• Journal of agricultural medicine and community health
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• v.34 no.3
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• pp.279-290
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• 2009

Objectives: WHO insisted on that we should study about association between residential environment and health status and make 'health city' concept as practical motto. This study analyzed about that how community environment affected their health. Methods: We surveyed residential environment satisfaction and health status of a apartment complex residents. We transformed Chun's index about housing environment study and social capital index of WHO and used as community health survey. We analyzed the association between health status and related factor by using principal compound analysis and logistic regression analysis. Results: We found out that the perceived health status 1 years ago was highly related to the residential environment and also extracted five residential environment component (APT maintenance, House, APT complex, Neighbor, APT building) by principal component analysis. After residential environment component, demographic and socioeconomic variable were controlled, the high satisfaction group of APT complex and neighbor relationship was in lower risk of perceived health status 1 years ago than the low satisfaction group. Conclusions: Recently, the importance of residential environment and neighborhood is shaped as community capacity. Therefore, social relationship and residential environment should be the core variable for health promotion of community. After all, we should know the relationship of residential environment and perceived health status 1 years ago. This helps the concept of health city clearly.

• Food Science and Preservation
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• v.24 no.3
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• pp.394-405
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• 2017

This study was conducted to confirm the usefulness of essential oil components in yuzu and kumquat cultivated in Korea for comparison with those in lemon and lime. The volatile flavor compounds in citrus fruits (yuzu, kumquat, lemon and lime) were extracted for 3 h with 100 mL redistilled n-pentane/diethylether (1:1, v/v) mixture, using a simultaneous steam distillation and extraction apparatus (SDE). The volatile flavor compositions of the samples were analyzed by gas chromatography-mass spectrometry (GC-MS). The aroma compounds analyzed were 104 (3,713.02 mg/kg) in yuzu, 87 (621.71 mg/kg) in kumquat 103 (3,024.69 mg/kg) in lemon and 106 (2,209.16 mg/kg) in lime. Limonene was a major volatile flavor compound in four citrus fruits. The peak area of limonene was 35.03% in yuzu, 63.82% in kumquat, 40.35% in lemon, and 25.06% in lime. In addition to limonene, the major volatile flavor compounds were ${\gamma}$-terpinene, linalool, ${\beta}$-myrcene, (E)-${\beta}$-farnesene, ${\alpha}$-pinene and ${\beta}$-pinene in yuzu, and ${\beta}$-myrcene, ${\alpha}$-pinene, (Z)-limonene oxide, (E)-limonene oxide, geranyl acetate and limonen-10-yl acetate in kumquat. Furthermore, ${\gamma}$-terpinene, ${\beta}$-pinene, ${\beta}$-myrcene, geranyl acetate, neryl acetate and (Z)-${\beta}$-bisabolene in lemon and ${\gamma}$-terpinene, ${\beta}$-pinene, (Z)-${\beta}$-bisabolene, neral, geranial and neryl acetate in lime were also detected. As a result, it was confirmed that the composition of volatile flavor compounds in four citrus fruits was different. Also, yuzu and kumquat are judged to be worthy of use alternatives for lemon and lime widely used in the fragrance industry.

• 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 Korean Society of Forest Science
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• v.52 no.1
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• pp.37-49
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• 1981

The purpose of the study is to find out the objective method of valuation on the forest stands through the analysis of logging costs that is positively related to timber production. The two forest (Amgog, Whangryoung), located nereby, but forest type, logging and skidding conditions being slightly different, were slected to carry out the study. The objective timber stumpage value were determined by investigating the appropriate timber production costs and profits of logging operations. The main result obtained in this study are as follows: 1. The rate of logging cost in consisting of timber market price is 13.15% in the area of Amgog logging place and 19.48% in Whangryoung. 2. The rate of the other production cost excluding logging cost is 15.36% in the area of Amgog logging place and 28.85% in Whangryoung. 3. The total rate of timber production cost in consisting of the market price is more than 28.51% in the area of Amgog logging place and 48.33% in Whangryoung, 4. Though the productivity of forest land is affected by the selection of tree species, tending, treatments and effective management of forest land, the more important problem is improvement of logging condition. 5. The rate of production cost in timber price is so high that we should endeavore to improve the productivity of labour and its quality, and minimize the difference of piece work per day in accordance to the various site condition. 6. Although the profit of forest industry is related to the period of recapturing investment, it is more closely related to the working condition, risk of investment and continuous change of social investment interest. 7. If the right variables which are related to the timber market, are objectively obtained, the stumpage value of mature forests can be objectively caculated by applying straight line discounting method or compound discounting method in caculating the stump to market price.