• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.745-749
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• 2006

The appearance of wirelsss internet service made accessing easier than existing mobile devices. Due to the properity of mobile devices, we can easily obtain his/her profile information compared to a wired internet service. It enables to provide a personalized service through mobile devices. In this paper, we propose a recommendation service based on collaborative filtering method and a content push service. Using users' profile information, we recommand a target user's favoriate content. The recommanded contents are stored in mobile device through the push service. When we connect a wireless internet service, our mobile push service starts to cache from user's favorite contents. Especially, when we select a large mobile content, our system can reduce a download time by using our recommandation service. Also, in case of a connectionless, we can use a cached data from pushed content in our mobile device.

• Journal of the Korea Society of Computer and Information
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• v.17 no.5
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• pp.81-91
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• 2012

Recently, as location-determination of indoor users is available with the development of variety of localization techniques for indoor location-based service, diverse indoor location based services are proposed. Accordingly, it is necessary to develop individualized POI recommendation service for recommending most interested points of large-scale commercial spaces such as shopping malls and departments. For POI recommendation, it is necessary to study the method for exploring location which users are interested in location with considering user's mobility in large-scale commercial spaces. In this paper, we proposed POI recommendation system with the definition of users' as 'Stay point' in order to consider users' various interest locations. By using the proposed algorithm, we analysis users' Stay points, then mining the users' visiting pattern to finished the proposed. POI Recommendation System. The proposed system decreased data more dramatically than that of using user's entire mobility data and usage of memory.

• Journal of Information Technology and Architecture
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• v.10 no.2
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• pp.251-261
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• 2013

The appearance of various mobile Internet environment access to existing networks of mobile devices is easier to tell. In addition, mobile device users to use the wireless environment than a wired environment, user profile information is readily available features. Mobile devices have features that use alone. These characteristics of mobile devices to apply the personalization service is the best system. This paper proposes for mobile device users a personalized mobile music content recommendation service. This service propose to utilizes the user's access history information using time-weighting and collaborative filtering. Access history information can find out information of user interest. Using this information, consider the preference of music genre and time-weighted based on the recommendations makes the music. This method the problem of the traditional music recommendation system, point user's favorite music genre is changing over time do not consider that to solve the problem.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.5 no.1
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• pp.102-107
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• 1994

Recently several studies showed a strong and specific association of Attention-Deficit Hyperactivity Disorder(ADHD) and generalized resistance to thyroid hormone(GRTH). The recommandation that all children with ADHD be screened for GRTH is an newer controversial issue in child psychiatric field. Author examined thyroid indices(T3, T4, TSH) and clinical characteristics in the 51 clinical populations with ADHD, developmental delay, and language disorders. The results are that 11 cases were out of the normal range of both T2 and T4 inspite of normal TSH. This finding is suggestive of the finding of GRTH cases. Therefore I suggest that child psychiatrist should pay attention to ADHD symptoms secondary to GRTH and that all children with familial ADHD and developmental delay(including launguage disorder) be screened for thyroid abnormalities.

• Korean Journal of Soil Science and Fertilizer
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• v.35 no.3
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• pp.162-168
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• 2002

The silica uptake of rice plant(Oryza sativa L.) and a potential capacity of paddy soil as a source of silica supply for rice plant was studied under field experimental condition. Amount of Si from irrigation water, rainfall, which was a source of silica supply, and percolating rate of water through paddy soil profile as a source of silica loss from paddy soil, was investigated. Rice plants were grown in three different conditions, which included Control as non-fertilized, RDA's recommandation(NPK, Urea-Fused phophate-Potassium chloride=$110-45-57kg\;ha^{-1}$) and RDA's recommandation with supplement of silicate fertilizer(NPK+Si, Urea-Fused phosphate-Potassium chloride+Si=$110\;N-45\;P_2O_5-57\;K_2O+267.2\;Si\;kg\;ha^{-1}$). An amount of silica supply from rainfall was $0.5kg\;ha^{-1}$ and average amount of silica supplied from irrigation water $42.5kg\;ha^{-1}$, ranging from $28.1kg\;ha^{-1}$ to $58.8kg\;ha^{-1}$. Silica amount percolated through the soil profile have uniform trend comparatively showing $62.9kg\;ha^{-1}$ in Control, $64.8kg\;ha^{-1}$ in NPK treatment and $62.9kg\;ha^{-1}$ in NPK+Si treatment. Silica uptaked by Rice plant was $335.6kg\;ha^{-1}$ in Control, $406.6kg\;ha^{-1}$ in NPK+Si treatment and $471.1kg\;ha^{-1}$ in NPK+Si treatment. The difference between an amount of Si input(from rainfall, irrigation water and silicate fertilizer) and an amount of Si output(percolated Si in soil, uptaked Si by rice plant) was $357.4kg\;ha^{-1}$ in control, $412.1kg\;ha^{-1}$ in NPK treatment and $238.2kg\;ha^{-1}$ in NPK+Si treatment. Results of our study imply that paddy soil is a potential pool as a source of Si supply during growing periods of rice plant.

• Journal of Gifted/Talented Education
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• v.24 no.4
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• pp.577-595
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• 2014

The purpose of this research was to investigate the possibility of peer recommendation and to provide a diverse perspectives identifying for gifted elementary school students. The subjects were 355 elementary school students who were either fourth, fifth, and sixth grade from D elementary school located in Gyeonggi province, 165 elementary school students who are either fourth, fifth, and sixth grade from J elementary school located in Gyeonggi province, and 16 teachers who were home-room teachers for students surveyed. This research investigate the difference of creative personality, achievement motivation, problem solving patterns, and task preference inventory between students recommended by peer and students not recommended by peer. The results of this research were as follows. Firstly, the students recommended by peer showed the significantly higher creative personality, achievement motivation, problem solving patterns, and task preference than the student not recommended by peer. Secondly, as a result of comparing the students recommended by peer and students not recommended by peer for each grade, fifth and sixth grade students showed a significantly higher score in the test than other graders. Fourth grade students showed significantly higher score in every sections in the test, except for the section of creative personality. Therefore, the peer recommandation method can be applied to fifth, and sixth graders. Thirdly, the student recommended by both teacher and peer showed significantly higher problem solving patterns, and task preference scores than the student recommended only by teacher. Therefore, peer recommendation method can be an useful data for complementing teacher recommendation and it can identify gifted elementary school students.

• The Journal of the Korean life insurance medical association
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• v.22
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• pp.55-98
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• 2003

본 연구는 질병별사망율연구(疾病別死亡率硏究)의 이론적 기초를 제시하고 일본 선진보험사의 질병별사망율연구(疾病別死亡率硏究)의 경험을 고찰하고 국내 보험사들의 질병사망율연관데이터의 현황분석을 통해 향후 질병별사망율연구(疾病別死亡率硏究)의 결과를 얻기 위해 현재 보험사들이 전사적으로 준비하여야 할 것에 대해 제언을 하고자 한다. 사망률연구(mortality study)란 인구통계학적 개념을 기본으로 하여 역학적 연구방법의 하나인 코호트방법과 생존분석방법을 결합하여 인구집단(또는 피보험자 집단)을 대상으로 대량의 자료를 장기적으로 관찰하여 그 사망의 빈도와 분포를 기술하고 사망연관지수들을 알아내어 생명보험사업에 있어서 위험선택기술을 향상시키는 것이다. 초과사망을 및 사망비 산출의 실제를 생명표 방법론과 급성심근 경색증 환자의 생존 분석을 통해 알아본다. 생명표 방법론을 이용한 생존 분석방법이란 의학저널에서 발표된 논문을 사망률표로 변경하기 위한 필수적인 단계에 대한 것이다 관찰된 생존 곡선을 생명표 작성법의 한 방법인 비교 경험 사망률로 바꾸는데 초점을 두었다. 일본생명(日本生命)의 경우, 일본 협영생명(協塋生命)의 경우, 일본사망율조사(MA)위원회 생명보험사망을 연구고서등을 통해 질병별사망율연구(疾病別死亡率硏究)를 살펴 보았다. 일본은 질병별사망율(疾病別死亡率)을 구하기 위해서 1950년대 이후부터 체계적으로 자료를 모으고 축적, 분석하여 지속성을 유지하였다. 또한 일본MA위원회의 경우처럼 보험의학의사, 계리, 통계, 전산부서로 구성된 전담위원회의 통일된 협조가 질병별사망율연구(疾病別死亡率硏究)를 가능하게 하였다. 그리고 의학적인 관점에서 볼 때 일본보험의학계는 일본만의 독특한 질병분류로 분석하여 온 것이 특이하다. 질병별사망율연구(疾病別死亡率硏究)에 대해서는 모두가 필요성을 인정하면서도 구체적인 대비책은 없는 것이 우리나라 보험업계의 실정이다. 이러한 현실의 직접적인 이유는 질병별사망율연구(疾病別死亡率硏究)라는 것이 그 특성상 중장기적인 계획이며 많은 전문인력의 통합되고 집중된 노력이 요구되기 때문이다. 우리도 "생명보험사사망율연구위원회(Life Insurance Mortality Committee" (가칭)를 설치하고 장기적인 계획안을 먼저 만드는 것이 선행되어야 할 것이다. 지금부터 질병별사망율(疾病別死亡率) 데이터를 축적하고 매 5년 또는 매 10년마다 데이터를 분석한다면 질병별사망율(疾病別死亡率)에 대해 고유의 기술을 습득하는 것이 그리 먼 미래의 일만은 아닐 것이다.

• Restorative Dentistry and Endodontics
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• v.27 no.5
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• pp.502-514
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• 2002

The aim of this study was to evaluate the marginal adaptation of direct class II sandwich restoration with packable composites(P-60), resin modified glass ionomer cement(Fuji-II LC), flowable compomer(Dyract Flow), flowable composites(Filtek Flow) in comparison with total bond restorations. In addition, for sandwich restorations, influence of different sandwich techniques was also evaluated. Large butt-joint box typed class II cavites with cervical margins 1mm below the cemento-enamel junction were cut into 70 extracted human molars. The cavities(7 groups, n=10) were filled using a closed/open sandwich restoration or total bond restoration technique with materials according to the manufacturer's recommandation using the single-component bonding agent for each system. Teeth were thermocycled 500 times between 5$^{\circ}C$ and 55$^{\circ}C$ with 30-second dwell time. The teeth were then coated with nail polish 1mm short of the restoration, placed in a 2% methylene blue for 24 hours, and sectioned with diamond wheel. Sections were examined with a stereoscope to determine the extent of microleakage. Dentine /Cementum margins were analyzed for microleakage on scale of 0(no leakage) to 4(entire axial wall) and interface between materials, on scale of 0(no leakage) to 3(axial wall). Results were evaluated with Kruskal Wallis Test, corrected for ties, to determine whether there were statistically significant differences among the seven groups. Pairs of groups were analyzed using the Student-Newman-Keuls Method and Dunn s Method. The results were as follows : 1. All groups showed some micoleakage in cervical portion. But there were no microleakage in interface between materials. 2. Closed sandwich restorations with Fuji-II LC and Filtek Flow had significantly lower leakage rating than total restorations with only P-60. However, open sandwich restorations with Dyract Flow showed significantly higher (P<0.05) 3. Closed sandwich restorations had significantly lower leakage rating than total restorations. However open sandwich restoration s showed significantly higher (P<0.05). 4. Sandwich restorations with Fuji-II LC were iou$.$or leakage than only P-60. Filtek Flow, Dyract Flow. But there were no statistically differences among the materials. From the results above, it could be concluded, closed sandwich restorations was effective in reducing microleakage of class II restorations. The best results showing the least microleakage were for the closed sandwich technique with Fuji-II LC and Filtek Flow.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1599-1607
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• 2022

The data mainly used for the model are as follows: the personal information, the information of insurance product, etc. With the data, we suggest three types of models: content-based filtering model, collaborative filtering model and classification models-based model. The content-based filtering model finds the cosine of the angle between the users and items, and recommends items based on the cosine similarity; however, before finding the cosine similarity, we divide into several groups by their features. Segmentation is executed by K-means clustering algorithm and manually operated algorithm. The collaborative filtering model uses interactions that users have with items. The classification models-based model uses decision tree and random forest classifier to recommend items. According to the results of the research, the contents-based filtering model provides the best result. Since the model recommends the item based on the demographic and user features, it indicates that demographic and user features are keys to offer more appropriate items.