• 천문학회보
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• 제40권1호
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• pp.64.3-64.3
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• 2015

We have developed a set of daily solar flare peak flux forecast models for strong flares using multiple linear regression and artificial neural network methods. We consider input parameters as solar activity data from January 1996 to December 2013 such as sunspot area, X-ray flare peak flux and weighted total flux of previous day, and mean flare rates of McIntosh sunspot group (Zpc) and Mount Wilson magnetic classification. For a training data set, we use the same number of 61 events for each C-, M-, and X-class from Jan. 1996 to Dec. 2004, while other previous models use all flares. For a testing data set, we use all flares from Jan. 2005 to Nov. 2013. The best three parameters related to the observed flare peak flux are weighted total flare flux of previous day (r = 0.51), X-ray flare peak flux (r = 0.48), and Mount Wilson magnetic classification (r = 0.47). A comparison between our neural network models and the previous models based on Heidke Skill Score (HSS) shows that our model for X-class flare is much better than the models and that for M-class flares is similar to them. Since all input parameters for our models are easily available, the models can be operated steadily and automatically in near-real time for space weather service.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권4호
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• pp.225-237
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• 2016

In conventional transportation problem (TP), all the parameters are always certain. But, many of the real life situations in industry or organization, the parameters (supply, demand and cost) of the TP are not precise which are imprecise in nature in different factors like the market condition, variations in rates of diesel, traffic jams, weather in hilly areas, capacity of men and machine, long power cut, labourer's over time work, unexpected failures in machine, seasonal changes and many more. To counter these problems, depending on the nature of the parameters, the TP is classified into two categories namely type-2 and type-4 fuzzy transportation problems (FTPs) under uncertain environment and formulates the problem and utilizes the trapezoidal fuzzy number (TrFN) to solve the TP. The existing ranking procedure of Liou and Wang (1992) is used to transform the type-2 and type-4 FTPs into a crisp one so that the conventional method may be applied to solve the TP. Moreover, the solution procedure differs from TP to type-2 and type-4 FTPs in allocation step only. Therefore a simple and efficient method denoted by PSK (P. Senthil Kumar) method is proposed to obtain an optimal solution in terms of TrFNs. From this fuzzy solution, the decision maker (DM) can decide the level of acceptance for the transportation cost or profit. Thus, the major applications of fuzzy set theory are widely used in areas such as inventory control, communication network, aggregate planning, employment scheduling, and personnel assignment and so on.

• 제어로봇시스템학회논문지
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• 제8권6호
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• pp.468-476
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• 2002

The confidence of information from image processing depends on the original image quality. Enhancing the confidence by an algorithm has an essential limitation. Especially, road images are exposed to lots of noisy sources, which makes image processing difficult. We, in this paper, propose a FNN (fuzzy-neural network) capable oi deciding the quality of a road image prior to extracting lane-related information. According to the decision by the FNN, road images are classified into good or bad to extract lane-related information. A CDF (cumulative distribution function), a function of edge histogram, is utilized to construct input parameters of the FNN, it is based on the fact that the shape of the CDF and the image quality has large correlation. Input pattern vector to the FNN consists of ten parameters in which nine parameters are from the CDF and the other one is from intensity distribution of raw image. Correlation analysis shows that each parameter represents the image quality well. According to the experimental results, the proposed FNN system was quite successful. We carried out simulations with real images taken by various lighting and weather conditions and achieved about 99% successful decision-making.

• 천문학회보
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• 제42권1호
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• pp.41.1-41.1
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• 2017

It is well known that there are good relations of coronal hole (CH) parameters such as the size, location, and magnetic field strength to the solar wind conditions and the geomagnetic storms. Especially in the minimum phase of solar cycle, CHs in mid- or low-latitude are one of major drivers for geomagnetic storms, since they form corotating interaction regions (CIRs). By adopting the method of Vrsnak et al. (2007), the Space Weather Research Center (SWRC) in Korea Astronomy and Space Science Institute (KASI) has done daily forecast of solar wind speed and Dst index from 2010. Through years of experience, we realize that the geomagnetic storms caused by CHs have different characteristics from those by CMEs. Thus, we statistically analyze the characteristics and causality of the geomagnetic storms by the CHs rather than the CMEs with dataset obtained during the solar activity was very low. For this, we examine the CH properties, solar wind parameters as well as geomagnetic storm indices. As the first result, we show the different trends of the solar wind parameters and geomagnetic indices depending on the degree of solar activity represented by CH (quiet) or sunspot number (SSN) in the active region (active) and then we evaluate our forecasts using CH information and suggest several ideas to improve forecasting capability.

• 한국지구과학회지
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• 제32권5호
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• pp.461-473
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• 2011

In this paper, trends of the widely used stability indices (SIs) and environmental parameters (EPs) were examined by using the 30-year routine rawinsonde data observed in three upper air observatories (Osan, Gwangju and Pohang) over South Korea. To take into account of the contribution of water vapor to a parcel density, we applied the virtual temperature correction in calculating the SIs and EPs. The trends of SIs and EPs indicated significant increases of temperature and moisture contents, especially at the low-to-mid troposphere during the last 10 years. The warming trend in the lower troposphere shows about 3 times greater than that of the global average (+0.10- $+0.20^{\circ}C$/10 years), whereas the cooling trend of lower stratosphere demonstrates a similar trend with the global average (-0.33- $-0.60^{\circ}C$/10 years). The vertical stability is clearly reduced due to the unsymmetrical change of atmospheric elements. The unstabilizing trend with the increased moisture contents gradually changed the atmospheric environment in South Korea into the conditions favorable for the occurrence of severe weather or intensifications of such events. These trends are consistent with the recent observations, which showed clear increase in the intensity and frequency of heavy rainfalls.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권12호
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• pp.2355-2373
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• 2011

Vision-based vehicle detector systems are becoming increasingly important in ITS applications. Real-time operation, robustness, precision, accurate estimation of traffic parameters, and ease of setup are important features to be considered in developing such systems. Further, accurate vehicle detection is difficult in varied complex traffic environments. These environments include changes in weather as well as challenging traffic conditions, such as shadow effects and jams. To meet real-time requirements, the proposed system first applies a color background to extract moving objects, which are then tracked by considering their relative distances and directions. To achieve robustness and precision, the color background is regularly updated by the proposed algorithm to overcome luminance variations. This paper also proposes a scheme of feedback compensation to resolve background convergence errors, which occur when vehicles temporarily park on the roadside while the background image is being converged. Next, vehicle occlusion is resolved using the proposed prior split approach and through reasoning for rule-based tracking. This approach can automatically detect straight lanes. Following this step, trajectories are applied to derive traffic parameters; finally, to facilitate easy setup, we propose a means to automate the setting of the system parameters. Experimental results show that the system can operate well under various complex traffic conditions in real time.

• 한국토양비료학회지
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• 제46권4호
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• pp.237-244
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• 2013

Radar remote sensing is appropriate for monitoring rice because the areas where this crop is cultivated are often cloudy and rainy. Especially, Synthetic Aperture Radar (SAR) can acquire remote sensing information with a high temporal resolution in tropical and subtropical regions due to its all-weather capability. This paper analyzes the relationships between backscattering coefficients of rice measured by RADARSAT-2 SAR and growth parameters during a rice growth period. We examined the temporal variations of backscattering coefficients with full polarization. Backscattering coefficients for all polarizations increased until Day Of Year (DOY 222) and then decreased along with Leaf Area Index (LAI), fresh weight, and Vegetation Water Content (VWC). Vertical transmit and Vertical receive polarization (VV)-polarization backscattering coefficients were higher than Horizontal transmit and Horizontal receive polarization (HH)-polarization backscattering coefficients in early rice growth stage and HH-polarization backscattering coefficients were higher than VV-polarization backscattering coefficients after effective tillering stage (DOY 186). Correlation analysis between backscattering coefficients and rice growth parameters revealed that HH-polarization was highly correlated with LAI, fresh weight, and VWC. Based on the observed relationships between backscattering coefficients and variables of cultivation, prediction equations were developed using the HH-polarization backscattering coefficients.

• 상하수도학회지
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• 제23권4호
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• pp.417-430
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• 2009

A BNR comprehensive performance evaluation (BNR CPE) system was established employing system-oriented evaluation methodology for biological nutrient removal (BNR) processes based on the CPE techniques developed by U.S. EPA for evaluation of conventional biological processes. The BNR CPE system applied to five domestic BNR plants adopting $A^2/O$ process confirmed that all target plants except the smallest one had not any serious defective performance and process stability was enhanced with increasing plant size. The system also clearly verified relatively poor performances in anoxic reactors without exception mainly due to influent carbon limit rather than functional defect. Consistent good performances were confirmed even during both winter season and wet weather generally known to be difficult to achieve satisfactory removals. Presentation of evaluation results by modified radar chart system simplified and clarified the evaluation and analysis procedures. The BNR CPE system could not only discover readily the causes of present and prospective poor performances but also facilitate the suggestion of their optimization options. Mutual effect and cause-and-effect among operation parameters and unit processes were also found easily using the evaluation system. The system justified that the adverse effect of defective operating parameters could be compensated by other favorable parameters, especially in anaerobic and anoxic reactors as well as during the winter season.

• 대한인간공학회지
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• 제36권3호
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• pp.169-181
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• 2017

Objective: The aim of this study was to explore the influence of outdoor weather conditions on subjective responses during physical activity. Background: The largest difference between indoor and outdoor conditions is the existence of the sun. The heat load from the sun has an influence on the heat gain of the human body and the intense degree of solar radiation affected thermal comfort. Method: Thirty eight people were exposed to a range of climatic conditions in the UK. Weather in England does not have extremely hot and cold temperature, and the current study was conducted under warm (summer and autumn) and cool (spring and summer) climates. Measurements of the climate included air temperature, radiant temperature (including solar load), humidity and wind around the subjects. Subjective responses were taken and physiological measurements included internal body temperature, heart rate and sweat loss. Results: This study was conducted under four kinds of environmental conditions and the environmental measurement was performed in September, December, March, and June. The values for sensation, comfort, preference, and pleasantness about four conditions were from 'neutral' to 'warm', from 'not uncomfortable' to 'slightly comfortable', from 'slightly cooler' to 'slightly warmer', and from 'neither pleasant nor unpleasant' and 'slightly unpleasant', respectively. All subjective responses showed differences depending on air temperature and wind speed, and had correlations with air temperature and wind speed (p<0.05). However, subjective responses showed no differences depending on the radiant temperature. The combined effects of environmental parameters were showed on some subjective responses. The combined effects of air temperature and radiant temperature on thermal sensation and pleasantness were significant. The combined effects of metabolic rate with air temperature, wind speed and solar radiation respectively have influences on some subjective responses. In the case of the relationships among subjective responses, thermal sensation had significant correlations with all subjective responses. The largest relationship was shown between preference and thermal sensation but acceptance showed the lowest relationship with the other subjective responses. Conclusion: The ranges of air temperature, radiant temperature, wind speed and solar radiation were $6.7^{\circ}C$ to $24.7^{\circ}C$, $17.9^{\circ}C$ to $56.6^{\circ}C$, $0.84ms^{-1}$ to $2.4ms^{-1}$, and $123Wm^{-2}$ to $876Wm^{-2}$ respectively. Each of air temperature and wind speed had significant relationships with subjective responses. The combined effects of environmental parameters on subjective responses were shown. Each radiant temperature and solar radiation did not show any relationships with subjective responses but the combinations of each radiant temperature and solar radiation with other environmental parameters had influences on subjective responses. The combinations of metabolic rate with air temperature, wind speed and solar radiation respectively have influences on subjective responses although metabolic rate alone hardly made influences on them. There were also significant relationships among subjective responses, and pleasantness generally showed relatively high relationships with comfort, preference, acceptance and satisfaction. Application: Subjective responses might be utilized to predict thermal stress of human and the application products reflecting human subjective responses might apply to the different fields such as fashion technology, wearable devices, and environmental design considering human's response etc.

• 환경영향평가
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• 제22권6호
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• pp.547-556
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• 2013

Recently, golf courses have increased over the years because golf became popular leisure sport. Various environmental problems have been then issued by a golf course during constructing and running them. A problem of pesticide, which is serious among various environmental problems, from golf course has harmful effect on surrounding area and makes human suffer from acute and chronic diseases. Pesticides are used for the cost-effective managing of golf course and the amount of pesticides also increases as the number of golf course increase. Since the assessment of pesticides on near-by surrounding has been focused on water and soil media, studies related to atmospheric dispersion have been hardly attempted. The method to assess an impact of pesticide nearby agricultural production by the atmospheric dispersion using AGDISP(AGricultural DISPersal) model was developed and applied to the actual planned golf course located in Hongcheon, Gangwon. For implementing AGDISP, parameters were investigated from the golf course's land use planning map, pesticide spray device, Hong-Cheon weather station and etc. First of all, a kind of pesticide, a form of spraying pesticide, geographical features, weather data, and distance(golf course to plantation) were investigated to understand how to work these parameters in AGDISP. Restricted data(slope angle, droplet size distribution and solar insolation) sensitivity analysis of these parameters to estimate effect of pesticide nearby a plantation and a high relative contribution data of analyzed data was selected for input data. Ethoprophos was chosen as the pesticide used in the golf course and the amounts of pesticide deposition per annual agricultural productions were predicted. The results show that maximum amount of pesticide deposition through atmospheric dispersion was predicted $2.32{\mu}/m^2$ at 96 m where the nearest organic plantation exists. The residues of pesticide were also estimated based on the annul production of the organic and the deposition amount of the pesticide. Consequently, buckwheat, wheat and millet were likely to exceed maximum residue limits for pesticides in foods(MRL) and sorghum, corn and peanut were likely to exceed MRL by organic farming as well.