• Journal of Astronomy and Space Sciences
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• v.18 no.2
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• pp.163-173
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• 2001

In this paper, space radiation environment and single event effect(SEE) have been analyzed for the KOMPSAT-2 operational orbit. As spacecraft external and internal space environment, trapped proton, SEP(solar energetic particle) and GCR(galactic cosmic ray) high energy Protons and heavy ions spectrums are analyzed. Finally, SEU and SEL rate prediction has been performed for the Intel 80386 microprocessor CPU that is planned to be used in the KOMPSAT-2. As the estimation results, under nominal operational condition, it is predicted that trapped proton and high energetic proton induced SBU effect will not occur. But, it is predicted that heavy ion induced SEU can occur several times during KOMPSAT-2 3-year mission operation. KOMPSAT-2 has been implementing system level design to mitigate SEU occurrence using processor CPU error detection function of the on-board flight software.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11B
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• pp.1200-1206
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• 2009

In this paper, we propose an energy-efficient MAC(Medium Access Control) protocol for processing context information in ubiquitous sensor network environments. CASMAC(Context Aware Sensor MAC) use context information for energy-efficient operation and its operation principle is as follows. First, we make scenarios with possible prediction for CASMAC. And then we save setted context information in server. When event occur at specific sensor node, and then it send three times sample data to server. According to context information, server process sample data. If server process sample data with event, it receive continuous data from event occur node by a transmission request signal. And then server send data transmission stop signal to event occur node when it do not need to data. If server process sample data with no event, it have not reply. Through we make energy consumption tables and an energy consumption model, we simulate analysis of CASMAC performance. In a result, we gains about 5.7 percents energy reduction compared to SMAC.

• Journal of Astronomy and Space Sciences
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• v.21 no.2
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• pp.93-100
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• 2004

We have investigated characteristic solar wind dynamics associated with relativistic electron events at geosynchronous orbit. Most of the events for April, 1999 through December, 2002 are found to be accompanied by a prolonged solar quiet period which is characterized as low solar wind density, weak interplanetary magnetic field (IMF), and fast alfvenic fluctuations in IMF $B_z$. In a typical relativistic event, electron fluxes begin to increase by orders of magnitude when solar wind parameters drop to low values (e.g., $n_{sw}∼5 cm^{-3}$ and ｜$B_{IMF}$∼5 nT) after sharp peaks. Then the elevated electron fluxes stay at the high level during the solar quiet period. This observation may suggest the following scenario for the occurrence of a geosynchronous relativistic event: (ⅰ) Quiet solar winds can yield a stable and more dipole-like magnetospheric configurations in which the geosynchronous orbit locates well inside the trapping boundary of the energetic electrons. (ⅱ) If a large population of MeV electrons are generated (by whatever acceleration process(es)) in the inner magnetosphere, they can be trapped and effectively accumulated to a high intensity. (ⅲ) The high electron flux can persist for a number of days in the geosynchronous region as long as the solar wind dynamics stays quiet. Therefore the scenario indicates that the occurrence of a relativistic event would be a result of a delicate balance between the effects of electron acceleration and loss. In addition, the sensitive dependence of a relativistic event on the solar wind conditions makes the prediction of solar wind variability as important as understanding of electron acceleration processes in the forecast of a relativistic event.

• Culinary science and hospitality research
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• v.10 no.1
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• pp.32-45
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• 2004

This study is about choice attribution of customers make in food and beverage events. The researcher provided practical plans to uplift food-related enterprises and activate management through surveys and positive analyses, targeting customers who use food services. First of all, all event plans must include customer demands, social changes, special qualities of the business, and market research. Second, low demand season must be customers will be induced to the events. Third, prediction for market variable and solutions must be thoroughly examined and plans should look into the future to maintain a long period of time. Fourth, sufficient communication between planners and employees should be made before the event starts, so that food and beverage businesses can gain trust and quality of event services.Fifth, immaterial service and visible goods/menus in business of food and beverage events must be closely matched. Sixth, menus introducing a variety of merchandise, quality of nutrition and health of the business should be developed. Also, events from countries(regions) should be hold to create a market of cultural exchange. Seventh, for hereafter event plans, feedbacks are needed concerning customers needs and demands through customer care, after the food and beverage events. Eight, faculty management for convenience, kindness, safety, and life preserver accommodations in parking areas must be made, as automobiles are necessaries for people in Mycar era. The ninth, off-line and on-line care through on-line business construction and production of homepage must be done, due to the fact that even the well-made events are bound to fail if they are not delivered to the customers.

• Journal of Korean Society of Transportation
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• v.34 no.2
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• pp.158-167
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• 2016

This study evaluates potential sources of errors in k-NN(k-nearest neighbor) algorithm such as procedures, variables, and input data. Previous research has been thoroughly reviewed for understanding fundamentals of k-NN algorithm that has been widely used for short-term traffic states prediction. The framework of this algorithm commonly includes historical data smoothing, pattern database, similarity measure, k-value, and prediction horizon. The outcomes of this study suggests that: i) historical data smoothing is recommended to reduce random noise of measured traffic data; ii) the historical database should contain traffic state information on both normal and event conditions; and iii) trial and error method can improve the prediction accuracy by better searching for the optimum input time series and k-value. The study results also demonstrates that predicted error increases with the duration of prediction horizon and rapidly changing traffic states.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.33-33
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• 2013

We are developing empirical space weather (solar flare, solar proton event, and geomagnetic storm) forecast models based on solar data. In this talk we will review our main results and recent progress. First, we have examined solar flare (R) occurrence probability depending on sunspot McIntosh classification, its area, and its area change. We find that sunspot area and its increase (a proxy of flux emergence) greatly enhance solar flare occurrence rates for several sunspot classes. Second, a solar proton event (S) forecast model depending on flare parameters (flare strength, duration, and longitude) as well as CME parameters (speed and angular width) has been developed. We find that solar proton event probability strongly depends on these parameters and CME speed is well correlated with solar proton flux for disk events. Third, we have developed an empirical storm (G) forecast model to predict probability and strength of a storm using halo CME - Dst storm data. For this we use storm probability maps depending on CME parameters such as speed, location, and earthward direction. We are also looking for geoeffective CME parameters such as cone model parameters and magnetic field orientation. We find that all superstorms (less than -200 nT) occurred in the western hemisphere with southward field orientations. We have a plan to set up a storm forecast method with a three-stage approach, which will make a prediction within four hours after the solar coronagraph data become available. We expect that this study will enable us to forecast the onset and strength of a geomagnetic storm a few days in advance using only CME parameters and the WSA-ENLIL model. Finally, we discuss several ongoing works for space weather applications.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.59-66
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• 2023

The Golden Cross is commonly seen as a buy signal in financial markets, but its reliability for predicting stock price movements is limited due to market volatility. This paper introduces a time-invariant approach that considers the Golden Cross as a singular event. Utilizing LSTM neural networks, we forecast significant stock price changes following a Golden Cross occurrence. By comparing our approach with traditional time series analysis and using a confusion matrix for classification, we demonstrate its effectiveness in predicting post-event stock price trends. To conclude, this study proposes a model with a precision of 83%. By utilizing the model, investors can alleviate potential losses, rather than making buy decisions under all circumstances following a Golden Cross event.

• Journal of Distribution Science
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• v.21 no.5
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• pp.101-111
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• 2023

Purpose: The purpose of this paper is to examine the effect of the VKOSPI index on short-term stock returns after a large-scale stock price shock of individual stocks of firms in the distribution industry in Korea. Research design, data, and methodology: This study investigates the effect of the change of the VKOSPI index or investor mood on abnormal returns after the event date from January 2004 to July 2022. The significance of the abnormal return, which is obtained by subtracting the rate of return estimated by the market model from the rate of actual return on each trading day after the event date, is determined based on T-test and multifactor regression analysis. Results: In Korea's distribution industry, the simultaneous occurrence of a bad investor mood and a large stock price decline, leads to stock price reversals. Conversely, the simultaneous occurrence of a good investor mood and a large-scale stock price rise leads to stock price drifts. We found that the VKOSPI index has strong explanatory power for these reversals and drifts even after considering both company-specific and event-specific factors. Conclusions: In Korea's distribution industry-related stock market, investors show an asymmetrical behavioral characteristic of overreacting to negative moods and underreacting to positive moods.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1571-1584
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• 2023

In this study, a numerical analysis was performed as part of an international joint research project to reproduce a real cable tray fire that occurred in the heater bay area of the turbine building of a nuclear power plant. A sensitivity analysis was performed on various input parameters to derive results consistent with the sprinkler activation time obtained from the fire event analysis. For all sensitive parameters, the normalized sprinkler activation time correlated well with the power function of the normalized sprinkler height. A correlation equation was developed to identify the sprinkler activation time at any location when determining the slope or fire growth rate under the conditions assuming a linear or t-squared heat release rate (HRR) time curve. Various cable fire growth assumptions were used to determine which assumption was better to provide the prediction coincident with the information given from the fire event analysis in terms of the sprinkler activation time and total energy generated from cables damaged by fire. In the comprehensive analysis of all the sensitive parameters, the standard deviation of the input parameters increased as the sprinkler height decreased. Within the range of the sensitivity parameter values given in this study, when considering all sprinkler heights, the standard deviation of the cable model change was the largest and that of the overhang position change was the smallest.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• v.2 no.1
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• pp.29-36
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• 1998

An instantaneous unit sediment graph (IUSG) model is investigated for prediction of sediment yield from an upland watershed in Northwestern Mississippi. Sediment yields are predicted by convolving source runoff with an IUSG. The IUSG is the distribution of sediment from an instantaneous burst of rainfall producing one unit of runoff. The IUSG, defined as a product of the sediment concentration distribution (SCD) and the instantaneous unit hydrograph (IUH), is known to depend on the characteristics of the effective rainfall. The IUH is derived by the Nash model for each event. The SCD is assumed to be an exponential function for each event and its parameters were correlated with the effective rainfall characteristics. A sediment routing function, based on travel time and sediment particle size, is used to predict the SCD.