• Journal of Information Processing Systems
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• v.18 no.4
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• pp.457-469
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• 2022

Hydraulic concrete buildings in the northwest of China are often subject to the combined effects of low-temperature frost damage, during drying and wetting cycles, and salt erosion, so the study of concrete deterioration prediction is of major importance. The prediction model of the relative dynamic elastic modulus (RDEM) of four different kinds of modified concrete under the special environment in the northwest of China was established using Grey residual Markov theory. Based on the available test data, modified values of the dynamic elastic modulus were obtained based on the Grey GM(1,1) model and the residual GM(1,1) model, combined with the Markov sign correction, and the dynamic elastic modulus of concrete was predicted. The computational analysis showed that the maximum relative error of the corrected dynamic elastic modulus was significantly reduced, from 1.599% to 0.270% for the BS2 group. The analysis error showed that the model was more adjusted to the concrete mixed with fly ash and mineral powder, and its calculation error was significantly lower than that of the rest of the groups. The analysis of the data for each group proved that the model could predict the loss of dynamic elastic modulus of the deterioration of the concrete effectively, as well as the number of cycles when the concrete reached the damaged state.

• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.385-392
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• 2011

Recently, the concern of IT-in-Agriculture convergence technology that combines information technology and agriculture is increasing rapidly. Especially, the crop cultivation related prediction services by spatial data mining (SDM) can play an important role in reducing the damage of natural disaster and enhancing crop productivity. However, the data conversion and integration procedure to acquire the learning dataset of SDM for the prediction service need a lot of effort and time, because of their heterogeneity between distributed data. In addition, calculating spatial neighborhood relationships between spatial and non-spatial data necessitates requires the complicated calculation procedure for large dataset. In this paper, we suggest a SOA-based data integration framework that can effectively integrate distributed heterogeneous data by treating each data source as a service unit and support to find the optimal prediction service by improving productivity of learning dataset for SDM. In our experiment, we confirmed that our framework can be effectively applied to find the optimal prediction service for the frost damage area, by considering the case of peach crop cultivation in Icheon in Korea.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.1151-1155
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• 2010

Frost depth is one of important factors to design roadway structure, and it can be estimated with numerical simulation on thermal distribution through subgrade soils. Thermal conductivity is a key parameter for accurate prediction on thermal distribution, but there are few studies on thermal conductivity of subgrade soils in Korea. Thermal conductivity can be affected by several factors such as dry density, moisture content, and saturation degree based on previous researches. Two empirical equations to estimate thermal conductivity are applied to access the accuracy of these equations with experimental data. Results indicate that the equation can be used to estimate thermal conductivity with proper quartz fraction.

• Journal of Korean Society of Transportation
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• v.15 no.3
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• pp.7-23
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• 1997

우리나라의 전면적인 약 95%가 계절적 동결지역에 속하며 동상과 융해로 인해 도로등 지반구조물은 피해을 입는다. 본 논문에서는 국립건설시험소의 10년간 실측자료중 지역별로 대표하여 15개 도시 528개 지점을 선정하여 최대동결지수를 4개 그룹(250이하, 250∼400, 400∼600, 600이상)으로 분류하여 분석하였다. 또한 동결심도 계산에 동결지수외에 흙의 함수비와 전조밀도를 각각 추가로 고려하여 새로운 산정식을 제시하였다. 그리고 지역에 따른 과다산정을 막기 위하여 동결지수 분류별로 4그룹으로 세분화하여 경제적인 설계가 가능하도록 하였다. 새 제안식과 기존식을 비교하여 보았을 때 새 제안식이 기존식보다 전반적으로 크게 산정되나 그 지역의 함수비나 건조밀도를 추가로 고려하였으므로 보다 합리적인 산정식이라 할 수 있다.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.381-394
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• 2005

In order to estimate the damage of orchards due' to natural disasters such as typhoon, severe rain, freezing or frost, it is necessary to estimate the number of fruit bearing before and after the damage. To estimate the fruit bearing after the damages are easily done by delegations, but it cost too high to survey every insured farm household and calculate the fruit bearing before the damage. In this article, we suggest to use a random coefficient model to predict the numbers of fruit bearing in the orchards before the damage based on the tree age and the area information.

• International Journal of Highway Engineering
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• v.20 no.2
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• pp.57-65
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• 2018

PURPOSES : The study aims to predict the service life of national highway asphalt pavements through deep learning methods by using maintenance history data of the National Highway Pavement Management System. METHODS : For the configuration of a deep learning network, this study used Tensorflow 1.5, an open source program which has excellent usability among deep learning frameworks. For the analysis, nine variables of cumulative annual average daily traffic, cumulative equivalent single axle loads, maintenance layer, surface, base, subbase, anti-frost layer, structural number of pavement, and region were selected as input data, while service life was chosen to construct the input layer and output layers as output data. Additionally, for scenario analysis, in this study, a model was formed with four different numbers of 1, 2, 4, and 8 hidden layers and a simulation analysis was performed according to the applicability of the over fitting resolution algorithm. RESULTS : The results of the analysis have shown that regardless of the number of hidden layers, when an over fitting resolution algorithm, such as dropout, is applied, the prediction capability is improved as the coefficient of determination ($R^2$) of the test data increases. Furthermore, the result of the sensitivity analysis of the applicability of region variables demonstrates that estimating service life requires sufficient consideration of regional characteristics as $R^2$ had a maximum of between 0.73 and 0.84, when regional variables where taken into consideration. CONCLUSIONS : As a result, this study proposes that it is possible to precisely predict the service life of national highway pavement sections with the consideration of traffic, pavement thickness, and regional factors and concludes that the use of the prediction of service life is fundamental data in decision making within pavement management systems.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.3
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• pp.185-191
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• 2005

An accurate prediction of dormancy release and bud burst in temperate zone fruit trees is indispensable for farmers to plan heating time under partially controlled environments as well as to reduce the risk of frost damage in open fields. A thermal time-based two-step phenological model that originated in Italy was applied to two important grapevine cultivars in Korea for predicting bud-burst dates. The model consists of two sequential periods: a rest period described by chilling requirement and a forcing period described by heating requirement. It requires daily maximum and minimum temperature as an input and calculates daily chill units (chill days in negative sign) until a pre-determined chilling requirement for rest release is met. After the projected rest release date, it adds daily heat units (anti-chill days in positive sign) to the chilling requirement. The date when the sum reaches zero isregarded as the bud-burst in the model. Controlled environment experiments using field sampled twigs of 'Campbell Early' and 'Kyoho' cultivars were carried out in the vineyard at the National Horticultural Research Institute (NHRI) in Suwon during 2004-2005 to derive the model parameters: threshold temperature for chilling and chilling requirement for breaking dormancy. The model adjusted with the selected parameters was applied to the 1994-2004 daily temperature data obtained from the automated weather station in the NHRI vineyard to estimate bud burst dates of two cultivars and the results were compared with the observed data. The model showed a consistently good performance in predicting the bud burst of 'Campbell Early' and 'Kyoho' cultivars with 2.6 and 2.5 days of root mean squared error, respectively.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.12
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• pp.789-794
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• 2008

Recently, much attention has been paid in the field of defrosting because clear windshield in vehicle without effecting the thermal comfort is realized essentially. Then in winter, defrosting performance is one of the important factors in vehicle design to make certain driver's view. In this study, the velocity profile, temperature distribution and frost melting pattern on the windshield screen have been predicted in three dimensional geometry of an automobile interior. Numerical analyses predict a detailed description of fluid flow and temperature patterns on the inside windshield screen, utilizing the flow through defroster nozzle. Numerical prediction established a good defrosting performance with the standard distance ratio and the defroster nozzle angle ranging from $30^{\circ}$ to $40^{\circ}$, which satisfy the condition of National Highway Traffic Safety Administration (NHTSA) completely.

• Korean Journal of Agricultural and Forest Meteorology
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• v.10 no.3
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• pp.107-112
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• 2008

"Jeung-Bo-San-Lim-Gyeong-Je" (meaning "Revised Forest Management") has been well recognized as the informative document that introduces scientific knowledge and experiences of Korean ancestors regarding weather and climate. The tradition of Gwan-Cheon-Mang-Gi(i.e., empirical forecasting of short-term weather phenomena based on the status of cloud or sky) has been continuously utilized as a civilian weather forecasting method and even for very short-term weather prediction by operational forecasters these days. This agricultural technology textbook, published during the Great King Youngjo in Chosun-Dynasty, may be regarded as a poorly written document from the modern standpoint. Nonetheless, this study demonstrates that by and large the empirical knowledge contained in the book is indeed science based although their applications are limited to several hours for local forecasts in agricultural practices and daily living. For example, the wisdom of keeping water at an optimum level in a paddy field after sowing to prevent young seedlings from late frost damages was not at all different from the present technique of vinyl covered seedling nursery.

• (The)Study of the Eastern Classic
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• no.57
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• pp.41-66
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• 2014

The Purpose of this paper is, through the character-figuration aspect of existing Yeoheon Jang Hyungwang(旅軒 張顯光, 1554~1637)-related folk tales, to determine the relation between the people's awareness on Yeoheon and the change in the folk tales. Only 4 pieces of Yeoheon-related folk tales are existed ; ; Forgiving a rude son of the provincial governor generously. ; Predicting 'the frost of May' and Preventing the cold-weather damage, when he served as Euiseong governor, and ; The folk tales of origins of the place name - Chimabawi Rockand Yeoheondae. shows the great scholar's liberal-hearted and generous personality. One day Jang Hyungwang looked shabby and a young person was quite rude to him. But Jang Hyungwang forgive him generously. Also Yeoheon teach him the thrift and modesty. described him as a governor filled with a love for the people. He tried to edify the people with the Confucian ethics and improve the life's work of the people. embodied him as a government official of high integrity. When his wife received the silk slip from the people, as farewell gift, he ordered his wife return that. and show the images of the Predicting the future and an extraordinary moralizer. Generally These folk tales are based on his personality, whereabouts and the real case. So we could find his images in the folk tales are close to his actual feature - thrift, modest, noble-minded, well-versed in Iching and practicing moral statesmanship.