• Journal of Digital Convergence
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• v.13 no.1
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• pp.297-304
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• 2015

Recently, the demand for a PRT(Personal Rapid Transit) system based on autonomous navigation is increasing. Accordingly, the applicability investigations of the PRT system on rail tracks or roadways have been widely studied. In the case of unmanned vehicle operations without physical guideways on roadways, to monitor the position of the vehicle in real time is very important for stable, robust and reliable guidance of an autonomous vehicle. The Global Positioning System (GPS) has been commercially used for vehicle positioning. However, it cannot be applied in environments as tunnels or interiors of buildings. The PRT navigation system based on magnetic markers reference sensing that can overcome these environmental restrictions and the vehicle dynamics model for its H/W configuration are presented in this study. In addition, the design of a control S/W dedicated for unmanned operation of a PRT vehicle and its prototype implementation for experimental validation on a pilot network were successfully achieved.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.161-168
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• 2007

Web attack uses structural, logical and coding error or web application rather than vulnerability to Web server itself. According to the Open Web Application Security Project (OWASP) published about ten types of the web application vulnerability to show the causes of hacking, the risk of hacking and the severity of damage are well known. The detection ability and response is important to deal with web hacking. Filtering methods like pattern matching and code modification are used for defense but these methods can not detect new types of attacks. Also though the security unit product like IDS or web application firewall can be used, these require a lot of money and efforts to operate and maintain, and security unit product is likely to generate false positive detection. In this research profiling method that attracts the structure of web application and the attributes of input parameters such as types and length is used, and by installing structural database of web application in advance it is possible that the lack of the validation of user input value check and the verification and attack detection is solved through using profiling identifier of database against illegal request. Integral security management system has been used in most institutes. Therefore even if additional unit security product is not applied, attacks against the web application will be able to be detected by showing the model, which the security monitoring log gathering agent of the integral security management system and the function of the detection of web application attack are combined.

• Journal of The Korean Society of Grassland and Forage Science
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• v.31 no.4
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• pp.409-414
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• 2011

This study was conducted to find out an alternative way of rapid and accurate analysis of forage quality. Near Infrared Reflectance Spectroscopy (NIRS) was used to evaluate the possibility of forage analysis. 175 samples consisted of Italian ryegrass, whole crop barley and pea seeded spring in 2009 were collected. The samples were analyzed for moisture, crude protein (CP), crude ash (CA), acid detergent fiber (ADF), and neutral detergent fiber (NDF), and also scanned using NIRSystem with wavelength from 400~2,500 nm. Multiple linear regression was used with wet analysis data for developing the calibration model and validated unknown samples. The important index in this experiment were SEC, SEP. The r2 value for moisture, CP, CA, ADF, and NDF in calibration set was 0.65, 0.97, 0.93, 0.99, and 0.97 and also was 0.15, 0.94, 0.96, 0.98 and 0.98 in validation set, respectively. The results of this experiment indicates that NIRS was reliable analytical method to assess forage quality for CP, CA ADF and NDF except moisture content in forage when proper samples incorporated into the equation development.

• Journal of the Korean Society for Railway
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• v.19 no.2
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• pp.145-158
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• 2016

This paper introduces a risk graph which is one method for determining the SIL as a measure of the effectiveness of signaling system. The purpose of this research is to make up for the weakness of the qualitative determination, which has input value ambiguity and a boundary problem in the SIL range. The fuzzy input valuable consists of consequence, exposure, avoidance and demand rate. The fuzzy inference produces forty eight fuzzy rule by adapting the calibrated risk graph in the IEC 61511. The Max-min composition is utilized for the fuzzy inference. The result of the fuzzy inference is the fuzzy value. Therefore, using the de-fuzzification method, the result should be converted to a crisp value that can be utilized for real projects. Ultimately, the safety requirement for hazard is identified by proposing a SIL result with a tolerable hazard rate. For the validation the results of the proposed method, the fuzzy risk graph model is compared with the safety analysis of the signaling system in CENELEC SC 9XA WG A10 report.

• Journal of Korea Water Resources Association
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• v.53 no.11
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• pp.929-938
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• 2020

In this study, we estimated missing evapotranspiration (ET) data at a eddy-covariance flux tower in the Cheongmicheon farmland site using the Artificial Neural Network (ANN). The ANN showed excellent performance in numerical analysis and is expanding in various fields. To evaluate the performance the ANN-based gap-filling, ET was calculated using the existing gap-filling methods of Mean Diagnostic Variation (MDV) and Food and Aggregation Organization Penman-Monteith (FAO-PM). Then ET was evaluated by time series method and statistical analysis (coefficient of determination, index of agreement (IOA), root mean squared error (RMSE) and mean absolute error (MAE). For the validation of each gap-filling model, we used 30 minutes of data in 2015. Of the 121 missing values, the ANN method showed the best performance by supplementing 70, 53 and 84 missing values, respectively, in the order of MDV, FAO-PM, and ANN methods. Analysis of the coefficient of determination (MDV, FAO-PM, and ANN methods followed by 0.673, 0.784, and 0.841, respectively.) and the IOA (The MDV, FAO-PM, and ANN methods followed by 0.899, 0.890, and 0.951 respectively.) indicated that, all three methods were highly correlated and considered to be fully utilized, and among them, ANN models showed the highest performance and suitability. Based on this study, it could be used more appropriately in the study of gap-filling method of flux tower data using machine learning method.

• Korean Chemical Engineering Research
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• v.56 no.2
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• pp.229-239
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• 2018

The purpose of this study was to effectively produce the biosugar from cell wall of lipid extracted microalgae (LEA) by using microwave-assisted pretreatment without enzymatic hydrolysis process. Response surface methodology (RSM) was applied to optimization of microwave-assisted pretreatment conditions for the production of biosugar based on enzyme-free process from LEA. Microwave power (198~702 W), extraction time (39~241 sec), and sulfuric acid (0~1.0 mol) were used as independent variables for central composite design (CCD) in order to predict optimum pretreatment conditions. It was noted that the pretreatment variables that affect the production of glucose (C6) and xylose (C5) significantly have been identified as the microwave power and extraction time. Additionally, the increase in microwave power and time had led to an increase in biosugar production. The superimposed contour plot for maximizing dependent variables showed the maximum C6 (hexose) and C5 (pentose) yields of 92.7 and 74.5% were estimated by the predicted model under pretreatment condition of 700 w, 185.7 sec, and 0.48 mol, and the yields of C6 and C5 were confirmed as 94.2 and 71.8% by experimental validation, respectively. This study showed that microwave-assisted pretreatment under low temperature below $100^{\circ}C$ with short pretreatment time was verified to be an effective enzyme free pretreatment process for the production of biosugar from LEA compared to conventional pretreatment methods.

• Journal of the Korean Recycled Construction Resources Institute
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• v.8 no.2
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• pp.227-234
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• 2020

Under consideration of construction waste recycling, candidate secondary products applicable for the civil and construction areas can be reliably employed based on the recycling cost analysis. For the validation purpose, probability-based cost analyses were performed to estimate recycling cost profit considering uncertainties. When recycling construction wastes, the costs at each stage are fully dependent on target products to be adopted. To achieve commercialization of each product, its quality has to be improved with economic efficiency through accurate evaluation of input costs. Based on the probabilistic recycling cost analysis, the cost benefit for target products was estimated with waste classification cost, transportation cost to recycling treatment facilities and production cost. All necessary information on the cost analysis were collected from literature, disclosure, and existing recycling companies. In addition, a cost difference between recycled and non-recycled events was made. As a result, a probability-based recycling cost estimate for candidate secondary products was herein presented.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.1
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• pp.28-35
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• 2006

An accurate prediction of budburst in grapevines is indispensable for vineyard frost warning system operations in spring because cold tolerance depends heavily on phonology. However, existing frost warning systems utilize only daily minimum temperature forecasts since there is no way to estimate the site-specific phonology of grapevines. A budburst estimation model based on thermal time was used to project budburst dates of two grapevine cultivars (Kyoho and Campbell Early), and advisories were issued depending on phonology as well as temperature. A 'warning' is issued if two conditions are met: the forecasted daily minimum temperature falls below $-1.5^{\circ}C$ and the estimated phonology is within the budburst period. A 'watch' is issued for a temperature range of -1.5 to $+1.5^{\circ}C$ with the same phonology condition. Validation experiments were done at 8 vineyards in Anseong in spring 2005, and the results showed a good agreement with the observations. This method was applied to the climatological normal year (1971-2000) to determine sites with high frost risk at a 30 m grid cell resolution. Among 608,585 grid cells constituting Anseong, 1,059 cells were identified as high risk for growing Kyoho and 2,788 cells for Campbell Early.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.881-881
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• 2012

낙동강유역에는 4대강 사업으로 8개의 보가 낙동강 본류에 새롭게 설치되었으며, 따라서 상류로부터 유입되는 유사가 보상류에 퇴적되어 하천제방이나 하천구조물의 안전을 위협할 수 있다. 또한 홍수시에는 농경지의 매몰과 저수지의 퇴적현상이 발생하는 등 유역유사에 의한 다양한 문제가 발생할 수 있으며, 강우로부터 유출되는 유사는 강우사상에 따라 빠르게 변할 수 있으나 수체에 즉각적인 영향을 유발하지 않을 경우 만성적인 특성으로 인해 침전물을 계속 이동시키며 축적되는 문제가 발생한다. 따라서 이러한 문제를 사전에 예측하고 낙동강유역에 대한 유역유사관리 대책마련을 마련하기 위해 유역유출과 유사의 이송 및 퇴적양상을 분석하여 유역관리를 위한 자료를 구축할 필요가 있다. 이러한 기초자료 분석을 위해 활용되는 유역모형 중 SWAT(Soil and Water Assessment Tool) 모형은 장기간 유역 유출로 인한 유사 모의를 수행하는데 가장 많이 활용되는 모형이며, 미국 농무성 농업연구소(USDA Agricultural Research Service, ARS)의 Jeff Amold 등에 의해 개발된 모형이다. SWAT 모형은 장기유출 및 유사 발생에 대한 시 공간적 변화를 모의하는 모형으로 넓은 범위의 유역에 대해 일단위 모의 간격으로 최대 100년까지 모의가 가능한 장기유역 모의에 최적화된 모형이다. 본 논문에서는 SWAT 모형을 이용하여 낙동강유역의 장기 유역 유출 및 유사 모의를 수행하기위해 2004년에서 2009년까지의 유출량 자료와 유량-유사량관계곡선 등을 이용하여 본류 및 지류 유출구 주요지점에 대해 검보정을 수행하고자 한다. 모의의 정확도 향상을 위해 안동댐, 임하댐, 영천댐, 합천댐, 남강댐, 밀양댐 및 낙동강 본류 등 총 7개 유역으로 구분하여 SWAT 모형을 구축하였으며, 각 유역별로 유출량과 유사량에 대하여 각각 보정 및 검증을 수행하였다. 낙동강 본류유역 총 7개의 댐 방류량자료와 20개의 대형하수종말처리장 방류량자료를 이용한 낙동강유역의 유출량 보정 및 검증 결과, 모의치가 실측치를 잘 반영하고 있는 것으로 나타났다. 또한 총 11개 지점의 수위관측소에 대해 유사량 측정 성과를 이용한 유사량 보정 및 검증 결과, 강우시 유사량 모의값은 유출량-유사량관계곡선 식을 잘 반영하였으나, 비강우시에는 모의값이 관계곡선 식의 결과값보다 대체적으로 높게 나타났다.

• Korean Journal of Food Science and Technology
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• v.46 no.5
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• pp.588-592
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• 2014

Under optimized condition mild pressure in combination with specific temperature for heat treatment transform the 6-gingerol into 6-shogaol. The purpose of this study was to optimize the conditions used for heat treatment under pressure for increasing 6-shogaol content in ginger (Zingiber officinale Roscoe). A central composite experimental design was used to evaluate the effects of application temperature ($70-130^{\circ}C$) and temperature-holding time (95-265 min) on the transformation of 6-shogaol. The experimental values were shown to be in significantly good agreement with the predicted values (adjusted determination coefficient, $R^2{_{Adj}}=0.9857$). 6-Shogaol content increased as the application temperature and temperature-holding time increased. By analyzing the response surface plots, the optimum conditions of heat treatment (temperature and time) for increasing 6-shogaol content were found to be $127^{\circ}C$ and 109 min, respectively. Under these optimal conditions, the predicted 6-shogaol content was 3.98 mg/g dried ginger. The adequacy of the model equation for predicting the optimum response values was effectively verified by the validation data.