• Korean Journal of Environment and Ecology
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• v.23 no.6
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• pp.569-576
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• 2009

Sediment and nutrient loading caused by the removal of forest cover and alteration of agricultural lands in catchments have led to the deterioration in Lake Shirarutoro. To examine the effects of deforestation and agricultural activities on water quality, I examined changes in total nitrogen (TN) and total phosphorus (TP) of lake water induced by land use change, and compared them with the various research data produced over the years. Our investigation showed that the level of TN and TP in the lake water decreased when forest cover increased but increased when farmland area increased. The concentration of TN and TP was high in Lake Shirarutoro despite that its catchment was surrounded by large forests and small farmlands. This result indicates that land uses near Lake Shirarutoro have affected the quality of the lake water. I have examined the changes of sediment yield in the lake's catchment over the last approximately 300 years. Eleven core samples were obtained from the lake sediment and analyzed to establish a chronology after using two tephra layers (Ko-c2 in 1694 and Ta-a in 1739) and a $^{137}Cs$ peak (in 1963). The average sediment yield under the natural condition during the first two periods was 8.4 tons/$km^2$/year in 1694~1739 and 8.9 tons/$km^2$/year in 1739~1963 respectively. The conversion of the Shirarutoro catchment into agricultural lands and deforestation intensified, leading to an increased sediment yield of 21.1 tons/$km^2$/year during 1963~2007.

• Journal of The Korean Association For Science Education
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• v.40 no.6
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• pp.611-620
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• 2020

The purpose of the study is to find creativity factors of students in the process of small group modeling and relate them to the types of interactions among students. In order to capture students' detailed interactions, this study was conducted as an 'essential case study' through qualitative analysis. We have developed the modules of nine lessons about terraforming, and they were used in an actual classroom. In order to understand the creativity of the students in the process of modeling, students' discourses and interview data were analyzed using 19 creative factors or abilities. The findings are as follows. Frequently found creativity factors are Elaboration, Evaluation, Visualization, Resist premature closer, Originality, Analysis and Concentration. And students' interactions that affect students' creativity in the process of modeling can be classified into four categories: Suggestion, Agreement, Questioning, Refutation, and Conversion. Through each interaction, students demonstrated the process of expressing and modifying their own thoughts and ideas in the modeling process. The findings of the study suggest that it is important to the teachers to understand types of interactions among students and the relationship between the types of interaction and creativity factors for students' creative modeling in modeling-based learning.

• Trans-
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• v.11
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• pp.37-63
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• 2021

This paper focused on documentaries and for specific places and described the documentary shooting methodology from the perspective of a Cinematographer. 'Old Seoul Station' and 'DSME' (DAEWOO Shipbuilding & Marine Engineering Co., Ltd.) are monumental spaces that reflect the value of Korea modernization and are shared by Koreans' collective memories, unconsciousness, and unique feelings for the place. 'Old Seoul Station' has changed its place identity to a new space called "Culture Station Seoul 284." 'DSME' is a large-scale industrial complex that still functions actively, and it is like an organism that seeks to change according to changes in its industrial structure. and observe and record images of space related to place identity and the people related to it. It shows the construction of staring into a space in a particular place and continuously recording and placing moments of experience, such as the appearance of people working and resting. If it is not recorded through this, it allows us to see intangible narratives related to volatile place identity, and enables specific place experiences through theaters. This study focuses on production theory based on examples of documentary filming methods for these specific places.

• Smart Media Journal
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• v.13 no.2
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• pp.52-61
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• 2024

In the shipyard, aerial images are acquired at regular intervals using Unmanned Aerial Vehicles (UAVs) for the management of external storage yards. These images are then investigated by humans to manage the status of the storage yards. This method requires a significant amount of time and manpower especially for large areas. In this paper, we propose an automated management technology based on a semantic segmentation foundation model to address these challenges and accurately assess the status of external storage yards. In addition, as there is insufficient publicly available dataset for external storage yards, we collected a small-scale dataset for external storage yards objects and equipment. Using this dataset, we fine-tune an object detector and extract initial object candidates. They are utilized as prompts for the Segment Anything Model(SAM) to obtain precise semantic segmentation results. Furthermore, to facilitate continuous storage yards dataset collection, we propose a training data generation pipeline using SAM. Our proposed method has achieved 4.00%p higher performance compared to those of previous semantic segmentation methods on average. Specifically, our method has achieved 5.08% higher performance than that of SegFormer.

• The Journal of the Acoustical Society of Korea
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• v.39 no.1
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• pp.16-23
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• 2020

In High-Intensity Focused Ultrasound (HIFU) treatment, effective localization of HIFU focus is important for developing a safe treatment plan. While Magnetic Resonance Imaging guided HIFU (MRIgHIFU) can visualize the ultrasound path during the treatment for localizing HIFU focus, it is challenging in ultrasound imaging guided HIFU (USIgHIFU). In the present study, a real-time ultrasound beam visualization technique capable of localizing HIFU focus is presented for USIgHIFU. In the proposed method, a short pulse, with the same center frequency of an imaging ultrasound transducer below the regulated acoustic intensity (i.e., Ispta < 720 mW/㎠), was transmitted through a HIFU transducer whereupon backscattered signals were received by the imaging transducer. To visualize the HIFU beam path, the backscattered signals underwent dynamic receive focusing and subsequent echo processing. From in vitro experiments with bovine serum albumin gel phantoms, the HIFU beam path was clearly depicted with low acoustic intensity (i.e., Ispta of 94.8 mW/㎠) and the HIFU focus was successfully localized before any damages were produced. This result indicates that the proposed ultrasound beam path visualization method can be used for localizing the HIFU focus in real time while minimizing unwanted tissue damage in USIgHIFU treatment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.19-29
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• 2011

Until now, many face recognition methods have been proposed, most of them use a 1-dimensional feature vector which is vectorized the input image without feature extraction process or input image itself is used as a feature matrix. It is known that the face recognition methods using raw image yield deteriorated performance in databases whose have severe illumination changes. In this paper, we propose a face recognition method using local statistics of gradients and correlations which are good for illumination changes. BDIP (block difference of inverse probabilities) is chosen as a local statistics of gradients and two types of BVLC (block variation of local correlation coefficients) is chosen as local statistics of correlations. When a input image enters the system, it extracts the BDIP, BVLC1 and BVLC2 feature images, fuses them, obtaining feature matrix by $(2D)^2$ PCA transformation, and classifies it with training feature matrix by nearest classifier. From experiment results of four face databases, FERET, Weizmann, Yale B, Yale, we can see that the proposed method is more reliable than other six methods in lighting and facial expression.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.9 s.351
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• pp.120-127
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• 2006

In Korea the vehicle enforcement system(VES) detects speeding vehicle using two inductive loop detectors. And the speed reliability of theirs are evaluated through the analysis of image frame which is captured from video camera. This method is validated to evaluate VES on Korea Laboratory Accreditation Scheme(KOLAS) but it needs much time and expense for the analysis of image frame. Because the number of VES are increasing rapidly, the requirement of new evaluation method is necessary. On this paper, the tape switch sensor as a substitution of existing method was introduced and its application on the site are discussed. On the site test we compared the tape switch sensor on the speed measurement of vehicle with the video image frame. As a result we have founded that the tape switch sensor is evaluated to be feasible system on site in respect to measure the overspeed vehicle.

• Spatial Information Research
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• v.22 no.3
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• pp.47-58
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• 2014

The credible measurement, reporting and verification (MRV) is among the most critical elements in UN-REDD (United Nations programme on Reducing Emissions from Deforestation and forest Degradation in Developing Countries). This study is intended to explore MRV potential in terms of UN-REDD opportunity cost estimation using satellite image for Mt. Geum-gang of North Korea. A visual interpretation were conducted to evaluate MRV conditions by sub-dividing or decomposing the images with different pixel size into a three types of hierarchical tree structure that helps dealing with spatial variability within each subarea. The permanent record of standard satellite remote sensing system demonstrated its capability of presenting area-wide visual evidences of MRV conditions in Mt. Geum-gang (such as the identification of forested area, degradation trends for forest space, three types of hierarchical land-cover and land use tree structure, carbon density in the landscape). Satellite data could be accepted as legally binding proof when it comes to REDD opportunity cost estimation since several cases exist where remote sensing has been used as legal evidence in ICJ (International Court of Justice) and UN resolution. It doesn't seem very difficult to comply with MRV requirements for UN-REDD opportunity cost calculation due to the probative value of satellite data. It is anticipated that this research output could be used as a valuable reference for Korea-based enterprises exploring REDD project sites and the carbon traders to ensure MRV potentials using satellite image in UN-REDD Opportunity Cost estimation.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.503-514
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• 2021

Rice production with adequate level of area is important for decision making of rice supply and demand policy. It is essential to grasp rice cultivation areas in advance for estimating rice production of the year. This study was carried out to classify paddy rice cultivation in Gimje-si using sentinel-1 SAR (synthetic aperture radar) and UAV imagery in early July. Time-series Sentinel-1A and 1B images acquired from early May to early July were processed to convert into sigma naught (dB) images using SNAP (SeNtinel application platform, Version 8.0) toolbox provided by European Space Agency. Farm map and parcel map, which are spatial data of vector polygon, were used to stratify paddy field population for classifying rice paddy cultivation. To distinguish paddy rice from other crops grown in the paddy fields, we used the decision tree method using threshold levels and random forest model. Random forest model, trained by mainly rice cultivation area and rice and soybean cultivation area in UAV image area, showed the best performance as overall accuracy 89.9%, Kappa coefficient 0.774. Through this, we were able to confirm the possibility of early estimation of rice cultivation area in Gimje-si using UAV image.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.547-554
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• 2021

In order to quickly and accurately diagnose pneumonia on a chest X-ray image, different batch sizes of 4, 8, 16, and 32 were applied to the same Xception deep learning model, and modeling was performed 3 times, respectively. As a result of the performance evaluation of deep learning modeling, in the case of modeling to which batch size 32 was applied, the results of accuracy, loss function value, mean square error, and learning time per epoch showed the best results. And in the accuracy evaluation of the Test Metric, the modeling applied with batch size 8 showed the best results, and the precision evaluation showed excellent results in all batch sizes. In the recall evaluation, modeling applied with batch size 16 showed the best results, and for F1-score, modeling applied with batch size 16 showed the best results. And the AUC score evaluation was the same for all batch sizes. Based on these results, deep learning modeling with batch size 32 showed high accuracy, stable artificial neural network learning, and excellent speed. It is thought that accurate and rapid lesion detection will be possible if a batch size of 32 is applied in an automatic diagnosis study for feature extraction and classification of pneumonia in chest X-ray images using deep learning in the future.