• Tuberculosis and Respiratory Diseases
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• v.44 no.6
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• pp.1296-1307
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• 1997

Background : Erdosteine is a thiol derivative developed for the treatement of chronic obstructive bronchitis, including acute infective exacerbation of chronic bronchitis. Erdosteine has mucomodulating and antioxidant properties and especially exhibits excellent gastrointestinal tolerability. Methods : The study was conducted as a prospective evaluation, with 2 comparative groups orally treated with erdosteine 300mg (bid.) or ambroxol 30mg (b.i.d.) for 7 days and the design of trial was double-blind. The treatments have been assigned randomly to patients (n=80) with acute or chronic bronchitis. The primary end-point used to determine efficacy in this study was subjective symptoms including expectorating frequence, expectoration volume, expectorating difficulty, expectoration viscosity, cough intensity and dyspnea. The secondary end-points of efficacy was the result of arterial blood gas analysis and pulmonary function test. Safety was evaluated with adverse drug reactions and laboratory tests monitoring. 61 patients was included in the efficacy analysis, due to the fact that 19 patients drop-out for different reasons. The obtained values have been analyzed with paired Hest., ANOVA test., multivariate $t^2$-test, repeated measures analysis of covariance, two sample t-test, loglinear-logit model analysis, Fisher's exact test. Results : 1) There was no significant difference on demographic data and vital signs between erdosteine and ambroxol treated groups. 2) The comparison between erdosteine and ambroxol treated groups showed no significant difference in improvement of each symptom in spite of the more favorable efficacy obtained with erdosteine. No difference on the contrary was observed for arterial blood gas analysis and pulmonary function test. 3) As safety is concerned, no clinical significant changes in laboratory test and symptom were induced in erdosteine and ambroxol treated group and two patients in ambroxol treated group drop-out for adverse reactions in symptom. 4) In the evaluation of final clinical efficacy, erdosteine improved more effectively patient's overall symptoms {very good effect (11/31), good effect (12/31), moderate effect (6/31), no effect (2/31), aggravation (0/31)} than ambroxol {very good effect (6/30), good effect (14/30), moderate effect (5/30), no effect (4/30), aggravation (2/30)}. And the probability of symptomatic improvement by erdosteine compared to ambroxol was 2.5 times. (p<0.05). Conclusion : This study showed that erdosteine was clinically effective and safe drug for treatment of acute and chronic bronchitis.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.109-131
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• 2014

As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.

• Journal of Radiation Protection and Research
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• v.31 no.4
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• pp.203-210
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• 2006

Purpose : To estimate the dose to the embryo/fetus of a pregnant patient with brain tumors, and to design an shielding device to keep the embryo/fetus dose under acceptable levels Materials and Methods : A shielding wall with the dimension of 1.55 m height, 0.9 m width, and 30 m thickness is fabricated with 4 trolleys under the wall. It is placed between a Patient and the treatment head of a linear accelerator to attenuate the leakage radiation effectively from the treatment head, and is placed 1 cm below the lower margin of the treatment field in order to minimize the dose to a patient from the treatment head. An anti-patient scattering neck supporters with 2 cm thick Cerrobend metal is designed to minimize the scattered radiation from the treatment fields, and it is divided into 2 section. They are installed around the patient neck by attach from right and left sides. A shielding bridge for anti-room scattered radiation is utilized to place 2 sheets of 3 mm lead plates above the abdomen to setup three detectors under the lead sheets. Humanoid phantom is irradiated with the same treatment parameters, and with and without shielding devices using TLD, and ionization chambers with and without a build-up cap. Results : The dose to the embryo/fetus without shielding was 3.20, 3.21, 1.44, 0.90 cGy at off-field distances of 30, 40, 50, and 60 cm. With shielding, the dose to embryo/fetus was reduced to 0.88, 0.60, 0.35, 0.25 cGy, and the ratio of the shielding effect varied from 70% to 80%. TLD results were 1.8, 1.2, 0.8, 1.2, and 0.8 cGy. The dose measured by the survey meter was 10.9 mR/h at the patient's surface of abdomen. The dose to the embryo/fetus was estimated to be about 1 cGy during the entire treatment. Conclusion : According to the AAPM Report No 50 regarding the dose limit of the embryo/fetus during the pregnancy, the dose to the embryo/fetus with little risk is less than 5 cGy. Our measurements satisfy the recommended values. Our shielding technique was proven to be acceptable.

• Journal of Global Scholars of Marketing Science
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• v.18 no.1
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• pp.59-80
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• 2008

Recently, e-sports are growing with potentiality as a new industry with conspicuous profit model. But studies that dealing with e-sports are not enough. Hence, proposes of this paper are both to establish basic model that is for the design of e-sport marketing strategy and to contribute toward future studies which are related to e-sports. Recently, the researches to explain sports-sponsorship through the identification theory have been discovered. Many researches say that somewhat proper identification is a requirement for most sponsors to improve the their images which is essential to sponsorship activity. Consequently, the research for sponsorship associated with identification in the e-sports, not in the physical sports is the core sector of this study. We extracted the variables from online's major characteristics and existing sport sponsorship researches. First, because e-sports mean the tournaments or leagues in the use of online game, the main event of the game is likely to call it online game. Online media's attributes are distinguished from those of offline. Especially, interactivity, anonymity, and expandibility as a e-sport game attributes are able to be mentioned. So, these inherent online attributes are examined on the relationship with flow. Second, in physical sports games, Fisher(1998) revealed that team similarity and team attractivity were positively related to team identification. Wann(1996) said that the result of former game influenced the evaluation of the next game, then in turn has an effect on the identification of team supporters. Considering these results in the e-sports side, e-sports gamer' attractivity, similarity, and match result seem to be important precedent variables of the identification with a gamer. So, these e-sport gamer attributes are examined on the relationship with both flow and identification with a gamer. Csikszentmihalyi(1988) defined the term flow as feeling status for him to be making current positive experience optimally. Hoffman and Novak(1996) also said that if a user experienced the flow he would visit a website without any reward. Therefore flow might be positively associated with user's identification with a gamer. And, Swanson(2003) disclosed that team identification influenced the positive results of sponsorship, which included attitude toward sponsors, sponsor patronage, and satisfaction with sponsors. That is, identification with a gamer expect to be connected with corporation identification significantly. According to the above, we can design the following research model. All variables used in this study(interactivity, anonymity, expandibility, attractivity, similarity, match result, flow, identification with a gamer, and identification with a sponsor) definitely were defined operationally underlying precedent researches. Sample collection was carried out to the person who has an experience to have enjoyed e-sports during June 2006. Much portion of samples is men because much more men than women enjoy e-sports in general. Two-step approach was used to test the hypotheses. First, confirmatory factor analysis was committed to guarantee the validity and reliability of variables. The results showed that all variables had not only intensive and discriminant validity, but also reliability. Then, research model was examined with fully structural equation using LISREL 8.3 version. The fitness of the suggested model mostly was at the acceptable level. Shortly speaking about the results, first of all, in e-sports game attributes, only interactivity which is called a basic feature in online situation affected flow positively. Secondly, in e-sports gamer's attributes, similarity with a gamer and match result influenced flow positively, but there was no significant effect in the relationship between the attractivity of a gamer and flow. And as expected, similarity had an effect on identification with a gamer significantly. But unexpectedly attractivity and match result did not influence identification with a gamer significantly. Just the same as the fact verified in the many precedent researches, flow greatly influenced identification with a gamer, and identification with a gamer continually had an influence on the identification with a sponsor significantly. There are some implications in these results. If the sponsor of e-sports supports the pro-game player who absolutely should have the superior ability to others and is similar to the user enjoying e-sports, many amateur gamers will feel much of the flow and identification with a pro-gamer, and then after all, feel the identification with a sponsor. Such identification with a sponsor leads people enjoying e-sports to have purchasing intention for products produced by the sponsor and to make a positive word-of-mouth for those products or the sponsor. For the future studies, we recommend a few ideas. Based on the results of this study, it is necessary to find new variables relating to the e-sports, which is not mentioned in this study. For this work to be possible, qualitative research seems to be needed to consider the inherent e-sport attributes. Finally, to generalize the results related to e-sports, a wide range of generations not a specific generation should be researched.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.157-175
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• 2013

Since Korean government announced 'Smartwork promotion strategy' in 2010, Korean firms and government organizations have started to adopt smartwork. However, the smartwork has been implemented only in a few of large enterprises and government organizations rather than SMEs (small and medium enterprises). In USA, both Yahoo! and Best Buy have stopped their flexible work because of its reported low productivity and job loafing problems. In addition, according to the literature on smartwork, we could draw obstacles of smartwork adoption and categorize them into the three types: institutional, organizational, and technological. The first category of smartwork adoption obstacles, institutional, include the difficulties of smartwork performance evaluation metrics, the lack of readiness of organizational processes, limitation of smartwork types and models, lack of employee participation in smartwork adoption procedure, high cost of building smartwork system, and insufficiency of government support. The second category, organizational, includes limitation of the organization hierarchy, wrong perception of employees and employers, a difficulty in close collaboration, low productivity with remote coworkers, insufficient understanding on remote working, and lack of training about smartwork. The third category, technological, obstacles include security concern of mobile work, lack of specialized solution, and lack of adoption and operation know-how. To overcome the current problems of smartwork in reality and the reported obstacles in literature, we suggest a novel smartwork service model based on NFC(Near Field Communication). This paper suggests NFC-based Smartwork Service Model composed of NFC-based Smartworker networking service and NFC-based Smartwork space management service. NFC-based smartworker networking service is comprised of NFC-based communication/SNS service and NFC-based recruiting/job seeking service. NFC-based communication/SNS Service Model supplements the key shortcomings that existing smartwork service model has. By connecting to existing legacy system of a company through NFC tags and systems, the low productivity and the difficulty of collaboration and attendance management can be overcome since managers can get work processing information, work time information and work space information of employees and employees can do real-time communication with coworkers and get location information of coworkers. Shortly, this service model has features such as affordable system cost, provision of location-based information, and possibility of knowledge accumulation. NFC-based recruiting/job-seeking service provides new value by linking NFC tag service and sharing economy sites. This service model has features such as easiness of service attachment and removal, efficient space-based work provision, easy search of location-based recruiting/job-seeking information, and system flexibility. This service model combines advantages of sharing economy sites with the advantages of NFC. By cooperation with sharing economy sites, the model can provide recruiters with human resource who finds not only long-term works but also short-term works. Additionally, SMEs (Small Medium-sized Enterprises) can easily find job seeker by attaching NFC tags to any spaces at which human resource with qualification may be located. In short, this service model helps efficient human resource distribution by providing location of job hunters and job applicants. NFC-based smartwork space management service can promote smartwork by linking NFC tags attached to the work space and existing smartwork system. This service has features such as low cost, provision of indoor and outdoor location information, and customized service. In particular, this model can help small company adopt smartwork system because it is light-weight system and cost-effective compared to existing smartwork system. This paper proposes the scenarios of the service models, the roles and incentives of the participants, and the comparative analysis. The superiority of NFC-based smartwork service model is shown by comparing and analyzing the new service models and the existing service models. The service model can expand scope of enterprises and organizations that adopt smartwork and expand the scope of employees that take advantages of smartwork.

• Journal of Animal Science and Technology
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• v.49 no.3
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• pp.329-340
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• 2007

This study was conducted to evaluate effects of fermented wild-ginseng culture by-product on growth performance, blood characteristics, meat quality and ginsenoside concentration of meat in finishing pigs. Forty-eight pigs(Landrace×Yorkshire×Duroc, 76.26±1.06kg average initial body weight) were used in 49d growth assay. Dietary treatments were included 1) CON(basal diet), 2) FWG1(basal diet+2.5% fermented wild-ginseng cultures by-product) and 3) FWG2(basal diet+5.0% fermented wild-ginseng cultures by-product). The pigs were allotted into four pigs per pen with four replicate pens per treatment by completely randomized design. No differences were found among treatments for ADG, ADFI and gain/feed from 0day to 49day of the experiment(P>0.05). Dry matter digestibility was greater in FWG1 treatment than CON treatment(P<0.05). In cholesterol concentration of blood, HDL cholesterol was significantly higher in CON treatment than FWG1 treatment(P<0.05). In meat quality, TBARS was significantly lower in FWG1 and FWG2 treatments than CON treatment(P<0.05). In sensory evaluation, Marbling was significantly higher in CON treatment than FWG1 treatment(P<0.05). Firmness in FWG2 and CON treatments was higher than FWG1 treatment(P<0.05). In meat color, L*-value of longissmus dorsi muscle was increased in FWG1 treatment compared to CON and FWG2 treatments(P<0.05). a* and b*-value of longissmus dorsi muscle were increased in CON and FWG1 treatments compared to FWG2 treatment (P<0.05). Ginsenoside concentration of meat was significantly higher in FWG2 treatment than CON treatment(P<0.05). In conclusion, fermented wild-ginseng culture by-product was effective for improving dry matter, TBARS, firmness, meat color and ginsenoside concentration of meat in finishing pigs.

• Korean Journal of Environment and Ecology
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• v.28 no.3
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• pp.357-364
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• 2014

This study aimed to determine effects of the use of water-retention additive, hydrophilic polymer, for extensive green roofs on growth of Juniperus chinensis var. sargentii and Euonymus fortunei 'Emerald and Gold' for woody plants, and Carex kobomugi and Carex pumila for herbaceous plants. Five different contents of hydrophilic polymer including 0% (Control), 1.0%, 2.5%, 5.0%, and 10% (polymer: medium (w/w), dry weight basis) were added to each of the container filed with a 100 kg of growth medium. Ten of plants were transplanted in each of square container ($1m(L){\times}1m(W){\times}0.3m$ (H)) built on the roof platforms in randomized complete block design in the $20^{th}$ of May, 2013. In results, excessively high volumetric soil water content, about 97-98%, was found in the substrate under elevated hydrophilic polymer concentration of at least 2.5%, during the entire growing period. The moisture content of the substrate containing 1.0% of hydrophilic polymer was higher about 20% in the range between 70% and 80%, compared tho that of Control substrate in the range between 50% and 60%, for 27 days after transplanting prior to abundant rainfall, indicating that the application of hydrophilic polymer to the extensive green roof substrate is effective to eliminate drought condition by retaining water in the substrate. Euonymus fortunei 'Emerald and Gold' and Carex kobomugi resulting in higher plant growth with 2.5% than those of the other treatment plants. Juniperus chinensis var. sargentii was observed the highest growth under 1.0% hydrophilic polymer treatement, and Carex pumila was founded the best growth with Control respectively. Plants that grown in both the 1.0% and 2.5% hydrophilic polymer survived all, while the plants that grown in the 5.0% and 10% hydrophilic polymer died after 3 months. These results suggest that advantage of the addition of hydrophilic polymer may be greater in drought-tolerant plants, but the mixture proportion of hydrophilic polymer should be determined according to the different features of the plant species being grown.

• Journal of the Korean Institute of Gas
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• v.22 no.5
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• pp.53-61
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• 2018

Low-salinity water based polymerflooding (LSPF) is one of promising enhanced oil recovery (EOR) method that has the synergetic effect of combining polymer injection method and low-salinity water injection method. In order to maximize EOR efficiency, it is essential to design low-salinity water appropriately considering the properties of polymer. In this aspect, the main purpose of this study is to investigate the effect of pH and $SO_4{^{2-}}$ ion which one of PDI (Potential Determining Ion) on oil production when applying LSPF to carbonate oil reservoir. First, the stability and adsorption of polymer molecule were analyzed in different pH of injection water and $SO_4{^{2-}}$ concentration in injection water. As a result, regardless of pH and $SO_4{^{2-}}$ concentration, when $SO_4{^{2-}}$ ion was contained in injection water, the stability of polymer solution was obtained. However, from the result of polymer retention analysis, in neutral state of injection water, since $SO_4{^{2-}}$ interfered the adsorption of polymer, the adsorption thickness of polymer was thinner as $SO_4{^{2-}}$ concentration was higher. On the other hand, when injection water was acidic as pH 4, the amount of polymer adsorption increased with the injection of polymer solution, so the mobility of polymer solution was greatly lowered. From the results of wettability alteration due to low-salinity water effect, in the case of neutral injection water injected, as $SO_4{^{2-}}$ concentration was increased, more oil which attached on rock surface was detached, altering wettability from oil-wet to water-wet. On the other hand, in acidic condition, due to complex effect of rock dissolution and polymer adsorption, wettability of the entire core system was less altered relatively to neutral condition. Therefore, it was evaluated that better EOR efficiency was obtained when injecting low-salinity water based polymer solution containing high concentration of $SO_4{^{2-}}$ with neutral condition, enhancing the oil production up to 12.3% compared to low-salinity water injection method.