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- 저자 : 최욱철 (검색결과 3 건)
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최욱철,Storm N. S. Reid,유제광,김윤숙,조영홍,전병환 한국조류학회I 2016 ALGAE Vol.31 No.2
This study evaluated the effects of γ-aminobutyric acid (GABA)-enriched fermented sea tangle (GFST), as a functional food, on brain derived neurotrophic factor (BDNF)-related muscle growth and lipolysis, in a sarcopenic obesity high-risk group. Twenty-one middle-aged women (53-63 y) participated in this randomized, double-blind, placebo controlled study. Participants ingested either 1,000 mg of GFST (n = 10) or a sucrose placebo (CON) (n = 11) everyday, for 8 weeks. Subjects were asked to abstain from any regular exercise. Fasting venous blood samples, body composition and muscular strength were measured before and after supplementation period. Collectively, we demonstrated that GFST significantly decreased total fat mass and triglyceride in body composition, as well as significantly increasing serum BDNF (p < 0.001), angiotensin converting enzyme (p < 0.001), human growth hormone and insulin-like growth factor-1 levels (p < 0.05 and p < 0.05, respectively) accompanied by increased total lean mass (p < 0.01). Furthermore, the reported improvements in total work, knee extension and flexion at 60° s-1 (p < 0.05), and peak torque normalized to body weight of knee flexion at 60° s-1 (p < 0.05), support an ergogenic effect of GABA associated with increased growth factor levels. The use of GFST, as a functional food ingredient, to elicit anti-obesity effects and stimulate the release of muscle-related growth factors with increasing serum BDNF levels may provide a protective intervention for age-related degeneration such as sarcopenic obesity.
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그룹운동 유형이 중년여성의 신체조성과 요부관련근력에 미치는 영향
최욱철(Choi, Wook-Chul),전병환(Jeon, Byeong-Whan) 한국체육과학회 2014 한국체육과학회지 Vol.23 No.1
The purpose of this study is to compare changes in the body composition and muscular strength of the lumbar region of middle-age women through 12 weeks of group exercises. Middle-aged Korean women (n=40) were divided into four groups (body pumping group(n=lO), Swiss ball group(n=10), aerobic dance group(n=lO), control group(n=lO)), and carried out 6O-minute of group exercise for 4 days a week for 12 weeks. To compare the changes in body composition and muscular strength of the lumbar region of dependent variables, paired samples t-test was carried out to test for difference before and after. To test the effect between groups, Analysis of Covariate (ANCOVA) was carried out. The result for changes in body composition, weight, body fat amount, visceral fat area, and abdominal circumference were decreased significantly, and the mineral mass, muscle mass in the lower limbs, and protein amount were significantly increased through 12 week-of body pumping exercise. In the Swiss ball group, the weight, body fat amount, and abdominal circumference decreased significantly. In the aerobic dance group, the weight, body fat amount, protein amount, visceral fat area, and abdominal circumference showed decrease statistically. For changes in the lumbar region, there was no significant change of abdominal muscular strength and back strength in the body pumping group and aerobic dance group. In the Swiss ball group, both abdominal and back strength increased significantly. Collectively, it is suggested to select those three kinds of group exercise for improving body composition, and Body Pump composed of complex exercises which are aerobic and anaerobic had a positive effect on muscle quantity of lower limbs, mineral and reduction of fat.
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뉴스기사와 머신러닝을 활용한 암호화폐 가격 변화 예측에 관한 연구
최욱철 ( Uk-cheol Choe ),구자환 ( Jahwan Koo ),김응모 ( Ungmo Kim ) 한국정보처리학회 2022 한국정보처리학회 학술대회논문집 Vol.29 No.1
주식과 암호화폐 거래는 매매방식에 있어서 유사한 점이 있지만 기업의 사업분야, 자본금, 순이익 등의 경영현황과 미래가치에 영향을 많이 받는 주식과는 다르게 암호화폐는 실물 실체가 없으며 탈 중앙화, 전산화된 데이터를 기반으로 하며 심리적인 요소가 크게 작용하여 단기적인 변동이 클 수 있다. 본 연구에서는 이러한 암호화폐 거래의 특성을 활용하여 특정 암호화폐에 관련된 뉴스기사들을 수집하고 그 암호화폐의 가격 변화 데이터와 연관되어 가격예측 딥러닝 모델을 생성하고 해당 암호화폐에 대한 신규 뉴스기사가 발생되었을 때 이를 이용하여 매수, 매도, 관망 등과 같은 매매 정보를 예측 적용할 수 있게 하였다. 첫째, 뉴스 기사에서 언급한 암호화폐를 매수, 매도, 관망 중 어느 편이좋을 것인지 추천하는 알고리즘을 구현하였고, 둘째, 매수 이후 매매 차익을 위한 매도 시점이나 매도 이후 저가매수에 유리한 시점을 제안하는 알고리즘을 구현하였다. 또한, 실시간 뉴스기사 수집 및 예측한 매매 판단에 따라 매매 자동화 시스템을 구현하여 수익률을 직접 확인함으로써 그 유효성을 검증하였다.
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