• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.515-522
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• 2024

Energy consumption is steadily increasing, and buildings in particular account for more than 20% of the total energy consumption around the world. As an effort to cost-effectively manage the energy consumption of buildings, many research groups have recently focused on Smart Building Energy Management Systems (BEMS), which are deepening the research depth by applying artificial intelligence(AI). In this paper, we propose a reinforcement learning-based energy control method for smart energy buildings integrated with V2G station, which aims to reduce the total energy cost of the building. The results of performance evaluation based on the energy consumption data measured in the real-world building shows that the proposed method can gradually reduce the total energy costs of the building as the learning process progresses.

• Ocean Systems Engineering
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• v.14 no.1
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• pp.85-99
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• 2024

Ocean surface currents have an essential role in the Earth's climate system and significantly impact the marine ecosystem, weather patterns, and human activities. However, predicting ocean surface currents remains challenging due to the complexity and variability of the oceanic processes involved. This review article provides an overview of the current research status, challenges, and opportunities in the prediction of ocean surface currents. We discuss the various observational and modelling approaches used to study ocean surface currents, including satellite remote sensing, in situ measurements, and numerical models. We also highlight the major challenges facing the prediction of ocean surface currents, such as data assimilation, model-observation integration, and the representation of sub-grid scale processes. In this article, we suggest that future research should focus on developing advanced modeling techniques, such as machine learning, and the integration of multiple observational platforms to improve the accuracy and skill of ocean surface current predictions. We also emphasize the need to address the limitations of observing instruments, such as delays in receiving data, versioning errors, missing data, and undocumented data processing techniques. Improving data availability and quality will be essential for enhancing the accuracy of predictions. The future research should focus on developing methods for effective bias correction, a series of data preprocessing procedures, and utilizing combined models and xAI models to incorporate data from various sources. Advancements in predicting ocean surface currents will benefit various applications such as maritime operations, climate studies, and ecosystem management.

• Steel and Composite Structures
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• v.52 no.2
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• pp.135-143
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• 2024

Once the foundation displacement of the transmission tower occurs, additional stress will be generated on the tower members, which will affect the seismic response of transmission tower-line systems (TTLSs). Furthermore, existing research has shown that the reciprocating slippage of joints needs to be considered in the seismic analysis. The hysteretic behavior of joints is obtained by model tests or numerical simulations, which leads to the low modeling efficiency of TTLSs. Therefore, this paper first utilized numerical simulation and model tests to construct a BP neural network for predicting the skeleton curve of joints, and then a numerical model for a TTLS considering the bolt slippage was established. Then, the seismic response of the TTLS under foundation displacement was studied, and the member stress changes and the failed member distribution of the tower were analyzed. The influence of foundation displacement on the seismic performance were discussed. The results showed that the trained BP neural network could accurately predict the hysteresis performance of joints. The slippage could offset part of the additional stress caused by foundation settlement and reduce the stress of some members when the TTLS with foundation settlement was under earthquakes. The failure members were mainly distributed at the diagonal members of the tower leg adjacent to the foundation settlement and that of the tower body. To accurately analyze the seismic performance of TTLSs, the influence of foundation displacement and the joint effect should be considered, and the BP neural network can be used to improve modeling efficiency.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.161-169
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• 2012

The RCP 8.5 scenario based temperature outlook (12.5 km resolution) was combined with high-definition gridded temperature maps (30 m grid spacing) across the Korean Peninsula in order to reclassify the cold hardiness zone for winter barley, a promising grain crop in the future under warmer winter conditions. Reference maps for the January minimum and mean temperature were prepared by applying the watershed-specific geospatial climate prediction schemes to the synoptic observations from 1981 to 2010 across North and South Korea. Decadal changes in the January minimum and mean temperatures projected by a regional version of RCP8.5 climate change scenario were prepared for the 2011-2100 period at 12.5 km grid spacing and were subsequently added to the reference maps, producing the 30 m resolution temperature surfaces for 9 decades from 2011 to 2100. A criterion for threshold temperature to grow winter barley safely in Korea was applied to the future temperature surfaces and the resulting maps were used to predict the production potential of 3 cultivar groups for the 9 future decades under the projected temperature conditions. By 2020s, hulled barley cultivars could be grown safely at the southern part of North Korea as well as the mountainous Gangwon province. Furthermore, most of South Korean rice paddies will be safe for growing naked barley after harvesting rice. Also, dual cropping systems such as 'winter-barley after rice' could be possible at most of the North Korean rice paddies by 2040s. Additional grain production in North Korea could increase up to 4 million tons per year if dual cropping systems can be fully operated, i.e., winter barley after rice at all lowlands and winter barley after maize or potato at all uplands.

• Atmosphere
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• v.31 no.2
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• pp.229-240
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• 2021

The Global Ocean Data Assimilation and Prediction System (GODAPS) in operation at the KMA (Korea Meteorological Administration) is introduced. GODAPS consists of ocean model, ice model, and 3-d variational ocean data assimilation system. GODAPS assimilates conventional and satellite observations for sea surface temperature and height, observations of sea-ice concentration, as well as temperature and salinity profiles for the ocean using a 24-hour data assimilation window. It finally produces ocean analysis fields with a resolution of 0.25 ORCA (tripolar) grid and 75-layer in depth. This analysis is used for providing a boundary condition for the atmospheric model of the KMA Global Seasonal Forecasting System version 5 (GloSea5) in addition to monitoring on the global ocean and ice. For the purpose of evaluating the quality of ocean analysis produced by GODAPS, a one-year data assimilation experiment was performed. Assimilation of global observing system in GODAPS results in producing improved analysis and forecast fields with reduced error in terms of RMSE of innovation and analysis increment. In addition, comparison with an unassimilated experiment shows a mostly positive impact, especially over the region with large oceanic variability.

• The Journal of Society for e-Business Studies
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• v.20 no.1
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• pp.183-199
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• 2015

Due to the Four Major Rivers Restoration Project, Nakdong River Estuary Barrage's designed flood quantity has been largely increased, and this has caused to construct several drainage gates at the right side of Eulsukdo island to secure the safety of downstream river area. For successful functioning of Nakdong River Estuary Barrage, such as flood control, disaster prevention, and the securing of sufficient water capacity, drainage gates at the both sides of island have to operate systematically and reliably. To manage this under restricted personnel and resources, we have implemented the IOS (Integrated Operation System) by integrating previous facilities and resources via information and communication technologies. The IOS has been designed to have higher availability and fault tolerance to function continuously even with the partial system's failure under the emergency situation like flood. Operators can use the system easily and acknowledge alarms of facilities through its IWS (Integrated Warning System) earlier. Preparing for Integrated Water Resources Management and Smart Water Grid, the architecture of IOS conformed to open system standards which will be helpful to link with the other systems easily.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.3
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• pp.195-206
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• 2014

In this study, soil contamination maps related to Cu and Pb were created at the Busan abandoned mine in Korea using a handheld X-Ray Fluorescence(XRF) and Geographic Information Systems(GIS). Hydrological analysis was performed using the Digital Elevation Model(DEM) of the study area to identify the flow directions of surface runoff where pollutants can be dispersed from the soil contamination sources. 24 locations for measuring the soil contamination related to Cu and Pb were selected by considering the result of hydrological analysis. The results measured at the 24 locations using the handheld XRF showed that the highest value of Cu contamination is 8,255ppm and that of Pb is 2,146ppm. The field investigation data were entered into ArcGIS software, and then soil contamination maps regarding Cu and Pb with a 5m grid-spacing were created after performing spatial interpolations using the ordinary kriging method. As a result, we could know that high concentrations of Cu and Pb are presented at the waste and tailings dumps around the abandoned mine openings. This study also showed that the handheld XRF and GIS can be utilized to create soil contamination maps related to Cu and Pb in the field.

• Journal of Biosystems Engineering
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• v.33 no.5
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• pp.362-369
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• 2008

There is developing interest in precision agriculture in Korea, despite the fact that typical Korean fields are less than 1 ha in size. Describing within-field variability in typical Korean production settings is a fundamental first step toward determining the size of management zones and the inter-relationships between limiting factors, for establishment of site-specific management strategies. Measurements of rice (Oriza Sativa L) yield, chlorophyll content, and soil properties were obtained in a small (100-m by 30-m) Korean rice paddy field. Yield data were manually collected on 10-m by 5-m grids (180 samples with 3 samples in each of 60 grid cells) and chlorophyll content was measured using a Minolta SPAD 502 in 2-m by 2-m grids. Soil samples were collected at 275 points to compare results from sampling at different scales. Ten soil properties important for rice production in Korea were determined through laboratory analyses. Variogram analysis and point kriging with and without median polishing were conducted to determine the variability of the measured parameters. Influence of variogram model selection and other parameters on the interpretation of the data was investigated. For many of the data, maximum values were greater than double the minimum values, indicating considerable spatial variability in the small paddy field, and large-scale spatial trends were present. When variograms were fit to the original data, the limits of spatial dependency for rice yield and SP AD reading were 11.5 m and 6.5 m, respectively, and after detrending the limits were reduced to 7.4 m and 3.9 m. The range of spatial dependency for soil properties was variable, with several having ranges as short as 2 m and others having ranges greater than 30 m. Kriged maps of the variables clearly showed the presence of both large-scale (trend) variability and small-scale variability in this small field where it would be reasonable to expect uniformity. These findings indicate the potential for applying the principles and technology of precision agriculture for Korean paddy fields. Additional research is needed to confirm the results with data from other fields and crops.d similar tendency with the result for the frequency less than 20 Hz, but the width of change was reduced highly.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.62-68
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• 2012

Steady-State Visually Evoked Potentials (SSVEP) are natural response signal associated with the visual stimuli with specific frequency. By using SSVEP, occipital lobe region is electrically activated as frequency form equivalent to stimuli frequency with bandwidth from 3.5Hz to 75Hz. In this paper, we propose an experimental paradigm for analyzing EEGs based on the properties of SSVEP. At first, an experiment is performed to extract frequency feature of EEGs that is measured from the image-based visual stimuli associated with specific objective with affordance and object-related affordance is measured by using mirror neuron system based on the frequency feature. And then, linear discriminant analysis (LDA) method is applied to perform the online classification of the objective pattern associated with the EEG-based affordance data. By using the SSVEP measurement experiment, we propose a Brain-Computer Interface (BCI) system for recognizing user's inherent intentions. The existing SSVEP application system, such as speller, is able to classify the EEG pattern based on grid image patterns and their variations. However, our proposed SSVEP-based BCI system performs object pattern classification based on the matters with a variety of shapes in input images and has higher generality than existing system.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.1
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• pp.83-93
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• 2020

East Asia, which includes China, Japan, Korea, and Mongolia, is highly impacted by hydroclimate extremes such drought, flood, and typhoon recent year. In 2017, more than 18.5 million hectares of crops have been damaged in China, and Korea has suffered economic losses as a result of severe drought. Satellite-derived rainfall products are becoming more accurate as space and time resolution become increasingly higher, and provide an alternative means of estimating ground-based rainfall. In this study, we verified the availability of rainfall products by comparing widely used satellite images such as Climate Hazards Groups InfraRed Precipitation with Station (CHIRPS), Global Precipitation Climatology Centre (GPCC), and Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) with ground stations in East Asia. Also, the satellite-based rainfall products were used to calculate the Standardized Precipitation Index (SPI). The temporal resolution is based on monthly images and compared with the past 30 years data from 1989 to 2018. The comparison between rainfall data based on each satellite image products and the data from weather station-based weather data was shown by the coefficient of determination and showed more than 0.9. Each satellite-based rainfall data was used for each grid and applied to East Asia and South Korea. As a result of SPI analysis, the RMSE values of CHIRPS were 0.57, 0.53 and 0.47, and the MAE values of 0.46, 0.43 and 0.37 were better than other satellite products. This satellite-derived rainfall estimates offers important advantages in terms of spatial coverage, timeliness and cost efficiency compared to analysis for drought assessment with ground stations.