, negotiation is a procedure to help negotiate between buyer and seller by adjusting their negotiation issues such as price and in terms of payment. We used intelligent agent and mobile device to promote new framework of e-commerce. Moreover, this framework can help buyers and sellers to carry their commercial transactions effectively. In regard to that issue, we need to carry out the research of negotiation agent that can be used in e-commerce fields. In this paper, we modeled the negotiation using CSP for the performance of agent in m-commerce environment. Furthermore we implemented interface for mobile device to extract buyer's requirement and preference easily Besides that we used utility function to make a decision for various evaluation functions and suggestions that are used for evaluation of negotiation issues. A difficulty of generating offer is dependent on the number of negotiation issues and the range of the values. Therefore, if any offer has a number of negotiation issues and the range of values are wide, the search space will be exponentially expanded. There have been many studies fur solving this problem, we applied those techniques to improve the agent's ability of negotiation. For example, a contract can be accomplished by exchanging seller and buyer's offer that is generated by agent to adjust the requisite profit for each party. Finally, we show the improvement of satisfaction as the negotiation is processed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.8
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• pp.273-284
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• 2017

This study performed meta-analysis of published articles to examine the relationship between sarcopenia and smoking. We searched the PubMed, EMBASE, Cochrane library, and RISS database sup to January 2017 using search terms such as sarcopenia AND (smoking OR tobacco OR cigarette). A total of 25 articles were included in the analysis (seven cohort studies and 18 cross-sectional studies). Incidence of sarcopenia in smokers and non-smokers was analyzed by the random effects model. Incidence of sarcopenia was OR 1.49 (95% CI 1.21, 1.84, p<.001, I2 = 88.20%), Asian (OR 1.28, 95% CI 0.91, 1.78, p=0.150, I2=85.32%), and Western (OR 1.65, 95% CI 1.25, 2.17, p<.001, I2=91.08%), Western smokers showed a significantly higher incidence of sarcopenia:males and females with OR 1.25(95% CI 1.11, 1.40, p<.001, 12=87.4%) and 1.80(95% CI 0.98, 3.30, p=.057, 12=89.1 %) respectively. Male smokers showed significantly higher incidence of sarcopenia. Based on the results of the study, smoking in Western males is related to sarcopenia. However, since the criteria for the diagnosis of sarcopenia and the criteria for smoking were different, cumulative individual clinical studies applying uniform assessment for the evaluation of sarcopenia and smoking status are needed in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.326-337
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• 2020

This study examined the public interest in high school Korean language instruction and the universal design for learning (UDL) using the social big data analysis method. The observations from 10,339 search results led to the conclusion that public interest in UDL was significantly lower than that of high school Korean language instruction. The results of the Big Data Association analysis showed that 17.22% of the terms were found to be related to "curriculum." In addition, a survey was conducted on a total of 330 high school students to examine how their teachers apply UDL in the classroom. High school students perceived computers as the most frequently used technology tool in daily classes (38.79%). Teacher-led lectures (52.12%) were the most frequently observed method of instruction. Compared to the second-year and third-year students, the first-year students appreciated the usage of technology tools and various instruction mediums more frequently (ps<.05). Students were relatively more positive in their response to the query on the provision of multiple means of representation. Consequently, the lesson contents became easier to understand for students with the availability of various study methods and materials. The first-year students were generally more positive towards teachers' incorporation of UDL.

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.641-649
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• 2004

The relationship between chemical structures and biological activities is researched briskly in the area of 'Medicinal Chemistry' At the base of these structure-based drug design tries, medicinal chemists search the existing drugs of similar chemical structure to target drug for the development of a new drug. Therefore, it is such necessary that an automatic system selects drug files that have a set of chemical moieties matching a user-defined query moiety. Substructure searching is the process of identifying a set of chemical moieties that match a specific query moiety. Testing for substructure searching was developed in the late 1950s. In graph theoretical terms, this problem corresponds to determining which graphs in a set are subgraph isomorphic to a specified query moiety. Testing for subgraph isomorphism has been proved, in the general case, to be an NP- complete problem. For the purpose of overcoming this difficulty, there were computational approaches. On the 1990s, a US patent has been granted on an atom-centered indexing scheme, used by the RS3 system; this has the virtue that the indexes generated can be searched by direct text comparison. This system is commercially used(http://www.acelrys.com/rs3). We define the RS3 system's drawback and present a new indexing scheme. The RS3 system treats substructure searching with substring matching by means of expressing chemical structure aspredefined strings. However, it has insufficient 'rerall' and 'precision‘ because it is impossible to index structures uniquely for same atom and same bond. To resolve this problem, we make the minimum-cost- spanning tree for one centered atom and describe a structure with paths per levels. Expressing 2D chemical structure into 1D a string has limit. Therefore, we break 2D chemical structure into 1D structure fragments. We present in this paper a new index technique to improve recall and precision surprisingly.

• KIISE Transactions on Computing Practices
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• v.21 no.11
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• pp.681-688
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• 2015

The k nearest neighbor (k-NN) graph construction is an important operation with many web-related applications, including collaborative filtering, similarity search, and many others in data mining and machine learning. Despite its many elegant properties, the brute force k-NN graph construction method has a computational complexity of $O(n^2)$, which is prohibitive for large scale data sets. Thus, (Key, Value)-based distributed framework, MapReduce, is gaining increasingly widespread use in Locality Sensitive Hashing which is efficient for high-dimension and sparse data. Based on the two-stage strategy, we engage the locality sensitive hashing technique to divide users into small subsets, and then calculate similarity between pairs in the small subsets using a brute force method on MapReduce. Specifically, generating a candidate group stage is important since brute-force calculation is performed in the following step. However, existing methods do not prevent large candidate groups. In this paper, we proposed an efficient algorithm for approximate k-NN graph construction by regrouping candidate groups. Experimental results show that our approach is more effective than existing methods in terms of graph accuracy and scan rate.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.80-90
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• 2002

Clustering is a useful technique for grouping data points such that points within a single group/cluster have similar characteristics. Many clustering algorithms have been developed and used in engineering applications including pattern recognition and image processing etc. Recently, it has drawn increasing attention as one of important techniques in data mining. However, clustering algorithms such as K-means and Fuzzy C-means suffer from difficulties. Those are the needs to determine the number of clusters apriori and the clustering results depending on the initial set of clusters which fails to gain desirable results. In this paper, we propose a new clustering algorithm, which solves mentioned problems. In our method we use evolutionary algorithm to solve the local optima problem that clustering converges to an undesirable state starting with an inappropriate set of clusters. We also adopt a new measure that represents how well data are clustered. The measure is determined in terms of both intra-cluster dispersion and inter-cluster separability. Using the measure, in our method the number of clusters is automatically determined as the result of optimization process. And also, we combine heuristic that is problem-specific knowledge with a evolutionary algorithm to speed evolutionary algorithm search. We have experimented our algorithm with several sets of multi-dimensional data and it has been shown that one algorithm outperforms the existing algorithms.

• The KIPS Transactions:PartD
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• v.11D no.2
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• pp.325-338
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• 2004

A data warehouse stores information that is collected from multiple, heterogeneous information sources for the purpose of complex querying and analysis. Information in the warehouse is typically stored In the form of materialized views, which represent pre-computed portions of frequently asked queries. One of the most important tasks of designing a warehouse is the selection of materialized views to be maintained in the warehouse. The goal is to select a set of views so that the total query response time over all queries can be minimized while a limited amount of time for maintaining the views is given(maintenance-cost view selection problem). In this paper, we propose an efficient solution to the maintenance-cost view selection problem using a genetic algorithm for computing a near-optimal set of views. Specifically, we explore the maintenance-cost view selection problem in the context of OR view graphs. We show that our approach represents a dramatic improvement in terms of time complexity over existing search-based approaches that use heuristics. Our analysis shows that the algorithm consistently yields a solution that only has an additional 10% of query cost of over the optimal query cost while at the same time exhibits an impressive performance of only a linear increase in execution time. We have implemented a prototype version of our algorithm that is used to evaluate our approach.

• Korea journal of population studies
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• v.31 no.3
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• pp.85-106
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• 2008

This study explores Korean youths' gender equality consciousness in an attempt to search for a way to increase youth's gender equality consciousness. First, this study carries out a survey of youths' gender equality consciousness based on questionnaires collected from a nationwide sample. Second, this study attempts to identify key points needed to evaluate youths' gender equality consciousness in terms of youths' general values. The data used for this survey is from the survey on youths' values conducted by Korean Institute for Health and Social Affairs in 2006 with a sample of 11,240 students from 132 schools nationwide. As a result, youths in 2006 had higher gender equality consciousness than that of previous years(2002). Especially, the support for the fair share of domestic work in the house by youths was significantly increased than the past. However, the survey of youths' values showed clear gender gaps in general attitudes of youths including gender equality consciousness. Female students not only had higher gender equality consciousness than male students but also had higher levels of 'universal value' which would allow one to become sensitive to discrimination and 'self development and achievement value'. In contrast, male students scored high on 'power-oriented value' related to discriminatory attitudes. Therefore, the study recommends focusing on alleviating the gender gaps through school education and other various media education.