• Journal of Korean Academy of Nursing
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• v.28 no.4
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• pp.1047-1059
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• 1998

Senile Dementia is one of the dispositional mental disorder which has been known to the world since Hippocratic age. It has become a wide-spread social problem all over the world because of chronic disease processes and the demands of dependent care for several years as well as improbability of treatment of it at the causal level. Essentially, life styles of the older generation differ from those of the younger generation. While the fomer is used to the patriarchal system and the spirit of filial piet and respect, the latter is pragmatized and individualized under the effects of the Western material civilization. These differences between the two generations cause conflict between family members. In particular, the pain and conflict of care-givers who take care of a totally dependent dementia patient not only is inciting to the collapse of the family union, but is expanding into a serious social problem. According to this practical difficulty, this study has tried to compare dementia care-givers' experiences inter-culturally and to help set up more proper nursing interventions, describing and explaining them through ethnographies by participant observation and in-depth interviews that enable seeing them in a more close, honest and certain way. It also tries to provide a theoetical model of nusing care for dementia patients which is proper to Korean culture. This study is composed of 12 participants (4 males, 8 females) whose ages range from 37-71 years. The relations of patients are 5 spouses(3 husbands, 2 wives), 4 daughters-in-law, 2 daughters, and 1 son-in-law. The following are the care-givers' meaning of experiences that results of the study shows. The first is "psychological conflict". It contains the minds of getting angry, reproaching, being driven to dispair, blaming oneself, giving up lives, and being afraid, hopeless, and resigned. The second is "physical, social and psychological pressure" . At this stage, care-givers are shown to be under stress of both body and soul for the lack of freedom and tiredness. They also feel constraint because they hardly cope with the care and live through others' eyes. The third is "isolation". It makes the relationship of patient care-giver to be estranged, without understanding each other. They, also, experience indifference such as being upset and left alone. The forth is "acceptance" They gradually have compassion, bear up and then adapt themselves to the circumstances they are in. The fifth is "love". Now they learn to reward the other with love. It is also shown that this stage contains the process of winning others' recognition. The final is "hope". In this stage they really want situations to go smoothly and hope everything will be O.K. These consequences enable us to summarize the principles of cue experience such as, in the early stage, negative response such as physical·psychological confusion, pain and conflict are primary. Then the stage of acceptance emerges. It is an initial positive response phase when care-givers may admit their situations. As time passes by a positive response stage emerges. At last they have love and hope. Three stages we noted above : however, there are never consistent situations. Rather it gradually comes into the stage of acceptance, repeating continuous conflict, pressure and isolation. If any interest and understanding of families or the support of surrounding society lack, it will again be converted to negative responses sooner or later. Otherwise, positive responses like hope and love can be encouraged if the family and the surroundings give active aids and understanding. After all, the principles of dementia care experiences neither stay at any stage, nor develop from negative stages to positive stages steadily. They are cycling systems in which negative responses and positive responses are constantly being converted. I would like to suggest the following based on the above conclusions : First, the systematic and planned education of dementia should be performed in order to enhance public relations. Second, a special medical treatment center which deals with dementia, under government's charge, should be managed. Third, the various studies approaching dementia care experiences result in the development of more reasonable and useful nursing guidelines.

• Radiation Oncology Journal
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• v.15 no.3
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• pp.175-186
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• 1997

Purpose : To evaluate the qualitative immunologic changes by ionizing radiation. we studied the altered capacities of the macrophages and lymphocytes to produce cytokines in conjunction with resistance to Listeria monocytegenes (LM) infection in mice Materials and Methods : BALB/c mice and Listeria monocytogenes were used. The mice were infected intraperitoneally with $10^5LM$ at 1 day after irradiation (300cGy) and sacrificed at 1, 3, 5 days after infection, and then the numbers of viable LM per spleen in the irradiated and control group were counted. Tumor necrosis factor-alpha ($TNF-\alpha$), interferon-gamma ($IFN-\gamma$). interleukin-2 (IL-2), and nitric oxide (NO) were assessed after irradiation. Results : Under gamma-ray irradiation with a dose range of 100-850cGy, the number of total splenocytes decreased markedly in a dose-dependent manner, while peritoneal macrophages did so slightly Cultured peritoneal macrophages produced more $TNF-\alpha$ in the presence of lipopolysaccharide (LPS) during the 24 hours after in vitro irradiation, but their capacity of $TNF-\alpha$ Production showed a decreased tendency at 5 days after in vivo total body irradiation. With 100cGy and 300cGy irradiation, cultured peritoneal macrophages produced more NO in the presence of LPS during the 24 hours after in vitro irradiation than without irradiation. Activated splenocytes from irradiated mice (300cGy) exhibited a decreased capacity to Produce IL-2 and $IFN-\gamma$ with Concavalin-A stimulation at 3 days after irradiation. When BALB/c mice were irradiated to the total body with a dose of 300cGy, they showed enhanced resistance during early innate phase, but a significant inhibition of resistance to LM was found in the late innate and acquired T-cell dependent phases. Conclusion : These results su99es1 that increased early innate and decreased late innate and acquired immunity to LM infection by ionizing radiation (300cGy) may be related to the biphasic altered capacity of the macrophages to produce $TNF-\alpha$ and the decreased capacities of the lymphocytes to produce IL-2 and $IFN-\gamma$ in addition to a marked decrease in the total number of cells.

• Journal of Life Science
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• v.21 no.9
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• pp.1346-1353
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• 2011

Sophora tonkinensis Gapnep has been used as a traditional herbal medicine in oriental regions since ancient times. In this study, the effect and mechanism of the MeOH extract of Sophora tonkinensis Gapnep (STME) on adipocite differentiation and adipogenesis in 3T3-L1 preadipocites were investigated. Treatment with STME in the concentration range of 0-200 ${\mu}g$/ml significantly inhibited the differentiation of 3T3-L1 preadipocites in a dose-dependent manner, as determined by a decrease in intracellular lipid droplets and lipid contents measured by Oil Red O staining. In association with the inhibitory effect of lipid accumulation, the expressions of the proteins concerned with adipogenesis in 3T3-L1 preadipocites were also investigated. Treatment with STME reduced the expressions of peroxisome proliferator-activated receptor ${\gamma}$ (PPAR${\gamma}$), cytidine-cytidine-adenosine-adenosine-thymine (CCAAT)/enhancer-binding proteins ${\alpha}$ and ${\beta}$ (C/EBP${\alpha}$ and C/EBP${\beta}$) and sterol regulatory element binding protein (SREBP), which are adipocyte specific markers. In flow cytometry analysis, the inhibitory effect of differentiation was caused by G1 arrest and following mitotic clonal expansion cease. Therefore, we also investigated the alteration of G1 phase arrest-related proteins. As a result, the expression of p21 protein was significantly increased, while the expressions of Cdk2, E2F-1 and phospho-Rb were reduced in a dose-dependent manner in STME treated 3T3-L1 cells. According to these results, STME might inhibit differentiation through G1 arrest in 3T3-L1 preadipocytes adipogenesis, and further studies, which are in progress, have to be completed to identify the active compounds.

• Korean Journal of Environmental Biology
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• v.27 no.1
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• pp.66-72
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• 2009

Diabetic Retinopathy (DR) is a leading cause of blindness among adults in the western countries. Hyperglycemia is a condition, that induces apoptotic cell death in a variety of cell types in diabetes, but the mechanism remains unclear. The aim of the study is to understand the effects of high Glucose on Human Retinal Endothelial Cells. Retinal endothelial cells were cultured in Iscove's Modified Dulbecco's Medium (IMDM) containing 5, 25 and 50 mM Glucose, incubated for 24, 36 and 48 hours in humidified 5 % CO$_2$ incubator at 37$^{\circ}C$. Human Retinal Endothelial Cell Line (HREC) were characterized for morphology with different treatment by phase contrast microscopic analysis. Number of dead and viable cells was counted by trypan blue exclusion and supported by MTT assay. The intracellular Hydrogen peroxide (H$_2$O$_2$), a Reactive Oxygen Species (ROS) generation in high glucose conditions was assessed by FOX II assay and apoptosis by caspase-3 assay. The high glucose treated cells undergoing DNA fragmentation was witnessed by Agarose gel electrophoresis. We found that the cells incubated with 25 and 50 mM glucose containing medium for 48 hours altered the morphology of the cell, induced apoptosis and DNA fragmentation. The dead cell number were high in 25 and 50 mM when compared to the cells incubated with 5 mM glucose for 24, 36, and 48 hours. Also, the H$_2$O$_2$ levels and the activity of caspase-3 were increased in high glucose treated cells. Conclusions/interpretation: Our results demonstrated that elevated glucose induces apoptosis in cultured HREC. The hyperglycemia-induced increase in apoptosis may be dependent on caspase activation. The association between ROS generation and caspase-3 activation on high glucose treated cells is yet to be investigated.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.22 no.2
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• pp.164-173
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• 2000

The p16 protein is a cyclin dependent kinase inhibitor that inhibits cell cycle progression from $G_1$ phase to S phase in cell cycle. Many p16 gene mutations have been noted in many cancer-cell lines and in some primary cancers, and alterations of p16 gene function by DNA methylation have been noticed in various kinds of cancer tissues and cell-lines. There have been a large body of literature has accumulated indicating that abnormal patterns of DNA methylation (both hypomethylation and hypermethylation) occur in a wide variety of human neoplasma and that these aberrations of DNA methylation may play an important epigenetic role in the development and progression of neoplasia. DNA methylation is a part of the inheritable epigenetic system that influences expression or silencing of genes necessary for normal differentiation and proliferation. Gene activity may be silenced by methylation of up steream regulatory regions. Reactivation is associated with demethylation. Although evidence or a high incidence of p16 alterations in a variety of cell lines and primary tumors has been reported, that has been contested by other investigators. The precise mechanisms by which abnormal methylation might contribute to carcinogenesis are still not fully elucidated, but conceivably could involve the modulation of oncogene and other important regulatory gene expression, in addition to creating areas of genetic instability, thus predisposing to mutational events causing neoplasia. There have been many variable results of studies of head and neck squamous cell carcinoma(HNSCC). This investigation was studied on 13 primary HNSCC for p16 gene status by protein expression in immunohistochemistry, and DNA genetic/epigenetic analyzed to determine the incidence, the mechanisms, and the potential biological significance of its Inactivation. As methylation detection method of p16 gene, the methylation specific PCR(MSP) is sensitive and specific for methylation of any block of CpG sites in a CpG islands using bisulfite-modified DNA. The genomic DNA is modified by treatment with sodium bisulfate, which converts all unmethylated cytosines to uracil(thymidine). The primers designed for MSP were chosen for regions containing frequent cytosines (to distinguish unmodified from modified DNA), and CpG pairs near the 5' end of the primers (to provide maximal discrimination in the PCR between methylated and unmethylated DNA). The two strands of DNA are no longer complementary after bisulfite treatment, primers can be designed for either modified strand. In this study, 13 paraffin embedded block tissues were used, so the fragment of DNA to be amplified was intentionally small, to allow the assessment of methylation pattern in a limited region and to facilitate the application of this technique to samlples. In this 13 primary HNSCC tissues, there was no methylation of p16 promoter gene (detected by MSP and automatic sequencing). The p16 protein-specific immunohistochemical staining was performed on 13 paraffin embedded primary HNSCC tissue samples. Twelve cases among the 13 showed altered expression of p16 proteins (negative expression). In this study, The author suggested that low expression of p16 protein may play an important role in human HNSCC, and this study suggested that many kinds of genetic mechanisms including DNA methylation may play the role in carcinogenesis.

• Radiation Oncology Journal
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• v.23 no.1
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• pp.51-60
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• 2005

Purpose : Selective inhibition of multiple molecular targets may improve the antitumor activity of radiation. Two specific inhibitors of selective cyclooxygenase-2 (COX-2) and epidermal growth factor receptor (EGFR) were combined with radiation on the HeLa cell line. To investigate cooperative mechanism with selective COX-2 inhibitor and EGFR blocker, in vitro experiments were done. Materials and Methods : Antitumor effect was obtained by growth inhibition and apoptosis analysis by annexin V-Flous method. Radiation modulation effects were determined by the clonogenic cell survival assay. Surviving fractions at 2 Gy ($SF_2$) and dose enhancement ratio at a surviving fraction of 0.25 were evaluated. To investigate the mechanism of the modulation of radiosensitivity, the cell cycle analyses were done by flow cytometry. The bcl-2 and bax expressions were analyzed by western blot. Results : A cooperative effect were observed on the apoptosis of the HeLa ceil line when combination of the two drugs, AG 1478 and NS 398 with radiation at the lowest doses, apoptosis of $22.70\%$ compare with combination of the one drug with radiation, apoptosis of $8.49\%$. In cell cycle analysis, accumulation of cell on $G_0/G_l$ phase and decrement of S phase fraction was observed from 24 hours to 72 hours after treatment with radiation, AG 1478 and NS 398. The combination of NS 398 and AG 1478 enhanced radiosensitivity on a concentration-dependent manner in HeLa cells with dose enhancement ratios of 3.00 and $SF_2$ of 0.12 but the combination of one drug with radiation was not enhanced radlosensitivity with dose enhancement ratios of 1.12 and SF2 of 0.68 (p=0.005). The expression levels of bcl-2 and bax were reduced when combined with AG 1478 and NS 398. Conclusion : Our results indicate that the selective COX-2 inhibitor and EGFR blocker combined with radiation have potential additive or cooperative effects on radiation treatment and may act through various mechanisms including direct inhibition of tumor cell proliferation, suppression of tumor cell cycle progression and inhibition of anti-apoptotic proteins.

• Journal of Radiation Protection and Research
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• v.37 no.3
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• pp.108-115
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• 2012

The Urban Areas Working Group within the EMRAS-2 ($\underline{E}$nvironmental $\underline{M}$odelling for $\underline{RA}$diation $\underline{S}$afety, Phase 2), which has been supported by the IAEA (International Atomic Energy Agency), has designed some types of accidental scenarios to test and improve the capabilities of models used for evaluation of radioactive contamination in urban areas. For the comparison of the results predicted from the different models, the absorbed doses in air were analyzed as a function of time following the accident with consideration of countermeasures to be taken. Two kinds of considerations were performed to find the dependency of the predicted results. One is the 'accidental season', i.e. summer and winter, in which an event of radioactive contamination takes place in a specified urban area. Likewise, the 'rainfall intensity' on the day of an event was also considered with the option of 1) no rain, 2) light rain, and 3) heavy rain. The results predicted using a domestic model of METRO-K have been submitted to the Urban Areas Working Group for the intercomparison with those of other models. In this study, as a part of these results using METRO-K, the countermeasures effectiveness in terms of dose reduction was analyzed and presented for the ground floor of a 24-story business building in a specified urban area. As a result, it was found that the countermeasures effectiveness is distinctly dependent on the rainfall intensity on the day of an event, and season when an event takes place. It is related to the different deposition amount of the radionuclides to the surfaces and different behavior on the surfaces following a deposition, and different effectiveness from countermeasures. In conclusion, a selection of appropriate countermeasures with consideration of various environmental conditions may be important to minimize and optimize the socio-economic costs as well as radiation-induced health detriments.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.1-17
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• 2015

In this paper, we report what we have observed with regards to a prediction model for the military based on enlisted men's internal(cumulative records) and external data(SNS data). This work is significant in the military's efforts to supervise them. In spite of their effort, many commanders have failed to prevent accidents by their subordinates. One of the important duties of officers' work is to take care of their subordinates in prevention unexpected accidents. However, it is hard to prevent accidents so we must attempt to determine a proper method. Our motivation for presenting this paper is to mate it possible to predict accidents using enlisted men's internal and external data. The biggest issue facing the military is the occurrence of accidents by enlisted men related to maladjustment and the relaxation of military discipline. The core method of preventing accidents by soldiers is to identify problems and manage them quickly. Commanders predict accidents by interviewing their soldiers and observing their surroundings. It requires considerable time and effort and results in a significant difference depending on the capabilities of the commanders. In this paper, we seek to predict accidents with objective data which can easily be obtained. Recently, records of enlisted men as well as SNS communication between commanders and soldiers, make it possible to predict and prevent accidents. This paper concerns the application of data mining to identify their interests, predict accidents and make use of internal and external data (SNS). We propose both a topic analysis and decision tree method. The study is conducted in two steps. First, topic analysis is conducted through the SNS of enlisted men. Second, the decision tree method is used to analyze the internal data with the results of the first analysis. The dependent variable for these analysis is the presence of any accidents. In order to analyze their SNS, we require tools such as text mining and topic analysis. We used SAS Enterprise Miner 12.1, which provides a text miner module. Our approach for finding their interests is composed of three main phases; collecting, topic analysis, and converting topic analysis results into points for using independent variables. In the first phase, we collect enlisted men's SNS data by commender's ID. After gathering unstructured SNS data, the topic analysis phase extracts issues from them. For simplicity, 5 topics(vacation, friends, stress, training, and sports) are extracted from 20,000 articles. In the third phase, using these 5 topics, we quantify them as personal points. After quantifying their topic, we include these results in independent variables which are composed of 15 internal data sets. Then, we make two decision trees. The first tree is composed of their internal data only. The second tree is composed of their external data(SNS) as well as their internal data. After that, we compare the results of misclassification from SAS E-miner. The first model's misclassification is 12.1%. On the other hand, second model's misclassification is 7.8%. This method predicts accidents with an accuracy of approximately 92%. The gap of the two models is 4.3%. Finally, we test if the difference between them is meaningful or not, using the McNemar test. The result of test is considered relevant.(p-value : 0.0003) This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of enlisted men's data. Additionally, various independent variables used in the decision tree model are used as categorical variables instead of continuous variables. So it suffers a loss of information. In spite of extensive efforts to provide prediction models for the military, commanders' predictions are accurate only when they have sufficient data about their subordinates. Our proposed methodology can provide support to decision-making in the military. This study is expected to contribute to the prevention of accidents in the military based on scientific analysis of enlisted men and proper management of them.