• 정보처리학회논문지C
• /
• 제11C권1호
• /
• pp.63-74
• /
• 2004

임시지역성은 웹 캐싱 전략에서 고려해야 할 중요한 요소 중의 하나이며, 이를 정확히 측정하는 것은 매우 중요하다. 임시지역성을 측정하기 위한 다양한 방법이 제시되었으나, 상호 참조시간을 고려하지 않는 스택을 이용한 측정도구를 사용함으로써 정확한 임시지역성 측정에 한계가 있었다. 본 연구에서는 상호참조시간을 고려한 단기간 임시지역성 측정도구를 제안하고, NLANR과 NASA의 로그 파일로 실험한 결과를 논의한다. 실험 결과 스택기반의 기존 측정도구보다 상호참조시간 기반의 제안 측정도구가 단기간 임시지역성을 보다 정확히 측정할 수 있었다.

• Toxicological Research
• /
• 제20권2호
• /
• pp.117-122
• /
• 2004

The present study was carried out to establish a short-term teratogenicity study for detecting developmental toxic potential induced by gamma radiation in ICR mice. Pregnant mice were exposed at dose levels of 0, 0.5, 1, 2, or 4 Gy on gestational day 8.5. All dams were subjected to caesarean section on gestational day 10.5 and their embryos were examined for growth, differentiation, and morphological abnormalities. An increase in the number of resorption was found at 4 Gy in a dose-dependent manner. Dose-dependent decreases in the developmental score of yolk sac circulation and olfactory system at above 1 Gy, in the number of somite pairs and developmental score of allantois, optic system, and maxillary process at above 2 Gy, and in the all growth and developmental parameters examined at 4 Gy were found. Various types of morphological abnormalities were seen at dose levels of 0.5 Gy or greater. Characteristic malformations induced by gamma radiation were abnormal axial rotation, hematoma, craniofacial hypoplasia, open neuropore, shortened prosencephalon, kinked somites, irregular somites, swelling, hydropericardium, absent branchial bar, and absent limb bud. Morphological alterations such as hematoma, craniofacial hypoplasia, open neuropore, and kinked somites were noted even in the lowest dose (0.5 Gy). These results indicated that the short-term teratogenicity study established in this study can be a useful tool for not only detecting the developmental toxic potential induced by gamma radiation, but also screening radio-protective agents in ICR mice.

• Journal of Electrical Engineering and Technology
• /
• 제13권2호
• /
• pp.591-598
• /
• 2018

Short term load forecasts complexly affected by socioeconomic factors and weather variables have non-linear characteristics. Thus far, researchers have improved load forecast technologies through diverse techniques such as artificial neural networks, fuzzy theories, and statistical methods in order to enhance the accuracy of load forecasts. Short term load forecast errors for special days are relatively much higher than that of weekdays. The errors are mainly caused by the irregularity of social activities and insufficient similar past data required for constructing load forecast models. In this study, the load characteristics of Lunar New Year's Day holidays well known for the highest error occurrence holiday period are analyzed to propose a load forecast technique for Lunar New Year's Day holidays. To solve the insufficient input data problem, the similarity of the load patterns of past Lunar New Year's Day holidays having similar patterns was judged by Euclid distance. Lunar New Year's Day holidays periods for 2011-2012 were forecasted by the proposed method which shows that the proposed algorithm yields better results than the comprehensive analysis method or the knowledge-based method.

• 아태비즈니스연구
• /
• 제9권1호
• /
• pp.77-89
• /
• 2018

Today, the sports teams are in a highly competitive environment where they don't know what may happen in the near future. While the front-runner teams suffer a serious slump, the teams in lower ladder stacks victories. This recent phenomenon proves that no team can secure the sustainable competitive edge over others. This is the time when a complete change of the mindset about the short-term competitive edge is needed. Therefore, we conducted the case study to the short-term competitive edges by selecting OK Savings Bank Rush & Cash volleyball team(hereafter referred to as OK Savings Bank). Thus, we presented the Transient Advantage Wave which describes the five stages of Initiating-Promotion-Utilization-Reconstruction-Withdrawal as a framework for the case study. Finally, we organized the results of the analysis and based on this result, we discussed the significance and the limitation of the short-term competitive edge that the sports team should pursue. This study contributed to the changes in strategies & tactics of various sports teams by suggesting the new strategy called short-term competitive edges that teams should utilize in order to get the best results in the sports league that has the strong quality of Time-based system.

• 한방안이비인후피부과학회지
• /
• 제22권1호
• /
• pp.219-236
• /
• 2009

Background : Recently the number of atopic dermatitis patients has increased, but the treatment of atopic dermatitis is not effective, and the recurrence rate of atopic dermatitis is high. Many patients are suffering from pruritus. A new standard treatment system is needed. Objective : This study investigated the effect of Oriental medicine program for atopic dermatitis patients during short term hospitalization. Method : 6 patients were admitted for short term hospitalization program. The program includes Acupuncture, herbal medicine, examination, education, cupping therapy, herbal dressing, exercise and etc. Everyday we evaluated the patients by Severity Scoring Atopic Dermatitis(SCORAD) index and took the photos of lesions, and the patients evaluated themselves by atopic dermatitis diary which consists of emotion, pruritus, sleep loss. Results : Admission duration was 7 to 14 days. The SCORAD scores of them were decreased. Most symptoms of 6 patients were improved. Especially herbal dressing was effective for severe oozing. Subjective scores of atopic dermatitis diary were reduced. Conclusion : We expect that the short term hospitalization program could be helpful for uncontrollable atopic dermatitis patients.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
• /
• pp.588-591
• /
• 2003

This paper presents a new short-term load forecasting system using data mining. Since the electric load has very different pattern according to the day, it definitely gives rise to the forecasting error if only one forecasting model is used. Thus, to resolve this problem, the fuzzy model-based classifier and predictor are proposed for the forecasting of the hourly electric load. The proposed classifier is the multi-input and multi-output fuzzy system of which the consequent part is composed of the Bayesian classifier. The proposed classifier attempts to categorize the input electric load into Monday, Tuesday$\sim$Friday, Saturday, and Sunday electric load, Then, we construct the Takagi-Sugeno (T-S) fuzzy model-based predictor for each class. The parameter identification problem is converted into the generalized eigenvalue problem (GEVP) by formulating the linear matrix inequalities (LMIs). Finally, to show the feasibility of the proposed method, this paper provides the short-term load forecasting example.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권4호
• /
• pp.1975-1988
• /
• 2019

Short-term traffic flow prediction plays an important role in intelligent transportation systems (ITS) in areas such as transportation management, traffic control and guidance. For short-term traffic flow regression predictions, the main challenge stems from the non-stationary property of traffic flow data. In this paper, we design an ensemble cascading prediction framework based on extremely randomized trees (extra-trees) using a boosting technique called EET to predict the short-term traffic flow under non-stationary environments. Extra-trees is a tree-based ensemble method. It essentially consists of strongly randomizing both the attribute and cut-point choices while splitting a tree node. This mechanism reduces the variance of the model and is, therefore, more suitable for traffic flow regression prediction in non-stationary environments. Moreover, the extra-trees algorithm uses boosting ensemble technique averaging to improve the predictive accuracy and control overfitting. To the best of our knowledge, this is the first time that extra-trees have been used as fundamental building blocks in boosting committee machines. The proposed approach involves predicting 5 min in advance using real-time traffic flow data in the context of inherently considering temporal and spatial correlations. Experiments demonstrate that the proposed method achieves higher accuracy and lower variance and computational complexity when compared to the existing methods.

• 한국콘텐츠학회논문지
• /
• 제21권10호
• /
• pp.753-766
• /
• 2021

본 연구는 단기해외봉사활동에 참여하였던 대학생을 대상으로 봉사활동경험의 의미와 본질을 탐구하고자 수행되었다. 자료는 K도에 소재한 일부 대학에 재학 중인 학생 14명을 2020년 5월 5일부터 8월 30일까지 면대면 심층면담을 통해 수집되었다. 면담자료는 Colaizzi(1978)의 현상학적 방법을 사용하여 분석하였으며 자료 분석 결과 10개 주제와 5개의 범주가 도출되었다. 5개 범주는 '해외봉사활동에 대한 기대감을 가짐', '환경은 다르지만 수용하며 다가감', '예상하지 못한 상황에 당황스러움', '활동의 한계를 자각함', '더 넓은 시야로 바라보게 됨'이다. 본 연구에서 대학생은 해외봉사활동을 통해 새로운 세계를 접하고 환경은 다르지만 수용하고 적응하면서 글로벌 시대에 필요한 좀 더 폭넓은 시야를 갖는 계기를 마련하였다.

• 한국산업정보학회논문지
• /
• 제26권1호
• /
• pp.1-10
• /
• 2021

본 연구에서는 EEG 신호를 기반으로 감정 인식에 유용한 딥러닝 기법을 제안한다. 감정이 시간에 따라 변화하는 특성을 반영하기 위해 Long-Short Term Memory 네트워크를 사용하였다. 또한, 특정 시점의 감정적 상태가 전체 감정 상태에 영향을 미친다는 이론을 기반으로 특정 순간의 감정 상태에 가중치를 주기 위해 어텐션 메커니즘을 적용했다. EEG 신호는 DEAP 데이터베이스를 사용하였으며, 감정은 긍정과 부정의 정도를 나타내는 정서가(Valence)와 감정의 정도를 나타내는 각성(Arousal) 모델을 사용하였다. 실험 결과 정서가(Valence)와 각성(Arousal)을 2단계(낮음, 높음)로 나누었을 때 분석 정확도는 정서가(Valence)의 경우 90.1%, 각성(Arousal)의 경우 88.1%이다. 낮음, 중간, 높음의 3단계로 감정을 구분한 경우 정서가(Valence)는 83.5%, 각성(Arousal)은 82.5%의 정확도를 보였다.

• 한국정보통신학회:학술대회논문집
• /
• 한국정보통신학회 2021년도 춘계학술대회
• /
• pp.249-251
• /
• 2021

본 논문에서는 노령층 인구가 도보시 일어날 수 있는 낙상상황을 텐서플로워를 이용하여 인지하기 위한 시스템에 대하여 소개한다. 낙상감지는 고령자의 몸에 착용한 가속센서 데이터에 대해서 텐서플로워를 이용하여 학습된 LSTM(long short-term memory)을 기반하여 낙상과 일상생활을 판별한다. 각각 7가지의 행동 패턴들에 대하여 학습을 실행하며, 4가지는 일상생활에서 일어나는 행동 패턴이고, 나머지 3가지는 낙상시의 패턴에 대하여 학습한다. 3축 가속도 센서의 가공하지 않은 데이터와 가공한 SVM(Sum Vector Magnitude)를 이용하여 LSTM에 적용해서 학습하였다. 이 두 가지 경우에 대해서 테스트한 결과 데이터를 혼합하여 학습하면 더 좋은 결과를 기대할 수 있을 것으로 예상된다.