• Journal of Korea Game Society
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• v.7 no.2
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• pp.53-60
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• 2007

This paper proposes the knowledge structure of an extended script for advertisement style game embodiment. This approach is able to allow for developing game and advertisement module. Research to reconsider contradictory awareness about existent game have been evolving from game education system, advertisement style game and simulation game for training and so on. In this paper, a situation hierarchy structure which allows the designer for simulating high-level specifications of game structure. And we describes with mathematical structure for proposed situation structure. Game unfolding utilizes with causality. Game reflects situation of a spatiotemporal real world. For this goal, we applied extended script to game world. Advertisement style module progresses by method to provide company's advertisement to user while game is gone. The advantage of proposed method are able to allows for novice to effectively insert banner image, video and so on into advertisement module. The proposed method was implemented in the "Shooting BaDuk" among games.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.4
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• pp.23-32
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• 2021

For agricultural water management, it is essential to establish the digital infrastructure data such as agricultural watershed, irrigated area and canal network in rural areas. Approximately 70,000 irrigation facilities in agricultural watershed, including reservoirs, pumping and draining stations, weirs, and tube wells have been installed in South Korea to enable the efficient management of agricultural water. The total length of irrigation and drainage canal network, important components of agricultural water supply, is 184,000 km. Major problem faced by irrigation facilities management is that these facilities are spread over an irrigated area at a low density and are difficult to access. In addition, the management of irrigation facilities suffers from missing or errors of spatial information and acquisition of limited range of data through direct survey. Therefore, it is necessary to establish and redefine accurate identification of irrigated areas and canal network using up-to-date high resolution images. In this study, previous existing data such as RIMS (Rural Infrastructure Management System), smart farm map, and land cover map were used to redefine irrigated area and canal network based on appropriate image data using satellite imagery, aerial imagery, and drone imagery. The results of the building the digital infrastructure in rural areas are expected to be utilized for efficient water allocation and planning, such as identifying areas of water shortage and monitoring spatiotemporal distribution of water supply by irrigated areas and irrigation canal network.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.3
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• pp.25-37
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• 2024

Global warming-induced drought inflicts significant socio-economic and environmental damage. In Korea, the persistent drought in the southern region since 2022 has severely affected water supplies, agriculture, forests, and ecosystems due to uneven precipitation distribution. To effectively prepare for and mitigate such impacts, it is imperative to develop proactive measures supported by early monitoring systems. In this study, we analyzed the spatiotemporal changes of multiple evapotranspiration-based drought indices, focusing on the flash drought event in the southern region in 2022. The indices included the Evaporative Demand Drought Index (EDDI), Standardized Precipitation Evapotranspiration Index (SPEI) considering precipitation and temperature, and the Evaporative Stress Index (ESI) based on satellite images. The Standardized Precipitation Index (SPI) and SPEI indices utilized temperature and precipitation data from meteorological observation stations, while the ESI index was based on satellite image data provided by the MODIS sensor on the Terra satellite. Additionally, we utilized the Evaporative Demand Drought Index (EDDI) provided by the North Oceanic and Atmospheric Administration (NOAA) as a supplementary index to ESI, enabling us to perform more effective drought monitoring. We compared the degree and extent of drought in the southern region through four drought indices, and analyzed the causes and effects of drought from various perspectives. Findings indicate that the ESI is more sensitive in detecting the timing and scope of drought, aligning closely with observed drought trends.

• Korean Journal of Cognitive Science
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• v.20 no.1
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• pp.79-107
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• 2009

Episodic memory, i.e. memorization of information within a spatiotemporal environment, is affected Alzheimer's disease(AD), but its impairment may also be occurred in the normal aging process. The purpose of this study is to analyze and evaluate memory in with Dementia of Alzheimer Type by examining their cognitive skills in episodic memory using the technique. This new method involves assessing the mental images the subject's own past in the mind like projected and movies. Three patients in the early stage of Dementia of Alzheimer Type, one with mild depression, and 2 healthy controls for comparison were asked to retrieve their episodic memory of the previous day, week, month, and a day testing day. The answers were then analyzed with regards to their specific features as emotional state, color, and time order. In the following day, the subjects were tasked to recall again the images they reproduced in the day's test order to observe of memory. Results showed that all 3 patients failed to arrange the retrieved images in time order and their images of the previous day were unclear in color and were stationary like photographs, even when they reproduced the mental images at much quantity as controls. patients could not remember particular events of yesterday, and only recalled the general occurrences of every day life. These results suggest that in the early stage of Dementia of Alzheimer Type, difficulties in the retrieval of recent episodic memory begin to primarily occur, and qualitative impairment happens earlier than quantitative.

• Journal of radiological science and technology
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• v.39 no.3
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• pp.369-376
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• 2016

Positron Emission Tomography(PET) is nuclear medical tests which is a combination of several compounds with a radioactive isotope that can be injected into body to quantitatively measure the metabolic rate (in the body). Especially, Phenomena that increase (sing) glucose metabolism in cancer tissue using the $^{18}F$-FDG (Fluorodeoxyglucose) is utilized widely in cancer diagnosis. And then, Numerous studies have been reported that incidence seems high availability even in the modern diagnosis of dementia and Parkinson's (disease) in brain disease. When using a dynamic PET iamge including the time information in the static information that is provided for the diagnosis many can increase the accuracy of diagnosis. For this reason, clinical researchers getting great attention but, it is the lack of tools to conduct research. And, it interfered complex mathematical algorithm and programming skills for activation of research. In this study, in order to easy to use and enable research dPET, we developed the software based graphic user interface(GUI). In the future, by many clinical researcher using DIA-Tool is expected to be of great help to dPET research.

• Journal of The Korean Astronomical Society
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• v.56 no.2
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• pp.213-224
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• 2023

Type II solar radio bursts show frequency drifts from high to low over time. They have been known as a signature of coronal shock associated with Coronal Mass Ejections (CMEs) and/or flares, which cause an abrupt change in the space environment near the Earth (space weather). Therefore, early detection of type II bursts is important for forecasting of space weather. In this study, we develop a deep-learning (DL) model for the automatic detection of type II bursts. For this purpose, we adopted a 1-D Convolution Neutral Network (CNN) as it is well-suited for processing spatiotemporal information within the applied data set. We utilized a total of 286 radio burst spectrum images obtained by Hiraiso Radio Spectrograph (HiRAS) from 1991 and 2012, along with 231 spectrum images without the bursts from 2009 to 2015, to recognizes type II bursts. The burst types were labeled manually according to their spectra features in an answer table. Subsequently, we applied the 1-D CNN technique to the spectrum images using two filter windows with different size along time axis. To develop the DL model, we randomly selected 412 spectrum images (80%) for training and validation. The train history shows that both train and validation losses drop rapidly, while train and validation accuracies increased within approximately 100 epoches. For evaluation of the model's performance, we used 105 test images (20%) and employed a contingence table. It is found that false alarm ratio (FAR) and critical success index (CSI) were 0.14 and 0.83, respectively. Furthermore, we confirmed above result by adopting five-fold cross-validation method, in which we re-sampled five groups randomly. The estimated mean FAR and CSI of the five groups were 0.05 and 0.87, respectively. For experimental purposes, we applied our proposed model to 85 HiRAS type II radio bursts listed in the NGDC catalogue from 2009 to 2016 and 184 quiet (no bursts) spectrum images before and after the type II bursts. As a result, our model successfully detected 79 events (93%) of type II events. This results demonstrates, for the first time, that the 1-D CNN algorithm is useful for detecting type II bursts.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1295-1305
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• 2021

Satellite-derived ocean color products are required to effectively monitor clear open ocean and coastal water regions for various research fields. For this purpose, accurate correction of atmospheric effect is essential. Currently, the Geostationary Ocean Color Imager (GOCI)-II ground segment uses the reanalysis of meteorological fields such as European Centre for Medium-Range Weather Forecasts (ECMWF) or National Centers for Environmental Prediction (NCEP) to correct gas absorption by water vapor and ozone. In this process, uncertainties may occur due to the low spatiotemporal resolution of the meteorological data. In this study, we develop water vapor absorption correction model for the GK-2 combined GOCI-II atmospheric correction using Advanced Meteorological Imager (AMI) total precipitable water (TPW) information through radiative transfer model simulations. Also, we investigate the impact of the developed model on GOCI products. Overall, the errors with and without water vapor absorption correction in the top-of-atmosphere (TOA) reflectance at 620 nm and 680 nm are only 1.3% and 0.27%, indicating that there is no significant effect by the water vapor absorption model. However, the GK-2A combined water vapor absorption model has the large impacts at the 709 nm channel, as revealing error of 6 to 15% depending on the solar zenith angle and the TPW. We also found more significant impacts of the GK-2 combined water vapor absorption model on Rayleigh-corrected reflectance at all GOCI-II spectral bands. The errors generated from the TOA reflectance is greatly amplified, showing a large error of 1.46~4.98, 7.53~19.53, 0.25~0.64, 14.74~40.5, 8.2~18.56, 5.7~11.9% for from 620 nm to 865 nm, repectively, depending on the SZA. This study emphasizes the water vapor correction model can affect the accuracy and stability of ocean color products, and implies that the accuracy of GOCI-II ocean color products can be improved through fusion with GK-2A/AMI.