• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.117-126
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• 2022

Currently, the number of bridge structures in Korea is continuously increasing and enlarged, and the number of old bridges that have been in service for more than 30 years is also steadily increasing. Bridge aging is being treated as a serious social problem not only in Korea but also around the world, and the existing manpower-centered inspection method is revealing its limitations. Recently, various bridge damage detection studies using deep learning-based image processing algorithms have been conducted, but due to the limitations of the bridge damage data set, most of the bridge damage detection studies are mainly limited to one type of crack, which is also based on a close set classification model. As a detection method, when applied to an actual bridge image, a serious misrecognition problem may occur due to input images of an unknown class such as a background or other objects. In this study, five types of bridge damage including crack were defined and a data set was built, trained as a deep learning model, and an open set recognition-based bridge multiple damage recognition model applied with OpenMax algorithm was constructed. And after performing classification and recognition performance evaluation on the open set including untrained images, the results were analyzed.

• Journal of Agricultural Extension & Community Development
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• v.20 no.4
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• pp.1023-1043
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• 2013

This study has a purpose to research the effects of 'growing lettuce program for science inquiry skills' on science inquiry skills' on science inquiry skills for five grade elementary school student. The program which applied in this research was integrated by plants that could be grown easily for teachers and students and inquiry factors of elementary school science curriculum. To achieve the purpose, the 'Growing lettuce program for science inquiry skills' was provided for total 10 times, eighty minutes every week, through the discretionary activity time from April 5 to June 14 2013. The experimental group was fifth grade one class of H elementary school located in Suwon, and control group was fifth grade other class in the same school. We investigated scientific inquiry competence before and after the survey of two groups all. The total scores for scientific inquiry competence for experimental group and control group were increased significantly before and after running the 'Growing lettuce program for science inquiry skills'. However, the experimental group showed more improvement in six inquiry factors of observation, classification, inference, expectation, data interpretation, and hypothesis establishment than the control group.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.183-190
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• 2011

In this paper, we propose a prototype system for abnormal sound detection and identification which detects and recognizes the abnormal situations by means of analyzing audio information coming in real time from CCTV cameras under surveillance environment. The proposed system is composed of two layers: The first layer is an one-class support vector machine, i.e., support vector data description (SVDD) that performs rapid detection of abnormal situations and alerts to the manager. The second layer classifies the detected abnormal sound into predefined class such as 'gun', 'scream', 'siren', 'crash', 'bomb' via a sparse representation classifier (SRC) to cope with emergency situations. The proposed system is designed in a hierarchical manner via a mixture of SVDD and SRC, which has desired characteristics as follows: 1) By fast detecting abnormal sound using SVDD trained with only normal sound, it does not perform the unnecessary classification for normal sound. 2) It ensures a reliable system performance via a SRC that has been successfully applied in the field of face recognition. 3) With the intrinsic incremental learning capability of SRC, it can actively adapt itself to the change of a sound database. The experimental results with the qualitative analysis illustrate the efficiency of the proposed method.

• The korean journal of orthodontics
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• v.29 no.4 s.75
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• pp.467-481
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• 1999

Cleft lip and/or palate is one of the most common congenital craniofacial anomalies. According to previous epidemiologic studies, incidence of cleft lip and/or palate has been increasing nowadays. However, there is no report about epidemiologic study of cleft lip and/or palate patients who visited dept. of orthodontics in Korea. So the purpose of this study was to provide the epidemiological characteristics and important basic clinical data for the diagnosis and the treatment of the cleft lip and/or palate patients. With the orthodontic and cleft charts, diagnostic models and X-ray films from 250 patients with cleft lip and/or palate who visited Dept. of Orthodontics, Seoul National University Dental Hospital during the last 11 years, the authors investigated patient's visiting yew, types of cleft, patient's gender, and Angle's classification of malocclusion, and surgery timing. The results were as follows ; 1. The number of cleft patients who visited Dept. of Orthodontics, SNUDH increased during 1988-1990 and then it declined until 1992. From 1993 to 1996, it showed a stationary trend. After 1997 it showed an overwhelmingly increasing trend. 2. In the cleft type, the ratio of cleft lip cleft lip and alveolus cleft palate : cleft lip and palate was 7.6:19.2:9.6:63.6. In cleft position, unilateral clefts were more than bilateral ones (cleft lip 79:21, cleft lip and alveolus 77:23, cleft lip and palate 75.5:24.5). In cleft side, left clefts were mote than right clefts (cleft lip 53.3:46.7 cleft lip and alveolus 59.5:40.5, cleft lip and palate 59.2:40.8). 3. In gender ratio, males were more than females in cleft lip (57.9:42.1), cleft lip and alveolus (68.8:31.2) and cleft lip and palate (76.1:23.9). But in cleft Palate females were more than males as 41.7: 58.3. 4. In the age groups, 7-12 year group was the most abundant as $52\%$, and then 0-6 year group ($20.4\%$), 13-18 year group ($17.2\%$), more than 18 yew group ($10.4\%$) were followed as descending order. 5. Most of the cleft lip repair surgeries were operated in 0-3 month ($60.3\%$) and 4-6 month ($17.9\%$). 6. The cleft palate repair surgeries were done in 1-2 year ($31.7\%$), 0-1 year ($25.6\%$), 2-3 year ($12.1\%$), more than 5 year ($11.6\%$) as descending order. 7. The lip scar revision surgeries were done before admission at elementary school in $60\%$. (4-6 you ($27.5\%$), 6-8 year ($19.6\%$), more than 10 year ($19.6\%$), 2-4 year ($13.7\%$) as descending order) 8. The rhinoplasties were done before admission at elementary school in $51.7\%$. (0-2 year ($7.1\%$), 2-4 year ($14.3\%$), 4-6 year ($21.4\%$), 6-8 year ($14.3\%$)). 9. The pharyngeal flap were done at 6 Y (72.5 months) after birth on average and there was even distribution of surgery timing. 10. In relationship between Angle's classification of malocclusion and cleft types, Class I was most abundant and Class III, Class II were followed as descending order in cleft lip group. But Class III was most abundant and Class I, Class II were followed as descending order in cleft lip and alveolus group, cleft palate group, and cleft lip and Palate group. The percentage of frequency in Class III malocclusion was overwhelmingly higher in cleft lip and palate group than any other groups. 11. Because the frequency of class III malocclusion was most prevalent in all age groups, anterior crossbite was the most common chief complaint of cleft patients.

• Asia Marketing Journal
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• v.14 no.2
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• pp.157-176
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• 2012

Brand switching data frequently used in market structure analysis is adequate to analyze non- durable goods, because it can capture competition between specific two brands. But brand switching data sometimes can not be used to analyze goods like automobiles having long term duration because one of main assumptions that consumer preference toward brand attributes is not changed against time can be violated. Therefore a new type of data which can precisely capture competition among durable goods is needed. Another problem of using brand switching data collected from actual purchase behavior is short of explanation why consumers consider different set of brands. Considering above problems, main purpose of this study is to analyze market structure for durable goods with consideration set. The author uses exploratory approach and latent class clustering to identify market structure based on heterogeneous consideration set among consumers. Then the relationship between some factors and consideration set formation is analyzed. Some benefits and two demographic variables - age and income - are selected as factors based on consumer behavior theory. The author analyzed USA automotive market with top 11 brands using exploratory approach and latent class clustering. 2,500 respondents are randomly selected from the total sample and used for analysis. Six models concerning market structure are established to test. Model 1 means non-structured market and model 6 means market structure composed of six sub-markets. It is exploratory approach because any hypothetical market structure is not defined. The result showed that model 1 is insufficient to fit data. It implies that USA automotive market is a structured market. Model 3 with three market structures is significant and identified as the optimal market structure in USA automotive market. Three sub markets are named as USA brands, Asian Brands, and European Brands. And it implies that country of origin effect may exist in USA automotive market. Comparison between modal classification by derived market structures and probabilistic classification by research model was conducted to test how model 3 can correctly classify respondents. The model classify 97% of respondents exactly. The result of this study is different from those of previous research. Previous research used confirmatory approach. Car type and price were chosen as criteria for market structuring and car type-price structure was revealed as the optimal structure for USA automotive market. But this research used exploratory approach without hypothetical market structures. It is not concluded yet which approach is superior. For confirmatory approach, hypothetical market structures should be established exhaustively, because the optimal market structure is selected among hypothetical structures. On the other hand, exploratory approach has a potential problem that validity for derived optimal market structure is somewhat difficult to verify. There also exist market boundary difference between this research and previous research. While previous research analyzed seven car brands, this research analyzed eleven car brands. Both researches seemed to represent entire car market, because cumulative market shares for analyzed brands exceeds 50%. But market boundary difference might affect the different results. Though both researches showed different results, it is obvious that country of origin effect among brands should be considered as important criteria to analyze USA automotive market structure. This research tried to explain heterogeneity of consideration sets among consumers using benefits and two demographic factors, sex and income. Benefit works as a key variable for consumer decision process, and also works as an important criterion in market segmentation. Three factors - trust/safety, image/fun to drive, and economy - are identified among nine benefit related measure. Then the relationship between market structures and independent variables is analyzed using multinomial regression. Independent variables are three benefit factors and two demographic factors. The result showed that all independent variables can be used to explain why there exist different market structures in USA automotive market. For example, a male consumer who perceives all benefits important and has lower income tends to consider domestic brands more than European brands. And the result also showed benefits, sex, and income have an effect to consideration set formation. Though it is generally perceived that a consumer who has higher income is likely to purchase a high priced car, it is notable that American consumers perceived benefits of domestic brands much positive regardless of income. Male consumers especially showed higher loyalty for domestic brands. Managerial implications of this research are as follow. Though implication may be confined to the USA automotive market, the effect of sex on automotive buying behavior should be analyzed. The automotive market is traditionally conceived as male consumers oriented market. But the proportion of female consumers has grown over the years in the automotive market. It is natural outcome that Volvo and Hyundai motors recently developed new cars which are targeted for women market. Secondly, the model used in this research can be applied easier than that of previous researches. Exploratory approach has many advantages except difficulty to apply for practice, because it tends to accompany with complicated model and to require various types of data. The data needed for the model in this research are a few items such as purchased brands, consideration set, some benefits, and some demographic factors and easy to collect from consumers.

• Journal of Chest Surgery
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• v.41 no.5
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• pp.591-597
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• 2008

Background: Pulmonary endarterectomy is widely accepted as a treatment for chronic thromboembolic pulmonary hypertension. Based on our experiences, we sought to find ways to reduce perioperative complications and to improve surgical outcomes in patients undergoing pulmonary endarterectomy. Material and Method: This study was designed as a retrospective analysis of 20 patients with pulmonary hypertension who underwent pulmonary endarterectomy between January 1998 and March 2008. All patients presented with chronic dyspnea. Deep vein thrombosis (DVT) was the major cause of chronic pulmonary thromboembolism (55%). Seventeen patients (85%) underwent inferior vena cava (IVC) filter placement. Thirteen patients underwent surgery under total circulatory arrest, while the others underwent surgery while on low flow cardiopulmonary bypass. Concomitant tricuspid annuloplasty was done in 6 patients (66%) whose tricuspid regurgitation was as severe as grade IV/IV. The mean follow-up duration was $45{\pm}32$ months. Result: Using of University of California, San Diego (UCSD), thromboembolism classification, 4 patients (20%) were type 1, 8 patients (40%) were type II, and 8 patients (40%) were type III. Right ventricular systolic pressure was reduced significantly from $77{\pm}29$ mmHg to $37{\pm}19$ mmHg after pulmonary endarterectomy (p<0.001). The degree of tricuspid regurgitation and the NYHA functional class were all improved postoperatively. Reperfusion edema occurred in 7 cases (35%). The incidence of reperfusion edema was higher in the UCSD type III group than in the other group (25% vs 50%, p=0.25) and the length of postoperative intensive care unit stay was longer in type III group ($5{\pm}2$ days vs $9{\pm}7$ days, p=0.07). The early mortality rate was 10%, and the late mortality rate was 15% (n=3); one death was due to progression of underlying non-Hodgkin's lymphoma, and the other deaths were related to recurrent thromboembolism and persistent pulmonary hypertension, respectively. Conclusion: Pulmonary endarterectomy, as a curative surgical method for treating chronic thromboernbolic pulmonary hypertension, should be performed aggressively in patients diagnosed with chronic thromboembolic pulmonary hypertension, and an effort should be made to reduce the frequency of perioperative complications and to improve surgical outcomes.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.43-62
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• 2019

At one time, the anomaly detection sector dominated the method of determining whether there was an abnormality based on the statistics derived from specific data. This methodology was possible because the dimension of the data was simple in the past, so the classical statistical method could work effectively. However, as the characteristics of data have changed complexly in the era of big data, it has become more difficult to accurately analyze and predict the data that occurs throughout the industry in the conventional way. Therefore, SVM and Decision Tree based supervised learning algorithms were used. However, there is peculiarity that supervised learning based model can only accurately predict the test data, when the number of classes is equal to the number of normal classes and most of the data generated in the industry has unbalanced data class. Therefore, the predicted results are not always valid when supervised learning model is applied. In order to overcome these drawbacks, many studies now use the unsupervised learning-based model that is not influenced by class distribution, such as autoencoder or generative adversarial networks. In this paper, we propose a method to detect anomalies using generative adversarial networks. AnoGAN, introduced in the study of Thomas et al (2017), is a classification model that performs abnormal detection of medical images. It was composed of a Convolution Neural Net and was used in the field of detection. On the other hand, sequencing data abnormality detection using generative adversarial network is a lack of research papers compared to image data. Of course, in Li et al (2018), a study by Li et al (LSTM), a type of recurrent neural network, has proposed a model to classify the abnormities of numerical sequence data, but it has not been used for categorical sequence data, as well as feature matching method applied by salans et al.(2016). So it suggests that there are a number of studies to be tried on in the ideal classification of sequence data through a generative adversarial Network. In order to learn the sequence data, the structure of the generative adversarial networks is composed of LSTM, and the 2 stacked-LSTM of the generator is composed of 32-dim hidden unit layers and 64-dim hidden unit layers. The LSTM of the discriminator consists of 64-dim hidden unit layer were used. In the process of deriving abnormal scores from existing paper of Anomaly Detection for Sequence data, entropy values of probability of actual data are used in the process of deriving abnormal scores. but in this paper, as mentioned earlier, abnormal scores have been derived by using feature matching techniques. In addition, the process of optimizing latent variables was designed with LSTM to improve model performance. The modified form of generative adversarial model was more accurate in all experiments than the autoencoder in terms of precision and was approximately 7% higher in accuracy. In terms of Robustness, Generative adversarial networks also performed better than autoencoder. Because generative adversarial networks can learn data distribution from real categorical sequence data, Unaffected by a single normal data. But autoencoder is not. Result of Robustness test showed that he accuracy of the autocoder was 92%, the accuracy of the hostile neural network was 96%, and in terms of sensitivity, the autocoder was 40% and the hostile neural network was 51%. In this paper, experiments have also been conducted to show how much performance changes due to differences in the optimization structure of potential variables. As a result, the level of 1% was improved in terms of sensitivity. These results suggest that it presented a new perspective on optimizing latent variable that were relatively insignificant.

• Journal of the Korean Home Economics Association
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• v.25 no.3
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• pp.63-82
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• 1987

This is the forth consecutive study on the 'Standardization of Measurement for Korean Kitchen Work Centers and Cabinets for Future Design Criteria'. The purpose of the present research was (1) to classify homemakers' representative like styles related to the kitchen, (2) to examine homemakers' present concerns on the kitchen space, and (3) to investigate homemakers' desire and preference on the kitchen space. Twenty two hundred homemakers of upper and middle class residing in Seoul, Busan, Daegu, Incheon, Gwangju and Daejeon were selected for the survey and 1,843 among them were used for data analysis. Data were selected for the survey and 1,843 among them were used for data analysis. Data were analyzed using the SAS program package. The statistics used were frequency, percentage, mean, factor analysis, F-test, Duncan's multiple range test, X2-test, cluster analysis. Findings from the research as follows: (1) Four factors were found as indicaters of the life style; values on the household work, desire on social function of the kitchen, degree on cooperation of family members on the household work, and convenient management. It was noticeable that homemakers had positive responses in terms of desire on social function of the kitchen and degree on cooperation of family members on the household work. Homemakers' life styles related to the kitchen space were classified into 6 categories. (2) Relatively a few respondents answered that the kitchens were very well furnished. If, however, the economic conditions become better, substantial number of them wanted to invest for better kitchen following the one for living room. (3) It was found that most respondents preferred the arrangement of space, where dining and kitchen in one space, and a hard wall or soft treatment was between living and dining/kitchen area. (4) Many respondents desired pantry, utility and laundry area be near the kitchen or in the same space with it, thereby forming a utility core in a housing space.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.7
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• pp.183-194
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• 2018

With the rapid development of IoT(Internet of Things) technology, various convenient services such as smart home and smart city have been realized. However, IoT devices in unmanned environments are exposed to various security threats including eavesdropping and data forgery, information leakage due to unauthorized access. To build a secure IoT environment, it is necessary to use proper cryptographic technologies to IoT devices. But, it is impossible to apply the technologies applied in the existing IT environment, due to the limited resources of the IoT devices. In this paper, we survey the classification of IoT devices according to the performance and analyze the security requirements for IoT devices. Also we survey and analyze the use of cryptographic technologies in the current status of IoT open standard platform such as AllJoyn, oneM2M, IoTivity. Based on the research of cryptographic usage, we examine whether each platform satisfies security requirements. Each IoT open platform provides cryptographic technology for supporting security services such as confidentiality, integrity, authentication an authorization. However, resource constrained IoT devices such as blood pressure monitoring sensors are difficult to apply existing cryptographic techniques. Thus, it is necessary to study cryptographic technologies for power-limited and resource constrained IoT devices in unattended environments.

• Journal of the Korean Institute of Rural Architecture
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• v.24 no.4
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• pp.67-75
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• 2022

The purpose of this paper is to provide basic data to Si and Gun preparing for rural agreements in the future through consideration and case analysis for rural conventions, such things as living standards, hierarchical analysis methods, and general rural development projects. In the 1970s, sporadic and one-off projects focused on individual projects were repeatedly carried out in rural areas, which were undergoing dramatic changes in population movement, land use, landscape, economic growth and living. The keyword of the government's policy has changed to a way that existing rural development projects are planned and promoted by local governments themselves in conjunction with the issue of autonomy and decentralization. In addition, with the introduction of Rural Convention, the central and local governments are striving to achieve common policy goals. However, due to the lack of understanding of the Rural Convention introduced as a pilot project in 2020, the lack of living areas setting-standards, unclear classification of hierarchical structure, and excessive goal consciousness for general agricultural and fishing village development projects remain, fading the original purpose of the Rural Convention. Therefore, this study analyzed the seven reports of the Gyeongsang region selected in the 2021 Rural Convention to identify the characteristics of living area, hierarchical structure analysis, and detailed projects (rural center revitalization project, basic living base development project) and provided them as basic data. As a result of the study, first, according to the results of the hierarchical structure analysis, the first class was derived from 6 out of 7 Si and Gun. This is judged to be the result of the current rural population, social, and economic problems. Second, according to the results of the division of living areas, it was confirmed that except for one local government in seven cities and counties, the remaining six local governments were divided into three single living areas and three two living areas. This is the result obtained through a comprehensive review by overlapping the results of various analyses such as hierarchical analysis and resident surveys and OD data, and shows a different form from the existing upper or related plans. It is judged that this is the result of including qualitative contents such as residents' opinions along with various analyses when determining the living area. Third, the proportion of the budget for rural center revitalization and basic living base development projects to the total project cost subject to the Rural Convention was 59.6%, which was relatively higher than that of other general agricultural and fishing village development projects. It is judged that it is preferred because the unit project cost is relatively high in Si and Gun, and that quantitative results can be visually shown after the project is terminated.