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Effect of Nanopowdered Peanut Sprouts on Physicochemical and Sensory Properties of Milk
안유진,Palanivel Gansesan,곽해수 한국축산식품학회 2013 한국축산식품학회지 Vol.33 No.1
A study was conducted to examine the physicochemical and sensory properties of milk supplemented with nanopowdered peanut sprouts (NPPS) at different concentrations (1, 3, 5, 7, and 9%, w/v) during the storage at 4oC for 16 d. The size of NPPS ranged from 300-350 nm as observed by the particle size analyzer. The pH values of all samples ranged from 6.8 to 6.6 during the storage of 16 d. In color, the L* value of milk samples were not remarkably influenced by NPPS supplementation,whereas the b* and a* values significantly increased with the NPPS supplementation at all concentrations at 0 d storage,due to the original yellow color of NPPS powder (p<0.05). DPPH study revealed that higher antioxidant activity of milk supplement with higher concentrations of NPPS. TBARS value found to lower at the lower concentrations (1 and 3%, w/v)of NPPS supplementation. The sensory test revealed that the overall acceptability scores of NPPS supplemented milk samples (1 and 3%, w/v) were quite similar to control throughout the storage period of 16 d. Based on the data obtained from the present study, it was concluded that the concentrations (1 and 3%, w/v) of NPPS could be used to produce NPPS-supplemented milk without significant adverse effects on physicochemical and sensory properties, and enhance functional components from the supplementation.
병원전 119구급대원의 화상환자 응급처치 적절성 및 유형에 관한 연구– 미국 응급의학회 가이드라인을 중심으로 –
안유진,박상규,김진화 한국웰니스학회 2018 한국웰니스학회지 Vol.13 No.1
This study aimed to observe the types of first aid provided to the patients by the 119 rescue crew in the early stage of burn damage before the arrival to the hospitals, and provide the baseline data for the qualitative improvement of the first aid for the burned patients through the appropriateness evaluation of the treatment for the patients with common or severe burn damage through the investigation and analysis of the daily rescue records, targeting 1,287 burned patients transferred from the site to the hospitals by the 119 rescue crew of Seoul Metropolitan Fire & Disaster Headquarters from January to December, 2013. The appropriateness assessment of the first aid provided for the burned patients was analyzed using the guideline agreed in a paper by the American Academy of Emergency Medicine presented by Allison K and Porter K(2004). It was found that the first aid for the burned patients was relatively decent, but the rate of pain control and fluid treatment was significantly low; the burn treatment was insufficient when the patients’ consciousness became lower; and it was found that a larger number of treatments were provided as the distance from the site to the hospital increased. Hence, it is suggested that the removal of barriers against the rescue crew’s securement of the vein path and administration of drugs, which is the improvement of the operation scope and administrative support, will be needed. 본 연구는 2013년 1월부터 12월까지 서울소방재난본부 119구급대를 통하여 현장에서 병원으로 이송된 화상환자 1,287명에 대한 구급활동일지의 조사, 분석을 통해 병원전 119구급대원의 초기 화상환자 응급처치에 대한 유형을 관찰하고, 일반 및 중증 화상환자 처치의 적절성 평가를 통해 화상환자 응급처치의 질적 향상을 위한 기초자료 제공에 목적이 있다. 화상환자 응급처치 적절성 평가는 2004년에 Allison K와 Porter K가 발표한 미국 응급의학회 논문인 ‘Consensus on the prehospital approach to burns patient management’에 합의된 가이드라인을 기준으로 분석하였다. 화상환자의 응급처치는 비교적 양호하게 시행되고 있었으나 통증조절과 수액처치는 매우 낮은 시행률을 보였으며, 의식상태가 낮아질수록 화상에 대한 처치는 미흡했고, 현장에서 거리가 먼 병원일수록 많은 처치를 했다는 것을 알 수 있었다. 이에 병원전 화상환자의 응급처치 적절성을 높이기 위해서는 구급대원의 정맥로 확보와 약물 투여에 대한 방해요인 제거, 즉 업무범위의 개선 및 제도적 지원이 필요할 것이며, 다각도의 평가 도구를 활용한 지속적인 분석과 화상환자 프로토콜에 대한 꾸준한 교육이 동반되어야 할 것이다.
Composition, Structure, and Bioactive Components in Milk Fat Globule Membrane
안유진,Palanivel Ganesan,곽해수 한국축산식품학회 2011 한국축산식품학회지 Vol.31 No.1
A unique biophysical membrane which surrounds the milk fat globules is called the milk fat globule membrane (MFGM). Various researches were studied about origin, composition, structure and bioactive components of MFGM. Bioactive protein components of MFGM play an important beneficiary function such as defense mechanism in new born. Among the bioactive lipid components from MFGM phospholipids showed health enhancing functions. The phospholipids also help in the production of certain dairy product from deterioration. MFGM phospholipids also showed antioxidant activity in some dairy products such as butter and ghee produced from milk of buffalo. Based on the beneficial effects, researchers developed MFGM as functional ingredients in various food products. This current review focuses on health enhancing function of MFGM and its components in various dairy products.
On-Chain Data를 활용한 LSTM 기반 비트코인 가격 예측
안유진,오하영,An, Yu-Jin,Oh, Ha-Young 한국정보통신학회 2021 한국정보통신학회논문지 Vol.25 No.10
최근 10여 년 동안 가장 가파르게 가치가 상승한 자산군을 꼽자면 단연 비트코인이라고 할 수 있을 것이다. 특히 비트코인은 중앙통제 기관이 없음에도 불구하고 첫 등장을 한 2009년의 사실상 0달러에서 2021년 최고점인 65,000 달러 수준까지 치솟아 역사에 길이 남을 가치 상승을 보여주었다. 이에 따라 비트코인의 가능성에 대해서 반신반의 했던 상당수 투자자들의 포트폴리오에도 비트코인이 상당한 비중을 차지하는 경우가 많아졌으며, 제도권 내의 금융권에서도 이런 비트코인의 움직임에 주목하고 있다. 비트코인에 대한 관심과 더불어 비트코인의 가격에 거시경제 변수나 센티멘트가 비트코인의 가격이 어떻게 움직이는가에 대한 연구 또한 상당히 진전되었다. 하지만, 이들 연구에서 활용한 변수들은 비트코인만의 특징적인 데이터라고 할 수 있는 블록체인 내의 데이터를 취합하여 가공한 온체인 데이터를 적극적으로 활용하지는 않았다. 따라서, 본 논문에서는 시계열 데이터 예측에 적극적으로 활용되고 있는 LSTM을 기반으로 온체인 데이터를 활용하여 비트코인의 가격을 예측해보고자 한다. During the past decade, it seems apparent that Bitcoin has been the best performing asset class. Even without a centralized authority that takes control over, Bitcoin, which started off with basically no value at all, reached around 65000 dollars in 2021, showing a movement that will definitely go down in history. Thus, even those who were skeptical of Bitcoin's intangible nature are stacking bitcoin as a huge part of their portfolios. Bitcoin's exponential growth in value also caught the attention of traditional banking and investment firms. Along with the spotlight Bitcoin is getting from the investment world, research using macro-economic variables and investor sentiment to explain Bitcoin's price movement has shown progress. However, previous studies do not make use of On-Chain Data, which are data processed using transaction data in Bitcoin's blockchain network. Therefore, in this paper, we will be utilizing LSTM, a method widely used for time-series data prediction, with On-Chain Data to predict the price of Bitcoin.