• 한국지구물리탐사학회:학술대회논문집
• /
• 1999.08a
• /
• pp.137-155
• /
• 1999

Recently, Televiewer(Borehole Acoustic Scanner(Televiewer)) has come to be widely used specially for the general engineering construction design. The Televiewer tool using a focussed acoustic beam is to detect the amplitude and traveltime of each reflected acoustic signal at the wall, resulting in the amplitude- and traveltime image respectively. Fractures can be well detected, because they easily scatter the acoustic energy due to the highly narrow beam. In addition, the drilling work will rough the borehole wall so that the acoustic energy can be scattered simply due to the roughness of the wall. Thus, the amplitude level can be directed associated with the elastic properties(impedance) and the hardness of the rock as well. Meanwhile, the traveltime image provides an information about the borehole shape and can be converted to a high precision 3D caliper log(max. 288 arms). In this paper, based on the high resolution of Televiewer images, general evaluation methods are illustrated to derive very reliable rock parameters.

• The KIPS Transactions:PartB
• /
• v.10B no.3
• /
• pp.281-286
• /
• 2003

A large number of features are collected for problem solving in real life, but to utilize ail the features collected would be difficult. It is not so easy to collect of correct data about all features. In case it takes advantage of all collected data to learn, complicated learning model is created and good performance result can't get. Also exist interrelationships or hierarchical relations among the features. We can reduce feature's number analyzing relation among the features using heuristic knowledge or statistical method. Heuristic technique refers to learning through repetitive trial and errors and experience. Experts can approach to relevant problem domain through opinion collection process by experience. These properties can be utilized to reduce the number of feature used in learning. Experts generate a new feature (highly abstract) using raw data. This paper describes machine learning model that reduce the number of features used in learning using heuristic function and use abstracted feature by neural network's input value. We have applied this model to the win/lose prediction in pro-baseball games. The result shows the model mixing two techniques not only reduces the complexity of the neural network model but also significantly improves the classification accuracy than when neural network and heuristic model are used separately.

• The Korean Journal of Nuclear Medicine
• /
• v.33 no.4
• /
• pp.422-429
• /
• 1999

Purpose: The measurement of radiation absorbed dose is useful to predict the response after I-131 labeled metaiodobenzylguanidine (MIBG) therapy and determine therapy dose in patients with unresectable or malignant pheochromocytoma. We estimated the absorbed dose in tumor tissue after high dose I-131 MIBG in a patient with pheochromocytoma using a gamma camera and Medical Internal Radiation Dose (MIRD) formula. Materials and Methods: A 64-year old female patient with pheochromocytoma who had multiple metastases of mediastinum, right kidney and periaortic lymph nodes, received 74 GBq (200 mCi) of I-131 MIBG. We obtained anterior and posterior images at 0.5, 16, 24, 64 and 145 hours after treatment. Two standard sources of 37 and 74 MBq of I-131 were imaged simultaneously. Cummulated I-131 MIBG uptake in tumor tissue was calculated after the correction of background activity, attenuation, system sensitivity and count loss at a high count rate. Results: The calculated absorbed radiation dose was 32-63 Gy/ 74 GBq, which was lower than the known dose for tumor remission (150-200 Gy). follow-up studies at 1 month showed minimally reduced tumor size on computed tomography, and mildly reduced I-131 MIBG uptake. Conclusion: We estimated radiation absorbed dose after therapeutic I-131 MIBG using a gamma camera and MIRD formula, which can be peformed in a clinical nuclear medicine laboratory. Our results suggest that the measurement of radiation absorbed dose in I-131 MIBG therapy is feasible as a routine clinical practice that can guide further treatment plan. The accuracy of dose measurement and correlation with clinical outcome should be evaluated further.

• Korean Journal of Ecology and Environment
• /
• v.42 no.2
• /
• pp.200-211
• /
• 2009

A mathematical modeling program called Soil and Water Assessment Tool (SWAT) developed by USDA was applied to Kyongan stream watershed. It was run under BASINS (Better Assessment Science for Integrating point and Non-point Sources) program, and the model was calibrated and validated using KTMDL monitoring data of 2004${\sim}$2008. The model efficiency of flow ranged from very good to fair in comparison between simulated and observed data and it was good in the water quality parameters like flow range. The model reliability and performance were within the expectation considering complexity of the watershed and pollutant sources. The results of pollutant loads estimation as yearly (2004${\sim}$2008), pollutant loadings from 2006 were higher than rest of year caused by high precipitation and flow. Average non-point source (NPS) pollution rates were 30.4%, 45.3%, 28.1% for SS, TN and TP respectably. The NPS pollutant loading for SS, TN and TP during the monsoon rainy season (June to September) was about 61.8${\sim}$88.7% of total NPS pollutant loading, and flow volume was also in a similar range. SS concentration depended on precipitation and pollution loading patterns, but TN and TP concentration was not necessarily high during the rainy season, and showed a decreasing trend with increasing water flow. SWAT based on BASINS was applied to the Kyongan stream watershed successfully without difficulty, and it was found that the model could be used conveniently to assess watershed characteristics and to estimate pollutant loading including point and non-point sources in watershed scale.

• Journal of Animal Environmental Science
• /
• v.18 no.sup
• /
• pp.81-90
• /
• 2012

This study was evaluated high end research grade Near infrared spectrophotometer (NIRS) to low end popular field grade multiple Near infrared spectrophotometer (NIRS) for rapid analysis at forage quality at sight with 241 samples of Italian ryegrass silage during 3 years collected whole country for evaluate accuracy and precision between instruments. Firstly collected and build database high end research grade NIRS using with Unity Scientific Model 2500X (650 nm~2,500 nm) then trim and fit to low end popular field grade NIRS with Unity Scientific Model 1400 (1,400 nm~2,400 nm) then build and create calibration, transfer calibration with special transfer algorithm. The result between instruments was 0.000%~0.343% differences, rapidly analysis for chemical constituents, NDF, ADF, and crude protein, crude ash and fermentation parameter such as moisture, pH and lactic acid, finally forage quality parameter, TDN, DMI, RFV within 5 minutes at sight and the result equivalent with laboratory data. Nevertheless during 3 years collected samples for build calibration was organic samples that make differentiate by local or yearly bases etc. This strongly suggest population evaluation technique needed and constantly update calibration and maintenance calibration to proper handling database accumulation and spread out by knowledgable control laboratory analysis and reflect calibration update such as powerful control center needed for long lasting usage of forage analysis with NIRS at sight. Especially the agriculture products such as forage will continuously changes that made easily find out the changes and update routinely, if not near future NIRS was worthless due to those changes. Many research related NIRS was shortly study not long term study that made not well using NIRS, so the system needed check simple and instantly using with local language supported signal methods Global Distance (GD) and Neighbour Distance (ND) algorithm. Finally the multiple popular field grades instruments should be the same results not only between research grade instruments but also between multiple popular field grade instruments that needed easily transfer calibration and maintenance between instruments via internet networking techniques.

• Journal of Digital Convergence
• /
• v.20 no.4
• /
• pp.147-157
• /
• 2022

This study tried to propose a smart farm technology strategy suitable for the domestic situation, focusing on the differentiation suitable for the domestic situation of ICT technology. In the case of advanced countries in the overseas agricultural industry, it was confirmed that they focused on the development of a specific stage that reflected the geographical characteristics of each country, the characteristics of the agricultural industry, and the characteristics of the people's demand. Confirmed that no enemy development is being performed. Therefore, in response to problems such as a rapid decrease in the domestic rural population, aging population, loss of agricultural price competitiveness, increase in fallow land, and decrease in use rate of arable land, this study aims to develop smart farm ICT technology in the future to create quality agricultural products and have price competitiveness. It was suggested that the smart farm should be promoted by paying attention to the excellent performance, ease of use due to the aging of the labor force, and economic feasibility suitable for a small business scale. First, in terms of economic feasibility, the ICT technology is configured by selecting only the functions necessary for the small farm household (primary) business environment, and the smooth communication system with these is applied to the ICT technology to gradually update the functions required by the actual farmhouse. suggested that it may contribute to the reduction. Second, in terms of performance, it is suggested that the operation accuracy can be increased if attention is paid to improving the communication function of ICT, such as adjusting the difficulty of big data suitable for the aging population in Korea, using a language suitable for them, and setting an algorithm that reflects their prediction tendencies. Third, the level of ease of use. Smart farms based on ICT technology for the development of the Industry6.0 (1.0(Agriculture, Forestry) + 2.0(Agricultural and Water & Water Processing) + 3.0 (Service, Rural Experience, SCM)) perform operations according to specific commands, finally suggested that ease of use can be promoted by presetting and standardizing devices based on big data configuration customized for each regional environment.

• Land and Housing Review
• /
• v.12 no.2
• /
• pp.33-45
• /
• 2021

Due to recent changes in government policy, officetels have received attention as alternative assets, along with the uplift of office and apartment prices in Seoul. However, the current officetel price indexes use small-size samples and, thus, there is a critique on their accuracy. They rely on valuation prices which lag the market trend and do not properly reflect the volatile nature of the property market, resulting in 'smoothing'. Therefore, the purpose of this paper is to create the officetel price index using transaction data. The data, provided by the Ministry of Land, Infrastructure and Transport from 2005 to 2020, includes sales prices and rental prices - Jeonsei and monthly rent (and their combinations). This study employed a repeat sales model for sales, jeonsei, and monthly rent indexes. It also contributes to improving conversion rates (between deposit and monthly rent) as a supplementary indicator. The main findings are as follows. First, the officetel price index and jeonsei index reached 132.5P and 163.9P, respectively, in Q4 2020 (1Q 2011=100.0P). However, the rent index was approximately below 100.0. Sales prices and jeonsei continued to rise due to high demand while monthly rent was largely unchanged due to vacancy risk. Second, the increase in the officetel sales price was lower than other housing types such as apartments and villas. Third, the employed approach has seen a potential to produce more reliable officetel price indexes reflecting high volatility compared to those indexes produced by other institutions, contributing to resolving 'smoothing'. As seen in the application in Seoul, this approach can enhance accuracy and, therefore, better assist market players to understand the market trend, which is much valuable under great uncertainties such as COVID-19 environments.

• Korean Journal of Culture and Social Issue
• /
• v.22 no.4
• /
• pp.523-541
• /
• 2016

Both the child's and defendant's testimonies play crucial roles in the court's ruling of a child abuse case. Thus, empirical studies examining a child's truthful report, that is, disclosure, of his or her experience and recantation of the disclosure have manifold practical implications. The objective of the present study was to examine how easily a child recants his or her testimony after witnessing and disclosing an adult engaging in a small mistake. Furthermore, this study examined whether the child's age and emotional support from his or her caregiver predict the recantation of the child's testimony. Children of age 5-8 years played with dolls with the experimenter and witnessed the experimenter breaking the doll mask. The experimenter asked the children to keep it a secret. Then the children had the first memory interview, during which the interviewer induced the child to disclose the incident. Based on the treatment conditions, some children were provided supportive feedback while other received unsupportive feedback from their primary caregivers (mother) regarding the disclosure, then were interviewed for the second time. First, the author of this study examined whether the children would recant their disclosure (whether they would deny the incident after telling the truth of about what happened to the doll), and also examined the features of the child's voluntary reports, that is, the degree of their honesty. The findings of the experiment indicated that there were age-specific differences in the frequency of recantation, meaning that older children (8-9-year-olds) showed a stronger tendency to maintain their recantation in the second interview than relatively younger children (6-7-year-olds). Furthermore, children who received supportive responses from their mothers regarding the disclosure demonstrated more honest reports compared to those who received unsupportive responses from their mothers. The findings of this study assist the understanding of the effects of social-motivational factors on the process of children disclosing the truth when voluntarily recalling a negative incident that they had experienced and provide practical implications in legal aspects.

• Economic Analysis
• /
• v.26 no.1
• /
• pp.84-132
• /
• 2020

A central bank infers market expectations of future yields based on yield curves. The central bank needs to precisely understand the changes in market expectations of future yields in order to have a more effective monetary policy. This need explains why a range of models have attempted to produce yield curves and market expectations that are as accurate as possible. Alongside the development of bond markets, the interconnectedness between them and macroeconomic factors has deepened, and this has rendered understanding of what macroeconomic variables affect yield curves even more important. However, the existence of various theories about determinants of yields inevitably means that previous studies have applied different macroeconomics variables when estimating yield curves. This indicates model uncertainties and naturally poses a question: Which model better estimates yield curves? Put differently, which variables should be applied to better estimate yield curves? This study employs the Dynamic Nelson-Siegel Model and takes the Bayesian approach to variable selection in order to ensure precision in estimating yield curves and market expectations of future yields. Bayesian variable selection may be an effective estimation method because it is expected to alleviate problems arising from a priori selection of the key variables comprising a model, and because it is a comprehensive approach that efficiently reflects model uncertainties in estimations. A comparison of Bayesian variable selection with the models of previous studies finds that the question of which macroeconomic variables are applied to a model has considerable impact on market expectations of future yields. This shows that model uncertainties exert great influence on the resultant estimates, and that it is reasonable to reflect model uncertainties in the estimation. Those implications are underscored by the superior forecasting performance of Bayesian variable selection models over those models used in previous studies. Therefore, the use of a Bayesian variable selection model is advisable in estimating yield curves and market expectations of yield curves with greater exactitude in consideration of the impact of model uncertainties on the estimation.

• Current Research on Agriculture and Life Sciences
• /
• v.4
• /
• pp.141-153
• /
• 1986

This study intends to document the existing cyclical fluctuations of garic and onion price at farm gate level during the period of 1966-1986 in Korea. The existing patterns of such cyclical fluctuations were estimated systematically by removing the seasonal fluctuation and irregular movement as well as secular trend from the original price through the moving average method. It was found that the cyclical fluctuations of garic and onion prices repeated six and seven times respectively during the same period, also the amplitude coefficient of cyclical fluctuations showed speed up in recent years. It was noticed that the cyclical fluctuations of price in onion was higher than that of in garic.