• 한국수소및신에너지학회논문집
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• 제21권5호
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• pp.460-469
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• 2010

To develop coal gasfication system, many studies have been actively conducted to describe the simulation of steady state. Now, it is necessary to study the gasification system not only in steady state but also in dynamic state to elucidate abnormal condition such as start-up, shut-down, disturbance, and develop control logic. In this study, a model was proposed with process simulation in dynamic state being conducted using a chemical process simulation tool, where a heat and mass transfer model in the gasifier is incorporated, The proposed model was verified by comparison of the results of the simulation with those available from NETL (National Energy Technology Laboratory) report under steady state condition. The simulation results were that the coal gas efficiency was 80.7%, gas thermal efficiency was 95.4%, which indicated the error was under 1 %. Also, the compositions of syngas were similar to those of the NETL report. Controlled variables of the proposed model was verified by increasing oxygen flow rate to gasifier in order to validate the dynamic state of the system. As a result, trends of major process variables were resonable when oxygen flow rate increased by 5% from the steady state value. Coal flow rate to gasifier and quench gas flow rate were increased, and flow rate of liquid slag was also increased. The proposed model in this study is able to be used for the prediction of gasification of various coals and dynamic analysis of coal gasification.

• 한국융합학회논문지
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• 제11권5호
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• pp.175-182
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• 2020

계단 보행 시 로봇의 최적 궤도 계산은 유전자 알고리즘과 계산 토크 컨트롤러를 사용하여 수행되었다. 첫째, 생식, 교배, 돌연변이로 이루어진 실시간 유전 알고리즘 (RCGA)을 사용하여 총 에너지 효율이 최소화되었다. 보폭의 시작과 끝, 그리고 조인트, 각도, 각속도 위치 어셈블리 관련 재현성 조건은 선형 제약이다. 다음은 고르지 못한 제약은 코너 스윙 다리와 계단의 외부와의 충돌을 막기 위한 조건, 운동 학적 특이성을 막기 위한 무릎 관절의 조건 및 진행 방향의 안전은 보장되지 않음 이란 조건을 따른다. 마지막으로, 각 관절의 각도 궤도는 염색체를 근사 계수를 가지는 4차 다항식에 의해 정의된다. 이것은 보통 도보를 의미한다. 이 연구에서는 최적의 궤도의 에너지 효율을 7개의 링크로 구성된 7자유도의 2족 로봇을 통한 컴퓨터 시뮬레이션을 통해 분석했다.

• 한국산학기술학회논문지
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• 제15권2호
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• pp.666-671
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• 2014

최근 디젤 차량과 같은 내연기관의 고효율화에 따라, 보조난방 열원으로서 PTC 히터의 사용이 증가하는 추세이다. 디젤 차량의 시동 초기에는 냉각수의 온도가 난방으로 직접 사용하기에 충분히 높지 않으므로, 동절기 난방을 위해 보조난방 열원은 필수적이다. 본 연구에서는 스크린 인쇄 전극공정을 바탕으로 한 PTC 소자를 제작하였고, 이를 활용한 PTC 소자 모듈 및 히터를 설계 및 제작하였다. PTC 소자 모듈의 방열핀 접촉형상 및 전열소자의 크기 변경에 따른 난방성능 변화를 열유동 해석을 통해 분석하였고, 난방성능 실험을 수행하여 PTC 히터의 난방성능 및 효율 특성을 살펴보았다. PTC 히터 시작품의 경우, 기존 PTC 히터와 동등한 수준 이상의 난방성능 및 효율을 나타내었으며, 향후 이를 바탕으로 PTC 소자와 히터에 대한 공정개선 및 성능증대 연구를 수행할 계획이다.

• 한방안이비인후피부과학회지
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• 제14권2호
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• pp.207-223
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• 2001

The Wonyenaejang is equivalent to the (senile)cataract in western medicine. The word cataract is used to describe the natural lens that has turned cloudy. As the natural lens of the eye becomes cloudy, it does not allow light to pass through it. Cataracts usually start as a slight cloudiness that progressively grows more opaque. As the cataract becomes more mature(increasingly opaque and dense), the retina receives less and less light. The light that does reach the retina becomes increasingly blurred and distorted. This causes gradual impairment of vision. If left untreated, cataracts can cause needless blindness. Although there are many kinds of cataracts, a senile cataract is the most common one. We chose the oriental medicine textbooks and the oriental medicine journals that were dealing with the symptoms, etiology, and internal/external treatments. The results were as follows : 1. The main causes of this disease are weak liver and kidney, burning up of the wind and heat in the liver and gall, weak spleen and stomach. 2. As the internal treatment of the Cataract, Geegukjihwangtang is mostly prescribed. 3. As the external treatment of the Cataract, (l) In the field of medicine for external application is commonly prescribed (2) In the field of drug action, frequently used treatments are as follows. emission of the evil, alleviation of fever, removal of lump of blood, and the medicine for external applications. (3) In the field of four Qi, cold medicine is commonly prescribed. (4) In the field of five tastes, bitter/hot/sweet mdicine are commonly prescribed. (5) In the field of toxicity, non-togic medicine is commonly prescribed. (6) In the field of channel distribution, most of the medicine belong to liver channel.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2008년도 제31회 추계학술대회논문집
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• pp.137-142
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• 2008

액체로켓엔진 재생냉각 연소기에서 산화제 선공급 cyclogram시의 점화 특성에 대해 기술하였다. 연소기의 연소압력은 60 bar, 추진제 유량은 약 89 kg/s 그리고 노즐 팽창비는 12이다. 산화제 선공급 cyclogram을 위해 수행한 연소기로의 연료 및 산화제 수류시험, 산화제 선공급에 따른 점화기 작동성 확인을 위한 점화시험, 연소기의 주 점화 및 연소 확인을 위한 저압 연소시험 그리고 설계점에서 연소기 작동성/연소 안정성 및 연소성능/재생냉각 성능 확인을 위한 연소시험 등에 대해 기술하였다. 산화제 선공급 점화 및 연소시험은 성공적으로 이루어졌으며 연소기에 대한 안정적인 점화 cyclogram을 개발하였다.

• BMB Reports
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• 제54권8호
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• pp.419-424
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• 2021

Cold-induced norepinephrine activates β3-adrenergic receptors (β3-AR) to stimulate the kinase cascade and cAMP-response element-binding protein, leading to the induction of thermogenic gene expression including uncoupling protein 1 (Ucp1). Here, we showed that stimulation of the β3-AR by its agonists isoproterenol and CL316,243 in adipocytes increased the expression of Ucp1 and Heme Oxygenase 1 (Hmox1), the principal Nrf2 target gene, suggesting the functional interaction of Nrf2 with β3-AR signaling. The activation of Nrf2 by tert-butylhydroquinone and reactive oxygen species (ROS) production by glucose oxidase induced both Ucp1 and Hmox1 expression. The increased expression of Ucp1 and Hmox1 was significantly reduced in the presence of a Nrf2 chemical inhibitor or in Nrf2-deleted (knockout) adipocytes. Furthermore, Nrf2 directly activated the Ucp1 promoter, and this required DNA regions located at -3.7 and -2.0 kb of the transcription start site. The CL316,243-induced Ucp1 expression in adipocytes and oxygen consumption in obese mice were partly compromised in the absence of Nrf2 expression. These data provide additional insight into the role of Nrf2 in β3-AR-mediated Ucp1 expression and energy expenditure, further highlighting the utility of Nrf2-mediated thermogenic stimulation as a therapeutic approach to diet-induced obesity.

• 한국인터넷방송통신학회논문지
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• 제22권6호
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• pp.173-178
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• 2022

최근, 소셜 네트워크 서비스에서 딥러닝을 활용한 추천시스템이 활발하게 연구되고 있다. 하지만 딥러닝을 이용한 추천시스템의 경우 콜드스타트 문제와 복잡한 연산으로 인해 늘어난 학습시간이 단점으로 존재한다. 본 논문에서는 사용자의 메타데이터를 활용하여 사용자 맞춤형 운동 루틴 추천 알고리즘을 제안한다. 본 논문에서 제안하는 알고리즘은 메타데이터(사용자의 키, 몸무게, 성, 등)를 입력받아 설계된 모델에 적용한다. 본 논문에서 제안한 운동 추천시스템 모델은 matrix factorization 알고리즘과 multi-layer perceptron을 활용한 neural collaborative filtering(NCF) 알고리즘을 기반으로 설계된다. 제안된 모델은 사용자 메타데이터와 운동 정보를 입력받아 학습을 진행한다. 학습이 완료된 모델은 특정 운동이 입력되면 사용자에게 추천도를 제공한다. 실험 결과에서 제안하는 운동 추천시스템 모델이 기존 NCF 모델보다 10% 추천 성능 향상과 50% 학습 시간 단축을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권12호
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• pp.3798-3814
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• 2022

Social recommendation algorithm can alleviate data sparsity and cold start problems in recommendation system by integrated social information. Among them, matrix-based decomposition algorithms are the most widely used and studied. Such algorithms use dot product operations to calculate the similarity between users and items, which ignores user's potential preferences, reduces algorithms' recommendation accuracy. This deficiency can be avoided by a metric learning-based social recommendation algorithm, which learns the distance between user embedding vectors and item embedding vectors instead of vector dot-product operations. However, previous works provide no theoretical explanation for its plausibility. Moreover, most works focus on the indirect impact of social friends on user's preferences, ignoring the direct impact on user's rating preferences, which is the influence of user rating preferences. To solve these problems, this study proposes a user bias drift social recommendation algorithm based on metric learning (BDML). The main work of this paper is as follows: (1) the process of introducing metric learning in the social recommendation scenario is introduced in the form of equations, and explained the reason why metric learning can replace the click operation; (2) a new user bias is constructed to simultaneously model the impact of social relationships on user's ratings preferences and user's preferences; Experimental results on two datasets show that the BDML algorithm proposed in this study has better recommendation accuracy compared with other comparison algorithms, and will be able to guarantee the recommendation effect in a more sparse dataset.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2022년도 추계학술발표대회
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• pp.377-379
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• 2022

POI refers to the point of Interest in Location-Based Social Networks (LBSNs). With the rapid development of mobile devices, GPS, and the Web (web2.0 and 3.0), LBSNs have attracted many users to share their information, physical location (real-time location), and interesting places. The tremendous demand of the user in LBSNs leads the recommendation systems (RSs) to become more widespread attention. Recommendation systems assist users in discovering interesting local attractions or facilities and help social network service (SNS) providers based on user locations. Therefore, it plays a vital role in LBSNs, namely POI recommendation system. In the machine learning model, most of the training data are stored in the centralized data storage, so information that belongs to the user will store in the centralized storage, and users may face privacy issues. Moreover, sharing the information may have safety concerns because of uploading or sharing their real-time location with others through social network media. According to the privacy concern issue, the paper proposes a recommendation model to prevent user privacy and eliminate traditional RS problems such as cold-start and data sparsity.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2023년도 춘계학술발표대회
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• pp.357-359
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• 2023

This paper proposes a hybrid recommendation system (RS) model that overcomes the limitations of traditional approaches such as data sparsity, cold start, and scalability by combining collaborative filtering and context-aware techniques. The objective of this model is to enhance the accuracy of recommendations and provide personalized suggestions by leveraging the strengths of collaborative filtering and incorporating user context features to capture their preferences and behavior more effectively. The approach utilizes a novel method that combines contextual attributes with the original user-item rating matrix of CF-based algorithms. Furthermore, we integrate k-mean++ clustering to group users with similar preferences and finally recommend items that have highly rated by other users in the same cluster. The process of partitioning is the use of the rating matrix into clusters based on contextual information offers several advantages. First, it bypasses of the computations over the entire data, reducing runtime and improving scalability. Second, the partitioned clusters hold similar ratings, which can produce greater impacts on each other, leading to more accurate recommendations and providing flexibility in the clustering process. keywords: Context-aware Recommendation, Collaborative Filtering, Kmean++ Clustering.