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Resolving the 'Gray sheep' Problem Using Social Network Analysis (SNA) in Collaborative Filtering (CF) Recommender Systems (소셜 네트워크 분석 기법을 활용한 협업필터링의 특이취향 사용자(Gray Sheep) 문제 해결)

  • Kim, Minsung;Im, Il
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.137-148
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    • 2014
  • Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used

    . Past studies to improve CF performance typically used additional information other than users' evaluations such as demographic data. Some studies applied SNA techniques as a new similarity metric. This study is novel in that it used SNA to separate dataset. This study shows that performance of CF can be improved, without any additional information, when SNA techniques are used as proposed. This study has several theoretical and practical implications. This study empirically shows that the characteristics of dataset can affect the performance of CF recommender systems. This helps researchers understand factors affecting performance of CF. This study also opens a door for future studies in the area of applying SNA to CF to analyze characteristics of dataset. In practice, this study provides guidelines to improve performance of CF recommender systems with a simple modification.

  • A Study on the Determinants of Patent Citation Relationships among Companies : MR-QAP Analysis (기업 간 특허인용 관계 결정요인에 관한 연구 : MR-QAP분석)

    • Park, Jun Hyung;Kwahk, Kee-Young;Han, Heejun;Kim, Yunjeong
      • Journal of Intelligence and Information Systems
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      • v.19 no.4
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      • pp.21-37
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      • 2013
    • Recently, as the advent of the knowledge-based society, there are more people getting interested in the intellectual property. Especially, the ICT companies leading the high-tech industry are working hard to strive for systematic management of intellectual property. As we know, the patent information represents the intellectual capital of the company. Also now the quantitative analysis on the continuously accumulated patent information becomes possible. The analysis at various levels becomes also possible by utilizing the patent information, ranging from the patent level to the enterprise level, industrial level and country level. Through the patent information, we can identify the technology status and analyze the impact of the performance. We are also able to find out the flow of the knowledge through the network analysis. By that, we can not only identify the changes in technology, but also predict the direction of the future research. In the field using the network analysis there are two important analyses which utilize the patent citation information; citation indicator analysis utilizing the frequency of the citation and network analysis based on the citation relationships. Furthermore, this study analyzes whether there are any impacts between the size of the company and patent citation relationships. 74 S&P 500 registered companies that provide IT and communication services are selected for this study. In order to determine the relationship of patent citation between the companies, the patent citation in 2009 and 2010 is collected and sociomatrices which show the patent citation relationship between the companies are created. In addition, the companies' total assets are collected as an index of company size. The distance between companies is defined as the absolute value of the difference between the total assets. And simple differences are considered to be described as the hierarchy of the company. The QAP Correlation analysis and MR-QAP analysis is carried out by using the distance and hierarchy between companies, and also the sociomatrices that shows the patent citation in 2009 and 2010. Through the result of QAP Correlation analysis, the patent citation relationship between companies in the 2009's company's patent citation network and the 2010's company's patent citation network shows the highest correlation. In addition, positive correlation is shown in the patent citation relationships between companies and the distance between companies. This is because the patent citation relationship is increased when there is a difference of size between companies. Not only that, negative correlation is found through the analysis using the patent citation relationship between companies and the hierarchy between companies. Relatively it is indicated that there is a high evaluation about the patent of the higher tier companies influenced toward the lower tier companies. MR-QAP analysis is carried out as follow. The sociomatrix that is generated by using the year 2010 patent citation relationship is used as the dependent variable. Additionally the 2009's company's patent citation network and the distance and hierarchy networks between the companies are used as the independent variables. This study performed MR-QAP analysis to find the main factors influencing the patent citation relationship between the companies in 2010. The analysis results show that all independent variables have positively influenced the 2010's patent citation relationship between the companies. In particular, the 2009's patent citation relationship between the companies has the most significant impact on the 2010's, which means that there is consecutiveness regarding the patent citation relationships. Through the result of QAP correlation analysis and MR-QAP analysis, the patent citation relationship between companies is affected by the size of the companies. But the most significant impact is the patent citation relationships that had been done in the past. The reason why we need to maintain the patent citation relationship between companies is it might be important in the use of strategic aspect of the companies to look into relationships to share intellectual property between each other, also seen as an important auxiliary of the partner companies to cooperate with.

    The recent essay of Bijeung - Study of III- (비증(痺證)에 대(對)한 최근(最近)의 제가학설(諸家學說) 연구(硏究) - 《비증전집(痺證專輯)》 에 대(對)한 연구(硏究) III -)

    • Yang, Tae-Hoon;Oh, Min-Suk
      • Journal of Haehwa Medicine
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      • v.9 no.1
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      • pp.513-545
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      • 2000
    • I. Introduction Bi(痺) means blocking. It can reach at the joints or muscles or whole body and make pains. Numbness and movement disorders. BiJeung can be devided into SilBi and HeoBi. In SilBi there are PungHanSeupBi, YeolBi and WanBi. In HeoBi, there are GiHyeolHeoBi, EumHeoBi and YangHeoBi. The common principle for the treatment of BiJeung is devision of the chronic stage and the acute stage. In the acute stage, BiJeung is usually cured easily but in the chronic stage, it is difficult. In the terminal stage, BiJeung can reach at the internal organs. BiJeung is one kind of symptoms making muscles, bones and jonts feel pain, numbness or edema. For example it can be gout or SLE etc. Many famous doctors studied medical science by their fathers or teachers. So the history of medical science is long. So I studied ${\ll}Bijeungjujip{\gg}$. II. Final Decision 1. BanSuMun(斑秀文) thought that BiJeung can be cured by blocking of blood stream. So he insisted that the important thing to cure BiJeung is to improve the blood stream. He usually used DangGuiSaYeokTang(當歸四逆湯), DangGuiJakYakSanHapORyeongSan, DoHong-SaMulTang(桃紅四物湯), SaMyoSanHapHeuiDongTang and HwangGiGyeJiOMulTang. 2. JangGeonBu(張健夫) focused on soothing muscles and improving blood seam. So he used many herbs like WiRyeongSeon(威靈仙), GangHwal(羌活), DokHwal(獨活), WooSeul(牛膝), etc. Especially he pasted wastes of the boiled herbs. 3. OSeongNong(吳聖農) introduced four rules to treat arthritis. So he usually used SeoGak-SanGaGam(犀角散加減), BoYanHwanOTang(補陽還五湯), ODuTang(烏頭湯), HwangGiGyeJiOMulTang. 4. GongJiSin thought disk hernia as one kind of BiJeung. And he said that Pung can hurt upper limbs and Seup can hurt lower limbs. He used to use GyeJiJakYakJiMoTang(桂枝芍藥知母湯). 5. LoJiJeong(路志正) introduced four principles to treat BiJeung. He used BangPungTang(防風湯), DaeJinGuTang) for PungBi(風痺), OPaeTang(烏貝湯) for HanBi(寒痺), YukGunJaTang(六君子湯) for SeupBi(濕痺) and SaMyoTang(四妙湯), SeonBiTang(宣痺湯), BaekHoGaGyeTang(白虎加桂湯) for YeolBi(熱痺). 6. GangChunHwa(姜春華) discussed herbs. He said SaengJiHwang(生地黃) is effective for PungSeupBi and WiRyungSun(威靈仙) is effective for the joints pain. He usually used SipJeonDaeBoTang(十全大補湯), DangGuiDaeBoTang(當歸大補湯), YoukGunJaTang(六君子湯) and YukMiJiHwanTang(六味地黃湯). 7. DongGeonHwa(董建華) said that the most important thing to treat BiJeung is how to use herbs. He usually used CheonO(川烏), MaHwang(麻黃) for HanBi, SeoGak(犀角) for YeolBi, BiHae) or JamSa(蠶沙) for SeupBi, SukJiHwang(熟地黃) or Vertebrae of Pigs for improving the function of kidney and liver, deer horn or DuChung(杜沖) for improving strength of body and HwangGi(黃?) or OGaPi(五加皮) for improving the function of heart. 8. YiSuSan(李壽山) devided BiJeung into two types(PungHanSeupBi, PungYeolSeupBi). And he used GyeJiJakYakJiMoTang(桂枝芍藥知母湯) for the treatment of gout. And he liked to use HwanGiGyeJiOMulTangHapSinGiHwan 枝五物湯合腎氣丸) for the treat ment of WanBi(頑痺). 9. AnDukHyeong(顔德馨) made YongMaJeongTongDan(龍馬定痛丹)-(MaJeonJa(馬錢子) 30g, JiJaChung 3g, JiRyong(地龍) 3g, JeonGal(全蝎) 3g, JuSa(朱砂) 0.3g) 10. JangBaekYou(張伯臾) devided BiJeung into YeolBi and HanBi. And he focused on improving blood stream. 11. JinMuO(陳茂梧) introduced anti-wind and dampness prescription(HoJangGeun(虎杖根) 15g, CheonChoGeun 15g, SangGiSaeng(桑寄生) 15g, JamSa(蠶絲) 15g, JeMaJeonJa(制馬錢子) 3g). 12. YiChongBo(李總甫) explained basic prescriptions to treat BiJeung. He used SinJeongChuBiEum(新定推痺陰) for HaengBi(行痺), SinJeongHwaBiSan(新定化痺散) for TongBi(痛痺), SinJeongGaeBiTang(新定開痺湯) for ChakBi(着痺), SinJeongCheongBiEum(新定淸痺飮) for SeupYeolBi(濕熱痺), SinRyeokTang(腎瀝湯) for PoBi(胞痺), ORyeongSan for BuBi(腑痺), OBiTang(五痺湯) for JangBi(臟痺), SinChakTang(腎着湯) for SingChakByeong(腎着病). 13. HwangJeonGeuk(黃傳克) used SaMu1SaDeungHapJe(四物四藤合制) for the treatment of a acute arthritis, PalJinHpPalDeungTang(八珍合八藤湯) or BuGyeJiHwangTangHapTaDeungTang(附桂地黃湯合四藤湯) for the chronic stage and ByeolGapJeungAekTongRakEum(鱉甲增液通絡飮) for EumHeo(陰虛) 14. GaYeo(柯與參) used HwalRakJiTongTang(活絡止痛湯) for shoulder ache, SoJongJinTongHwalRakTank(消腫鎭痛活絡湯) for YeolBi(熱痺), LiGwanJeolTang(利關節湯) for ChakBi(着痺), SinBiTang(腎痺湯) for SinBi(腎痺) and SamGyoBoSinHwan(三膠補腎丸) for back ache. 15. JangGilJin(蔣길塵) liked to use hot-character herbs and insects. And he used SeoGeunLipAnTang(舒筋立安湯) as basic prescription. 16. RyuJangGeol(留章杰) used GuMiGangHwalTang(九味羌活湯) and BangPungTang(防風湯) at the acute stage, ODuTang(烏頭湯) or GyeJiJakYakJiMoTang(桂枝芍藥知母湯) for HanBi of internal organs, YangHwaHaeEungTang(陽和解凝湯) for HanBi, DokHwalGiSaengTang(獨活寄生湯), EuiYiInTang(薏苡仁湯) for SeupBi, YukGunJaTang(六君子湯) for GiHeoBi(氣虛痺) and SeongYouTang(聖兪湯) for HyeolHeoBi(血虛痺). 17. YangYuHak(楊有鶴) liked to use SoGyeongHwalHyelTang(疏經活血湯) and he would rather use DoIn(桃仁), HongHwa(紅花), DangGui(當歸), CheonGung(川芎) than insects. 18. SaHongDo(史鴻濤) made RyuPungSeupTang(類風濕湯)-((HwangGi 200g, JinGu 20g, BangGi(防己) 15g, HongHwa(紅花) 15g, DoIn(桃仁) 15g, CheongPungDeung(靑風藤) 20g, JiRyong(地龍) 15g, GyeJi(桂枝) 15g, WoSeul(牛膝) 15g, CheonSanGap(穿山甲) 15g, BaekJi(白芷) 15g, BaekSeonPi(白鮮皮) 15g, GamCho(甘草) 15g).

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    Study of BiJeung by 18 doctors - Study of II - (18인(人)의 비증(痺證) 논술(論述)에 대(對)한 연구(硏究) - 《비증전집(痺證專輯)》 에 대(對)한 연구(硏究) II -)

    • Sohn, Dong Woo;Oh, Min Suk
      • Journal of Haehwa Medicine
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      • v.9 no.1
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      • pp.595-646
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      • 2000
    • I. Introduction Bi(痺) means blocking. BiJeung is one kind of symptoms making muscles, bones and jonts feel pain, numbness or edema. For example it can be gout or SLE etc. says that Bi is combination of PungHanSeup. And many doctors said that BiJeung is caused by food, fatigue, sex, stress and change of weather. Therefore we must treat BiJeung by character of patients and characteristic of the disease. Many famous doctors studied medical science by their fathers or teachers. So the history of medical science is long. So I studied ${\ll}Bijeungjujip{\gg}$. II. Final Decision 1. JoGeumTak(趙金鐸) devided BiJeung into Pung, Han, Seup and EumHeo, HeulHeo, YangHeo, GanSinHeo by charcter or reaction of pain. And he use DaeJinGyoTang, GyegiGakYakJiMoTang, SamyoSan, etc. 2. JangPaeGyeu(張沛圭) focused on division of HanYeol(寒熱; coldness and heat) in spite of complexity of BiJeung. He also used insects for treatment. They are very useful for treatment of BiJeung because they can remove EoHyeol(瘀血). 3. SeolMaeng(薛盟) said that the actual cause of BiJeung is Seup. So he thought that BiJeung can be divided into PungSeup, SeupYeol, HanSeup. And he established 6 rules to treat BiJeung and he studied herbs. 4. JangGi(張琪) introduced 10 prescriptions and 10 rules to cure BiJeung. The 1st prescription is for OyeSa, 2nd for internal Yeol, 3rd for old BiJeung, 4th for Soothing muscles, 5th for HanSeup, 6th for regular BiJeung, 7th for functional disorder, 8th for YeolBi, 9th for joint pain and 10th for pain of lower limb. 5. GangSeYoung(江世英) used PungYeongTang(風靈湯) for the treatment of PungBi, OGyeHeukHoTang(烏桂黑虎湯) for HanBi, BangGiMokGwaTang(防己木瓜湯) for SeupBi, YeolBiTang(熱痺湯) for YeolBi, WoDaeRyeokTang(牛大力湯) for GiHei, HyeolPungGeunTang(血楓根湯) for HyeolHeo, ToJiRyongTang(土地龍湯) for the acute stage of SeupBi, OJoRyongTang(五爪龍湯) for the chronic stage of SeupBi, and so on. 6. ShiGeumMook(施今墨) devided BiJeung into four types. They are PungSeupYeol, PungHanSeup, GiHyeolSil(氣血實) and GiHyeolHeo(氣血虛). And he introduced the eight rules of the treatment(SanPun(散風), ChukHan(逐寒), GeoSeuP(, CheongYeol(淸熱), TongRak(通絡), HwalHyeol(活血), HaengGi(行氣), BoHeo(補虛)). 7. WangYiYou(王李儒) explained the acute athritis and said that it can be applicable to HaneBi(行痺). And he used GyeJiJakYakJiMoTang(桂枝芍蘂知母湯) for HanBi and YeolBiJinTongTang(熱痺鎭痛湯) for YeolBi. 8. JangJinYeo(章眞如) said that YeolBi is more common than HanBi. The sympthoms of YeolBi are severe pain, fever, dried tongue, insomnia, etc. And he devided YeolBi into SilYeol and HeoYeol. In case of SilYeol, he used GyeoJiTangHapBaekHoTang(桂枝湯合白虎湯) and in case of HeoYeol he used JaEumYangAekTang(滋陰養液湯). 9. SaHaeJu(謝海洲) introduced three important rules of treatment and four appropriate rules of treatment of BiJeung. 10. YouDoJu(劉渡舟) said that YeolBi is more common than HanBi. He used GaGamMokBanGiTang(加減木防已湯) for YeolBi, GyeJiJakYakJiMoTang or GyeJiBuJaTang(桂枝附子湯) for HanBi and WooHwangHwan(牛黃丸) for the joint pain. 11. GangYiSon(江爾遜) focused on the internal cause. The most important internal cause is JeongGiHeo(正氣虛). So he tried to treat BiJeung by means of balance of Gi and Hyeol. So he ususlly used ODuTang(烏頭湯) and SamHwangTang(三黃湯) for YeolBi, OJeokSan(五積散) for HanBi, SamBiTang(三痺湯) for the chronic BiJeung. 12. HoGeonHwa(胡建華) said that to distinguish YeolBi from Hanbi is very difficult. So he used GyeJiJakYakJiMoTang in case of mixture of HanBi and YeoBi. 13. PiBokGo(畢福高) said that the most common BiJeung is HanBi. He usually used acupuncture with medicine. He followed the theory of EumYongHwa(嚴用和)-he focused on SeonBoHuSa(先補後瀉). 14. ChoiMunBin(崔文彬) used GeoPungHwalHyeolTang(祛風活血湯) for HanBi, SanHanTongRakTang(散寒通絡湯) for TongBi(痛痺), LiSeupHwaRakTang(利濕和絡湯) for ChakBi(着痺), CheongYeolTongGyeolChukBiTang(淸熱通經逐痺湯) for YeolBi(熱痺) and GeoPungHwalHyeolTang(祛風活血湯) for PiBi(皮痺). 15. YouleokSeon(劉赤選) introduced the common principle for the treatment of BiJeung. He used HaePuneDeungTang(海風藤湯) for HaengBi(行痺), SinChakTang(腎着湯), DokHwalGiSaengTang(獨活寄生湯) for TongBi(痛痺), TongPungBang(痛風方) for ChakBi(着痺) and SangGiYiMiTangGaYeongYangGakTang(桑枝苡米湯加羚羊角骨) for YeolBi(熱痺). 16. LimHakHwa(林鶴和) said about TanTan(movement disorders or numbness) and devided TanTan into the acute stage and the chronic stage. He used acupuncture at the meridian spot like YeolGyeol(列缺), HapGok(合谷), etc. And he also used MaHwangBuJaSeSinTang(麻黃附子細辛湯) in case of the acute stage. In the chronic stage he used BangPungTang(防風湯). 17. JinBaekGeun(陳伯勤) liked to use three rules(HwaHyeol(活血), ChiDam(治痰), BoSin(補腎)) to treat BiJeung. He used JinTongSan(鎭痛散) for the purpose of HwalHyeol(活血), SoHwalRakDan(小活絡丹) for ChiDam(治痰) and DokHwalGiSaengTang(獨活寄生湯) for BoSin(補腎). 18. YimGyeHak(任繼學) focused on YangHyeolJoGi(養血調氣) if the stage of BiJeung is chronic. And in the chronic stage he insisted on not using GalHwal(羌活), DokHwal(獨活) and BangPung(防風).

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    The Effect of Two Terpenoids, Ursolic Acid and Oleanolic Acid on Epidermal Permeability Barrier and Simultaneously on Dermal Functions (우솔릭산과 올레아놀산이 피부장벽과 진피에 미치는 영향에 대한 연구)

    • Suk Won, Lim;Sung Won, Jung;Sung Ku, Ahn;Bora, Kim;In Young, Kim;Hee Chang , Ryoo;Seung Hun, Lee
      • Journal of the Society of Cosmetic Scientists of Korea
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      • v.30 no.2
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      • pp.263-278
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      • 2004
    • Ursolic acid (UA) and Oleanolic acid (ONA), known as urson, micromerol and malol, are pentacyclic triterpenoid compounds which naturally occur in a large number of vegetarian foods, medicinal herbs, and plants. They may occur in their free acid form or as aglycones for triterpenoid saponins, which are comprised of a triterpenoid aglycone, linked to one or more sugar moieties. Therefore UA and ONA are similar in pharmacological activity. Lately scientific research, which led to the identification of UA and ONA, revealed that several pharmacological effects, such as antitumor, hepato-protective, anti-inflammatory, anticarcinogenic, antimicrobial, and anti-hyperlipidemic could be attributed to UA and ONA. Here, we introduced the effect of UA and ONA on acutely barrier disrupted and normal hairless mouse skin. To evaluate the effects of UA and ONA on epidermal permeability barrier recovery, both flanks of 8-12 week-old hairless mice were topically treated with either 0.01-0.1mg/mL UA or 0.1-1mg/mL ONA after tape stripping, and TEWL (transepidermal water loss) was measured. The recovery rate increased in those UA or ONA treated groups (0.1mg/mL UA and 0.5mg/mL ONA) at 6h more than 20% compared to vehicle treated group (p < 0.05). Here, we introduced the effects of UA and ONA on acute barrier disruption and normal epidermal permeability barrier function. For verifying the effects of UA and ONA on normal epidermal barrier, hydration and TEWL were measured for 1 and 3 weeks after UA and ONA applications (2mg/mL per day). We also investigated the features of epidermis and dermis using electron microscopy (EM) and light microscopy (LM). Both samples increased hydration compared to vehicle group from 1 week without TEWL alteration (p < 0.005). EM examination using RuO4 and OsO4 fixation revealed that secretion and numbers of lamellar bodies and complete formation of lipid bilayers were most prominent (ONA=UA > vehicle). LM finding showed that thickness of stratum corneum (SC) was slightly increased and especially epidermal thickening and flattening was observed (UA > ONA > vehicle). We also observed that UA and ONA stimulate epidermal keratinocyte differentiation via PPAR Protein expression of involucrin, loricrin, and filaggrin increased at least 2 and 3 fold in HaCaT cells treated with either ONA (10${\mu}$M) or UA (10${\mu}$M) for 24 h respectively. This result suggested that the UA and ONA can improve epidermal permeability barrier function and induce the epidermal keratinocyte differentiation via PPAR Using Masson-trichrome and elastic fiber staining, we observed collagen thickening and elastic fiber elongation by UA and ONA treatments. In vitro results of collagen and elastin synthesis and elastase inhibitory activity measurements were also confirmed in vivo findings. These data suggested that the effects of UA and ONA related to not only epidermal permeability barrier functions but also dermal collagen and elastic fiber synthesis. Taken together, UA and ONA can be relevant candidates to improve epidermal and dermal functions and pertinent agents for cosmeseutical applications.

    A comparative study on the correlation between Korean foods and the fractures of PFG and all ceramic crowns for posterior applications (구치용 도재소부금관과 전부도재관에 파절을 일으키는 한국음식에 관한 연구)

    • Kim, Jeong-Ho;Lee, Jai-Bong
      • The Journal of Korean Academy of Prosthodontics
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      • v.47 no.2
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      • pp.156-163
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      • 2009
    • Statement of problem: Recently, there have been increased esthetic needs for posterior dental restorations. The failure of posterior dental ceramic restoration are possible not only by the characters of the component materials but also by the type of food. Purpose: The research aim was to compare the in vitro fracture resistance of simulated first molar crowns fabricated using 4 dental ceramic systems, full-porcelain-occlusal-surfaced PFG, half-porcelain-occlusal-surfaced PFG, Empress 2, Ice Zirkon and selected Korean foods. Material and methods: Eighty axisymmetric crowns of each system were fabricated to fit a preparation with 1.5- to 2.0-mm occlusal reduction. The center of the occlusal surface on each of 15 specimens per ceramic system was axially loaded to fracture in a Instron 4465, and the maximum load(N) was recorded. Afterwards, selected Korean foods specimens(boiled crab, boiled chicken with bone, boiled beef rib, dried squid, dried anchovy, round candy, walnut shell) were prepared. 15 specimens per each food were placed under the Instron and the maximum fracture loads for them were recorded. The 95% confidence intervals of the characteristic failure load were compared between dental ceramic systems and Korean foods. Afterwards, on the basis of previous results, 14Hz cyclic load was applied on the 4 systems of dental ceramic restorations in MTS. The reults were analyzed by analysis of variance and Post Hoc tests. Results: 95% confidence intervals for mean of fracture load 1. full porcelain occlusal surfaced PFG Crown: 2599.3 to 2809.1 N 2. half porcelain occlusal surfaced PFG Crown: 3689.4 to 3819.8 N 3. Ice Zirkon Crown: 1501.2 to 1867.9 N 4. Empress 2 Crown: 803.2 to 1188.5 N 5. boiled crab: 294.1 to 367.9 N 6. boiled chicken with bone: 357.1 to 408.6 N 7. boiled beef rib: 4077.7 to 4356.0 N 8. dried squid: 147.5 to 190.5 N 9. dried anchovy: 35.6 to 46.5 N 10. round candy: 1900.5 to 2615.8 N 11. walnut shell: 85.7 to 373.1 N under cyclic load(14Hz) in MTS, fracture load and masticatory cycles are: 1. full porcelain occlusal surfaced PFG Crown fractured at 95% confidence intervals of 4796.8-9321.2 cycles under 2224.8 N(round candy)load, no fracture under smaller loads. 2. half porcelain occlusal surfaced PFG Crown fractured at 95% confidence intervals of 881705.1-1143565.7 cycles under 2224.8 N(round candy). no fracture under smaller loads. 3. Ice Zirkon Crown fractured at 95% confidence intervlas of 979993.0-1145773.4 cycles under 382.9 N(boiled chicken with bone). no fracture under smaller loads. 4. Empress 2 Crown fractured at 95% confidence intervals of 564.1-954.7 cycles under 382.9 N(boiled chicken with bone). no fracture under smaller loads. Conclusion: There was a significant difference in fracture resistance between experimental groups. Under single load, Korean foods than can cause fracture to the dental ceramic restorations are boiled beef rib and round candy. Even if there is no fracture under single load, cyclic dynamic load can fracture dental posterior ceramic crowns. Experimental data with 14 Hz dynamic cyclic load are obtained as follows. 1. PFG crown(full porcelain occlusion) was failed after mean 0.03 years under fracture load for round candy(2224.8 N). 2. PFG crown(half porcelain occlusion) was failed after mean 4.1 years under fracture load for round candy(2224.8 N). 3. Ice Zirkon crown was failed after mean 4.3 years under fracture load for boiled chicken with bone(382.9 N). 4. Empress 2 crown was failed after mean 0.003 years under fracture load for boiled chicken with bone(382.9 N).

    Pareto Ratio and Inequality Level of Knowledge Sharing in Virtual Knowledge Collaboration: Analysis of Behaviors on Wikipedia (지식 공유의 파레토 비율 및 불평등 정도와 가상 지식 협업: 위키피디아 행위 데이터 분석)

    • Park, Hyun-Jung;Shin, Kyung-Shik
      • Journal of Intelligence and Information Systems
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      • v.20 no.3
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      • pp.19-43
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      • 2014
    • The Pareto principle, also known as the 80-20 rule, states that roughly 80% of the effects come from 20% of the causes for many events including natural phenomena. It has been recognized as a golden rule in business with a wide application of such discovery like 20 percent of customers resulting in 80 percent of total sales. On the other hand, the Long Tail theory, pointing out that "the trivial many" produces more value than "the vital few," has gained popularity in recent times with a tremendous reduction of distribution and inventory costs through the development of ICT(Information and Communication Technology). This study started with a view to illuminating how these two primary business paradigms-Pareto principle and Long Tail theory-relates to the success of virtual knowledge collaboration. The importance of virtual knowledge collaboration is soaring in this era of globalization and virtualization transcending geographical and temporal constraints. Many previous studies on knowledge sharing have focused on the factors to affect knowledge sharing, seeking to boost individual knowledge sharing and resolve the social dilemma caused from the fact that rational individuals are likely to rather consume than contribute knowledge. Knowledge collaboration can be defined as the creation of knowledge by not only sharing knowledge, but also by transforming and integrating such knowledge. In this perspective of knowledge collaboration, the relative distribution of knowledge sharing among participants can count as much as the absolute amounts of individual knowledge sharing. In particular, whether the more contribution of the upper 20 percent of participants in knowledge sharing will enhance the efficiency of overall knowledge collaboration is an issue of interest. This study deals with the effect of this sort of knowledge sharing distribution on the efficiency of knowledge collaboration and is extended to reflect the work characteristics. All analyses were conducted based on actual data instead of self-reported questionnaire surveys. More specifically, we analyzed the collaborative behaviors of editors of 2,978 English Wikipedia featured articles, which are the best quality grade of articles in English Wikipedia. We adopted Pareto ratio, the ratio of the number of knowledge contribution of the upper 20 percent of participants to the total number of knowledge contribution made by the total participants of an article group, to examine the effect of Pareto principle. In addition, Gini coefficient, which represents the inequality of income among a group of people, was applied to reveal the effect of inequality of knowledge contribution. Hypotheses were set up based on the assumption that the higher ratio of knowledge contribution by more highly motivated participants will lead to the higher collaboration efficiency, but if the ratio gets too high, the collaboration efficiency will be exacerbated because overall informational diversity is threatened and knowledge contribution of less motivated participants is intimidated. Cox regression models were formulated for each of the focal variables-Pareto ratio and Gini coefficient-with seven control variables such as the number of editors involved in an article, the average time length between successive edits of an article, the number of sections a featured article has, etc. The dependent variable of the Cox models is the time spent from article initiation to promotion to the featured article level, indicating the efficiency of knowledge collaboration. To examine whether the effects of the focal variables vary depending on the characteristics of a group task, we classified 2,978 featured articles into two categories: Academic and Non-academic. Academic articles refer to at least one paper published at an SCI, SSCI, A&HCI, or SCIE journal. We assumed that academic articles are more complex, entail more information processing and problem solving, and thus require more skill variety and expertise. The analysis results indicate the followings; First, Pareto ratio and inequality of knowledge sharing relates in a curvilinear fashion to the collaboration efficiency in an online community, promoting it to an optimal point and undermining it thereafter. Second, the curvilinear effect of Pareto ratio and inequality of knowledge sharing on the collaboration efficiency is more sensitive with a more academic task in an online community.

    Intelligent VOC Analyzing System Using Opinion Mining (오피니언 마이닝을 이용한 지능형 VOC 분석시스템)

    • Kim, Yoosin;Jeong, Seung Ryul
      • Journal of Intelligence and Information Systems
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      • v.19 no.3
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      • pp.113-125
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      • 2013
    • Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.

    Efficient Topic Modeling by Mapping Global and Local Topics (전역 토픽의 지역 매핑을 통한 효율적 토픽 모델링 방안)

    • Choi, Hochang;Kim, Namgyu
      • Journal of Intelligence and Information Systems
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      • v.23 no.3
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      • pp.69-94
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      • 2017
    • Recently, increase of demand for big data analysis has been driving the vigorous development of related technologies and tools. In addition, development of IT and increased penetration rate of smart devices are producing a large amount of data. According to this phenomenon, data analysis technology is rapidly becoming popular. Also, attempts to acquire insights through data analysis have been continuously increasing. It means that the big data analysis will be more important in various industries for the foreseeable future. Big data analysis is generally performed by a small number of experts and delivered to each demander of analysis. However, increase of interest about big data analysis arouses activation of computer programming education and development of many programs for data analysis. Accordingly, the entry barriers of big data analysis are gradually lowering and data analysis technology being spread out. As the result, big data analysis is expected to be performed by demanders of analysis themselves. Along with this, interest about various unstructured data is continually increasing. Especially, a lot of attention is focused on using text data. Emergence of new platforms and techniques using the web bring about mass production of text data and active attempt to analyze text data. Furthermore, result of text analysis has been utilized in various fields. Text mining is a concept that embraces various theories and techniques for text analysis. Many text mining techniques are utilized in this field for various research purposes, topic modeling is one of the most widely used and studied. Topic modeling is a technique that extracts the major issues from a lot of documents, identifies the documents that correspond to each issue and provides identified documents as a cluster. It is evaluated as a very useful technique in that reflect the semantic elements of the document. Traditional topic modeling is based on the distribution of key terms across the entire document. Thus, it is essential to analyze the entire document at once to identify topic of each document. This condition causes a long time in analysis process when topic modeling is applied to a lot of documents. In addition, it has a scalability problem that is an exponential increase in the processing time with the increase of analysis objects. This problem is particularly noticeable when the documents are distributed across multiple systems or regions. To overcome these problems, divide and conquer approach can be applied to topic modeling. It means dividing a large number of documents into sub-units and deriving topics through repetition of topic modeling to each unit. This method can be used for topic modeling on a large number of documents with limited system resources, and can improve processing speed of topic modeling. It also can significantly reduce analysis time and cost through ability to analyze documents in each location or place without combining analysis object documents. However, despite many advantages, this method has two major problems. First, the relationship between local topics derived from each unit and global topics derived from entire document is unclear. It means that in each document, local topics can be identified, but global topics cannot be identified. Second, a method for measuring the accuracy of the proposed methodology should be established. That is to say, assuming that global topic is ideal answer, the difference in a local topic on a global topic needs to be measured. By those difficulties, the study in this method is not performed sufficiently, compare with other studies dealing with topic modeling. In this paper, we propose a topic modeling approach to solve the above two problems. First of all, we divide the entire document cluster(Global set) into sub-clusters(Local set), and generate the reduced entire document cluster(RGS, Reduced global set) that consist of delegated documents extracted from each local set. We try to solve the first problem by mapping RGS topics and local topics. Along with this, we verify the accuracy of the proposed methodology by detecting documents, whether to be discerned as the same topic at result of global and local set. Using 24,000 news articles, we conduct experiments to evaluate practical applicability of the proposed methodology. In addition, through additional experiment, we confirmed that the proposed methodology can provide similar results to the entire topic modeling. We also proposed a reasonable method for comparing the result of both methods.

    THE EFFECT OF INTERMITTENT COMPOSITE CURING ON MARGINAL ADAPTATION (복합레진의 간헐적 광중합 방법이 변연적합도에 미치는 영향)

    • Yun, Yong-Hwan;Park, Sung-Ho
      • Restorative Dentistry and Endodontics
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      • v.32 no.3
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      • pp.248-259
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      • 2007
    • The aim of this research was to study the effect of intermittent polymerization on marginal adaptation by comparing the marginal adaptation of intermittently polymerized composite to that of continuously polymerized composite. The materials used for this study were Pyramid (Bisco Inc., Schaumburg, U.S.A.) and Heliomolar (Ivoclar Vivadent, Liechtenstein) . The experiment was carried out in class II MOD cavities prepared in 48 extracted human maxillary premolars. The samples were divided into 4 groups by light curing method: group 1- continuous curing (60s light on with no light off), group 2-intermittent curing (cycles of 3s with 2s light on & 1s light off for 90s); group 3- intermittent curing (cycles of 2s with 1s light on & 1s light off for 120s); group 4- intermittent curing (cycles of 3s with 1s light on & 2s light off for 180s). Consequently the total amount of light energy radiated was same in all the groups. Each specimen went through thermo-mechanical loading (TML) which consisted of mechanical loading (720,000 cycles, 5.0 kg) with a speed of 120 rpm for 100hours and thermocycling (6000 thermocycles of alternating water of $50^{\circ}C$ and $55^{\circ}C$). The continuous margin (CM) (%) of the total margin and regional margins, occlusal enamel (OE), vertical enamel (VE), and cervical enamel (CE) was measured before and after TML under a $\times200$ digital light microscope. Three-way ANOVA and Duncan's Multiple Range Test was performed at 95% level of confidence to test the effect of 3 variables on CM (%) of the total margin: light curing conditions, composite materials and effect of TML. In each group, One-way ANOVA and Duncan's Multiple Range Test was additionally performed to compare CM (%) of regions (OE, VE CE). The results indicated that all the three variables were statistically significant (p < 0.05). Before TML, in groups using Pyramid, groups 3 and 4 showed higher CM (%) than groups 1 and 2, and in groups using Heliomolar. groups 3 and 4 showed higher CM (%) than group 1 (p < 0.05). After TML, in both Pyramid and Heliomo)ar groups, group 3 showed higher CM (%) than group 1 (p < 0.05) CM (%) of the regions are significantly different in each group (p < 0.05). Before TML, no statistical difference was found between groups within the VE and CE region. In the OE region, group 4 of Pyramid showed higher CM (%) than group 2, and groups 2 and 4 of Heliomolar showed higher CM (%) than group 1 (p < 0.05). After TML, no statistical difference was found among groups within the VE and CE region. In the OE region, group 3 of Pyramid showed higher CM (%) than groups 1 and 2, and groups 2,3 and 4 of Heliomolar showed higher CM (%) than group 1 (p < 0.05). It was concluded that intermittent polymerization may be effective in reducing marginal gap formation.


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