• The Journal of Bigdata
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• v.7 no.2
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• pp.1-9
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• 2022

In the global era, the importance of imported food safety management is increasing. Address information of overseas food companies is key information for imported food safety management, and must be verified for prompt response and follow-up management in the event of a food risk. However, because each country's address system is different, one verification system cannot verify the addresses of all countries. Also, the purpose of address verification may be different depending on the field used. In this paper, we deal with the problem of classifying a given overseas food business address into the administrative district level of the country. This is because, in the event of harm to imported food, it is necessary to find the administrative district level from the address of the relevant company, and based on this trace the food distribution route or take measures to ban imports. However, in some countries the administrative district level name is omitted from the address, and the same place name is used repeatedly in several administrative district levels, so it is not easy to accurately classify the administrative district level from the address. In this study we propose a deep learning-based administrative district level classification model suitable for this case, and verify the actual address data of overseas food companies. Specifically, a method of training using a label powerset in a multi-label classification model is used. To verify the proposed method, the accuracy was verified for the addresses of overseas manufacturing companies in Ecuador and Vietnam registered with the Ministry of Food and Drug Safety, and the accuracy was improved by 28.1% and 13%, respectively, compared to the existing classification model.

• Journal of Korea Water Resources Association
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• v.47 no.4
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• pp.343-356
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• 2014

The SWMM (storm water management model) has been widely used in the world and is a watershed runoff simulation model used for a single event or a continuous simulation of runoff quantity and quality. However, there are many uncertain parameters in the watershed runoff continuous simulation module and the water quality module, which make it difficult to use the SWMM. The purpose of the study is to develop an automatic calibration module of the SWMM not only for watershed runoff continuous simulation, but also water quality simulation. The automatic calibration module was developed by linking the SWMM with the SCE-UA (shuffled complex evolution-University of Arizona) that is a global optimization algorithm. Estimation parameters of the SWMM were selected and search ranges of them were reasonably configured. The module was validated by calibration and verification of the watershed runoff continuous simulation model and the water quality model for the Donghyang Stage Station Basin. The calibration results for watershed runoff continuous simulation model were excellent and those for water quality simulation model were generally satisfactory. The module could be used in various studies and designs for watershed runoff and water quality analyses.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.587-599
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• 2023

As climate change increasesthe frequency and risk of flooding in major cities around theworld, the importance ofsimulation technology that can quickly and accurately analyze high-resolution 2D flooding information in large-scale areasis emerging. The physically-based approaches based on the Shallow Water Equations (SWE) often requires huge computer resources hindering high-resolution flood prediction. This study investigated the theoretical background of Weighted Cellular Automata 2D (WCA2D), which simulates spatio-temporal changes offlooding using transition rules and weight-based system, and assessed feasibility to simulate pluvial flooding in the urbancatchment, theOncheon-cheon catchmentinBusan, SouthKorea.Inaddition,the computation performancewas compared by applying versions using OpenComputing Language (OpenCL) andOpenMulti-Processing (OpenMP) parallel computing techniques. Simulationresultsshowed that the maximuminundation depthmap by theWCA2Dmodel cansimilarly reproduce historical inundation maps. Also, it can precisely simulate spatio-temporal changes of flooding extent in the urban catchment with complex topographic characteristics. For computation efficiency, parallel computing schemes, theOpenCLandOpenMP, improved the computation by about 8~14 and 5~6 folds respectively, compared to the sequential computation.

• The Journal of Korean Society for Radiation Therapy
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• v.21 no.2
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• pp.83-88
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• 2009

Purpose: Cone beam computed tomography (CBCT) using an on board imager (OBI) can check the movement and setup error in patient position and target volume by comparing with the image of computer simulation treatment in real.time during patient treatment. Thus, this study purposed to check the change and movement of patient position and target volume using CBCT in IMRT and calculate difference from the treatment plan, and then to correct the position using an automated match system and to test the accuracy of position correction using an electronic portal imaging device (EPID) and examine the usefulness of CBCT in IMRT and the accuracy of the automatic match system. Materials and Methods: The subjects of this study were 3 head and neck patients and 1 pelvis patient sampled from IMRT patients treated in our hospital. In order to investigate the movement of treatment position and resultant displacement of irradiated volume, we took CBCT using OBI mounted on the linear accelerator. Before each IMRT treatment, we took CBCT and checked difference from the treatment plan by coordinate by comparing it with the image of CT simulation. Then, we made correction through the automatic match system of 3D/3D match to match the treatment plan, and verified and evaluated using electronic portal imaging device. Results: When CBCT was compared with the image of CT simulation before treatment, the average difference by coordinate in the head and neck was 0.99 mm vertically, 1.14 mm longitudinally, 4.91 mm laterally, and 1.07o in the rotational direction, showing somewhat insignificant differences by part. In testing after correction, when the image from the electronic portal imaging device was compared with DRR image, it was found that correction had been made accurately with error less than 0.5 mm. Conclusion: By comparing a CBCT image before treatment with a 3D image reconstructed into a volume instead of a 2D image for the patient's setup error and change in the position of the organs and the target, we could measure and correct the change of position and target volume and treat more accurately, and could calculate and compare the errors. The results of this study show that CBCT was useful to deliver accurate treatment according to the treatment plan and to increase the reproducibility of repeated treatment, and satisfactory results were obtained. Accuracy enhanced through CBCT is highly required in IMRT, in which the shape of the target volume is complex and the change of dose distribution is radical. In addition, further research is required on the criteria for match focus by treatment site and treatment purpose.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.6
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• pp.439-446
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• 2011

In this research, enhanced land-cover classification methods using high-resolution satellite image (HRSI) and GIS in terms of practicality and accuracy was proposed. It aims for understanding non-point pollutant origin/loading, assessment the efficiency of rainfall storage/infiltration facilities and sounds water-environment management. The result of applying enhanced land-cover classification methods to the urban region verifies that roof and road area are including various vegetations such as roof garden, flower bed in the median strip and street tree. This accounts for 3% of total study area, and more importantly it was counted as impervious area by GIS alone or conventional indoor work. The feasibility of the method was assessed by applying to rainfall-runoff analysis for three weak rainfall in the range of 7.1-10.5 mm events in 2000, Chiba, Japan. A good agreement between simulated and observed runoff hydrograph was obtained. In comparison, the hydrograph simulated with land-use parameters by the detailed land-use information of 10m grid had an error between 31%~71%, while enhanced method showed 4% to 29%, and showed the improvement particularly for reproducing observed peak and recession flow rate of hydrograph in weak rainfall condition.

• Korean Journal of Remote Sensing
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• v.29 no.5
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• pp.569-579
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• 2013

In this study, land-cover classification was implemented using features extracted from multi-temporal SAR data through 3D wavelet transform and the applicability of the 3D wavelet transform as a feature extraction approach was evaluated. The feature extraction stage based on 3D wavelet transform was first carried out before the classification and the extracted features were used as input for land-cover classification. For a comparison purpose, original image data without the feature extraction stage and Principal Component Analysis (PCA) based features were also classified. Multi-temporal Radarsat-1 data acquired at Dangjin, Korea was used for this experiment and five land-cover classes including paddy fields, dry fields, forest, water, and built up areas were considered for classification. According to the discrimination capability analysis, the characteristics of dry field and forest were similar, so it was very difficult to distinguish these two classes. When using wavelet-based features, classification accuracy was generally improved except built-up class. Especially the improvement of accuracy for dry field and forest classes was achieved. This improvement may be attributed to the wavelet transform procedure decomposing multi-temporal data not only temporally but also spatially. This experiment result shows that 3D wavelet transform would be an effective tool for feature extraction from multi-temporal data although this procedure should be tested to other sensors or other areas through extensive experiments.

• Journal of Korea Water Resources Association
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• v.57 no.9
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• pp.585-598
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• 2024

To mitigate natural disasters and efficiently manage water resources, it is essential to enhance hydrologic prediction while reducing model structural uncertainties. This study analyzed the impact of lumped and semi-distributed GR4J model structures on simulation performance and evaluated uncertainties with and without data assimilation techniques. The Ensemble Kalman Filter (EnKF) and Particle Filter (PF) methods were applied to the Namgang Dam basin. Simulation results showed that the Kling-Gupta efficiency (KGE) index was 0.749 for the lumped model and 0.831 for the semi-distributed model, indicating improved performance in semi-distributed modeling by 11.0%. Additionally, the impact of uncertainties in meteorological forcings (precipitation and potential evapotranspiration) on data assimilation performance was analyzed. Optimal uncertainty conditions varied by data assimilation method for the lumped model and by sub-basin for the semi-distributed model. Moreover, reducing the calibration period length during data assimilation led to decreased simulation performance. Overall, the semi-distributed model showed improved flood simulation performance when combined with data assimilation compared to the lumped model. Selecting appropriate hyper-parameters and calibration periods according to the model structure was crucial for achieving optimal performance.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.707-723
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• 2022

Although satellite-based sea surface temperature (SST) is advantageous for monitoring large areas, spatiotemporal data gaps frequently occur due to various environmental or mechanical causes. Thus, it is crucial to fill in the gaps to maximize its usability. In this study, daily SST composite fields with a resolution of 4 km were produced through a two-step machine learning approach using polar-orbiting and geostationary satellite SST data. The first step was SST reconstruction based on Data Interpolate Convolutional AutoEncoder (DINCAE) using multi-satellite-derived SST data. The second step improved the reconstructed SST targeting in situ measurements based on light gradient boosting machine (LGBM) to finally produce daily SST composite fields. The DINCAE model was validated using random masks for 50 days, whereas the LGBM model was evaluated using leave-one-year-out cross-validation (LOYOCV). The SST reconstruction accuracy was high, resulting in R² of 0.98, and a root-mean-square-error (RMSE) of 0.97℃. The accuracy increase by the second step was also high when compared to in situ measurements, resulting in an RMSE decrease of 0.21-0.29℃ and an MAE decrease of 0.17-0.24℃. The SST composite fields generated using all in situ data in this study were comparable with the existing data assimilated SST composite fields. In addition, the LGBM model in the second step greatly reduced the overfitting, which was reported as a limitation in the previous study that used random forest. The spatial distribution of the corrected SST was similar to those of existing high resolution SST composite fields, revealing that spatial details of oceanic phenomena such as fronts, eddies and SST gradients were well simulated. This research demonstrated the potential to produce high resolution seamless SST composite fields using multi-satellite data and artificial intelligence.

• 한국해양학회지
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• v.4 no.2
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• pp.83-86
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• 1969

해양관측의 세계적인 공통성으로 해서 염분검정법이 이미 오래 전부터 통일화 되었지만 근래에 와서는 용존산소량 정량법도 국제적인 Intercalibration을 하는 등규격화에의 기운이 나고 있다. 다시 Kuroshio 합동조사에서는 영양염의 정량에 있어 공통된 표준용액을 사용하므로써 조작상의 편리와 측정치의 신뢰성을 더욱 향상시키자는 의도에서 일본이 국제적인 영양염 표준용액의 조제 및 배포에 관한 안을 내어 1965년 Manila 회의를 거쳐 일본 상모중앙화학연구소의 관원씨가 이를 맡아 1966년부터 시작하여 1967년까지에 요오드산칼리움, 아질산염, 인산염, 규산염의 표준용액을 만들어 1968년 봄부터 시험적으로 일본국내와 동남아 수개국에 나누어 사용해 왔던 것이다. 다시 1968년 9월의 SCOR 의 영양염에 관한 Working Group 회의에서 CSK Std. Solution을 사용하여 세계각국에서 현재 사용하고 있는 영양염 분석방법의 Intercalibration을 하자는 회의가 있었고, 이것을 권고사항으로 SCOR에 보고하여 1968년 11월에 ICES가 승인하므로써 Intercalibration에 관한 원칙이 정해졌다. 동시에 Finland의 Koroleff씨와 Palmork씨가 organizer로 정해졌던 것이다. 이 보다 약간 앞서 본인이 상모중연에 가 있을 때 Std. Solution으로서 아질산염용액 만으로 각종무기질소화합물의 표준용액으로 대용한다는 것은 비합리적이므로 질산염과 암모늄염의 표준용액이 있어야 한다고 주장하여 우선 질산염용액을 추가로 만들기로 하여 1968년 11월부터 표준물질의 정제부터 시작 되었다. 1969년 1월에 Intercalibration 에 관한 구체적인 회의를 위해 Scripps 해양연구소에 관원, Wooster Rakestraw, Cieskes씨등이 모여 우선 일본상모중연에서 만들고 있는 인산염, 질산염, 아질산염, 규산염의 CSK 표준용액을 표준시료로하여 SCOR 과 ICES의 해양화학분과에서 선정한 세계 100개처에 나누어 현재 각자가 사용하고 있는 방법의 정밀도와 정확도를 check하는 소위 International intercalibration을 1969년 9월부터 시작하기로 확정을 보았고, 동시에 구체적인 지시가 있었던 것이다. 이시료를 받는 사람에게는 다만 그것의 농도범위만 알려주고 정확한 농도는 Koreleff와 관원씨만이 알고 있기로 하여 측정에 분석자의 주관이 개입되지 못하도록 했고, 분석치는 SCOR가 모아 해석하되 번호제로 하여 어떤 나라의 누구가 했다는 것은 밝히지 않기로 되어 있다. 이같은 내력으로 CSK Std. Solution이 국제적인 Intercalibration용의 표준시료로서 시험적으로 사용되기 까지는 되었으나, CSK Std. Solution 그자체에 관해서는 아직도 해결해야 할 점, 개량을 요하는 점이 많다. 이하에서는 주로 개량을 요하는 점에 관해 몇가지 언급하고자 한다.

• Journal of Korea Multimedia Society
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• v.16 no.8
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• pp.927-933
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• 2013

Face detection algorithm of OpenCV recognizes the faces by Haar matching between input image and Haar features which are learned through a set of training images consisting of many front faces. Therefore the face detection method by Haar matching yields a high face detection rate for the front faces but not in the case of the pan and deformed faces. On the assumption that distributional characteristics of color histogram is similar even if deformed or side faces, a face detection method using the histogram pattern matching is proposed in this paper. In the case of the missed detection and false detection caused by Haar matching, the proposed face detection algorithm applies the histogram pattern matching with the correct detected face area of the previous frame so that the face region with the most similar histogram distribution is determined. The experiment for evaluating the face detection performance reveals that the face detection rate was enhanced about 8% than the conventional method.