• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.132-140
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• 2019

Recently, many cities around the world introduced and operated shared bicycle system to reduce the traffic and air pollution. Seoul also provides shared bicycle service called as "Ddareungi" since 2015. As the use of shared bicycle increases, the demand for bicycle in each station is also increasing. In addition to the restriction on budget, however, there are managerial issues due to the different demands of each station. Currently, while bicycle rebalancing is used to resolve the huge imbalance of demands among many stations, forecasting uncertain demand at the future is more important problem in practice. In this paper, we develop forecasting model for demand for Seoul shared bicycle using statistical time series analysis and apply our model to the real data. In particular, we apply Holt-Winters method which was used to forecast electricity demand, and perform sensitivity analysis on the parameters that affect on real demand forecasting.

• Journal of radiological science and technology
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• v.43 no.6
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• pp.431-441
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• 2020

The purpose of this study was to construct a model of MVCT(Megavoltage Computed Tomography) dose calculation by using Dosimetry Check™, a program that radiation treatment dose verification, and establish a protocol that can be accumulated to the radiation treatment dose distribution. We acquired sinogram of MVCT after air scan in Fine, Normal, Coarse mode. Dosimetry Check™(DC) program can analyze only DICOM(Digital Imaging Communications in Medicine) format, however acquired sinogram is dat format. Thus, we made MVCT RC-DICOM format by using acquired sinogram. In addition, we made MVCT RP-DICOM by using principle of generating MLC(Multi-leaf Collimator) control points at half location of pitch in treatment RP-DICOM. The MVCT imaging dose in fine mode was measured by using ionization chamber, and normalized to the MVCT dose calculation model, the MVCT imaging dose of Normal, Coarse mode was calculated by using DC program. As a results, 2.08 cGy was measured by using ionization chamber in Fine mode and normalized based on the measured dose in DC program. After normalization, the result of MVCT dose calculation in Normal, Coarse mode, each mode was calculated 0.957, 0.621 cGy. Finally, the dose resulting from the process for acquisition of MVCT can be accumulated to the treatment dose distribution for dose evaluation. It is believed that this could be contribute clinically to a more realistic dose evaluation. From now on, it is considered that it will be able to provide more accurate and realistic dose information in radiation therapy planning evaluation by using Tomotherapy.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.4
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• pp.311-320
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• 2021

A study is performed for the real time fault diagnosis during operation and health estimation relating to performance deterioration in a turbojet engine used for an unmanned air vehicle. For this study the real time dynamic model is derived from the transient thermodynamic gas path analysis. For real fault conditions which are manipulated for the simulation, the detection techniques are applied such as Kalman filter and probabilistic decision-making approach based on statistical hypothesis test. Thereby the effectiveness is verified by showing good fault detection and isolation performances. For the health estimation with measurement parameters, it shows using an assumed performance degradation that the method by adaptive Kalman filter is feasible in practice for a condition based diagnosis and maintenance.

• Smart Media Journal
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• v.11 no.4
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• pp.9-18
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• 2022

Recently, research and system using AI is rapidly increasing in various fields. Smart farm using artificial intelligence and information communication technology is also being studied in agriculture. In addition, data-based precision agriculture is being commercialized by convergence various advanced technology such as autonomous driving, satellites, and big data. In Korea, the number of commercialization cases of facility agriculture among smart agriculture is increasing. However, research and investment are being biased in the field of facility agriculture. The gap between research and investment in facility agriculture and open-air agriculture continues to increase. The fields of fruit trees and plant factories have low research and investment. There is a problem that the big data collection and utilization system is insufficient. In this paper, we are proposed the system for determining the fruit tree growth stage using a deep learning-based object detection model. The system was proposed as a hybrid app for use in agricultural sites. In addition, we are implemented an object detection function for the fruit tree growth stage determine.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.809-812
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• 2021

Air bubbles which may be generated during the PCB coating process can be a major cause of malfunction. so it is necessary to detect the bubbles in advance. In previous studies, candidates for bubbles were extracted using the brightness characteristics of bubbles, and the candidates were verified using CNN(Convolutional Neural Networks). In this paper, we propose a bubble detection method using a transfer learning-based CNN model. The VGGNet is adopted and sigmoid is used as a classification layer, and the last convolutional layer and classification layer are trained together when transfer learning is applied. The performance of the proposed method is F1-score 0.9044, which shows an improvement of about 0.17 compared to the previous study.

• Journal of Environmental Impact Assessment
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• v.31 no.5
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• pp.271-285
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• 2022

The AERMET, the AERMOD meteorological preprocessing program, mainly used for environmental impact assessment and Integrated Environmental Permit System (IEPS) in Korea, has not considered the land covers characterasitics, and used only the past meteorological data format CD-144. In this study, two results of AERMET application considering CD-144 format and ISHD format, being used internationally, were compared. Also, the atmospheric dispersion characteristics were analyzed with consideration of land cover. In the case of considered the CD-144 format, the actual wind speed was not taken into account in the weak wind (0.6~0.9m/s) and other wind speed due to the unit conversion problem. The predicted concentration considering land cover data was up to 387% larger depending on the topographic and emission conditions than without consideration of land cover. In conclusion, when using meteorological preprocessing program in AERMOD modelling, AERMET, with ISHD format, land cover characterasitics in the area should be considered.

• Atmosphere
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• v.33 no.1
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• pp.49-59
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• 2023

Blocking refers to a class of weather phenomena appearing in the mid and high latitudes, whose characteristics are blocked airflow of persistence. Frequently found over the Pacific and Atlantic regions of the Northern Hemisphere, blocking affects severe weather in the surrounding areas with different mechanisms depending on the type of blocking patterns. Along with lots of studies about persistent weather extremes focusing on the specific types of blocking, a new categorization using Rossby wave breaking has emerged. This study aims to apply this concept to the classification of blockings over the Pacific and examine how different wave breakings specify the associated cold weather in the Korean peninsula. At the same time, we investigate a strongly developing ridge around the Pacific by designing a new detection algorithm, where a reversal method is modified to distinguish ridge-type blocking patterns. As result, Kamchatka blocking (KB) and strong ridge over the Central Pacific are observed the most frequently during 20 years (2001~2020) of the studied period, and anomalous low pressures with cold air over the Korean Peninsula are accompanied by blocking events. When it considers the Rossby wave breaking, cyclonic wave-breaking is dominant in KB, which generates low-pressure anomalies over the Korean Peninsula. However, KB with anticyclone wave breaking appears with the high-pressure anomalies over the Korean Peninsula and it generates the warm temperature anomaly. Lastly, the low-pressure anomalies are also generated by the strong ridge over the Central Pacific, which persists for approximately three days and give a significant impact on cold surge on the Korean Peninsula.

• Journal of the Korean Geotechnical Society
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• v.25 no.11
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• pp.5-15
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• 2009

Dynamic shear properties of Nak-Dong river sand were investigated to build a soil property database for Nak-Dong delta region. Samples were taken from the estuary and the midstream of the river. Laboratory specimens were prepared by air pluviation method, and were tested by using RC/TS apparatus at various confining stresses, relative densities and numbers of cycles. Shear modulus reduction and damping curves were developed using Ramberg-Osgood and Modified Hyperbolic Models. The developed curves, compared to those reported by other investigators, show only a slight difference. The outcome of this RC/TS experiments can be very important resources when accessing the dynamic response of sandy soils in Nak-Dong delta region in the future.

• Atmosphere
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• v.34 no.1
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• pp.23-34
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• 2024

The Korea Meteorological Administration has improved medium-range weather forecasts by implementing post-processing methods to minimize numerical model errors. In this study, we employ a statistical correction technique known as the minimum continuous ranked probability score (CRPS) to refine medium-range forecast guidance. This technique quantifies the similarity between the predicted values and the observed cumulative distribution function of the Unified Model Ensemble Prediction System for Global (UM EPSG). We evaluated the performance of the medium-range forecast guidance for surface air temperature and relative humidity, noting significant enhancements in seasonal bias and root mean squared error compared to observations. Notably, compared to the existing the medium-range forecast guidance, temperature forecasts exhibit 17.5% improvement in summer and 21.5% improvement in winter. Humidity forecasts also show 12% improvement in summer and 23% improvement in winter. The results indicate that utilizing the minimum CRPS for medium-range forecast guidance provide more reliable and improved performance than UM EPSG.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.107-120
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• 2023

The public bicycle of Seoul, Ttareungyi, was launched at October 2015 to reduce traffic and carbon emissions in downtown Seoul and now, 2023 Oct, the cumulative number of user is upto 4 million and the number of bike is about 43,000 with about 2700 stations. However, super growth of Ttareungyi has caused the several problems, especially demand/supply mismatch, and thus the Seoul citizen has been complained about out of stock. In this point, this study conducted a real time demand forecasting model to prevent stock out bike at stations. To develop the model, the research team gathered the rental·return transaction data of 20,000 bikes in whole 1600 stations for 2019 year and then analyzed bike usage, user behavior, bike stations, and so on. The forecasting model using machine learning is developed to predict the amount of rental/return on each bike station every hour through daily learning with the recent 90 days data with the weather information. The model is validated with MAE and RMSE of bike stations, and tested as a prototype service on the Seoul Bike Management System(Mobile App) for the relocation team of Seoul City.