• Journal of Animal Environmental Science
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• v.9 no.1
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• pp.27-34
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• 2003

This experiment was carried out to investigate the effect of dietary supplementation of fermented microbial complex(Eco-Farm$^{(R)}$) on performance of finishing pigs and indoor air quality in finishing building. A total 135 crossbred [(Landrace ${\times}$ Yorkshire) ${\times}$ Duroc] pigs were randomly arranged into nine groups and assigned to three treatments. Pigs were fed a basal diet supplemented with 0, 0.5 and 1% level of fermented microbial complex(Eco-Farm$^{(R)}$) until the market weight for 40 days of the experimental period. Average daily feed intake and feed conversion ratio were significantly improved (p<0.05) with dietary supplementation of 0.5% fermented microbial complex (Eco-Farm$^{(R)}$): however, average daily gain was not affected by dietary supplementation of fermented microbial complex(Eco-Farm$^{(R)}$). Indoor ammonia and hydrogen sulfide concentrations in the finishing building were significantly(p<0.05) decreased by dietary supplementation of fermented microbial complex(Eco-Farm$^{(R)}$) compared with those of control, however, indoor carbon dioxide concentration was not affected by dietary supplementation of fermented microbial complex(Eco-Farm$^{(R)}$). In conclusion, the results obtained from this experiment suggest that the dietary supplementation of fermented microbial complex(Eco-Farm$^{(R)}$) for finishing pigs improved performance and indoor air quality in the finishing building.hing building.

• Environmental and Resource Economics Review
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• v.31 no.2
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• pp.165-204
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• 2022

This study organized data from 2000 to 2014 for 20 grid-connected countries in Europe and analyzed the determinants of carbon emissions through the panel GLS method considering the problem of heteroscedasticity and autocorrelation. At the same time, the effect of introducing ETS was considered by dividing the sample period as of 2005 when the European emission trading system was introduced. Carbon emissions from individual countries were used as dependent variables, and proportion of generation by each source, power self-sufficiency ratio of neighboring countries, power production from resource-holding countries, concentration of power sources, total energy consumption per capita in the industrial sector, tax of electricity, net electricity export per capita, and size of national territory per capita. According to the estimation results, the proportion of nuclear power and renewable energy generation, concentration of power sources, and size of the national territory area per capita had a negative (-) effect on carbon emissions both before and after 2005. On the other hand, the proportion of coal power generation, the power supply and demand rate of neighboring countries, the power production of resource-holding countries, and the total energy consumption per capita in the industrial sector were found to have a positive (+) effect on carbon emissions. In addition, the proportion of gas generation had a negative (-) effect on carbon emissions, and tax of electricity were found to have a positive (+) effect. However, all of these were only significant before 2005. It was found that net electricity export per capita had a negative (-) effect on carbon emissions only after 2005. The results of this study suggest macroscopic strategies to reduce carbon emissions to green growth, suggesting mid- to long-term power mix optimization measures considering the electricity trade market and their role.

• Journal of the Korean Geographical Society
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• v.29 no.3
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• pp.297-317
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• 1994

This study demonstrates the changes in the spatial organization of Korea by the construction of Seoul-Pusan railroad. This Seoul-Pusan line, which is the most important one in Korea was constructed in 1905. The original plan of the line was selected to cross the main traditional roads to control the entire Korean peninsular and to mobilize the Korean commercial potentials. It was the line to exploit the staples and to expand the Japanese market in Korea. In accordance with the contracts between Japan and Korean government, Korean government had to supply the lands for railroad, office, and service facilities. That was one of the important reasons that Korean government had been broken down. The main findings of this study are as follows: 1. The Seoul-Pusan railroad line was constructed Japanese colonial policy which emphasized three main purposes; the first was to reorganize the economic space and to collapse the traditional Korean markets for Japanese ruling, and the second was to find out the military supply routes, and the third was to search for the transcontinental line for China and Siberia. As the results, the old Korean pedestrian routes, which were the Eastern, the mid, the westren, and the Samnam route lost their functions. 2. Japanese requested for Korean government usually ten times of wider space for the site of stations than the needed one. The land was expropriated, and constructed the new centers aparted from the original Korean towns. In this process Japanese got the most developmental and windfall profits. The newly constructed centers were for Japanese immigration and the town service facilities which would be used to control the Korean financial market. At last, they easily converted the Korean spatial economy into Japanese colonial one, which made to reinforce the sphere of Seoul-Pusan line. 3. Japanese planned the stations as the central points in Korea. So the railroad stations were located apart from the centers of towns, to avoid the Korean resistances, and to maximize their profits. The mean distance from staiton to 'the town center is about 1km while the Japanese case is 0.6km. 4. The pattern of present Korean railroads is not the 'X type'. Because the Honam line is not the trunk one. So, we could call the Korean railroad pattern as the 'Ip(Chinese character 入) type' . The operational effects of Seoul-Pusan line brought out the concentration of the national economy to this line as Japanese planned. And the polorization had occurred between this line and the other parts of Korea. For twenty years (1910-1930), the transported freights were increased about 5 times. In 1930, the total freight of Seoul-Pusan line became 2, 010, 444 metric tons. If we examine this process, the underconstructing Seoul-Pusan express electric railroad should avoid adjacent this line to reduce the regional and ecological imbalance. 5. The forms of centers on the Seoul-Pusan line were classified into six types in relation to station, town center, and built-up area; the compact (integrated) type, the elongated one, the splited (independent) one, the absorbed one, the consolidated one, and the declined one. All types of these towns might be developed in accordance with the centrality, railroad function, and the other transportational functions. 6. The Seoul-Pusan line plays the most important role among Korean railroads but the ratio of passenger and freight become lower because the effiects of other inaugurated railoads the different transportation modes such as trucks and cars would be got more merits in competition. 7. The results of cluster analyses on the cities of railroad stations showed the rudimentary urban systems in 1910 and 1930. In 1930, the cities were classified into three groups; the group of small cites, the intermediate (developing) city-group, and the special city-group. In 1930s the spatial organization and urban system of Korea were similar to the present ones. We call appreciate that these were the effects of the Seoul-Pusan line.

• Journal of Korea Port Economic Association
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• v.31 no.4
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• pp.75-89
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• 2015

This study examines 31 import and export cargo items handled in each port to investigate which items face the most competition among the ports and how many of them are transited to other ports. The study aims to suggest implications for the future port policy of Incheon Port. It was found that the volume concentration in the Western Coast region from 2005 to 2014 became increasingly decentralized. The decentralization began in earnest in 2009 in particular, and the value was 0.448 in 2014, indicating fierce competition among the regions. According to the static and dynamic positioning analyses results for Incheon Port, Pyeongtaek and Dangjin Port, and Gunsan Port, using BCG Matrix, the static positioning analysis showed that Incheon Port belongs to the 3rd quadrant (Cash Cows), Pyeongtaek and Dangjin Port belongs to the 2nd quadrant (Question Marks), and Gunsan Port belongs to the (Dogs) group. This implies that Incheon Port has maintained its position with large shares compared to those of other ports, despite its low growth rate. However, the market position and growth rate of Incheon Port decreased according to the dynamic positioning analysis results. The shift-share analysis results indicated that the volumes of Incheon Port and Gunsan Port were shifting to Pyeongtaek and Dangjin Port. Moreover, the ratio of absolute growth to potential growth of Incheon Port and Gunsan Port turned out to be significantly lower than that of Pyeongtaek and Dangjin Port, implying that Incheon Port and Gunsan Port are declining as compared to Pyeongtaek Port and Dangjin Port. According to the LQ index analysis results, specialized items from Incheon Port that do not overlap with other ports included the following ten items: meat, fish and crustaceans, bituminous coals, crude oil and petroleum, petroleum-refined products, plastic rubber and products, textiles, nonferrous metal and products, electric machinery, and aircrafts and ships. In particular, it was confirmed that the bulk cargo of Incheon Port was actually shifting to Pyeongtaek and Dangjin Port following the policy of re-establishing port functions.

• Journal of the Korean Wood Science and Technology
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• v.48 no.4
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• pp.472-487
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• 2020

With the emergence of abnormal climate due to the rapid industrialization, the importance of water quality management and management costs are increasing every year. In Korea, for the management of total phosphorus and total nitrogen, the major materials causing the water quality pollution, coagulants are injected in sewage treatment plants to process organic compounds. However, if the coagulant is injected in an excessive amount to PAC (Poly Aluminium Chloride), a secondary pollution problem might occur. As such, a study on the applicability of natural material-based coagulant is being conducted in Korea. Thus, this study aimed to evaluate the applicability of a mixed coagulant developed by analyzing water quality pollutants T-P, T-N as well as their turbidity, in order to derive the optimum mixing ratio between PAC and torrefied wood flour for the primary settling pond effluent. Under the condition where the content of PAC (10%) and torrefied wood flour is 1%, T-P showed the maximum removal efficiency of 92%, and T-N showed approximately 22%. This indicates that removal of T-N which includes numerous positively charged organic compounds that are equivalent to mixed coagulant is not well accomplished. Turbidity showed the removal efficiency of approximately 91%. As such, 1% of torrefied wood flour was determined to be the optimum addition. As a result of analyzing the removal efficiency for organic compounds by reducing PAC concentration to 7%, T-P showed a high maximum removal efficiency of 91%, T-N showed 32%, and turbidity showed the maximum of 90%. In addition, a coagulation process is performed by using the mixed coagulant based on 1% content of torrefied wood flour produced in this study by performing a coagulation performance comparative experiment with PAC (10%). As a result, PAC concentration was reduced to 30-50%, a similar performance with other coagulants in market was secured, PAC injection amount was reduced that an economic effect can be achieved, and it is considered to perform a stable water treatment that reduces the secondary pollution problem.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Journal of Food Hygiene and Safety
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• v.32 no.1
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• pp.42-49
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• 2017

The aim of this study was to determine total mercury and methyl mercury level in fishes (Deep-sea Fish, Tuna, Billfish) and fishery products. A total of 101 fishes and 44 fishery products samples collected from commercial market in Gyeonggi-do. Total mercury were analysed by mercury analyzer and methyl mercury were analyzed by gas chromatography with electron capture detector. In the fishes, total mercury was detected in all samples and methylmercury was detected in 92 samples of them. The detection rate of methylmercury was 91.1% in fishes. The mean concentration (mg/kg) of total mercury and methylmercury were $1.968{\pm}0.505/0.496{\pm}0.057$ for Billfish, $0.665{\pm}0.091/0.252{\pm}0.033$ for Deep-sea Fish and $0.577{\pm}0.085/0.218{\pm}0.025$ for Tuna, respectively. The Swordfish contains the highest level of total mercury (1.968 mg/kg) and methylmercury (0.496 mg/kg). In Mabled rockfish, the ratio of methylmercury's contents about total mercury's contents was the highest as 66.5%. In case of fishery products, frozens made of 100% of raw material contained the highest level of total mercury and methyl mercury. The weekly intake of total mercury and methylmercury was calculated in 4.72% and 5.24% of Provisional Tolerable Weekly Intake (PTWI) respectively. This study showed that the weekly intake of methylmercury from Deep-sea Fish, Tuna and Billfish was less than the PTWI recommended by the Joint FAO/WHO expert committee on food additives.