• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.11
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• pp.1649-1657
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• 2016

The purpose of this study was to investigate the body mass index (BMI), dietary intake attitudes, and nutrient intake status according to sugar-containing food intake frequency of 409 college students in Gyeonggi-do. Subjects were categorized into three groups according to sugar-containing food intake frequency: rare intake group (n=113), average intake group (n=195), and frequent intake group (n=101). The average height and weight (P<0.001) of each group were $163.8{\pm}0.11cm$ and $52.9{\pm}8.6kg$, $164.4{\pm}0.1cm$ and $56.2{\pm}6.4kg$, and $167.9{\pm}0.1cm$ and $68.0{\pm}15.7kg$, respectively. The average BMIs of the groups were $19.6{\pm}2.3$, $20.7{\pm}0.8$, and $24.0{\pm}2.7$, respectively (P<0.001). Dietary intake attitude scores of the groups were $30.73{\pm}5.68$, $30.11{\pm}5.51$, and $28.00{\pm}5.31$, respectively (P<0.001). As a result of nutrient intake status, daily averages of energy and carbohydrate intake of the frequent intake group were significantly higher than those of the rare intake group (P<0.05). On the other hand, vitamin A, vitamin $B_1$, and vitamin C intakes of the rare intake group were significantly higher than those of the frequent intake group (P<0.05). Using multiple regression analysis, we found that BMI was the most significant variable affecting sugar-containing food intake. Therefore, nutrition education is necessary to improve nutrient intake while considering sugar intake for maintenance of healthy weight.

• Journal of Animal Environmental Science
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• v.16 no.1
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• pp.81-92
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• 2010

This study was conducted to evaluate the effects of fermented diets including liquid by-products on nutrient digestibility and nitrogen balance in growing pigs. Treatments were 1) CON (basal diet), 2) F (fermented diet with basal diet), 3) KF (fermented diet with basal diet including 30% kale pomace), 4) AF (fermented diet with basal diet including 30% angelica keiskei pomace), 5) CF (fermented diet with basal diet including 30% carrot pomace) and 6) OF (fermented diet with basal diet including 30% grape pomace). A total of 24 pigs (41.74kg average initial body weight, Landrace $\times$ Yorkshire $\times$ Duroc), were assigned to 6 treatments, 4 replicates and 1 pig per metabolic cage in a randomized complete block (RCB) design. Pigs were housed in $0.5\times1.3m$ metabolic cage in a 17d digestibility trial. During the entire experimental period, Digestibility of dry matter (p<0.05) of treatment CON, F and CF were higher than other treatments. In crude protein digestibility, treatment F was higher than treatment AF and GF (p<0.05). Treatment GF showed the lowest digestibility of crude fiber among all treatments (p<0.05). In ether extract digestibility, treatment AF and CF showed higher than other treatments (p<0.05) except KF treatment. CF treatment showed the best digestibility of ash among all treatments (p<0.05). Whereas, For Ca and P digestibility, CF and OF treatments were improved than other treatments (p<0.05). Energy digestibility (p<0.05) of CON, F and CF treatments were higher than KF, AF and GF treatments. In total essential amino acid digestibility, F treatment was improved than AF, CF and GF treatments (p<0.05). In total non-essential amino acid digestibility, F treatment was higher than CON, AF and GF treatments (p<0.05). In total amino acid digestibility, F treatment was higher than AF and CF treatments (p<0.05) and GF treatment showed the lowest digestibility (p<0.05). In fecal nitrogen excretion ratio, GF treatment was greatest among all treatments (p<0.05) and F treatment was decreased than other treatments (p<0.05). In urinary nitrogen excretion ratio, CON and GF treatments showed the lowest among all treatments (p<0.05). In nitrogen retention ratio, CON treatment showed the high and KF treatment showed the lost among all treatments (p<0.05). Therefore, this experiment suggested that fermented diet could improve nutrient and amino acid digestibilities of growing pigs.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

• Journal of Environmental Impact Assessment
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• v.26 no.2
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• pp.93-104
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• 2017

CCS (Carbon Capture and Storage) is a technical process to capture $CO_2$ from industrial and energy-based sources, to transfer and sequestrate impressed $CO_2$ in geological formations, oceans, or mineral carbonates. However, potential $CO_2$ leakage exists and causes environmental problems. Thus, this study was conducted to analyze the spatial and temporal variations of $CO_2$ fluxes and concentrations after artificial $CO_2$ release. The Environmental Impact Evaluation Test Facility (EIT) was built in Eumseong, Korea in 2015. Approximately 34kg $CO_2$ /day/zone were injected at Zones 2, 3, and 4 among the total of 5 zones from October 26 to 30, 2015. $CO_2$ fluxes were measured every 30 minutes at the surface at 0m, 1.5m, 2.5m, and 10m from the $CO_2$ releasing well using LI-8100A until November 13, 2015, and $CO_2$ concentrations were measured once a day at 15cm, 30cm, and 60cm depths at every 0m, 1.5m, 2.5m, 5m, and 10m from the well using GA5000 until November 28, 2015. $CO_2$ flux at 0m from the well started increasing on the fifth day after $CO_2$ release started, and continued to increase until November 13 even though the artificial $CO_2$ release stopped. $CO_2$ fluxes measured at 2.5m, 5.0m, and 10m from the well were not significantly different with each other. On the other hand, soil $CO_2$ concentration was shown as 38.4% at 60cm depth at 0m from the well in Zone 3 on the next day after $CO_2$ release started. Soil $CO_2$ was horizontally spreaded overtime, and detected up to 5m away from the well in all zones until $CO_2$ release stopped. Also, soil $CO_2$ concentrations at 30cm and 60cm depths at 0m from the well were measured similarly as $50.6{\pm}25.4%$ and $55.3{\pm}25.6%$, respectively, followed by 30cm depth ($31.3{\pm}17.2%$) which was significantly lower than those measured at the other depths on the final day of $CO_2$ release period. Soil $CO_2$ concentrations at all depths in all zones were gradually decreased for about 1 month after $CO_2$ release stopped, but still higher than those of the first day after $CO_2$ release stared. In conclusion, the closer the distance from the well and the deeper the depth, the higher $CO_2$ fluxes and concentrations occurred. Also, long-term monitoring should be required because the leaked $CO_2$ gas can remains in the soil for a long time even if the leakage stopped.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.37-51
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• 2015

Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.

• Korean Journal of Psychosomatic Medicine
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• v.4 no.2
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• pp.269-276
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• 1996

A theroretical study was made on the psychodynamism of somatoform disorder. Somatoform disorder is caused by a defense mechanism of somatization. Somatization is the tendency to react to stimuli(drives, defenses, and conflict between them) physically rather than psychically(Moore, 1990). Ford(1983) said it is a way of life, and Dunbar(1954) said it is the shift of psychic energy toward expression in somatic symptoms. As used by Max Shur(1955), somatization links symptom formation to the regression that may occur in response to acute and chronic conflict. In the neurotic individual psychic conflict often provokes regressive phenomena that may include somatic manifestations characteristic of an earlier developmental phase. Schur calls this resomatization. Pain is the most common example of a somatization reaction to conflict. The pain has an unconscious significance derived from childhood experiences. It is used to win love, to punish misdeeds, as well as a means to amend. Among all pains, chest pain has a special meaning. Generally speaking, 'I have pain in my chest' is about the same as 'I have pain in my mind'. The chest represent the mind, and the mind reminds us about the heart. So we have a high tendency to recognize mental pain as cardiac pain. Kellner(1990) said rage and hostility, especially repressed hostility, are important factors in somatization. In 'Psychoanalytic Observation on Cardiac Pain', psychoanalyst Bacon(1953) presented clinical cases of patients who complained of cardiac pain in a psychoanalytic session that spread from the left side of their chests down their left arms. The pain was from rage and fear which came after their desire to be loved was frustrated by the analyet. She said desires related to cardiac pain were dependency needs and aggressions. Empatic relationship and therapeutic alliances are indispensable to psychotherapy in somatoform disorder. The beginning of therapy is to discover a precipitating event from the time their symptoms have started and to help the patient understand a relation between the symptom and precipitating event. Its remedial process is to find and interpret a intrapsychic conflict shown through the symptoms of the patient. Three cases of somatoform disorder patients treated based on this therapeutic method were introduced. The firt patient, Mr. H, had been suffering from hysterical aphasia with repressed rage as ie psychodynamic cause. An interpretation related to the precipitating event was given by written communication, and he recovered from his aphasia after 3 days of the session. The second patient was a dentist in a cardiac neurosis with agitation and hypochondriasis, whose psychodynamism was caused by a fear that he might lose his father's love. His symptom was also interpreted in relation to the precipitating event. It showed the patient a child-within afraid of losing his father's love. His condition improved after getting a didactic interpretation which told him, to be master of himself, The third patient was a lady transferred from the deparment of internal medicine. She had a frequent and violent fit of chest pains, whose psychodynamic cause was separation anxiety and a rage due to the frustration of dependency needs. Her symptom vanished dramatically when she wore a holler EKG monitor and did not occur during monitoring. By this experience she found her symptom was a psychogenic one, and a therapeutic alliance was formed. later in reguar psychotherapy sessions, she was told the relaton between symptoms and precipitating events. Through this she understood that her separation anxiety was connected to the symptom and she became less terrifide when it occurred. Now she can travel abroad and take well part in social activities.

• Applied Chemistry for Engineering
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• v.17 no.4
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• pp.349-356
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• 2006

We have investigated adsorption and desorption properties of CO adsorption on silica supported Ru/Ni alloys at various Ru/Ni mole content ratio as well as CO partial pressures using Fourier transform infrared spectrometer (FT-IR). For Ru-$SiO_{2}$ sample, four bands were observed at $2080.0cm^{-1}$, $2021.0{\sim}2030.7cm^{-1}$, $1778.9{\sim}1799.3cm^{-1}$, $1623.8cm^{-1}$ on adsorption and three bands were observed at $2138.7cm^{-1}$, $2069.3cm^{-1}$, $1988.3{\sim}2030.7cm^{-1}$ on vacumn desorption. For Ni-$SiO_{2}$ sample, four bands were observed at $2057.7cm^{-1}$, $2019.1{\sim}2040.3cm^{-1}$, $1862.9{\sim}1868.7cm^{-1}$, $1625.7cm^{-1}$ on adsorption and two bands were observed at $2009.5{\sim}2040.3cm^{-1}$, $1828.4{\sim}1868.7cm^{-1}$ on vacumn desorption. These absorption bands correspond with those of the previous reports approximately. For Ru/Ni(9/1, 8/2, 7/3, 6/4, 5/5; mole content ratio)-$SiO_{2}$ samples, three bands were observed at $2001.8{\sim}2057.7cm^{-1}$, $1812.8{\sim}1926.5cm^{-1}$, $1623.8{\sim}1625.7cm^{-1}$ on adsorption and three bands were observed at $2140.6cm^{-1}$, $2073.1cm^{-1}$, $1969.0{\sim}2057.7cm^{-1}$ on vacumn desorption. The spectrum pattern observed for Ru/Ni-$SiO_{2}$ sample at 9/1 Ru/Ni mole content ratio on CO adsorption and on vacumn desorption is almost like the spectrum pattern observed for Ru-$SiO_{2}$ sample. But the spectrum patterns observed for Ru/Ni-$SiO_{2}$ samples under 8/2 Ru/Ni mole content ratio on CO adsorption and vacumn desorption are almost like the pattern observed for $Ni-SiO_{2}$ sample. It may be suggested surfaces of alloy clusters on the Ru/Ni-$SiO_{2}$ samples contain more Ni components than the mole content ratio of the sample considering the above phenomena. With Ru/Ni-$SiO_{2}$ samples the absorption band shifts may be ascribed to variations of surface concentration, strain variation due to atomic size difference, variation of bonding energy and electronic densities, and changes of surface geometries according to surface concentration variation. Studies for CO adsorption on Ru/Ni alloy cluster surface by LEED and Auger spectroscopy, interation between Ru/Ni alloy cluster and $SiO_{2}$, and MO calculation for the system would be needed to look into the phenomena.

• Journal of the Korean Wood Science and Technology
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• v.10 no.3
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• pp.96-108
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• 1982

Pinus is one of the most important species supplying domestic industrial timbers such as constitutional lumber, pulpwood, and mine props. It occupies nearly 50 percent of the total forest resources in Korea. With above conception, to develop this forest resources and to obtain the basic data on the reasonable and effective utilization of Pinus, this study was carried out. Five species (P. koraiensis S. et Z., P. densiflora S. et Z., P. thunbergii Parlat, P. densiflara far erecta, P. rigida Miller) grown in Kwangnoong experimental forest stand, Chungcheongnam-Do, and Gangwon-Do regions were selected as sample trees. Anatomical, physical, mechanical and chemical properties of them were investigated.

• Analytical Science and Technology
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• v.5 no.1
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• pp.41-49
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• 1992

An attempt was made to prepare two series of tetrakis eight-coordinate tungsten(IV) and cerium(IV) complexes containing the 5,7-dichloro-8-quinolinol(N:${\pi}$-acceptor atom, O:${\pi}$-donor atom) ligand. Tetrakis eight-coordinate tungsten(IV) complex of 2-mercaptopyrimidine(N:${\pi}$-acceptor atom, S:${\pi}$-donor atom) ligand have also been prepared. And the new series of mixed-ligand eight-coordinate tungsten(IV) complexes containing bidentate ligands 5,7-dichloro-8-quinolinol and 2-mercaptopyrimidine have been prepared, isolated by TLC and characterized. $W(dcq)_4$, $W(dcq)_3(mpd)_1$, $W(dcq)_2(mpd)_2$, $W(dcq)_1W(dcq)_3$ and $W(mpd)_4$ complexes of MLCT absorption band appeared to 710nm, 680nm, 625nm, 581nm, and 571nm(${\varepsilon}\;max={\sim}>{\times}10^4$) on low-energy respectively. The specific absorption wave length of $Ce(dcq)_4$ is appeared 520nm(${\varepsilon}\;max={\sim}>{\times}10^4$). The Chemical shift values by proton of coordinated position appeared to $W(dcq)_4$ [$H_2:8.9ppm$]; $W(dcq)_3(mpd)_1$ [$H_2:9.3$,$H_6:9.2ppm$]; $W(dcq)_2(mpd)_2$ [$H_2:9.7$,$H_6:8.95ppm$]; $W(dcq)_1(mpd)_3$ [$H_2:9.8$,$H_6:9.4ppm$]; $W(mpd)_4$ [$H_6:8.8ppm$]; $Ce(dcq)_4$ [$H_2:9.3ppm$] with $^1H$-NMR. The inertness of mixed-ligand eight coordinate tungsten(IV) complexes have been investigated by UV-Vis. spectroscopic method in dimethylsulfoxide at $90^{\circ}C$. The inertness of $W(dcq)_n(mpd)_{4-n}$ complexes showed the following order, $W(dcq)_3(mpd)_1;k_{obs.}=3.8{\times}10^{-6}$ > $W(mpd)_4;k_{obs.}=6.0{\times}10^{-6}$ > $W(dcq)_4;k_{obs.}=6.4{\times}10^{-6}$ > $W(dcq)_2(mpd)_2;k_{obs.}=7.0{\times}10^{-6}$ > $W(dcq)_1(mpd)_3;k_{obs.}=1.7{\times}10^{-5}$, which showed the inertness until 16days, 10days, 9days, 8days, and 4days. The $W(mpd)_4$ is very inert as $k_{obs.}=3.6{\times}10^{-6}$(16days) in xylene at $90^{\circ}C$ and $k_{obs.}=6.0{\times}10^{-6}$(10days) in DMSO at $90^{\circ}C$.

• Journal of Environmental Policy
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• v.13 no.4
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• pp.3-49
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• 2014

Growing interest of stakeholders on corporate responsibilities for environment and tightening environmental regulations are highlighting the importance of environmental management more than ever. However, companies' awareness of the importance of environment is still falling behind, and related academic works have not shown consistent conclusions on the relationship between environmental performance and economic performance. One of the reasons is different ways of measuring these two performances. The evaluation scope of economic performance is relatively narrow and the performance can be measured by a unified unit such as price, while the scope of environmental performance is diverse and a wide range of units are used for measuring environmental performances instead of using a single unified unit. Therefore, the results of works can be different depending on the performance indicators selected. In order to resolve this problem, generalized and standardized performance indicators should be developed. In particular, the performance indicators should be able to cover the concepts of both environmental and economic performances because the recent idea of environmental management has expanded to encompass the concept of sustainability. Another reason is that most of the current researches tend to focus on the motive of environmental investments and environmental performance, and do not offer a guideline for an effective implementation strategy for environmental management. For example, a process improvement strategy or a market discrimination strategy can be deployed through comparing the environment competitiveness among the companies in the same or similar industries, so that a virtuous cyclical relationship between environmental and economic performances can be secured. A novel method for measuring eco-efficiency by utilizing Data Envelopment Analysis (DEA), which is able to combine multiple environmental and economic performances, is proposed in this report. Based on the eco-efficiencies, the environmental competitiveness is analyzed and the optimal combination of inputs and outputs are recommended for improving the eco-efficiencies of inefficient firms. Furthermore, the panel analysis is applied to the causal relationship between eco-efficiency and economic performance, and the pooled regression model is used to investigate the relationship between eco-efficiency and economic performance. The four-year eco-efficiencies between 2010 and 2013 of 23 companies are obtained from the DEA analysis; a comparison of efficiencies among 23 companies is carried out in terms of technical efficiency(TE), pure technical efficiency(PTE) and scale efficiency(SE), and then a set of recommendations for optimal combination of inputs and outputs are suggested for the inefficient companies. Furthermore, the experimental results with the panel analysis have demonstrated the causality from eco-efficiency to economic performance. The results of the pooled regression have shown that eco-efficiency positively affect financial perform ances(ROA and ROS) of the companies, as well as firm values(Tobin Q, stock price, and stock returns). This report proposes a novel approach for generating standardized performance indicators obtained from multiple environmental and economic performances, so that it is able to enhance the generality of relevant researches and provide a deep insight into the sustainability of environmental management. Furthermore, using efficiency indicators obtained from the DEA model, the cause of change in eco-efficiency can be investigated and an effective strategy for environmental management can be suggested. Finally, this report can be a motive for environmental management by providing empirical evidence that environmental investments can improve economic performance.