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김주한(Ju-Han Kim),김다비(Da-Bi Kim),김도연(Do-Yeon Kim),김명교(Myung-Kyo Kim),김진성(Jin-Sung Kim),김영옥(Young-Ok Kim),신동혁(Dong-Hyuk Shin) 한국IT서비스학회 2021 한국IT서비스학회 학술대회 논문집 Vol.2021 No.-
본 연구는 광범위한 개념적 특성으로 인해 불명확한 메타버스의 개념을 분명히 정의함을 목적으로 하며, 현재 서비스 중인 국내 및 해외의 메타버스 플랫폼들을 매핑하여 실증분석하였다. 국내를 포함한 전세계에서 메타버스, AR, VR, MR, XR 등의 용어들이 의미상 명확한 구분 없이 혼용되면서 위 기술들에 대한 의미론적 불신으로 이어지고 마케팅 용어에 불과하다는 오해가 제기되는상황이다. 이러한 문제를 해결하고 메타버스 및 관련 기술들에 대한 올바른 포용을 유도하는 데에기여하기 위해 실제 서비스되고 있는 메타버스 플랫폼들의 기능 분석을 바탕으로 메타버스를 계층화하여 메타버스를 명확히 정의하고자 한다. 메타버스는 AR, VR, XR로 나누어 계층화하였으며 각각 출력 가능 범위와 기능이 확장된 정도를 계층 상승의 기준으로 정하였다.
( Han-bi Kim ),( Jin Cheol Kim ),( Ji-young Um ),( Seok Young Kang ),( Bo Young Chung ),( Chun Wook Park ),( Hye One Kim ) 대한피부과학회 2021 대한피부과학회 학술발표대회집 Vol.73 No.1
Background: Previous studies have identified differences in skin surface and intestinal microbiota between healthy humans and patients with atopic dermatitis. However, the microbiome of the skin has very different characteristics depending on the dry, wet, and oily areas. Objectives: This study was purposed to identify whether the skin microflora and tryptophan metabolites are different between atopic dermatitis patients group and normal control group. Methods: Skin samples of 60 volunteers were collected from the nose, abdomen, antecubital fossa by swabs and tapping, and stool samples were collected with cotton swabs. Results: In the atopic dermatitis patients, the Kocuria, Megamonas, Unassigned, Enterocloster, Tyzzerella, Veillonella, and Rhodospirillum are increased in the fecal samples. The Comamonas, Finegoldia, Haemophilus, Porphyromonas, Staphylococcus, Neisseria, Thermodesulfobacterium, and Prevotella are increased in skin samples of the atopic dermatitis group. Indole-3-lactic acid, a tryptophan metabolite, was significantly decreased in skin of the atopic dermatitis patients group. Conclusion: This study showed the skin microflora and tryptophan metabolites are different between atopic dermatitis patients group and normal control group.
Quality characteristics and antioxidant activities of extruded mulberry leaves added milk spread
Han Bi Kim,Mina Kim,Jeong-Sook Choe 한국식품영양과학회 2021 한국식품영양과학회 학술대회발표집 Vol.2021 No.10
This study, the applicability of products using mulberry leaves to enhance palatability and functionality was evaluated by preparing a milk spread with extruded mulberry leaf powder and studying physicochemical quality characteristics, sensory characteristics, and antioxidant activity. When preparing the spread, extruded mulberry leaves were added at 1.3%, 2.5%, 3,7% of thee total material. ln the sensory test, color, taste, texture (adhesion, spreadability), and overall preference were evaluated. The spread with 12 g of mulberry leaves was the most preferred. Based on this, a milk spread containing fructo oligosaccharide and butter was prepared using 3.7% extruded mulberry leaves. Milk spread prepared with extrusion mulberry leaf powder was higher than pH of the control group. The sugar content of extruded mulberry milk spread was similar in all samples at 1.7∼1.8 Brix. The moisture content and the Hunter’s color L and b values increased in milk spread added extrusion mulberry leaf than that of the control. The 1,1-diphenyl-2-picrylhydrazyl radical scavenging and hydroxyl radical scavenging activity increased in extruded mulberry spread than that of the mulberry leaf spread.
( Han-bi Kim ),( Jin Cheol Kim ),( Ji-young Um ),( Seok Young Kang ),( Bo Young Chung ),( Chun Wook Park ),( Hye One Kim ) 대한피부과학회 2021 대한피부과학회 학술발표대회집 Vol.73 No.-
Background: Previous studies have identified differences in skin surface and intestinal microbiota between healthy humans and patients with atopic dermatitis. However, the microbiome of the skin has very different characteristics depending on the dry, wet, and oily areas. Objectives: This study was purposed to identify whether the skin microflora and tryptophan metabolites are different between atopic dermatitis patients group and normal control group. Methods: Skin samples of 60 volunteers were collected from the nose, abdomen, antecubital fossa by swabs and tapping, and stool samples were collected with cotton swabs. Results: In the atopic dermatitis patients, the Kocuria, Megamonas, Unassigned, Enterocloster, Tyzzerella, Veillonella, and Rhodospirillum are increased in the fecal samples. The Comamonas, Finegoldia, Haemophilus, Porphyromonas, Staphylococcus, Neisseria, Thermodesulfobacterium, and Prevotella are increased in skin samples of the atopic dermatitis group. Indole-3-lactic acid, a tryptophan metabolite, was significantly decreased in skin of the atopic dermatitis patients group. Conclusion: This study showed the skin microflora and tryptophan metabolites are different between atopic dermatitis patients group and normal control group.
Kim, Seung Cheol,Song, Yong Sang,Kim, Young-Tae,Kim, Young Tak,Ryu, Ki-Sung,Gunapalaiah, Bhavyashree,Bi, Dan,Bock, Hans L,Park, Jong-Sup Korean Society of Gynecologic Oncology and Colposc 2011 Journal of Gynecologic Oncology Vol.22 No.2
<P><B>Objective</B></P><P>The study assessed the immunogenicity and safety of human papillomavirus (HPV)-16/18 AS04-adjuvanted cervical cancer vaccine in healthy Korean women aged 15-25 years.</P><P><B>Methods</B></P><P>Phase IIIB, double-blind, randomised (2:1), multi-centre trial was conducted in Korea from June 2007 to March 2008. The study enrolled 225 women in the HPV (N=149) and placebo (N=76) groups who received three doses of HPV-16/18 AS04-adjuvanted vaccine or placebo (aluminium hydroxide) administered intramuscularly at 0, 1, and 6 months and were followed until one month post-dose 3. Serum samples were collected pre-vaccination and one month post-dose 3. Safety and reactogenicity data were collected throughout.</P><P><B>Results</B></P><P>In this trial, 208 women completed the study (141 in HPV group; 67 in placebo group). At month 7, all initially seronegative women had seroconverted for HPV-16 and HPV-18 antibodies with anti-HPV-16 and anti-HPV-18 geometric mean titres of 9,351.4 El.U/mL (95% CI, 8,145.5 to 10,735.8) and 4204.1 El.U/mL (95% CI, 3,626.5 to 4,873.6), respectively. Initially seropositive women showed similar increase in geometric mean titre levels. Compliance to the three dose vaccination course was 95.3% in HPV and 89.5% in placebo group. Solicited local (pain) and general (fatigue, myalgia or headache) symptoms were commonly reported in both groups. Three serious adverse events were reported (two in HPV group; one in placebo group), all unrelated to vaccination by the investigator; all recovered.</P><P><B>Conclusion</B></P><P>The HPV-16/18 AS04-adjuvanted vaccine was highly immunogenic with a clinically acceptable safety profile in Korean women. This study was in line with previous global studies in Europe, North America, and Brazil. (ClinicalTrials.gov number, NCT 00485732.)</P>
Han Bi KIM,Dong Hoon HAN 한국유통과학회 2023 Journal of Korea Artificial Intelligence Associati Vol.1 No.1
Accurate hospital case modeling and prediction are crucial for efficient healthcare. In this study, we demonstrate the implementation of regression analysis methods in machine learning systems utilizing mathematical statics and machine learning techniques. The developed machine learning model includes Bayesian linear, artificial neural network, decision tree, decision forest, and linear regression analysis models. Through the application of these algorithms, corresponding regression models were constructed and analyzed. The results suggest the potential of leveraging machine learning systems for medical research. The experiment aimed to create an Azure Machine Learning Studio tool for the speedy evaluation of multiple regression models. The tool faciliates the comparision of 5 types of regression models in a unified experiment and presents assessment results with performance metrics. Evaluation of regression machine learning models highlighted the advantages of boosted decision tree regression, and decision forest regression in hospital case prediction. These findings could lay the groundwork for the deliberate development of new directions in medical data processing and decision making. Furthermore, potential avenues for future research may include exploring methods such as clustering, classification, and anomaly detection in healthcare systems.