• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.211-228
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• 2023

Ground-penetrating radar (GPR) surveys are commonly used to monitor embankments, which is a nondestructive geophysical method. The results of GPR surveys can be complex, depending on the situation, and data processing and interpretation are subject to expert experiences, potentially resulting in false detection. Additionally, this process is time-intensive. Consequently, various studies have been undertaken to detect cavities in GPR survey data using deep learning methods. Deep-learning-based approaches require abundant data for training, but GPR field survey data are often scarce due to cost and other factors constaining field studies. Therefore, in this study, a deep- learning-based model was developed for embankment GPR survey cavity detection using data augmentation strategies. A dataset was constructed by collecting survey data over several years from the same embankment. A you look only once (YOLO) model, commonly used in computer vision for object detection, was employed for this purpose. By comparing and analyzing various strategies, the optimal data augmentation approach was determined. After initial model development, a stepwise process was employed, including box clustering, transfer learning, self-ensemble, and model ensemble techniques, to enhance the final model performance. The model performance was evaluated, with the results demonstrating its effectiveness in detecting cavities in embankment GPR survey data.

• Journal of the Korean Society of Radiology
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• v.81 no.2
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• pp.310-323
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• 2020

To treat congenital heart disease, it is important to understand the anatomical structure correctly. Three-dimensional (3D) printed models of the heart effectively demonstrate the structural features of congenital heart disease. Occasionally, the exact characteristics of complex cardiac malformations are difficult to identify on conventional computed tomography, magnetic resonance imaging, and echocardiography, and the use of 3D printed models can help overcome their limitations. Recently, 3D printed models have been used for congenital heart disease education, preoperative simulation, and decision-making processes. In addition, we will pave the way for the development of this technology in the future and discuss various aspects of its use, such as the development of surgical techniques and training of cardiac surgeons.

• Korean Journal of Radiology
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• v.24 no.4
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• pp.294-304
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• 2023

Objective: We aimed to investigate whether image standardization using deep learning-based computed tomography (CT) image conversion would improve the performance of deep learning-based automated hepatic segmentation across various reconstruction methods. Materials and Methods: We collected contrast-enhanced dual-energy CT of the abdomen that was obtained using various reconstruction methods, including filtered back projection, iterative reconstruction, optimum contrast, and monoenergetic images with 40, 60, and 80 keV. A deep learning based image conversion algorithm was developed to standardize the CT images using 142 CT examinations (128 for training and 14 for tuning). A separate set of 43 CT examinations from 42 patients (mean age, 10.1 years) was used as the test data. A commercial software program (MEDIP PRO v2.0.0.0, MEDICALIP Co. Ltd.) based on 2D U-NET was used to create liver segmentation masks with liver volume. The original 80 keV images were used as the ground truth. We used the paired t-test to compare the segmentation performance in the Dice similarity coefficient (DSC) and difference ratio of the liver volume relative to the ground truth volume before and after image standardization. The concordance correlation coefficient (CCC) was used to assess the agreement between the segmented liver volume and ground-truth volume. Results: The original CT images showed variable and poor segmentation performances. The standardized images achieved significantly higher DSCs for liver segmentation than the original images (DSC [original, 5.40%-91.27%] vs. [standardized, 93.16%-96.74%], all P < 0.001). The difference ratio of liver volume also decreased significantly after image conversion (original, 9.84%-91.37% vs. standardized, 1.99%-4.41%). In all protocols, CCCs improved after image conversion (original, -0.006-0.964 vs. standardized, 0.990-0.998). Conclusion: Deep learning-based CT image standardization can improve the performance of automated hepatic segmentation using CT images reconstructed using various methods. Deep learning-based CT image conversion may have the potential to improve the generalizability of the segmentation network.

• Journal of The Korean Association For Science Education
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• v.29 no.8
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• pp.934-950
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• 2009

This study attempts to identify the relationship between students' images of science and science learning, and their career choices. A total of 163 students (seventh graders) from three different middle schools participated in this study. Students' images of science and science learning were investigated using the Draw-A-Scientist Test (DAST) and the Draw-A-Science-Learner Test (DASLT), respectively. Then, students' drawings were analyzed using the Draw-A-Scientist Test Checklist (DAST-C) and the Draw-A-Science-Learner Test Checklist (DASLT-C). The relationship between each element composing the students' images and their career choices were analyzed. Among several elements constituting the students' image of science, 'expression,' 'lab coat,' 'oddity,' 'knowledge symbol,' 'technology symbol,' 'co-work,' 'danger,' and 'STS' showed significant differences between students who chose a science-related career and students who did not. It was also revealed that the following elements - 'expression,' 'learning type,' 'inquiry symbol,' and 'learning place' - were more significantly associated with a science-related career choice compared to other elements consisting of an image of science learning.

• The Korean Journal of Air & Space Law and Policy
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• v.30 no.2
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• pp.403-425
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• 2015

The Chicago Convention and Annexes have become the basis of aviation safety regulations for every contracting state. Generally, the State's aviation safety regulations refer to the Standards and Recommended Practices(SARPs) provided in the Annexes of the Chicago Convention. In order to properly reflect international aviation safety regulations, constant studies of the aviation fields are of paramount importance. This Paper is intended to identify the main differences between korean and foreign regulation and suggest a few amendment proposals on Mixed-fleet Flying(at or more two aircraft type operation) of flight crew. Comparing with these regulations, the korean regulations and implementations have some insufficiency points. I suggest some amendment proposals of korean regulations concerning Mixed-fleet Flying that flight crew operate aircraft of different types. Basically an operator shall not assign a pilot-in-command or a co-pilot to operate at the flight controls of a type of airplane during take-off and landing unless that pilot has operated the flight controls during at least three take-offs and landings within the preceding 90 days on the same type of airplane or in a flight simulator. Also, flight crew members are familiarized with the significant differences in equipment and/or procedures between concurrently operated types. An operator shall ensure that piloting technique and the ability to execute emergency procedures is checked in such a way as to demonstrate the pilot's competence on each type or variant of a type of airplane. Proficiency check shall be performed periodically. When an operator schedules flight crew on different types of airplanes with similar characteristics in terms of operating procedures, systems and handling, the State shall decide the requirements for each type of airplane can be combined. In conclusion, it is necessary for flight crew members to remain concurrently qualified to operate multiple types. The operator shall have a program to include, as a minimum, required differences training between types and qualification to maintain currency on each type. If the Operator utilizes flight crew members to concurrently operate aircraft of different types, the operator shall have qualification processes approved or accepted by the State. If applicable, the qualification curriculum as defined in the operator's Advanced Qualification Program could be applied. Flight crew members are familiarized with the significant differences in equipment and/or procedures between concurrently operated types. The difference among different types of airpcrafts decrease and standards for these airpcrafts can be applied increasingly because function and performance have been improved by aircraft manufacture company in accordance to basic aircraft system in terms of developing new aircrafts for flight standard procedure and safety of flight. Also, it becomes more necessary for flight crews to control multi aircraft types due to various aviation business and activation of leisure business. Nevertheless, in terms of flight crew training and qualification program, there are no regulations in Korea to be applied to new aircraft types differently in accordance with different levels. In addition, it has no choice different programs based on different levels because there are not provisions to restrict or limit and specific standards to operate at or more than two aircraft types for flight safety. Therefore the aviation authority introduce Flight Standardization and/or Operational Evaluation Board in order to analysis differences among aircraft types. In addition to that, the aviation authority should also improve standard flight evaluation and qualification system among different aircraft types for flight crews to apply reasonable training and qualification efficiently. For all the issue mentioned above, I have studied the ICAO SARPs and some state's regulation concerning operating aircraft of different types(Mixed-fleet flying), and suggested some proposals on the different aircraft type operation as an example of comprehensive problem solving. I hope that this paper is 1) to help understanding about the international issue, 2) to help the improvement of korean aviation regulations, 3) to help compliance with international standards and to contribute to the promotion of aviation safety, in addition.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.131-150
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• 2015

Omission of noun phrases for obligatory cases is a common phenomenon in sentences of Korean and Japanese, which is not observed in English. When an argument of a predicate can be filled with a noun phrase co-referential with the title, the argument is more easily omitted in Encyclopedia texts. The omitted noun phrase is called a zero anaphor or zero pronoun. Encyclopedias like Wikipedia are major source for information extraction by intelligent application systems such as information retrieval and question answering systems. However, omission of noun phrases makes the quality of information extraction poor. This paper deals with the problem of developing a system that can restore omitted noun phrases in encyclopedia documents. The problem that our system deals with is almost similar to zero anaphora resolution which is one of the important problems in natural language processing. A noun phrase existing in the text that can be used for restoration is called an antecedent. An antecedent must be co-referential with the zero anaphor. While the candidates for the antecedent are only noun phrases in the same text in case of zero anaphora resolution, the title is also a candidate in our problem. In our system, the first stage is in charge of detecting the zero anaphor. In the second stage, antecedent search is carried out by considering the candidates. If antecedent search fails, an attempt made, in the third stage, to use the title as the antecedent. The main characteristic of our system is to make use of a structural SVM for finding the antecedent. The noun phrases in the text that appear before the position of zero anaphor comprise the search space. The main technique used in the methods proposed in previous research works is to perform binary classification for all the noun phrases in the search space. The noun phrase classified to be an antecedent with highest confidence is selected as the antecedent. However, we propose in this paper that antecedent search is viewed as the problem of assigning the antecedent indicator labels to a sequence of noun phrases. In other words, sequence labeling is employed in antecedent search in the text. We are the first to suggest this idea. To perform sequence labeling, we suggest to use a structural SVM which receives a sequence of noun phrases as input and returns the sequence of labels as output. An output label takes one of two values: one indicating that the corresponding noun phrase is the antecedent and the other indicating that it is not. The structural SVM we used is based on the modified Pegasos algorithm which exploits a subgradient descent methodology used for optimization problems. To train and test our system we selected a set of Wikipedia texts and constructed the annotated corpus in which gold-standard answers are provided such as zero anaphors and their possible antecedents. Training examples are prepared using the annotated corpus and used to train the SVMs and test the system. For zero anaphor detection, sentences are parsed by a syntactic analyzer and subject or object cases omitted are identified. Thus performance of our system is dependent on that of the syntactic analyzer, which is a limitation of our system. When an antecedent is not found in the text, our system tries to use the title to restore the zero anaphor. This is based on binary classification using the regular SVM. The experiment showed that our system's performance is F1 = 68.58%. This means that state-of-the-art system can be developed with our technique. It is expected that future work that enables the system to utilize semantic information can lead to a significant performance improvement.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.149-155
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• 2021

Early warning systems for weather risk management in the agricultural sector have been developed to predict potential wind damage to crops. These systems take into account the daily maximum wind speed to determine the critical wind speed that causes fruit drops and provide the weather risk information to farmers. In an effort to increase the accuracy of wind risk predictions, an artificial neural network for binary classification was implemented. In the present study, the daily wind speed and other weather data, which were measured at weather stations at sites of interest in Jeollabuk-do and Jeollanam-do as well as Gyeongsangbuk- do and part of Gyeongsangnam- do provinces in 2019, were used for training the neural network. These weather stations include 210 synoptic and automated weather stations operated by the Korean Meteorological Administration (KMA). The wind speed data collected at the same locations between January 1 and December 12, 2020 were used to validate the neural network model. The data collected from December 13, 2020 to February 18, 2021 were used to evaluate the wind risk prediction performance before and after the use of the artificial neural network. The critical wind speed of damage risk was determined to be 11 m/s, which is the wind speed reported to cause fruit drops and damages. Furthermore, the maximum wind speeds were expressed using Weibull distribution probability density function for warning of wind damage. It was found that the accuracy of wind damage risk prediction was improved from 65.36% to 93.62% after re-classification using the artificial neural network. Nevertheless, the error rate also increased from 13.46% to 37.64%, as well. It is likely that the machine learning approach used in the present study would benefit case studies where no prediction by risk warning systems becomes a relatively serious issue.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.32 no.4
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• pp.24-36
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• 2014

The result of the research conducted for the purpose of investigating the semantic value and the layout of the Cheongryu Gugok of Dorimsa Valley, which exhibits a high level of completeness and scenic preservation value among the three gugoks distributed in the area around Mt. Dongak of Gogseong is as follows.4) The area around Cheongryu Gugok shows a case where the gugok culture, which has been enjoyed as a model of the Neo-Confucianism culture and bedrock scenery, such as waterfall, riverside, pond, and flatland, following the beautiful valley, has been actually substituted, and is an outstanding scenery site as stated in a local map of Gokseong-hyeon in 1872 as "Samnam Jeil Amban Gyeryu Cheongryu-dong(三南第一巖盤溪流 淸流洞: Cheongryu-dong, the best rock mooring in the Samnam area)." Cheongryu Gugok, which is differentiated through the seasonal scenery and epigrams established on both land route and waterway, was probably established by the lead of Sun-tae Jeong(丁舜泰, ?~1916) and Byeong-sun Cho(曺秉順, 1876~1921) before 1916 during the Japanese colonization period. However, based on the fact that a number of Janggugiso of ancient sages, such as political activists, Buddhist leaders, and Neo-Confucian scholars, have been established, it is presumed to have been utilized as a hermit site and scenery site visited by masters from long ago. Cheongryu Gugok, which is formed on the rock floor of the bed rock of Dorimsa Valley, is formed in a total length of 1.2km and average gok(曲) length of 149m on a mountain type stream, which appears to be shorter compared to other gugoks in Korea. The rock writings of the three gugoks in Mt. Dongak, such as Cheongryu Gugok, which was the only one verified in the Jeonnam area, total 165 in number, which is determined to be the assembly place for the highest number of rock writings in the nation. In particular, a result of analyzing the rock writings in Cheongryu Gugok totaling 112 places showed 49pieces(43.8%) with the meaning of 'moral training' in epigram, 21pieces (18.8%) of human life, 16pieces(14.2%) of seasonal scenery, and 12pieces(10.6%) of Janggugiso such as Jangguchur, and the ratio occupied by poem verses appeared to be six cases(3.6%). Sweyeonmun(鎖烟門), which was the first gok of land route, and Jesiinganbyeolyucheon(除是人間別有天) which was the ninth gok of the waterway, corresponds to the Hongdanyeonse(虹斷烟鎖) of the first gok and Jesiinganbyeolyucheon of the ninth gok established in Jaecheon, Chungbuk by Se-hwa Park(朴世和, 1834~1910), which is inferred to be the name of Gugok having the same origin. In addition, the Daeeunbyeong(大隱屛) of the sixth gok. of land route corresponds to the Chu Hsi's Wuyi-Gugok of the seventh gok, which is acknowledged as the basis for Gugok Wollim, and the rock writings and stonework of 'Amseojae(巖棲齋)' and 'Pogyeongjae(抱經齋)' between the seventh gok and eighth gok is a trace comparable with Wuyi Jeongsa(武夷精舍) placed below Wuyi Gugok Eunbyeon-bong, which is understood to be the activity base of Cheongryu-dong of the Giho Sarim(畿湖士林). The rock writings in the Mt. Dongak area, including famous sayings by masters such as Sunsaeuhje(鮮史御帝, Emperor Gojong), Bogahyowoo(保家孝友, Emperor Gojong), Manchunmungywol(萬川明月, King Joengjo), Biryeobudong(非禮不動, Chongzhen Emperor of the Ming Dynasty)', Samusa(思無邪, Euijong of the Ming Dynasty), Baksechungpwoong(百世淸風, Chu Hsi), and Chungryususuk-Dongakpungkyung(淸流水石 動樂風景, Heungseon Daewongun) can be said to be a repository of semantic symbolic cultural scenery, instead of only expressing Confucian aesthetics. In addition, Cheongryu Gugok is noticeable with its feature as a cluster of cultural scenery of the three religions of Confucian-Buddhism-Taoism, where the Confucianism value system, Buddhist concept, and Taoist concept co-exists for mind training and cultivation. Cheongryu Gugok has a semantic feature and spatial character as a basis for history and cultural struggle for the Anti-Japan spirit that has been conceived during the process of establishing and utilizing the spirit of the learning, loyalty for the Emperor and expulsion of barbarians, and inspiration of Anti-Japan force, by inheriting the sense of Dotong(道統) of Neo-Confucianism by the Confucian scholar class at the end of the Joseon era that is represented by Ik-hyun Choi(崔益鉉, 1833~1906), Woo Jeon(田愚, 1841~1922), Woo-man Gi(奇宇萬, 1846~1916), Byung-sun Song(宋秉璿, 1836~1905), and Hyeon Hwang(黃玹, 1855~1910).

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• 대한공업교육학회지
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• v.36 no.2
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• pp.131-150
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• 2011

The purpose of this study vocational courses in general high schools in each city in order to operate efficiently. Provinces operating status and the general high school vocational courses through the regular high school vocational courses siltae analysis to identify operational problems, and that is to derive ways to improve. Operating in the desired direction, the typical high school vocational courses ilbango select students that meet the purpose of operating as one that students admit you need the correct promotion and career guidance and vocational courses ilbango teachers of vocational courses is operating correctly recognize the purpose and students with career guidance and vocational courses so that you can operate effectively at: Provincial Office-wide need to conduct a systematic study. Vocational courses also target students ilbango sosokgyo (wonjeokgyo) to be completed in the course stated in the plan for the school and the need to practice, and professional students ilbango by configuring a separate class is most preferable to operate. If the person is prime target, with each region run by creating a class needs to definitely consider. Entrusted to the agency's key performance improvements in order to improve the employment rate in the direction of promotional materials for the students selected to take advantage of college enrollment than the employment data for the students and their parents ilbango vocational courses for the purpose and intent is necessary to provide accurate information In addition, the employment rate is relatively low industrial (information) to install the school department employment, and employment representatives (industry-academia co-coordinator), and by placing career paths and industries to ensure the needs of industry, including working conditions and students who wish adjusting to the role, and industrial college (2 years), industrial (information) through the school's agreement to the aggressive promotional schemes seonchwieop hujinhak. Getting the need to encourage. Vocational courses ilbango in the new and the abolition, rather than the case of some popular course when you are away from work and there, so if the course-changing industry, new or repealed to reflect the demands of social work and careful review of how to connect carefully to decide by. Commissioned a systematic quality management in education, in terms of industry (information) schools and public vocational training institutions or private vocational school is better than school. However, 16 cities across the country. Also only five of the major cities around the school has industry information. Ilbango vocational courses at the expected continued demand. Degrees, the operation in terms of comparative advantage in many ways the school's new industry information is necessary to consider.