• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.1-16
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• 2015

Traffic accident is one of the major cause of death worldwide for the last several decades. According to the statistics of world health organization, approximately 1.24 million deaths occurred on the world's roads in 2010. In order to reduce future traffic accident, multipronged approaches have been adopted including traffic regulations, injury-reducing technologies, driving training program and so on. Records on traffic accidents are generated and maintained for this purpose. To make these records meaningful and effective, it is necessary to analyze relationship between traffic accident and related factors including vehicle design, road design, weather, driver behavior etc. Insight derived from these analysis can be used for accident prevention approaches. Traffic accident data mining is an activity to find useful knowledges about such relationship that is not well-known and user may interested in it. Many studies about mining accident data have been reported over the past two decades. Most of studies mainly focused on predict risk of accident using accident related factors. Supervised learning methods like decision tree, logistic regression, k-nearest neighbor, neural network are used for these prediction. However, derived prediction model from these algorithms are too complex to understand for human itself because the main purpose of these algorithms are prediction, not explanation of the data. Some of studies use unsupervised clustering algorithm to dividing the data into several groups, but derived group itself is still not easy to understand for human, so it is necessary to do some additional analytic works. Rule based learning methods are adequate when we want to derive comprehensive form of knowledge about the target domain. It derives a set of if-then rules that represent relationship between the target feature with other features. Rules are fairly easy for human to understand its meaning therefore it can help provide insight and comprehensible results for human. Association rule learning methods and subgroup discovery methods are representing rule based learning methods for descriptive task. These two algorithms have been used in a wide range of area from transaction analysis, accident data analysis, detection of statistically significant patient risk groups, discovering key person in social communities and so on. We use both the association rule learning method and the subgroup discovery method to discover useful patterns from a traffic accident dataset consisting of many features including profile of driver, location of accident, types of accident, information of vehicle, violation of regulation and so on. The association rule learning method, which is one of the unsupervised learning methods, searches for frequent item sets from the data and translates them into rules. In contrast, the subgroup discovery method is a kind of supervised learning method that discovers rules of user specified concepts satisfying certain degree of generality and unusualness. Depending on what aspect of the data we are focusing our attention to, we may combine different multiple relevant features of interest to make a synthetic target feature, and give it to the rule learning algorithms. After a set of rules is derived, some postprocessing steps are taken to make the ruleset more compact and easier to understand by removing some uninteresting or redundant rules. We conducted a set of experiments of mining our traffic accident data in both unsupervised mode and supervised mode for comparison of these rule based learning algorithms. Experiments with the traffic accident data reveals that the association rule learning, in its pure unsupervised mode, can discover some hidden relationship among the features. Under supervised learning setting with combinatorial target feature, however, the subgroup discovery method finds good rules much more easily than the association rule learning method that requires a lot of efforts to tune the parameters.

• Radiation Oncology Journal
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• v.27 no.3
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• pp.145-152
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• 2009

Purpose: We retrospectively studied the outcomes and prognostic factors of patients with locally advanced, unresectable pancreatic cancer who were treated with concurrent chemoradiotherapy (CCRT) or radiotherapy only. Materials and Methods: Fifty-one patients with locally advanced, unresectable pancreatic cancer (stage IIA~III) who recevied radiotherapy ($\geq$30 Gy) between January 1994 and August 2008 were reviewed retrospectively. The median radiation dose was 39 Gy. Chemotherapy consisted of gemcitabine, cisplatin, or 5-FU alone or in various combinations, and was administered concurrently with radiotherapy in 38 patients. Results: The follow-up period ranged from 2~40 months (median, 8 months). The median survival, and the 1-and 2-year overall survival (OS) rates were 7 months, 15.7%, and 5.9%, respectively. Based on univariate analysis, the baseline CA19-9, performance status, and chemotherapy regimen were significant prognostic factors. The median survival was 8 months for CCRT, and 6 months for radiotherapy alone. The patients treated with gemcitabine-containing regimens had longer survival (median, 10 months) than the patients treated with radiotherapy alone (p=0.027). Twenty-three patients were available to evaluate the patterns of failure. Distant metastases (DM) occured in 18 patients and regional recurrences were demonstrated in 4 patients. Local progression developed in 14 patients. We analyzed the association between the time-to-DM and the baseline CA19-9 levels for 18 evaluable patients. The median time-to-DM was 20 months for patients with normal baseline CA19-9 levels and 2 months for patients with baseline CA19-9 levels $\geq$200 U/ml. Conclusion: CCRT with gemcitabine-based regimens was effective in improving OS in patients with locally advanced, unresectable pancreatic cancer. We suggest that the baseline CA19-9 level is valuable in determining the treatment strategy for patients with locally advanced, unresectable pancreatic cancer.

• Journal of Chest Surgery
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• v.38 no.6 s.251
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• pp.410-414
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• 2005

There are several options for choosing a graft in CABG, we routinely chose LIMA for LAD and great saphenous vein for other target vessels. To evaluate the posoperative graft patency, we have studied the results using a 16 slices multi-detector computed tomography. Material and Method: From 1995 to 2003, 80 CABG patients who did not complain any event of MACE have been examined by 16-MDCT, mostly in an out patient clinic. Result: There were 61 men and 19 women. MDCT was used as early as 7 days to 9 years post-operatively with a median follow-up period of 6.5 years, and mean follow-up peiod of $31.5\pm25.4$ months. Mean age was $58.4\pm12.6$ years old in men and $61.5\pm17.2$ years old in women. 72180 patients received LIMA to LAD, and all other patients received vein grafts for bypass. The target vessel of vein grafts were 8 in LAD, 47 in RCA, 60 in diagonals, and 61 in obtuse marginals. Among them 42 sequential anastomoses were performed. The mean graft number was $3.1\pm1.8$ grafts. 5 year graft patency rate of each grafts was as followings; $93.1\%$ in LIMA to LAD, $94.9\%$ in vein to diagonals, $92.1\%$ in vein to obtuse marginals, and $79.2\%$ in vein to RCA. Sequential grafting showed better graft patency than the isolated grafting $(95.2\%\;vs\;78.7\~95.0\%)$. Conclusion: In this study, CABG with LIMA and saphenous veins showed satisfactory longterm results. 16-MDCT provided good images for follow-up study after CABG. Additionally, as radiologic tools (64-MDCT, MRI) improve more in the future, they can be used for diagnosing preoperative anatomical coronary disease as well as cardiac functions.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.3
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• pp.89-98
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• 1965

The experimental studies were intended to clarify the effects of selection, and also aimed at estimating the heritabilities, the genotypic correlations among some agronomic characters, and at calculating the selection index on some selective characters for the selection of desirable lines, under different climatic conditions. Finally practical implications of these studies, especially on the selection index, were discussed. Twenty-two varieties, determinate growing habit type, were selected at random from the 138 soybean varieties cultivated the year before, were grown in a randomized block design with three replicates at Chinju, Korea, under May and June sowing conditions. The method of estimating heritabilities for the eleven agronomic characters-flowering date, maturity date, stem length, branch numbers per plant, stem diameter, plant weight, pod numbers per plant, grain numbers per plant and 100 grain weight, shown in Table 3, was the variance components procedures in a replicated trial for the varieties. The analysis of covariance was used to obtain the genotypic correlations and phenotypic correlations among the eight characters, and the selection indexes for some agronomic characters were calculated by Robinson's method. The results are summarized as follows: Heritabilities : The experiment on the genotype-environment interaction revealed that in almost all of the characters investigated the interaction was too large to be neglected and materially affected the estimates of various genotypic parameters. The variation in heritability due to the change of environments was larger in the characters of low heritability than in those of high heritability. Heritability values of flowering date, fruiting period (days from flowering to maturity), stem length and 100 grain weight were the highest in both environments, those of yield(grain weight) and other characters were showed the lower values(Table 3). These heritability values showed a decreasing trend with the delayed sowing in the experiments. Further, all calculated heritability values were higher than anticipated. This was expected since these values, which were the broad sense heritability, contain the variance due to dominance and epistasisf in addition to the additive genetic variance. Genotypic correlations : Genotypic correlations were slightly higher than the corresponding phenotypic correlations in both environments, but the variation in values due to the change of environment appeared between grain weight and some other characters, especially an increase between grain weight and flowering date, and the total growing period(Table 6). Genotypic correlations between grain weight and other characters indicated that high seed yield was genetically correlated with late flowering, late maturity, and the other five characters namely branch numbers per plant, stem diameter, plant weight, pod numbers per plant and grain numbers per plant, but not with 100 grain weight of soybeans. Pod numbers and grain numbers per plant were more closely correlated with seed yields than with other characters. Selection index : For the comparison and the use of selection indexes in the selection, two kinds of selection indexes were calculated, the former was called selection index A and the later selection index B as shown in Table 7. Selection index A was calculated by the values of grain weight per plant as the character of yield(character Y), but the other, selection index B, was calculated by the values of pod numbers per plant, instead of grain weight per plant, as the character of yield'(character Y'). These results suggest that selection index technique is useful in soybean breeding. In reality, however, as the selection index varies with population and environment, it must be calculated in each population to which selection is applied and in each environment in which the population is located. In spite of the expected usefulness of selection index technique in soybean breeding, unsolved problems such as the expense, time and labor involved in calculating the selection index remain. For these reasons and from these experimental studies, it was recognized that in the breeding of self-fertilized soybean plants the selection for yield should be based on a more simple selection index such as selection index B of these experiments rather than on the complex selection index such as selection index A. Furthermore, it was realized that the selection index for the selection should be calculated on the basis of the data of some 3-4 agronomic characters-maturity date(X$_1$), branch numbers per plant(X$_2$), stem diameter(X$_3$) and pod numbers per plant etc. It must be noted that it should be successful in selection to select for maturity date(X$_1$) which has high heritability, and the selection index should be calculated easily on the basis of the data of branch numbers per plant(X$_2$), stem diameter(X$_3$) and pod numbers per plant, directly after the harvest before drying and threshing. These characters should be very useful agronomic characters in the selection of Korean soybeans, determinate growing habit type, as they could be measured or counted easily thus saving time and expense in the duration from harvest to drying and threshing, and are affected more in soybean yields than the other agronomic characters.

• Korean Journal of Agricultural Science
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• v.8 no.1
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• pp.72-81
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• 1981

This study was conducted to determine the differences in the growth and milk production performance of Holstein Crossbreds (Korean Native Cattle(♀)${\times}$Holstein(♂)) and Korean Native Cattle produced at the Livestock Experiment Station of the Office of Rural Developement from 1973 to 1978. The number of heifers and cows used in this experiment were 15 head of Korean Native Cattle and 11 head pf Holstein Crossbreds Cattle. Body weight and body measurements were taken at birth, 6, 12, 24 and 36 months of age, however, body measurements were not taken at birth. Milk production was checked from the 11 th day to 180th day after calving. The data was analyzed using the least square procedure in order to estimate the effect of the mating group, year of birth, calving season and parity. The results obtained from this study were as follows: 1. The body weights of the Holstein Crossbreds were heavier than the body weights of purebred Korean Native Cattle. The body weight of the Holstein Crossbreds averaged 28.09kg, 146.64kg, 254.48kg, 392.04kg and 454.46kg at birth, 6, 12, 24 and 36 months of age, respectively. However, the body weights of purebreds Korean Native Cattle averaged 22.45kg, 132.82kg, 220.68kg, 363.54kg and 365.54kg at the same ages. 2. The year of birth affected on body weight at each point during the growing stage, except birth, heifers born in the spring and autumn were heavier than the others, but calving season did not affect on body weight during the growing stage except at birth and 6 months. 3. Parity showed significant differences on body weight in the growing stage. Calves from the 5th parity had a tendency to be heavier than the other calves. 4. The year of birth, calving season and parity at calving had no affect on the change of body measurements, but the wither height, hip height, chest depth, chest girth and hip width were significantly greater in the Holstein Crossbreds at 24 months of age. 5. Mating groups had a significant affect on milk production during the growing stage. Year of birth and calving season did not affect milk production, but parity was significant from 11 days after calving. 6. The least-squares means used to determine the daily milk production were 3.60 and 8.26kg/day for Korean Native Cattle and the Holstein Crossbreds, respectively.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.4
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• pp.100-118
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• 2015

This study established a land-cover classification method on objects using satellite images, and figured out distributional patterns of land cover according to categories through spatial statistics techniques. Object-based classification generated each land cover classification map by spectral information, texture information, and the combination of the two. Through assessment of accuracy, we selected optimum land cover classification map. Also, to figure out spatial distribution pattern of land cover according to categories, we analyzed hot spots and quantified them. Optimal weight for an object-based classification has been selected as the Scale 52, Shape 0.4, Color 0.6, Compactness 0.5, Smoothness 0.5. In case of using the combination of spectral information and texture information, the land cover classification map showed the best overall classification accuracy. Particularly in case of dry fields, protected cultivation, and bare lands, the accuracy has increased about 12 percent more than when we used only spectral information. Forest, paddy fields, transportation facilities, grasslands, dry fields, bare lands, buildings, water and protected cultivation in order of the higher area ratio of DMZ according to categories. Particularly, dry field sand transportation facilities in Yanggu occurred mainly in north areas of the civilian control line. dry fields in Cheorwon, forest and transportation facilities in Inje fulfilled actively in south areas of the civilian control line. In case of distributional patterns according to categories, hot spot of paddy fields, dry fields and protected cultivation, which is related to agriculture, was distributed intensively in plains of Yanggu and in basin areas of Cheorwon. Hot spot areas of bare lands, waters, buildings and roads have similar distribution patterns with hot spot areas related to agriculture, while hot spot areas of bare lands, water, buildings and roads have different distributional patterns with hot spot areas of forest and grasslands.

• Journal of Life Science
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• v.28 no.7
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• pp.835-840
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• 2018

Quantitative determination of the protein expression levels is one of the most important parts in assessment of the safety of foods derived from genetically modified (GM) crops. Overexpression of AtCYP78A7, a gene encoding cytochrome P450 protein, has been reported to improve tolerance to abiotic stress, such as drought and salt stress, in transgenic rice (Oryza sativa L.). In the present study, an enzyme-linked immunosorbent assay (ELISA) kit for diagnosing AtCYP78A7 protein including AtCYP78A7-specific monoclonal antibody was developed. GST-AtCYP78A7 recombinant protein was induced and purified by affinity column. Four monoclonal antibodies (mAb 6A7, mAb 4C2, mAb 11H6, and mAb 7E8) against recombinant protein were also produced and biotinylated with avidin-HRP. After pairing test using GST-AtCYP78A7 protein and lysate of rice samples, mAb 4C2 and mAb 7E8 were selected as a capture antibody and a detecting antibody, respectively, for ELISA kit. Product test using rice samples indicated that percentages of detected protein in total protein were greater than 0.1% in AtCYP78A7-overexpressing transgenic rice (Line 10B-5 and 18A-4), whereas those in negative control non-transgenic rice (Ilpum and Hwayoung) were less than 0.1%. The ELISA kit developed in this study can be useful for the rapid detection and safety assessment of transgenic rice overexpressing AtCYP78A7.

• Tuberculosis and Respiratory Diseases
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• v.42 no.3
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• pp.322-331
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• 1995

Introduction: This study was performed to evaluate the diagnostic usefulness of simultaneous determination of 3 tumor markers {serum carcinoembryonic antigen(CEA), squamous cell carcinoma antigen (SCC Ag) and neuron specific enolase(NSE)} in lung cancer patients. Method: In 113 patients with primary lung cancer(70 with squamous cell carcinoma, 30 with adenocarcinoma, 13 with small cell carcinoma) and 103 patients with benign lung diseases, serum CEA and NSE were measured by enzyme immunoassay, and SCC Ag was measured by microparticle enzyme immunoassay. Results: 1) The mean serum levels of 3 tumor markers were significantly higher in lung cancer groups than benign lung disease groups respectively(p=0.001). 2) In squamous cell carcinoma, the SCC Ag was elevated in 67%, in adenocarcinoma CEA was elevated in 77% and in small cell carcinoma NSE was elevated in 77%, but there were no significant differences according to the stage of each cancer cell types. 3) CEA was the most sensitive marker, but nonspecific to cancer types. SCC Ag was less sensitive than other markers, but more specific toward squamous cell carcinoma, and NSE was more specific to primary lung cancer. 4) As the number of positive tumor markers was increased, the relative possibility of lung cancer was also increased. If two markers were positive, it increased to 77%, and if three markers were positive it increased to 90%. Conclusion: The simultaneous measurement of serum CEA, SCC Ag and NSE would provide additional information for the diagnosis of lung cancer.

• Journal of Preventive Medicine and Public Health
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• v.33 no.3
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• pp.299-305
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• 2000

Objectives : To investigate the difference in the occurrence of lung cancer between foundry workers and non-foundry workers by comparing the number of workers diagnosed with lung cancer through health insurance data. Methods : The study population was comprised of 28,884 workers who had undergone at least one general or special medical examination between January 1995 and December 1997 at the occupational health center. All of the subjects had health insurance during this period. We combined the medical examination data with the health insurance data to compare the number of foundry workers diagnosed with lung cancer and the number of non-foundry workers diagnosed with lung cancer. Results : Seven workers were diagnosed with lung cancer among the 1,591 foundry workers, compared to twelve workers among the 27,293 non-foundry workers (odds ratio: 10.04, 95% confidence interval: 3.95-25.55). The seven foundry workers diagnosed with lung cancer were all exposed to dust, and six out these seven workers were engaged in finishing or shake-out processes. Conclusions : Although the information for this study was obtained from health insurance data, which has limitations such as accuracy and completeness, the number of foundry workers diagnosed with lung cancer was significantly higher than that of non-foundry workers. Therefore, a well-designed cohort study should be followed to confirm the higher lung cancer rates in foundry workers.

• Journal of Chest Surgery
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• v.41 no.5
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• pp.550-562
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• 2008

Background: We attempted to reproduce a previously reported method that is known to be effective for decellularization, and we sought to find the optimal condition for decellularization by introducing some modifications to this method. Material and Method: Porcine semilunar valves, arterial walls and pericardium were processed for decellularization with using a variety of combinations and concentrations of decellularizing agents under different conditions of temperature, osmolarity and incubation time. The degree of decellularization and the preservation of the extracellular matrix were evaluated by staining with hematoxylin and eosin and with alpha-Gal and DAPI in some of the decellularized tissues. Result: Decellularization was achieved in the specimens that were treated with sodium deoxycholate, sodium dodesyl sulfate, Triton X-100 and sodium dodesyl sulfate with Triton X-100 as single-step methods, and this was also achieved in the specimens that were treated with hypotonic solution ${\rightarrow}$ Triton X-100 ${\rightarrow}$ sodium dodesyl sulfate, sodium deoxycholate ${\rightarrow}$ hypotonic solution ${\rightarrow}$ sodium dodesyl sulfate, and hypotonic solution sodium dodesyl sulfate as multi-step methods. Conclusion: Considering the number and the amount of the chemicals that were used, the incubation time and the degree of damage to the extracellular matrix, a single-step method with sodium dodesyl sulfate and Triton X-100 and a multi-step method with hypotonic solution followed by sodium dodesyl sulfate were both relatively optimal methods for decellularization in this study.