• Korean Journal of Soil Science and Fertilizer
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• v.43 no.5
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• pp.705-715
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• 2010

The adoption of carbon foot print system is being activated mostly in the developed countries as one of the long-term response towards tightened up regulations and standards on carbon emission in the agricultural sector. The Korean Ministry of Environment excluded the primary agricultural products from the carbon foot print system due to lack of LCI (life cycle inventory) database in agriculture. Therefore, the research on and establishment of LCI database in the agriculture for adoption of carbon foot print system is urgent. Development of LCA (life cycle assessment) methodology for application of LCA to agricultural environment in Korea is also very important. Application of LCA methodology to agricultural environment in Korea is an early stage. Therefore, this study was carried out to find out the effect of lettuce cultivation on agricultural environment by establishing LCA methodology. Data collection of agricultural input and output for establishing LCI was carried out by collecting statistical data and documents on income from agro and livestock products prepared by RDA. LCA methodology for agriculture was reviewed by investigating LCA methodology and LCA applications of foreign countries. Results based on 1 kg of lettuce production showed that inputs including N, P, organic fertilizers, compound fertilizers and crop protectants were the main sources of major emission factor during lettuce cropping process. The amount of inputs considering the amount of active ingredients was required to estimate the actual quantity of the inputs used. Major emissions due to agricultural activities were $N_2O$ (emission to air) and ${NO_3}^-$/${PO_4}^-$ (emission to water) from fertilizers, organic compounds from pesticides and air pollutants from fossil fuel combustion in using agricultural machines. The softwares for LCIA (life cycle impact assessment) and LCA used in Korea are 'PASS' and 'TOTAL' which have been developed by the Ministry of Knowledge Economy and the Ministry of Environment. However, the models used for the softwares are the ones developed in foreign countries. In the future, development of models and optimization of factors for characterization, normalization and weighting suitable to Korean agricultural environment need to be done for more precise LCA analysis in the agricultural area.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.121-139
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• 2014

Predicting corporate failure has been an important topic in accounting and finance. The costs associated with bankruptcy are high, so the accuracy of bankruptcy prediction is greatly important for financial institutions. Lots of researchers have dealt with the topic associated with bankruptcy prediction in the past three decades. The current research attempts to use ensemble models for improving the performance of bankruptcy prediction. Ensemble classification is to combine individually trained classifiers in order to gain more accurate prediction than individual models. Ensemble techniques are shown to be very useful for improving the generalization ability of the classifier. Bagging is the most commonly used methods for constructing ensemble classifiers. In bagging, the different training data subsets are randomly drawn with replacement from the original training dataset. Base classifiers are trained on the different bootstrap samples. Instance selection is to select critical instances while deleting and removing irrelevant and harmful instances from the original set. Instance selection and bagging are quite well known in data mining. However, few studies have dealt with the integration of instance selection and bagging. This study proposes an improved bagging ensemble based on instance selection using genetic algorithms (GA) for improving the performance of SVM. GA is an efficient optimization procedure based on the theory of natural selection and evolution. GA uses the idea of survival of the fittest by progressively accepting better solutions to the problems. GA searches by maintaining a population of solutions from which better solutions are created rather than making incremental changes to a single solution to the problem. The initial solution population is generated randomly and evolves into the next generation by genetic operators such as selection, crossover and mutation. The solutions coded by strings are evaluated by the fitness function. The proposed model consists of two phases: GA based Instance Selection and Instance based Bagging. In the first phase, GA is used to select optimal instance subset that is used as input data of bagging model. In this study, the chromosome is encoded as a form of binary string for the instance subset. In this phase, the population size was set to 100 while maximum number of generations was set to 150. We set the crossover rate and mutation rate to 0.7 and 0.1 respectively. We used the prediction accuracy of model as the fitness function of GA. SVM model is trained on training data set using the selected instance subset. The prediction accuracy of SVM model over test data set is used as fitness value in order to avoid overfitting. In the second phase, we used the optimal instance subset selected in the first phase as input data of bagging model. We used SVM model as base classifier for bagging ensemble. The majority voting scheme was used as a combining method in this study. This study applies the proposed model to the bankruptcy prediction problem using a real data set from Korean companies. The research data used in this study contains 1832 externally non-audited firms which filed for bankruptcy (916 cases) and non-bankruptcy (916 cases). Financial ratios categorized as stability, profitability, growth, activity and cash flow were investigated through literature review and basic statistical methods and we selected 8 financial ratios as the final input variables. We separated the whole data into three subsets as training, test and validation data set. In this study, we compared the proposed model with several comparative models including the simple individual SVM model, the simple bagging model and the instance selection based SVM model. The McNemar tests were used to examine whether the proposed model significantly outperforms the other models. The experimental results show that the proposed model outperforms the other models.

• Progress in Medical Physics
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• v.6 no.2
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• pp.71-81
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• 1995

Consecutive brain 〔Tc-99m〕ECD SPECT studies before and after acetazolamide (Diamox) administration have been performed with patients for the evaluation of cerebrovascular hemodynamic reserve. However, the quantitaitve potential of SPECT Diamox imaging is limited as a result of degrading fractors such as finite detector resolution, attenuation, scatter, poor counting statistics, and methods of data analysis. Making physical measurements in phantoms filled with known amounts of radioactivity can help characterize and potentially quantify the sensitivities. However, it is often very difficult to make a realistic phantom simulating patients in clinical situations. By computer simulation, we studied the sensitivities of ECD SPECT before and after Diamox administration. The sensitivity is defined as ($\Delta$N/N)/($\Delta$S/S)$\times$100％, where $\Delta$N denotes the differences in mean counts between post-and pre-Diamox in the measured data, N denotes the mean counts before Diamox in the measure data, $\Delta$S denotes the differences in mean counts between post-and pre-Diamox in the model, and S denotes the mean counts before Diamox in the model. In clinical Diamox studies, the percentage changes of radioactivity could be determined to measure changes in radioactivity concentration by Diamox after subtracting pre-from post-Diamox data. However, the optimal amount of subtraction for 100％ sensitivity is not known since this requires a thorough sensitivity analysis by computer simulation. For consecutive brain SPECT imaging model before and after Diamox, when 30％ increased radioactivity concentrations were assingned for Diamox effect in model, the sensitivities were measured as 51.03, 73.4, 94.00, 130.74％ for 0, 100, 150, 200％ subtraction, respectively. Sensitivity analysis indicated that the partial voluming effects due to finite detector resolution and statistical noise result in a significant underestimation of radioactivity measurements and the amount of underestimation depends on the. ％ increase of radioactivity concentration and ％ subtraction of pre-from post-Diamox data. The 150％ subtraction appears to be optimal in clinical situations where we expect approximately 30％ changes in radioactivity concentration. The computer simulation may be a powerful technique to study sensitivities of ECD SPECT before and after Diamox administration.

• Journal of Distribution Science
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• v.10 no.1
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• pp.43-52
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• 2012

With the slowdown in environmental issues and the change of environmental consciousness, ecotourism is being discussed in various social fields. Ecotourism is being popularized for environmental protection, and now it is becoming a mainstream product from one of mass tourism. Ecotourism's emphasis on sustainable development in the tourism destination's society, economy, and environment, through ecotourism study and education, enable people to understand the core value of the ecological environment. 2011 was nominated as "the Year of World Forest" by the UN. In the recent years, forests are becoming increasingly important with their own values and functions in environment, economy, society, and culture. In particular, the global environmental issues caused by climate change are becoming an international agenda. Forests are the only effective solution for the carbon dioxide that causes global warming. Moreover, forests constitute a major part of ecotourism, and are now most used by ecotourists. For example, Korea, wherein 60% of the land is forest, attracts ecotourists. With the increasing interests in environment, the number of tourists visiting the ecosystem forest, which is highly valued for its conservation, is increasing significantly every year and is receiving considerable attention from the government. However, poor facilities in the forest ecotourism sites and improper market strategies are the reasons for the poor running of these sites. Furthermore, tourists' environmental awareness affects ecology environmental pollution or the optimization of forest ecotourism. In order to verify the relationships among tourist attractiveness, environmental consciousness, charm degrees of the attractions, and attitudes after tours, we established some scales based on existing research achievement. Then, using these scales, the researcher completed the questionnaire survey. From December 20, 2010 to February 20, 2011, after conducting surveys for 12 weeks, we finally obtained 582 valid questionnaires, from a total of 700 questionnaires, that could be used in statistical analysis. First, for the method of research and analysis, the researcher initially applied the Cronbach's (Alpha) for verifying the reliability, and subsequently applied the Exploratory factor analysis for verifying the validity. Second, in order to analyze the demographics, the researcher makes use of the Frequency analysis for the AMOS, measurement model, structural equation model computing, and also utilizes construct validity, convergent validity, discriminant validity, and nomological validity. Third, for the analysis of the ecotourists' environmental consciousness, impacts on tourist attractiveness, charm degrees of the attractions, and attitudes after the tour, the researcher uses AMOS 19, with the path analysis and equation of structure. After the research, researchers found that high awareness of natural protection lead to high tourist motivation and satisfaction and more positive attitude after the tour. Moreover, this research shows the psychological and behavioral reactions of the ecotourists to the ecotourist development. Accordingly, environmental consciousness does not affect the tourist attractiveness that has been interpreted as significant. Furthermore, people should focus on the change of natural protection consciousness and psychological reaction of ecotourists while ensuring the sustainable development of ecotourists and developing some ecotourist programs.

• Korean Chemical Engineering Research
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• v.47 no.6
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• pp.762-767
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• 2009

In this study, the feasibility of using vegetable oil extracted from tropical crop seed as a biodiesel feedstock was investigated by producing biodiesel and analysing the quality parameters as a transport fuel. In order to produce biodiesel efficiently, two step reaction process(pre-treatment and transesterificaion) was required because the tropical crop oil have a high content of free fatty acids. To determine the suitable acid catalyst for the pre-esterification, three kinds of acid catalysts were tested and sulfuric acid was identified as the best catalyst. After constructing the experimental matrix based on RSM and analysing the statistical data, the optimal pre-treatment conditions were determined to be 26.7% of methanol and 0.982% of sulfuric acid. Trans-esterification experiments of the pre-esterified oil based on RSM were carried out, then discovered 1.24% of KOH catalyst and 22.76% of methanol as the optimal trans-esterification conditions. However, the quantity of KOH was higher than the previously established KOH concentration of our team. So, we carried out supplemental experiment to determine the quantity of catalyst and methanol. As a result, the optimal transesterification conditions were determined to be 0.8% of KOH and 16.13% of methanol. After trans-esterification of tropical crop oil, the produced biodiesel could meet the major quality standard specifications; 100.8% of FAME, 0.45 mgKOH/g of acid value, 0.00% of water, 0.04% of total glycerol, $4.041mm^2/s$ of kinematic viscosity(at $40^{\circ}C$).

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.1
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• pp.103-113
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• 2020

Jack-up drilling rigs are widely used in the offshore oil and gas exploration industry. Although originally designed for use in shallow waters, trends in the energy industry have led to a growing demand for their use in deep sea and harsh environmental conditions. To extend the operating range of jack-up units, their design must be based on reliable analysis while eliminating excessive conservatism. In current industrial practice, jack-up drilling rigs are designed using the working(or allowable) stress design (WSD) method. Recently, classifications have been developed for specific regulations based on the load and resistance factor design (LRFD) method, which emphasises the reliability of the methods. This statistical method utilises the concept of limit state design and uses factored loads and resistance factors to account for uncertainly in the loads and computed strength of the leg components in a jack-up drilling rig. The key differences between the LRFD method and the WSD method must be identified to enable appropriate use of the LRFD method for designing jack-up rigs. Therefore, the aim of this study is to compare and quantitatively investigate the differences between actual jack-up lattice leg structures, which are designed by the WSD and LRFD methods, and subject to different environmental load-to-dead-load ratios, thereby delineating the load-to-capacity ratios of rigs designed using theses methods under these different enviromental conditions. The comparative results are significantly advantageous in the leg design of jack-up rigs, and determine that the jack-up rigs designed using the WSD and LRFD methods with UC values differ by approximately 31 % with respect to the API-RP code basis. It can be observed that the LRFD design method is more advantageous to structure optimization compared to the WSD method.

• KSBB Journal
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• v.22 no.5
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• pp.297-304
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• 2007

For large and rapid screening of high-yielding mutants of lovastatin produced by filamentous fungal cells of Aspergillus terreus, one of the most important stage is to test as large amounts of mutated strains as possible. For this purpose, we intended to develop a miniaturized cultivation method using $7m{\ell}$ culture tube instead of traditional $250m{\ell}$ flask (working volume $50m{\ell}$). For obtaining large amounts of conidiospores to be used as inoculums for miniaturized cultures, 4 components i.e., glucose, sucrose, yeast extract and $KH_2PO_4$ were intensively investigated, which had been observed to show positive effect on enhancement of spore production through Plackett-Burman design experimet. When optimum concentrations of these components that were determined through application of response surface method (RSM) based on central composite design (CCD) were used, maximum spore numbers amounting to $1.9\times10^{10}$ spores/plate were obtained, resulting in approximately 190 fold increase as compared to the commonly used PDA sporulation medium. Using the miniaturized cultures, intensive strain development programs were carried out for screening of lovastatin high-yielding as well as highly reproducible mutants. It was observed that, for maximum production of lovastatin, the producers should be activated through 'PaB' adaptation process during the early solid culture stage. In addition, they should be proliferated in condensed filamentous forms in miniaturized growth cultures, so that optimum amounts of highly active cells could be transferred to the production culture-tube as reproducible inoculums. Under these highly controlled fermentation conditions, compact-pelleted morphology of optimum size (less than 1 mm in diameter) was successfully induced in the miniaturized production cultures, which proved essential for maximal utilization of the producers' physiology leading to significantly enhanced production of lovastatin. As a result of continuous screening in the miniaturized cultures, lovastatin production levels of the 81% of the daughter cells derived from the high-yielding producers turned out to be in the range of 80%$\sim$120% of the lovastatin production level of the parallel flask cultures. These results demonstrate that the miniaturized cultivation method developed in this study is efficient high throughput system for large and rapid screening of highly stable and productive strains.

• Horticultural Science & Technology
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• v.31 no.2
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• pp.211-218
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• 2013

This study was conducted to investigate the quality characteristics of eight Kimchi cabbage cultivars and the effect of cold storage on the quality of two kinds of cabbage cultivars, such as 'CR-Nongshim', and 'Ryouckgwang'. Early planted and harvested cultivars at July showed that fresh weight was lower than late harvested cultivars at September, because early harvesting time of July was heavy rainy season at highlands of Gangwon province. The firmness was more than 10 N for all cultivars and 'Cheongock', 'Sanjanggoon', and 'Ryouckgwang' cultivars had high value of firmness among them. No differences among the cultivars were found in appearance, freshness, and texture evaluations at harvest. Sweetness and bitterness had statistical differences and showed high value in 'Ryouckgwang' and in 'CR-Nongshim' and 'Sooho'. Two Kimchi cabbage cultivars such as 'CR-Nongshim' and 'Ryouckgwang' were stored at $0^{\circ}C$, $2^{\circ}C$, $5^{\circ}C$, and room temperature ($25^{\circ}C$) with more than 90% RH. Significant difference was found in weight loss during room and low temperature storage. In general, weight loss of the Kimchi cabbages at room temperature was significantly increased by 15% within 3 days, whereas it was delayed at low temperature until 3 weeks on all Kimchi cabbage cultivars. Firmness of 'CR-Nongshim' was higher than 'Ryouckgwang' but there was no difference within low storage temperatures. Appearance among the sensory factors was a critical indicator to estimate storage periods. On the point of appearance, storage period at $0^{\circ}C$ was 1 week and $2^{\circ}C$ and $5^{\circ}C$ was 3 weeks and 1 week in 'CR-Nongshim' cultivar, respectively. The storage period of 'Ryouckgwang' cultivar was 2 weeks, 4 weeks, and 2 weeks, respectively. Conclusively, storage at $2^{\circ}C$ with more than 90% RH was recommended as optimum temperature to maintain quality in both cultivars.

• Journal of Korean Society of Transportation
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• v.22 no.3 s.74
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• pp.145-157
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• 2004

The cycle length design model of the Korean traffic responsive signal control systems is devised to vary a cycle length as a response to changes in traffic demand in real time by utilizing parameters specified by a system operator and such field information as degrees of saturation of through phases. Since no explicit guideline is provided to a system operator, the system tends to include ambiguity in terms of the system optimization. In addition, the cycle lengths produced by the existing model have yet been verified if they are comparable to the ones minimizing delay. This paper presents the studies conducted (1) to find shortcomings embedded in the existing model by comparing the cycle lengths produced by the model against the ones minimizing delay and (2) to propose a new direction to design a cycle length minimizing delay and excluding such operator oriented parameters. It was found from the study that the cycle lengths from the existing model fail to minimize delay and promote intersection operational conditions to be unsatisfied when traffic volume is low, due to the feature of the changed target operational volume-to-capacity ratio embedded in the model. The 64 different neural network based cycle length design models were developed based on simulation data surrogating field data. The CORSIM optimal cycle lengths minimizing delay were found through the COST software developed for the study. COST searches for the CORSIM optimal cycle length minimizing delay with a heuristic searching method, a hybrid genetic algorithm. Among 64 models, the best one producing cycle lengths close enough to the optimal was selected through statistical tests. It was found from the verification test that the best model designs a cycle length as similar pattern to the ones minimizing delay. The cycle lengths from the proposed model are comparable to the ones from TRANSYT-7F.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.29-37
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• 2019

Textile quality management targets the physical properties of fabrics and the subjective discriminations of color and fitting. Color is the most representative quality factor that consumers can use to evaluate quality levels without any instruments. For this reason, quantification using a color discrimination device has been used for statistical quality management in the textile industry. However, small and medium-sized domestic textile manufacturers use only visual inspection for color discrimination. As a result, color discrimination is different based on the inspectors' individual tendencies and work procedures. In this research, we want to develop a textile industry-friendly quality management method, evaluating the possibility of rapid color discrimination using a digital imaging device, which is one of the office-automation instruments. The results show that an imaging process-based color discrimination method is highly correlated with conventional color discrimination instruments ($R^2=0.969$), and is also applicable to field discrimination of the manufacturing process, or for different lots. Moreover, it is possible to recognize quality management factors by analyzing color components, ${\Delta}L$, ${\Delta}a$, ${\Delta}b$. We hope that our rapid discrimination method will be a substitute technique for conventional color discrimination instruments via elaboration and optimization.