• Tunnel and Underground Space
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• v.30 no.5
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• pp.462-472
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• 2020

Rock classification is fundamental discipline of exploring geological and geotechnical features in a site, which, however, may not be easy works because of high diversity of rock shape and color according to its origin, geological history and so on. With the great success of convolutional neural networks (CNN) in many different image-based classification tasks, there has been increasing interest in taking advantage of CNN to classify geological material. In this study, a feasibility of the deep CNN is investigated for automatically and accurately identifying rock types, focusing on the condition of various shapes and colors even in the same rock type. It can be further developed to a mobile application for assisting geologist in classifying rocks in fieldwork. The structure of CNN model used in this study is based on a deep residual neural network (ResNet), which is an ultra-deep CNN using in object detection and classification. The proposed CNN was trained on 10 typical rock types with an overall accuracy of 84% on the test set. The result demonstrates that the proposed approach is not only able to classify rock type using images, but also represents an improvement as taking highly diverse rock image dataset as input.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1219-1229
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• 1999

일반적으로 AND, OR, NOT과 같은 연산자를 사용하는 불리언 질의는 사용자의 검색의도를 정확하게 표현할 수 있기 때문에 검색 전문가들은 불리언 질의를 사용하여 높은 검색성능을 얻는다고 알려져 있지만, 일반 사용자는 자신이 원하는 정보를 불리언 형태로 표현하는데 익숙하지 않다. 본 논문에서는 검색성능의 향상과 사용자 편의성을 동시에 만족하기 위하여 사용자의 자연어 질의를 확장 불리언 질의로 자동 변환하는 방법론을 제안한다. 먼저 자연어 질의를 범주문법에 기반한 구문분석을 수행하여 구문트리를 생성하고 연산자 및 키워드 정보를 추출하여 구문트리를 간략화한다. 다음으로 간략화된 구문트리로부터 명사구를 합성하고 키워드들에 대한 가중치를 부여한 후 불리언 질의를 생성하여 검색을 수행한다. 또한 구문분석의 오류로 인한 검색성능 저하를 최소화하기 위하여 상위 N개 구문트리에 대해 각각 불리언 질의를 생성하여 검색하는 N-BEST average 방법을 제안하였다. 정보검색 실험용 데이타 모음인 KTSET2.0으로 실험한 결과 제안된 방법은 수동으로 추출한 불리언 질의보다 8% 더 우수한 성능을 보였고, 기존의 벡터공간 모델에 기반한 자연어질의 시스템에 비해 23% 성능향상을 보였다. Abstract There have been a considerable evidence that trained users can achieve a good search effectiveness through a boolean query because a structural boolean query containing operators such as AND, OR, and NOT can make a more accurate representation of user's information need. However, it is not easy for ordinary users to construct a boolean query using appropriate boolean operators. In this paper, we propose a boolean query formulation method that automatically transforms a user's natural language query into a extended boolean query for both effectiveness and user convenience. First, a user's natural language query is syntactically analyzed using KCCG(Korean Combinatory Categorial Grammar) parser and resulting syntactic trees are structurally simplified using a tree-simplifying mechanism in order to catch the logical relationships between keywords. Next, in a simplified tree, plausible noun phrases are identified and added into the same tree as new additional keywords. Finally, a simplified syntactic tree is automatically converted into a boolean query using some mapping rules and linguistic heuristics. We also propose an N-BEST average method that uses top N syntactic trees to compensate for bad effects of single incorrect top syntactic tree. In experiments using KTSET2.0, we showed that a proposed method outperformed a traditional vector space model by 23%, and surprisingly manually constructed boolean queries by 8%.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.4
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• pp.129-136
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• 2020

PM2.5 which is a very tiny air particulate matter even smaller than PM10 has been issued in the environmental problem. Since PM2.5 can cause eye diseases or respiratory problems and infiltrate even deep blood vessels in the brain, it is important to predict PM2.5. However, it is difficult to predict PM2.5 because there is no clear explanation yet regarding the creation and the movement of PM2.5. Thus, prediction methods which not only predict PM2.5 accurately but also have the interpretability of the result are needed. To predict hourly PM2.5 of Seoul city, we propose a method using random forest with the adjusted bootstrap number from the time series ground data preprocessed on different sources. With this method, the prediction model can be trained uniformly on hourly information and the result has the interpretability. To evaluate the prediction performance, we conducted comparative experiments. As a result, the performance of the proposed method was superior against other models in all labels. Also, the proposed method showed the importance of the variables regarding the creation of PM2.5 and the effect of China.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.3
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• pp.179-188
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• 2012

Performance analyses of vertical breakwaters were conducted for fictitiously designed breakwaters for various water depths to analyze the influence of climate change on the structures. The performance-based design method considering sea level rise and wave height increase due to climate change was used for the performance analysis. One of the problems of the performance-based design method is the large calculation time of wave transformation. To overcome this problem, the SWAN model combined with artificial neural network was used. The significant wave height and principal wave direction at the breakwater site are quickly calculated by using a trained neural network with inputs of deepwater significant wave height and principal wave direction, and tidal level. In general, structural stability becomes low due to climate change impacts, but the trend of stability is different depending on water depth. Outside surf zone, the influence of wave height increase becomes more significant, while that of sea level rise becomes negligible, as water depth increases. Inside surf zone, the influence of both wave height increase and sea level rise diminishes as water depth decreases, but the influence of wave height increase is greater than that of sea level rise. Reinforcement and maintenance policies for vertical breakwaters should be established with consideration of these results.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.6
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• pp.689-695
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• 2015

The offshore plant crews that were commissioned in the commercial startup phase boarded the offshore plant in two shifts until the end of the project. The crews who were hired by the owner side stayed in the original offshore plant during the project. However, most of the offshore plant commissioned members who were dispatched from the shipyard were accommodated in the offshore accommodation barge. For this reason, they were exposed to many accidents since there are a lot of people staying in a small space. This study suggested a method for improving survival rate at offshore accommodation barge in terms of life safety. It is assumed that the fire accident among unfortunate events which take place in the offshore accommodation barge mainly occurred. So, this study analyzed the safety evacuation for offshore plant employees using fire simulation model based on both domestic and international law criteria. In particular, When fire occurs in the offshore accommodation barge, the periodically well trained crews are followed safety evacuation procedure. whereas many employees who have different background such as various occupations, cultural differences, races and nationality can be commissioned with improper evacuation behaviors. As a result, the risk will be greater than normal situation due to these inappropriate behaviors. Therefore, This study analyzed the Required Safe Escape Time (RSET) and Available Safe Escape Time (ASET). Also it was suggested the improvement of structure design and additional arrangement of safety equipment to improve the survival rate of the residents in offshore accommodation barge.

• Journal of the Ergonomics Society of Korea
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• v.30 no.5
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• pp.637-644
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• 2011

Objective & Background: When applying various evaluation tools that analyze work posture risk through observation, accurate measurement of body flexion angle is very important. Method: This study investigated differences and appropriateness of 5 different existing reference points commonly used in the analysis of the work posture. Twenty five ergonomist and trained professionals were participated in this study. A Same flexion angle was utilized for the evaluation of risk assessment of musculoskeletal disorders using five different reference points to investigate the degree of difference between them. To investigate how different the observers' preferred flexion angle measuring methods were compared to the ISO 11226 Reference Posture, a virtual body model was constructed using the Poser 6.0 program. Six types of body flexion postures were constructed, and since neck flexion differs according to body angle, five types of neck flexion postures were constructed with the trunk bending $20^{\circ}$ forward, making up a total of 30 virtual flexion postures. Results: Results showed that the observers used personally preferred reference points instead of reference points recommend in the evaluation tools. Also the results revealed the their seems to be 6 types of flexion angle for the trunk and 11 types of measurement methods for the neck flexion angle in the form of personally preferred reference points. The results showed that a mean difference of $14^{\circ}$($4{\sim}23^{\circ}$) occurred in the trunk, and a mean difference of $20^{\circ}$($-8{\sim}51^{\circ}$) occurred in the neck. To increase accuracy when using the 5 evaluation tools in combination, the ISO 11226 standards, observers' preferred flexion posture standards, and common flexion posture standards of the evaluation tools were compared with the reference points of the 5 evaluation tools. Results showed considerable variance in angle difference for each evaluation tool. Conclusion: According to the results of this study, considering the angle difference between the flexion angle reference points of the evaluation tool and the reference points selected by the observers, it is concluded that instead of personally preferred reference points, the standardized reference points to enhance the accuracy and the objectivity. Application: The result of this study can be used as reference guide to develop the standardized reference point in the future.

• Korean Business Review
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• v.19 no.2
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• pp.207-230
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• 2006

The study which it sees probably is the tourist' from the tourist resort, a emotional response and the change of stay hour and the follows in crowding perceived degree and it examines it does. In order to achieve the purpose of this study, carried out literature study of a related field and set up a study model. We used one method. The first method was directly distributing questionnaires to tourist' by use of one researcher who has been trained in tourist site, in order to confirm hypothesis established according to a theoretical background. And as the site of study, chose Mureung Valley which are located in the East Sea region which is one of the largest domestic vacation destinations. Through these methods, we were able to obtain participation of 450 people from across the country. Using 408 responses(42 responses removed). we derived statistics by means of Win SPSS Version 10.0 statistics program package. The analysis results ara as follows: First, Perceived Crowding affects tourists' Emotional Response and the Stay hour change. Specially, perceived Crowding is from in the Emotional Response factor it is joyful with there is relationship of excitation relationship effect. Second, There is relationship of effect even to sentimental reaction and stay hour change. This also is from in the Emotional Response factor it is joyful with there is relationship of excitation relationship effect. Finally, we discuss the results of analysis and suggest research limitation and future and future study.

• Journal of the Korea Society of Computer and Information
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• v.20 no.5
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• pp.53-63
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• 2015

Singing voice synthesis is the generation of a song using a computer given its lyrics and musical notes. Hidden Markov models (HMM) have been proved to be the models of choice for text to speech synthesis. HMMs have also been used for singing voice synthesis research, however, a huge database is needed for the training of HMMs for singing voice synthesis. And commercially available singing voice synthesis systems which use the piano roll music notation, needs to adopt the easy to read standard music notation which make it suitable for singing learning applications. To overcome this problem, we use a speech database for training context dependent HMMs, to be used for singing voice synthesis. Pitch and duration control methods have been devised to modify the parameters of the HMMs trained on speech, to be used as the synthesis units for the singing voice. This work describes a singing voice synthesis system which uses a MusicXML based music score editor as the front-end interface for entry of the notes and lyrics to be synthesized and a hidden Markov model based text to speech synthesis system as the back-end synthesizer. A perceptual test shows the feasibility of our proposed system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.1
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• pp.19-29
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• 2003

This paper presents a novel hybrid classifier for face recognition with artificially generated virtual training samples. We utilize both the nearest neighbor approach in feature angle space and a connectionist model to obtain a synergy effect by combining the results of two heterogeneous classifiers. First, a classifier called the nearest feature angle (NFA), based on angular information, finds the most similar feature to the query from a given training set. Second, a classifier has been developed based on the recall of stored frontal projection of the query feature. It uses a frontal recall network (FRN) that finds the most similar frontal one among the stored frontal feature set. For FRN, we used an ensemble neural network consisting of multiple multiplayer perceptrons (MLPs), each of which is trained independently to enhance generalization capability. Further, both classifiers used the virtual training set generated adaptively, according to the spatial distribution of each person's training samples. Finally, the results of the two classifiers are combined to comprise the best matching class, and a corresponding similarit measure is used to make the final decision. The proposed classifier achieved an average classification rate of 96.33% against a large group of different test sets of images, and its average error rate is 61.5% that of the nearest feature line (NFL) method, and achieves a more robust classification performance.

• Korean Journal of Childcare and Education
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• v.10 no.6
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• pp.25-42
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• 2014

The primary purpose of this study was to examine the variables as related to self-determination in preschoolers. In order to meet the purpose of this study preschoolers' self-determination, their playfulness, self-regulation, and self-esteem as well as goodness of fit between mother and child were taken into account as study variables of interest. Furthermore, the mediating effect of preschoolers' self-esteem in the effects of study variables on their self-esteem was examined. Three hundred thirty seven preschooler(aged 6-7 years old)-mother pairs who attended public subsidized child care facilities, located in Seoul and Gyeongi province were sampled. The data were obtained from mother-filled surveys, and on-site observations from both head teachers of the children as well as trained researchers. The obtained data were analyzed by using SPSS 21.0, and structural equation model (SEM) was tested with AMOS 21.0. The main results of this study were in the following. First, it was proven that self-determination of the preschoolers' influenced directly or indirectly on their self-esteem, their playfulness, and self-regulation, as well as goodness of mother-child fit. Also, the result pertaining to the mediational effects of child's self-esteem in the effects of study variables of interest on the child's self-determination were revealed. Along with results of this study, there is a strong need to empower the preschoolers' self-determination through improvement of their self-esteem in early childhood education and care as well as in family settings.