• The KIPS Transactions:PartC
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• v.11C no.1
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• pp.63-74
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• 2004

Temporal locality of Web server references is one of the important characteristics to be considered in the design of a Web caching strategy, and it is important to measure the temporal locality exactly. Various methods to estimate the temporal locality have been proposed, however, Web server designers have still troubles in its measurement by using the tools that don't reflect the interarrival time of document requests. In this paper, we propose a measurement tool for short-term temporal locality based on request interarrival time, and discuss the simulation results based on the flares from NLANR and NASA Web sites. The results show that the proposed tool estimates the short-term temporal locality more exactly than that based on a stack.

• Toxicological Research
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• v.20 no.2
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• pp.117-122
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• 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
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• v.13 no.2
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• pp.591-598
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• 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.

• Asia-Pacific Journal of Business
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• v.9 no.1
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• pp.77-89
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• 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.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.22 no.1
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• pp.219-236
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• 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.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.588-591
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• 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)
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• v.13 no.4
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• pp.1975-1988
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• 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.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.753-766
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• 2021

This study was conducted to explore the meaning and essence of college students' short-term overseas volunteer work experiences. Data were collected through in-depth interviews with fourteen college students who participated in short-term overseas volunteer work from May 5, 2020 to August 30, 2020. Data were analyzed using the phenomenological method of Colaizzi(1978), and as a result of data analysis, ten subjects and five categories were derived. The five categories are: having expectations for overseas volunteer work, accepting and approaching different environments, feeling embarrassed by unexpected situations, being aware of the limits of activities, and looking at the world from a broader perspective. In this study, college students encounter a new world through overseas volunteer work, accept and adapt to a different environment, and are provided an opportunity to have a broader perspective needed in the global era.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.1
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• pp.1-10
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• 2021

This study proposed a Long-Short Term Memory network to consider changes in emotion over time, and applied an attention mechanism to give weights to the emotion states that appear at specific moments. We used 32 channel EEG data from DEAP database. A 2-level classification (Low and High) experiment and a 3-level classification experiment (Low, Middle, and High) were performed on Valence and Arousal emotion model. As a result, accuracy of the 2-level classification experiment was 90.1% for Valence and 88.1% for Arousal. The accuracy of 3-level classification was 83.5% for Valence and 82.5% for Arousal.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.249-251
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• 2021

In this paper, we introduce the deep-learning system using Tensorflow for recognizing situations that can occur fall situations when the elderly are moving or standing. Fall detection uses the LSTM (long short-term memory) learned using Tensorflow to determine whether it is a fall or not by data measured from wearable accelerator sensor. Learning is carried out for each of the 7 behavioral patterns consisting of 4 types of activity of daily living (ADL) and 3 types of fall. The learning was conducted using the 3-axis acceleration sensor data. As a result of the test, it was found to be compliant except for the GDSVM(Gravity Differential SVM), and it is expected that better results can be expected if the data is mixed and learned.