• Geophysics and Geophysical Exploration
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• v.25 no.3
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• pp.109-119
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• 2022

The computational efficiency of reverse time migration (RTM) based on numerical modeling is not secured due to the high-frequency band of several hundred Hz or higher for data acquired through a three-dimensional (3D) ultra-high-resolution (UHR) seismic survey. Therefore, this study develops an RTM program to derive high-quality 3D geological structures using UHR seismic data. In the traditional 3D RTM program, an excitation amplitude technique that stores only the maximum amplitude of the source wavefield and a domain-limiting technique that minimizes the modeling area where the source and receivers are located were used to significantly reduce memory usage and calculation time. The program developed through this study successfully derived a 3D migration image with a horizontal grid size of 1 m for the 3D UHR seismic survey data obtained from the Korea Institute of Geoscience and Mineral Resources in 2019, and geological analysis was conducted.

• Smart Media Journal
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• v.11 no.10
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• pp.65-75
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• 2022

Deep learning is used as a creative tool that could overcome the limitations of existing analysis models and generate various types of results such as text, image, and music. In this paper, we propose a method necessary to preprocess audio data using the Niko's MIDI Pack sound source file as a data set and to generate music using Bi-LSTM. Based on the generated root note, the hidden layers are composed of multi-layers to create a new note suitable for the musical composition, and an attention mechanism is applied to the output gate of the decoder to apply the weight of the factors that affect the data input from the encoder. Setting variables such as loss function and optimization method are applied as parameters for improving the LSTM model. The proposed model is a multi-channel Bi-LSTM with attention that applies notes pitch generated from separating treble clef and bass clef, length of notes, rests, length of rests, and chords to improve the efficiency and prediction of MIDI deep learning process. The results of the learning generate a sound that matches the development of music scale distinct from noise, and we are aiming to contribute to generating a harmonistic stable music.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.274-284
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• 2022

To use kenaf (Hibiscus cannabinus L.) as a fiber and livestock feed, a high-yielding variety needs to be identified. For this, accurate phenotyping of plant height is required for this breeding purpose due to the strong relationship between plant height and yield. Plant height can be estimated using RGB images from unmanned aerial vehicles (UAV-RGB) and photogrammetry based on Structure from Motion (SfM) algorithms. In kenaf, accurate measurement of height is limited because kenaf stems have high flexibility and its height is easily affected by wind, growing up to 3 ~ 4 m. Therefore, we aimed to identify a method suitable for the accurate estimation of plant height of kenaf and investigate the feasibility of using the UAV-RGB-derived plant height map. Height estimation derived from UAV-RGB was improved using multi-point calibration against the five different wooden structures with known heights (30, 60, 90, 120, and 150 cm). Using the proposed method, we analyzed the variation in temporal height of 23 kenaf cultivars. Our results demontrated that the actual and estimated heights were reliably comparable with the coefficient of determination (R²) of 0.80 and a slope of 0.94. This method enabled the effective identification of cultivars with significantly different heights at each growth stages.

• Journal of Aerospace System Engineering
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• v.17 no.4
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• pp.67-74
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• 2023

Recently, Urban Aircraft Mobility (UAM) has been attracting attention as a transportation system of the future, and small drones also play a role in various industries. The failure of various types of aviation systems can lead to crashes, which can result in significant property damage or loss of life. In the defense industry, where aviation systems are widely used, the failure of aviation systems can lead to mission failure. Therefore, this study proposes an anomaly detection model using deep learning technology to detect anomalies in aviation systems to improve the reliability of development and production, and prevent accidents during operation. As training and evaluating data sets, current data from aviation systems in an extremely low-temperature environment was utilized, and a deep learning network was implemented using the convolutional neural network, which is a deep learning technique that is commonly used for image recognition. In an extremely low-temperature environment, various types of failure occurred in the system's internal sensors and components, and singular points in current data were observed. As a result of training and evaluating the model using current data in the case of system failure and normal, it was confirmed that the abnormality was detected with a recall of 98 % or more.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.84-84
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• 2023

소하천의 유속계측을 위해 가장 많이 사용되고 있는 표면영상유속계는 표면유속을 계측하는데, 계측된 표면유속을 이용하여 유량을 산정하기 위해서는 수심 평균유속으로 변환할 필요가 있다. 이때 평균-표면유속 환산계수가 주로 사용되는데, 적정 환산계수를 산정하기 위해서는 수심별로 유속을 직접 계측하고 계측된 유속분포를 이용하여 평균-표면유속 환산계수를 산정하는 방법을 사용한다. 그러나 소하천은 홍수시 유속이 매우 빨라 물속에 직접 들어가는 것이 어렵고 장비를 이용하여 간접적인 방법으로 계측을 한다고 하더라도 소류사와 유송잡물 등으로 계측기가 파손되어 직접 계측에는 한계가 있다. 또한 직선구간 확보나 식생 등으로 부자를 이용한 계측도 어려워 계측 결과를 이용하여 환산계수를 산정하는 방법은 한계가 있다. 이런 이유로 대부분은 USGS가 제시한 0.85 ~ 0.95 범위 값 중에서 현장 여건을 고려하여 최적값을 결정·사용하고 있다. 본 연구에서는 홍수시 수심-유속분포를 직접 계측하기 어려운 소하천에서 표면영상유속계를 이용하여 계측한 수심별 표면유속분포를 이용하여 평균-표면유속 환산계수를 산정하는 방법을 개발하였다. 개발한 방법을 정량적으로 평가하기 위하여 건설기술연구원의 안동 하천실험시설에서 표면영상유속계로 수심상승에 따른 횡방향 유속분포를 계측하고 수위가 완전히 상승한 이후의 안정된 흐름 조건에서 플로우트래커를 이용하여 수심별 횡방향 유속분포를 계측하여 두 계측결과를 1:1로 비교하였다. 비교 결과 표면영상유속계로 계측한 수심별 표면유속분포와 플로우트래커로 계측한 수심-유속분포 결과는 유사한 분포를 보이는 것으로 나타나 표면영상유속계로 계측한 수심별 표면유속분포를 이용하여 평균-표면유속 환산계수를 산정하는 것이 가능하다는 결론을 도출하였다. 본 연구에서는 개발한 평균-표면유속 환산계수 산정방법의 적용성을 검토하기 위하여 표면영상유속계가 설치된 5개 시범소하천에서 7년(2016~2022)간 계측한 수심별 표면유속 자료를 수집하고 이 결과를 이용하여 평균-표면유속 환산계수를 산정하였다. 산정결과 대부분 USGS가 제시한 범위내의 값을 보이는 것으로 나타나 향후 본 연구의 개발 방법을 평균-표면유속 환산계수 산정에 활용할 수 있을 것으로 판단된다. 본 연구에서는 개발한 환산계수 산정방법은 향후 보다 많은 수리실험과 현장실험 등으로 정밀검증을 수행한다면 홍수시 수심-유속분포를 직접 계측하기 어려운 소하천에서 간편하면서도 적용성이 큰 신기술 확보가 가능할 것으로 기대된다.

• 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.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.373-380
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• 2023

Due to abnormal climate phenomena and climate change in Korea, overgrowth of algae in rivers and reservoirs occurs frequently. Algae in rivers are classified into green algae, blue-green algae, diatom, and other types, and some species of blue-green algae cause problems due to odor and the discharge of toxic substances. In Korea, an algae alert system is in place, and it is issued based on the number of harmful blue-green algae cells. Thus, measuring harmful blue-green algal blooms is very important, and currently, the analysis method of algae involves taking field samples and determining the cell count of green algae, blue-green algae, and diatoms through algal microscopy, which takes a lot of time. Recently, the analysis of algae concentration through Phycocyanin, an alternative indicator for the number of harmful algae cells, has been conducted through remote sensing. However, research on the analysis of the number of blue-green algae cells is currently insufficient. In this study, we water samples for algal analyses were collected from river and counted the number of blue-green algae cells using algae microscopy. We also obtained the Phycocyanin concentration using an optical sensor and acquired algae spectra through a hyperspectral sensor. Based on this, we calculated the equation for estimating blue-green algae cell counts and estimated the number of blue-green algae cells.

• Journal of the Korean Society of Floral Art and Design
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• no.40
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• pp.97-123
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• 2019

The purpose of this study is to analyze the spatial characteristics of the unit of garden and to classify and symbolize it, to provide the basis for analyzing the works based on the characteristics of the space and to provide the data that can become the logical foundation for garden design. The research method first analyzed the behavioral scene analysis and the grounded theory methodology as the theory about the space type. It controls the subjectivity of the researcher and derives the characteristics of the space for the garden image based on the experiential knowledge of the expert, It is a qualitative analysis method that aims to increase credibility. The actual case target was the author garden which was exhibited at the 2017 Seoul Garden Expo. Through this process, we have simplified the characteristics of the space and the positives and negatives accordingly. We have grasped the relationship between spatial space, sculptural space, architectural space, and environmental space.. Research on qualitative topics such as the characteristics of space can not completely exclude the subjectivity of the researcher in terms of its characteristics, but such research can provide a rationale for interpreting and evaluating the gardens that depend on the individual's taste.. It can also contribute to the development of the field by providing reference materials for garden designs that rely on designer intuition, or by providing a logical basis for design.

• Journal of the Korean Society of Floral Art and Design
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• no.41
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• pp.45-59
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• 2019

The characters that could be connected to diverse cultural contents have formed diverse platforms with the development of digital technology, and the size of the relevant industry and market is rapidly growing. Recently, the utilization of character emoticons for smartphone messenger has been rapidly increased, so that the characters are settled down as a tool for non-verbal communication, on top of drawing attention as an independent area. With the expansion of character market, the importance of design that could give interest and familiarity to consumers is more emphasized. The body proportion of characters includes the implicative and symbolic meanings that could express diverse personalities. Thus, this study examined the body proportion of the characters with the high consumers' preference, and then analyzed the characteristics of formative elements of character design in accordance with the body proportion. In the results of the analysis, the exaggerated form of SD characters in two or three-head figure, and the realistic Real characters in seven or eight-head figure were preferred. For the SD characters, the colors with a high chroma showing the cute and cheerful image were used. For the Real characters, the cubic effect was expressed through the colors with active images and the light and shade of color. Even though the SD characters have limited motions due to the omitted body parts, the facial movements of animation characters are exaggerated while the Real characters describe the realistic and dynamic motions.

• Korea Science and Art Forum
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• v.29
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• pp.279-292
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• 2017

This study was started by recognizing that visual storytelling(VST) is an important factor that determines the success of the work. The goal of this study is to analyze the VST study approaching from the narrative and visual dimension by analyzing the conflict intensity and VST factor. Therefore, in this paper, we analyzed the conflicts of the theater animation(4) that succeeded in the worldwide success and attempted the VST interpretation by approaching it technically. The results and contents of the study are as follows. Firstly, based on the narrative theory of Sung bong-Sun and Robert McKee, we classified the conflict scenes and found the kinds of conflicts. In addition, based on the 5B model, a total of 108 conflict shots were extracted. Secondly, through expert experiment, we found the conflict intensity of conflict shots. Thirdly, the visual elements of fifteen significant conflicts were extracted from internal and super individual conflicts. Fourth, as a result of the experiment, it was confirmed that the reliability of the visual elements in the inner and super personal conflicts was in the range of 100-83.33%, and the frequency of usage was found to be widely distributed in 5.88-70.59% and 5-70%. This means that the VST expression, which relied on the sense of the artist, can be engineered. Finally, I expect that it will be the basis of the development of the VST Tool which can predict the conflict expression of the work in the animation pre - production stage successfully.