• Journal of Animal Science and Technology
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• v.52 no.4
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• pp.259-264
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• 2010

This study was carried out to estimate genetic parameters and breeding values of Hanwoo cows for carcass traits. Carcass records were collected from Korean steers raised at the private farms located in rural area of Gangwon-do and slaughtered from December 2004 to June 2008 at the three slaughter houses near fattening farm. The results obtained in this study were summarized as follows; The means and standard deviations of the carcass traits were $5.57{\pm}2.01$ for marbling score (MS), $10.87{\pm}4.06mm$ for backfat thickness (BFT), $87.87{\pm}9.07cm^2$ for eye muscle area (EMA), $426.75{\pm}49.27kg$ for carcass weight (CW), and $65.80{\pm}3.80$ for yield index (YI). Heritability estimates using single trait analyses were 0.36 for MS, 0.35 for BFT, 0.24 for EMA, 0.29 for CW, and 0.40 for YI, respectively. Genetic correlation coefficients of MS with BFT, EMA, CW, and YI were -0.21, 0.30, -0.21 and 0.30, and those of BFT with EMA, CW and YI were -0.12, 0.57 and -0.97, and those of EMA with CW and YI were 0.32 and 0.27, respectively. And genetic correlation of CW with YI was -0.62. Single trait selection for MS might lead to reducing BFT, but might be an obstacle to increase CW due to negative genetic correlations of MS with BFT and CW.

• Korean Journal of Poultry Science
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• v.46 no.4
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• pp.313-325
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• 2019

In most cases of HPAI (highly pathogenic avian influenza) outbreaks, stamping-out operations are initiated by officially designating the affected premise, which is subsequently followed by depopulation of infected flocks. The primary objective of this study was to develop an evaluation method that correlates the level of biosecurity and the risk of having an HPAI outbreak in domestic poultry farms. A total of eight farms were selected nationwide, including layer farms, broiler farms, and an animal welfare type farm. The biosecurity level of the chosen poultry farms was assessed based on a total scoring index of 183 divided into three categories, general management (51), quarantine management (106), and sanitation management (26). Conclusively, the five layer farms (JS, GE, CS, HS, OE), scored higher overall scores compared to the animal welfare farm (CH) and broiler farms (JG, LB). In terms of scoring, which adds up to a total of 183 points, most layer farms scored between 130 and 157, while the two broiler farms and the welfare farm scored 45, 75 and 70, respectively. Next, an independent HPAI risk assessment of the farms was carried out. Regarding the correlation between biosecurity levels and HPAI risks, in the farms that presented a higher overall score in terms of biosecurity and outweighed the risks of HPAI, they tended to earn more points in the quarantine management category. The results of this study suggest that a viable system for evaluating biosecurity levels can establish strong correlations with the risk of having HPAI.

• Radiation Oncology Journal
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• v.17 no.2
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• pp.136-140
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• 1999

Purpose : Prostate specific antigen (PSA) is a useful tumor marker, which is widely used as a diagnostic index and predictor of both treatment and follow-up result in prostate cancer. A prospective analysis was carried out to obtain the period of PSA normalization and the half life of PSA and to analyze the factors influencing the period of PSA normalization. The PSA level was checked before and serially after radical radiotherapy. Materials and Method : Twen쇼 patients with clinically localized prostate cancer who underwent radical external beam radiotherapy were enrolled in this study. Accrual period was from April 1993 to May 1998. Median follow-up period was 20 months. Radiotherapy was given to whole pelvis followed by a boost to prostate. Dose range for the whole pelvis was from 45 Gy to 50 Gy and boost dose to prostate, from 14 Gy to 20 Gy. The post-irradiation PSA normal value was under 3.0 ng/ml. The physical examination and serum PSA level evaluation were performed at 3 month interval in the first one year, and then at every 4 to 6 months. Results : PSA value was normalized in nineteen patients (95%) within 12 months. The mean period of PSA normalization was 5.3 (${\pm}$2.7) months. The half life of PSA Of the nonfailing patients was 2.1 (${\pm}$0.9) month. The nadir PSA level Of the nonfailing Patients waS 0.8 (${\pm}$0.5) ng/ml. The period of PSA normalization had the positive correlation with pretreatment PSA level (R$^{2}$=0.468). The nadir PSA level had no definite positive correlation with the pretreatment PSA level (R$^{2}$=0.075). The half life of serum PSA level also had no definite correlation with pretreatment PSA level (R$^{2}$=0.029). Conclusion :The PSA level was mostly normalized within 8 months (85%). If it has not normalized within 12 months, we should consider the residual disease in prostate or distant metastasis. In 2 patients, the PSA level increased 6 months or 20 months before clinical disease was detected. So the serum PSA level can be used as early diagnostic indicator of treatment failure.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.12
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• pp.844-861
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• 2008

The papers published in the Korean Journal of Air-Conditioning and Refrigeration Engineering during the year of 2007 have been reviewed. Focus has been put on current status of research in the aspect of heating, cooling, ventilation, sanitation and building environments. The conclusions are as follows. (1) The research trends of fluid engineering have been surveyed as groups of general fluid flow, fluid machinery and piping, etc. New research topics include micro nano fluid, micropump and fuel cell. Traditional CFD was still popular and widely used in research and development. Studies about fans and pumps were performed in the field of fluid machinery. Characteristics of flow and fin shape optimization are studied in the field of piping system. (2) The research works on heat transfer have been reviewed in the field of heat transfer characteristics, heat exchangers, and desiccant cooling systems. The research on heat transfer characteristics includes thermal transport in pulse tubes, high temperature superconductors, ground heat exchangers, fuel cell stacks and ice slurry systems. For the heat 'exchangers, the research on pin-tube heat exchanger, plate heat exchanger, condensers and gas coolers has been cordially implemented. The research works on heat transfer augmenting tubes have been also reported. For the desiccant cooling systems, the studies on the design and operating conditions for desiccant rotors as well as performance index are noticeable. (3) In the field of refrigeration, many papers were presented on the air conditioning system using CO2 as a refrigerant. The issues on the two-stage compression, the oil selection, and the appropriate oil charge were treated. The subjects of alternative refrigerants were also studied steadily. Hydrocarbons, DME and their mixtures were considered and various heat transfer correlations were proposed. (4) Research papers have been reviewed in the field of building facilities by grouping into the researches on heat and cold sources, air conditioning and air cleaning, ventilation and fire research including tunnel ventilation, flow control of piping system, and sound research with drain system. Main focuses have been addressed to the promotion of efficient or effective use of energy, which helps to save energy and results in reduced environmental pollution and operating cost. (5) Studies were mostly focused on analyzing the indoor environment in various spaces like cars, old tombs, machine rooms, and etc. in an architectural environmental field. Moreover, subjects of various fields such as the evaluation of noise, thermal environment, indoor air quality and development of energy analysis program were researched by various methods of survey, simulation, and field experiment.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.307-319
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• 2016

A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.175-190
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• 2018

Recently, policy of the marine advanced countries were switched from the preemption using ocean to post-project development. In this study, we suggest improvement and the pending issues when are deducted to the database of the marine spatial information is constructed over the GIS system for the Korean Marine Spatial Planning (KMSP). More than 250 spatial information in the seas of Korea were processed in order of data collection, GIS transformation, data analysis and processing, data grouping, and space mapping. It's process had some problem occurred to error of coordinate system, digitizing process for lack of the spatial information, performed by overlapping for the original marine spatial information, and so on. Moreover, solution is needed to data processing methods excluding personal information which is necessary when produce the spatial data for analysis of the used marine status and minimized method for different between the spatial information based GIS system and the based real information. Therefore, collection and securing system of lacking marine spatial information is enhanced for marine spatial planning. it is necessary to link and expand marine fisheries survey system. It is needed to the marine spatial planning. The marine spatial planning is required to the evaluation index of marine spatial and detailed marine spatial map. In addition, Marine spatial planning is needed to standard guideline and system of quality management. This standard guideline generate to phase for production, processing, analysis, and utilization. Also, the quality management system improve for the information quality of marine spatial information. Finally, we suggest necessity need for the depths study which is considered as opening extension of the marine spatial information and deduction on application model.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.6
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• pp.27-36
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• 2021

At a time when the equitable use of urban parks is gradually emerging as a social issue, this study was initiated to expand the influence of urban parks by improving the quality of park services, thereby resolving areas not covered by urban park services. This study targeted the Hangang Park in Seoul, where the qualitative service of parks shows the greatest difference. The influence relationship between the qualitative services of the park and the user's sphere of influence, which indicates the distribution of park users, was proposed to assess the influence of improvements in the quality of service. As a research method, the top three districts and the bottom three districts were selected through the Han River Park user satisfaction survey conducted from 2017 to 2019, and a qualitative service evaluation was carried out. It was derived using the data acquired in September. Afterward, by performing a spatial autocorrelation analysis on the user's sphere of influence, additional verification of the user's sphere of influence was performed numerically and visually. As a result of the study, the user influence in the top three districts, with high-quality service, was stronger and wider than that of the lower three districts. It was confirmed that the quality of service of the park affects the user influence. This shows that to realize park equity, it is necessary to improve the quality of services through continuous management and improvement of individual parks and the creation of new parks. This study has significance in that it recognizes the limitations of research on park services from a supplier's point of view and evaluates the qualitative services of parks from the perspective of actual park users. We propose an alternative to deal with the lower the park deprivation index.

• Journal of Conservation Science
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• v.33 no.6
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• pp.399-416
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• 2017

The 'Wat Phou and Associated Ancient Settlements within the Champasak Cultural Landscape' of Laos was designated as a UNESCO World Cultural Heritage in 2001. The uppermost structure of the Sanctuary in Wat Phou has been destroyed and being variably damaged, maintenance is required through scientific and systematic diagnosis. The Sanctuary of Wat Phou was constructed mainly using sandstones and bricks. There are physical damages including fracture, break out, exfoliation and interval as well as biological damages by lichen, mosses and weeds. According to the ultrasonic velocity measurement and property evaluation of the sandstones of the Sanctuary in Wat Phou, weathering index of the eastern side sandstones is 0.10 to 0.74 (mean 0.36), showing MW grade. Southern and northern side sandstones have relatively higher properties with average weathering indices of 0.30 and 0.32. The results of slope analysis of the Sanctuary, indicated that the 4th spot in the southern side has the largest slope of $5^{\circ}W$, seemingly due to the unstable ground around the Sanctuary. Based on the relative level measurement and past drawings, the Sanctuary is verified to have been located on ground with a certain slope rather than flatland. The ground of the southern side is inclined $1.51^{\circ}$ more than that of the northern side, which will affect the structural stability of the temple. The interval width of the selected southern spot is the largest with an average width of 159.5 mm, and the largest width is 328.3 mm at the top, since the width increases above rather than below, seemingly due to the unequal subsidence of the ground. Constant maintenance for conservation is required for the structural stability of the Sanctuary in Wat Phou, which was partly collapsed and has also suffered physical damage.