• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1177-1185
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• 2022

The water and sewage system is an infrastructure that provides safe and clean water to people. In particular, since the water and sewage pipelines are buried underground, it is very difficult to detect system defects. For this reason, the diagnosis of pipelines is limited to post-defect detection, such as system diagnosis based on the images taken after taking pictures and videos with cameras and drones inside the pipelines. Therefore, real-time detection technology of pipelines is required. Recently, pipeline diagnosis technology using advanced equipment and artificial intelligence techniques is being developed, but AI-based defect detection technology requires a variety of learning data because the types and numbers of defect data affect the detection performance. Therefore, in this study, various defect scenarios are implemented using 3D printing model to improve the detection performance when detecting defects in pipelines. Afterwards, the collected images are performed to pre-processing such as classification according to the degree of risk and labeling of objects, and real-time defect detection is performed. The proposed technique can provide real-time feedback in the pipeline defect detection process, and it would be minimizing the possibility of missing diagnoses and improve the existing water and sewerage pipe diagnosis processing capability.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.119-129
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• 2023

In many cases, trauma is overcome in a short periodtime, but for some, trauma results in long-term mental health issues such as in the form of post-traumatic stress disorder (PTSD). Natural disasters cause different types and extent of damage, meaning the degree of stress experienced also varies. In the case of damage to a house, the impact can be considerable. Therefore, this study examined the trauma experienced by households whose homes were damaged by natural disasters and to confirm the characteristics of psychological trauma. It was confirmed that traumas was greater when a house was damaged, compared with damage to other types of items. In addition, even in the case of trauma occurring, factors that affect the pattern of change to someone's mental state vary depending on the state's classification. And In addition, health services is significantly analyzed in all variables, and it was considered that the provision of basic services related to safety after a disaster is paramount. However, while psychological counseling has a positive effect on short-term traumas that manifests as anxiety and depression, it has an adverse effect on PTSD because of the depth and complexity of the suffering in PTSD, meaning the type of psychological support needs changing.

• The Journal of Korean Society for School & Community Health Education
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• v.24 no.4
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• pp.39-50
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• 2023

Objectives: This study aimed to provide a scoping review of the impact of COVID-19 on people with disabilities. Methods: PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Group's key questions (PICO) for systematic reviews, a literature search was conducted from January 1, 2020 to June 30, 2023 using the "AND" search formula. The databases used were Korea DB: RISS, SCIENCEON, and KoreaMed, and International DB: PubMed, CINAHL, and Embase. Results: Among a total of 22 selected articles, 4 studies were published in korea journals: 3 were survey studies (75.0%), 1 was an analysis study (25.0%), and 18 studies were published in international journals. Through a literature review, we confirmed the differences in difficulties between PwD (People with Disability) and PwoD (People without Disability) in the COVID-19 situation, differences by disability type, and post-COVID-19 impact. In order to examine this systematically and objectively, the results were examined by dividing them, which are components based on the International Classification of Functioning, Disability and Health (ICF). Conclusion: In order to respond well to crises and establish effective health policies in similar pandemic situations in the future, understanding and exploration of more diverse types and areas of disability are necessary. In addition, the development and application of appropriate health education and health promotion programs for disability type and ICF component area are required. In addition, it is necessary to develop and apply appropriate health education and health promotion programs tailored to the type of disability and ICF component area.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.187-204
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• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.

• KDI Journal of Economic Policy
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• v.12 no.4
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• pp.21-46
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• 1990

This paper, a sequel to Yoo and Lee (1990), attempts to investigate the interindustry determinants of technical efficiency in Korea's manufacturing industries, and also to conduct an exploratory analysis on the stability of technical efficiency over time. The hypotheses set forth in this paper are most found in the existing literature on technical efficiency. They are, however, revised and shed a new light upon, whenever possible, to accommodate any Korea-specific conditions. The set of regressors used in the cross-sectional analysis are chosen and the hypotheses are posed in such a way that our result can be made comparable to those of similar studies conducted for the U.S. and Japan by Caves and Barton (1990) and Uekusa and Torii (1987), respectively. It is interesting to observe a certain degree of similarity as well as differentiation between the cross-section evidence on Korea's manufacturing industries and that on the U.S. and Japanese industries. As for the similarities, we can find positive and significant effects on technical efficiency of relative size of production and the extent of specialization in production, and negative and significant effect of the variations in capital-labor ratio within industries. The curvature influence of concentration ratio on technical efficiency is also confirmed in the Korean case. There are differences, too. We cannot find any significant effects of capital vintage, R&D and foreign competition on technical efficiency, all of which were shown to be robust determinants of technical efficiency in the U.S. case. We note, however, that the variables measuring capital vintage effect, R&D and the degree of foreign competition in Korean markets are suspected to suffer from serious measurement errors incurred in data collection and/or conversion of industrial classification system into the KSIC (Korea Standard Industrial Classification) system. Thus, we are reluctant to accept the findings on the effects of these variables as definitive conclusions on Korea's industrial organization. Another finding that interests us is that the cross-industry evidence becomes consistently strong when we use the efficiency estimates based on gross output instead of value added, which provides us with an ex post empirical criterion to choose an output measure between the two in estimating the production frontier. We also conduct exploratory analyses on the stability of the estimates of technical efficiency in Korea's manufacturing industries. Though the method of testing stability employed in this paper is never a complete one, we cannot find strong evidence that our efficiency estimates are stable over time. The outcome is both surprising and disappointing. We can also show that the instability of technical efficiency over time is partly explained by the way we constructed our measures of technical efficiency. To the extent that our efficiency estimates depend on the shape of the empirical distribution of plants in the input-output space, any movements of the production frontier over time are not reflected in the estimates, and possibilities exist of associating a higher level of technical efficiency with a downward movement of the production frontier over time, and so on. Thus, we find that efficiency measures that take into account not only the distributional changes, but also the shifts of the production frontier over time, increase the extent of stability, and are more appropriate for use in a dynamic context. The remaining portion of the instability of technical efficiency over time is not explained satisfactorily in this paper, and future research should address this question.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.4
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• pp.37-52
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• 2022

The purpose of this study is to analyze the demand for cultural ecosystem services in urban forests based on user perception and experience value by using Naver blog posts and LDA topic modeling. Bukhansan National Park was used to analyze and review the feasibility of spatial assessments. Based on the results of topic modeling from blog posts, a review process was conducted considering the relevance of Bukhansan National Park's cultural services and its suitability as a spatial assessment case, and finally, an index for the spatial assessment of urban forest's cultural service was derived. Specifically, 21 topics derived through topic analysis were interpreted, and 13 topics related to cultural ecosystem services were derived based on the MA(Millennium Ecosystem Assessment)'s classification system for ecosystem services. 72.7% of all documents reviewed had data deemed useful for this study. The contents of the topic fell into one of the seven types of cultural services related to "mountainous recreation activities" (23.7%), "indirect use value linked to tourism and convenience facilities" (12.4%), "inspirational activities" (11.2%), "seasonal recreation activities" (6.2%), "natural appreciation and static recreation activities" (3.7%). Next, for the 13 cultural service topics derived from data gathered about Bukhansan National Park, the possibility of spatial assessment of the characteristics of cultural ecosystem services provided by urban forests was reviewed, and a total of 8 cultural service indicators were derived. The MA's cultural service classification system for ecosystem services, which was widely used in previous studies, has limitations in that it does not reflect the actual user demand of urban forests, but it is meaningful in that it categorizes cultural service indicators suitable for domestic circumstances. In addition, the study is significant as it presented a methodology to interpret and derive the demand for cultural services using a large amount of user awareness and experience data.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1211-1224
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• 2023

Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.181-193
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• 2024

The increasing atmospheric imbalance caused by climate change leads to an elevation in precipitation, resulting in a heightened frequency of flooding. Consequently, there is a growing need for technology to detect and monitor these occurrences, especially as the frequency of flooding events rises. To minimize flood damage, continuous monitoring is essential, and flood areas can be detected by the Synthetic Aperture Radar (SAR) imagery, which is not affected by climate conditions. The observed data undergoes a preprocessing step, utilizing a median filter to reduce noise. Classification techniques were employed to classify water bodies and non-water bodies, with the aim of evaluating the effectiveness of each method in flood detection. In this study, the Otsu method and Support Vector Machine (SVM) technique were utilized for the classification of water bodies and non-water bodies. The overall performance of the models was assessed using a Confusion Matrix. The suitability of flood detection was evaluated by comparing the Otsu method, an optimal threshold-based classifier, with SVM, a machine learning technique that minimizes misclassifications through training. The Otsu method demonstrated suitability in delineating boundaries between water and non-water bodies but exhibited a higher rate of misclassifications due to the influence of mixed substances. Conversely, the use of SVM resulted in a lower false positive rate and proved less sensitive to mixed substances. Consequently, SVM exhibited higher accuracy under conditions excluding flooding. While the Otsu method showed slightly higher accuracy in flood conditions compared to SVM, the difference in accuracy was less than 5% (Otsu: 0.93, SVM: 0.90). However, in pre-flooding and post-flooding conditions, the accuracy difference was more than 15%, indicating that SVM is more suitable for water body and flood detection (Otsu: 0.77, SVM: 0.92). Based on the findings of this study, it is anticipated that more accurate detection of water bodies and floods could contribute to minimizing flood-related damages and losses.

• Journal of Chest Surgery
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• v.20 no.2
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• pp.328-341
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• 1987

We reviewed 147 cases of primary carcinoma of the lung between January 1975 and December 1986 at the Thoracic and Cardiovascular Department, Yonsei university College of Medicine, Seoul, Korea. There were 116 males and 31 females with 93.72% ranging in age from 40 to 69 years. The mean age was 61.01 years. To 69 years of age with 61.01 years of mean age. There were 92 [62.59%] cases of squamous cell carcinoma, 29 [19.73%] cases of adenocarcinoma, 8 [5.44%] cases of undifferentiated large cell carcinoma, 8 [5.44%] cases of undifferentiated small cell carcinoma and 10 [6.8%] cases of bronchoalveolar cell carcinoma. 50 [34.01%] patients in stage I and 49 [33.26%] patients in stage II underwent pneumonectomies and lobectomies with a 67.27% rate of resection, where as only 49.12% of stage III patients were resected. Also 7 [30.43%] of the 23 stage IV cases were surgically resected and confirmed stage IV after surgical resection. The actuarial survival rate according to classification are as follows. The one and 3 year survival rate of the patients in stage I were 96% and 84% respectively. The one and `3 year survival rate of the patients in stage II were 100% and 66.6%, whereas the one and 3 year survival rate of the patients in stage III, T3 were 78.57% and 69.84%. The survival rates of patients in stage I, II, III T3 were better than those of the other stages. There were significant differences in observed survival for patients with stage II as compared with the patients with stage Ill, T3. [p=0.0005]. An aggressive surgical approach still offered the greatest chance for long-term survival even in stage Ill, T3. The survival rate in patients with resectable cases including stage III, T3 might be improved with an aggressive surgical approach. The one and 3 year survival rates of patients in stage III, N2 were 56.67% and 43.7 I%. The one and 3 year survival rates of patients in stage IV were 21.43% and 3.57%. Patients in stage III, N2 or IV had markedly decreased survival rates. When the carcinoma cell type was the basis for the determination of rate of survival, the result were as follows; The one, 3 and 5 year survival rates of squamous cell carcinoma were 78.33%, 60.19%, and 57.32%, and the one and 3 year survival rates of adenocarcinoma were 55.56% and 44.49%. The survival rates of large cell carcinoma were 66.67%, and 44.45%, at one, three and five years respectively. The one and 3 year survival rates of bronchoalveolar cell carcinoma were 71.43% and 47.62%, the one, 3 and 5 year survival rates of small cell carcinoma were 40%, 20% and 20%. The survival rate of squamous cell carcinoma was better than that of other cell carcinomas, the survival rate of small cell carcinoma was the worst. The operative mortality rate was 1.36%. There were 10 cases of post-operative complications including 2 cases of bleeding which required further surgery, 2 cases of wound infection, and 4 cases of empyema thoracis. The length of survival of three of the empyema thoracis cases was 16, 98 and 108 months respectively, Four male patients all older than 47 years survived more than 9 years, post surgery, although one developed empyema thoracis. These four cases were initially classified as 2 cases of stage I and one each of stage II and stage III, T3. We have concluded that the survival rates of patients in stages I, II and III, T3 were improved after complete surgical resection.

• Radiation Oncology Journal
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• v.15 no.2
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• pp.129-136
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• 1997

Purpose : We analyzed the survival and failure patterns of cervix cancer patients treated with irradiation alone to evaluate our treatment method and to compare with the others Methods and Materials : Two hundred and twenty cervical cancer patients, Stage IB, II A, and II B who completed the planned treatment between Mar 1987 and December 1991 were analyzed retrospectively. The Stage IB patients were restaged to the Stage IB1 and IB2 by the recently revised FIGO classification, Patients were treated with a combination of external irradiation and the intracavitary brachytherapy Determination of the tumor control was done at the time of 6 months Postirradiation. The follow-up time was ranged from 3 to 115 months and the mean was 62 months and the follow-up rate was $93.6\%$(206/220) Results : The overall 5-year survival rate of Stage IB1 (N=50), IB2(N: 15). II A(N=58), and II B(N=97) was $94\%,\;87\%,\;69\%,\;and\;56\%$. respectively. In the univariate analysis of prognostic factors, stage(0.00), initial Hg level (P=0.00), initial TA-4(tumor-associated) antigen level(p= 0.02), initial CEA level(p=0.02), barrel-shaped tumor(p=0.02), whole cervical involvement (0.00), pelvic tyrnphadenopathy(LAP) in CT(p=0.04), and Post-irradiation adiuvant chemotherapy(P=0.00) were statistically significant in survival analysis. In a while multivariate analysis showed that the stage was the most powerful Prognostic indicator and the Post-irradiation chemotherapy factor also showed the statistical significance. The overall local control rate was $81\%$ and by the stage, $100\%$ in Stage IBI, $86.7\%$ in Stage IBS, $84.5\%$ in Stage IIA, and $68.1\%$ in Stage IIB, respectively The overall tumor recurrence rate was $15.5\%$(27/174) and by the stage, $8\%$(4/50) in Stage IB1, $0\%$(0/l3) in Stage IB2, $22.4\%$(l1/49) in Stage II A, and $19.4\%$(12/62) in Stage II B, respectively. Conclusions : We obtained the similar treatment results to the other's ones in early stage cervical cancer patients. But in Stage II B, the local control rate was lower than that of the other institutes and also the survival was poorer. So it seems to be necessary to reevaluate the treatment method in advanced cervical cancer patients.