• Food Science and Preservation
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• v.11 no.2
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• pp.195-200
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• 2004

Microbial lethal value and nutrient retention of sous vide processed spinach were evaluated with mathematical model prediction and experimental trial for different package sizes and pasteurization temperatures. The package size covers 500 g, 1 kg and 2 kg, while the pasteurization temperature includes 80, 90 and 97$^{\circ}C$. The basic process scheme consists of filling blanched spinach into barrier plastic film pouch, sealing under vacuum, pasteurization in hot water with over pressure and final cooling to 3$^{\circ}C$. Pasteurization condition was designed based on attainment of 6 decimal inactivation of Listeria monocytogenes at geometric center of the pouch package by heating cycle, which was determined by general method. Heat penetration property of the package and thermal destruction kinetics were combined to estimate the retention of ascorbic acid and chlorophyll. Smaller packages with shorter pasteurization time gave better nutrient retention, physical and chemical qualities. Larger package size was estimated and confirmed experimentally to give higher pasteurization value at center, lower ascorbic acid and chlorophyll contents caused by longer heat process time. Lower pasteurization temperature with longer process time was predicted to give lower pasteurization value at center and lower ascorbic acid, while chlorophyll content was affected little by the temperature. Experimental trial showed better retention of ascorbic acid and chlorophyll for smaller package and higher pasteurization temperature with shorter heating time. The beneficial effect of smaller package and higher pasteurization temperature was also observed in texture, color retention and drip production.

• Radiation Oncology Journal
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• v.18 no.4
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• pp.300-308
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• 2000

Purpose :The aim of this study is to analysis of suwival and recurrence rates of the uterine cervical carcinoma patients whom received the radiation therapy respectively. The prognostic factors, such as Papanicolaou (Pap) smear, carcinoembriogenic antigen (CEA) and squamous cell carcinoma (SCC) antigen has been studied. Methods and Materials : From January 1981 to December 1998, eight-hundred twenty-seven uterine carvical cancer patients were treat with radiation therapy. All of the patients were divided into two groups : the radiation therapy only (S2l patients) group and the postoperative radiation therapy (326 patients) group. The age, treatment modality, clinical stage, histopathology, recurrence, follow-up Pap smears, CEA and SCC antigen were used as parameters for the evaluation. The prognostic factors such as survival and recurrence rates were peformed with the Kaplan-Meier method and the Cox hazard model, respectively. Median rollow-up was 38.6 months. Results :On the radiation therapy only group, 314 patients (60$\%$) achieved complete response (CR), 47 patients (9$\%$) showed local recurrence (LR), 78 patients (15$\%$) developed distant metastasis (DM). On the Postoperative radiation therapy group, showed 276 Patients (85$\%$) CR, 8 Patients (2$\%$) LR, 37 Patients (11$\%$) DM. The 5-year survival and recurrence rates was evaluated for all parameters. The statistically significant factors for the survival rate in univariate analysis were clinical stage (p=0.0001), treatment modality (p=0.0010), recurrence (p=0.0001), Pap smear (p=0.0329), CEA (p=0.0001) and SCC antigen (p=0.0001). Conclusion: This study indicated that after treatment, the follow-up studies of Pap smear, CEA and SCC antigen were significant parameter and prediction factors for the survival and recurrence of the uterine cervical carcinoma.

• Tuberculosis and Respiratory Diseases
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• v.41 no.6
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• pp.604-615
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• 1994

Background: Analysis of cells in bronchoalveolar lavage(BAL) fluid had been used to predict the histologic changes of the bronchioles and alveoli in patients with interstitial lung diseases(ILD). Definitive diagnosis can be a1so made in some cases of ILD, such as histiocytosis. However, there are a few data of the cellular components in BAL fluid in normal Korean individuals and in patients with ILD. In order to evaluate the role of the cellular analysis of BAL fluid in prediction of alveolitis and differential diagnosis among ILDs, we compared the cellular components in BAL fluid from 50 normal individuals and 86 ILD patients. Method: BAL was performed by instillation and retrievement of normal saline with fiberoptic bronchoscopy. The cell number was counted by Hemocytometer. Differential count was done up to 500 cells on slides prepared by Diff-Quik stain and non-specific esterase stain. We compared the recovery rate(RR), cell numbers(CN), and percentages of each cellular components(CP). Results: The results were as follows: 1) There was no difference in RR, CN and CP between the normal smoker group and normal non-smoker group. 2) Total cell numbers recoverd in BAL fluid increased in collagen vascular diseases(CVD), hypersensitivity pneumonitis(HP), idiopathic pulmonary fibrosis(IPF), and miliary tuberculosis(Mil TBC) groups. 3) The percentage of lymphocytes increased in HP, IPF and Mil TBC groups. Macrophage percentages increased in HP, IPF, and Mil TBC groups. Neutrophil percentages were increased in CVD, HP, IPF and Mil TBC groups. Eosinophil percentages were increased in HP, IPF and Mil TBC groups. The numbers of each cells showed same findings as the percentages did. Conclusion: The analysis of cellular components of BAL fluid can predict the presence of alveolitis in many cases of ILDs. However, It was not helpful in differential diagnosis among ILDs.

• Tuberculosis and Respiratory Diseases
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• v.44 no.2
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• pp.321-328
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• 1997

Background : we have evaluated the association of age, smoking, type of anesthesia, type of operation, duration of surgery, previous history of chronic pulmonary diseases with postoperative pulmonary complications and identified which parameter of preoperative spirometry was a predictor of postoperative pulmonary complications. Method : In 270 patients older than 60 years, the postoperative pulmonary complications were evaluated according to age, smoking, type of anesthesia, type of operation, duration of surgery, previous history of chronic pulmonary diseases and the parameters of preoperative spirometry were analyzed. Results : The postoperative pulmonary complications rates were significant higher among patients older than 70 years, and among those with previous chronic pulmonary diseases or their smoking history. The pulmonary complications were increased among patients with general anesthesia or duration of surgery more than 2 hours. The pulmonary complications rates did not differ according to sex, type of operation. The patients with hypercarbia($PaCO_2$ > 45mmHg) have more increased postoperative complications. The preoperative FEV1 less than $1\;{\ell}$, FVC, MMEFR & MVV less than 50% of predicted respectively were predictive of complications. Conclusion : Age $\geq$ 70, history of smoking,duration of operation more than 2 hours, general anesthesia, previous chronic pulmonary disease and hypercarbia ($\geq$45mmHg) on preoperative arterial blood gas analysis were predictive of pulmonary complications. Among the parameters of spirometry, FEV1, FVC, MMEFR and MVV were indicator of predicting postoperative pulmonary complications.

• The korean journal of orthodontics
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• v.27 no.1
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• pp.91-103
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• 1997

This paper aimed to study what the influences of orthodontic treatment of pronunciation are. We compared the duration and the acoustic wave patterns of Korean consonants pronounced by a control group with those of a patient who had his four premolars extracted and had been given orthodontic treatment The results were as follows : 1. Compared to the control group, the treatment group had a longer duration time of consonant pronunciation for all consonants but "ㅅ(s)" and "ㅌ($(t^h)$" in CV(consonant-vowel) pairs. Especially in the case of "ㅈ(dz)", "ㅆ$({\varphi}^h)$" for CV-pairs, and "ㄷ(d)" in VCV(vowel-consonant-vowel) clusters, the duration of consonant sound showed a sharp contrast between the control group and the treatment group. 2. There were clear differences in the acoustic wave patterns of "ㅉ(ts)", "ㅆ$({\varphi}^h)$" and "ㅊ$(c^h)$", all of which were in VCV-clusters. The acoustic wave pattern of "ㅉ(ts)", when pronounced by the treatment group, was stronger than the control group's. This phenomenon was most remarkable in the transitive section where the "ㅉ(ts)" sound flowed into the following vowel. When a preceding vowel shifted to the consonant "ㅆ$({\varphi}^h)$", the attack property of the appeared clearly in the acoustic waves of the treament group, while in the control group the starting point of consonart was indistinctive. Consonant duration for the treatment group was longer, and the appearance of a zero crossing point in the acoustic wave was more frequent. In the case of "ㅊ$(c^h)$", the treatment group produced a strong acoustic wave, and the property of aspiration was obvious in it. 3. When the treatment group pronounced "ㄷ(d)" and "ㅈ(dz)" in CV-pairs, the acoustic-wave was similar to that of aspirated "ㅌ$(t^h)$" and "ㅊ$(c^h)$". 4. The aspirated "ㅌ$(t^h)$" and "ㅊ$(c^h)$" pronounced by the treatment group showed the stronger airstream and acoustic wave form.

• Tuberculosis and Respiratory Diseases
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• v.44 no.6
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• pp.1285-1295
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• 1997

Background : EGFR is one of the initial step in signal transduction pathway about multistep carcinogenesis. It is homologous to oncogene erbB-2 and is the receptor for EGF and TGF alpha. EGFR has important role in the growth and differentiation of tumor cells. So, EGFR in non-small cell lung cancer was examined to search for possible evidence as clinical prognostic factor. Methods : To investigate the role of EGFR in lung cancer, the author performed immunohistochemical stain of EGFR on 57 resected primary non-small cell lung cancer specimens. And the author analyzed the correlation between EGFR expression, clinical parameters, Sand $G_1$ phase fraction and survival. Results : 1) EGFR were detected in 56% of total 57 patients (according to histologic type, squamous cancer 50%, adenocarcinoma 63%, large cell cancer 75%) (according to TNM stage, stage I 64%, stage II 38%, stage III 55%) (according to cellular differentiation, well 50%, moderately 52%, poorly 65%). All differences were insignificant 2) Using the flow cytometric analysis, mean S-phase fraction of EGFR (+) and (-) group were 22.3(${\pm}10.5$)%. 18.0(${\pm}10.9$)% (p>0.05), mean $G_1$-phase fraction of EGFR (+) and (-) group were 68.4(${\pm}11.6$)%, 71.1(${\pm}12.8$)%, (p>0.05) 3) Two-year survival rate of EGFR (+) and (-) group were 53%, 84%, median survival time of EGFR (+) and (-) group were 26, 53 months. (p<0.05, Kaplan-Meier, generalized Wilcox) Conclusion : EGFR immunostaining may be a simple and useful method for survival prediction in non-small cell lung cancer.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.281-286
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• 2003

A large number of features are collected for problem solving in real life, but to utilize ail the features collected would be difficult. It is not so easy to collect of correct data about all features. In case it takes advantage of all collected data to learn, complicated learning model is created and good performance result can't get. Also exist interrelationships or hierarchical relations among the features. We can reduce feature's number analyzing relation among the features using heuristic knowledge or statistical method. Heuristic technique refers to learning through repetitive trial and errors and experience. Experts can approach to relevant problem domain through opinion collection process by experience. These properties can be utilized to reduce the number of feature used in learning. Experts generate a new feature (highly abstract) using raw data. This paper describes machine learning model that reduce the number of features used in learning using heuristic function and use abstracted feature by neural network's input value. We have applied this model to the win/lose prediction in pro-baseball games. The result shows the model mixing two techniques not only reduces the complexity of the neural network model but also significantly improves the classification accuracy than when neural network and heuristic model are used separately.

• Journal of Science Education
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• v.33 no.1
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• pp.12-30
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• 2009

The purpose of this study was to analyze recognition characteristics of science gifted students on the earth system based on their thinking style. The subjects were 24 science gifted students at the Science Institute for Gifted Students of a university located in metropolitan city in Korea. The students' thinking styles were firstly examined on the basis of the Sternberg's theory of mental self-government. And then, the students were divided into two groups: Type I group(legislative, judicial, global, liberal) and Type II group(executive, local, conservative) based on Sternberg's theory. Data was collected from three different type of questionnaires(A, B, C types), interview, word association method, drawing analyses, concept map, hidden dimension inventory, and in-depth interviews. The findings of analysis indicated that their thinking styles were characterized by 'Legislative', 'Executive', 'Anarchic', 'Global', 'External', 'Liberal' styles. Their preference were conducting new projects and using creative problem solving processes. The results of students' recognition characteristics on earth system were as follows: First, though the two groups' quantitative value on 'System Understanding' was very similar, there were considerable distinctions in details. Second, 'Understanding the Relationship in the System' was closely connected to thinking styles. Type I group was more advantageous with multiple, dynamic, and recursive approach. Third, in the relation to 'System Generalization' both of the groups had similar simple interpretational ability of the system, but Type I group was better on generalization when 'hidden dimension inventory' factor was added. On the system prediction factor, however, students' ability was weak regardless of the type. Consequently, more specific development strategies on various objects are needed for the development and application of the system learning program. Furthermore, it is expected that this study could be practically and effectively used on various fields related to system recognition.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Fire Science and Engineering
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• v.18 no.1
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• pp.54-66
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• 2004

In this article, we are to suggest the hazard-assessing method for the underground pipelines, and find out the pipeline-maintenance schemes of high efficiency in cost. Three kinds of methods are applied in order to refer to the approaching methods of listing the hazards for the underground pipelines: the first is RBI(Risk Based Inspection), which firstly assess the effect of the neighboring population, the dimension, thickness of pipe, and working time. It enables us to estimate quantitatively the risk exposure. The second is the scoring system which is based on the environmental factors of the buried pipelines. Last we quantify the frequency of the releases using the present THOMAS' theory. In this work, as a result of assessing the hazard of it using SPC scheme, the hazard score related to how the gas pipelines erodes indicate the numbers from 30 to 70, which means that the assessing criteria define well the relative hazards of actual pipelines. Therefore. even if one pipeline region is relatively low score, it can have the high frequency of leakage due to its longer length. The acceptable limit of the release frequency of pipeline shows 2.50E-2 to 1.00E-l/yr, from which we must take the appropriate actions to have the consequence to be less than the acceptable region. The prediction of total frequency using regression analysis shows the limit operating time of pipeline is the range of 11 to 13 years, which is well consistent with that of the actual pipeline. Concludingly, the hazard-listing scheme suggested in this research will be very effectively applied to maintaining the underground pipelines.