• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.647-660
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• 2022

To prepare an atmospheric correction model suitable for CAS500-4 (Compact Advanced Satellite 500-4), this letter examined an atmospheric correction experiment using Sentinel-2 images having similar spectral characteristics to CAS500-4. Studies to compare the atmospheric correction results depending on different Aerosol Optical Depth (AOD) data are rarely found. We conducted a comparison of Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH), Sen2Cor, and Second Simulation of the Satellite Signal in the Solar Spectrum - Vector (6SV) version 1.1 and 2.1, using Geo-Kompsat 2A (GK2A) Advanced Meteorological Imager (AMI) and Aerosol Robotic Network (AERONET) AOD data. In this experiment, 6SV2.1 seemed more stable than others when considering the correlation matrices and the output images for each band and Normalized Difference Vegetation Index (NDVI).

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.43-50
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• 2024

This manuscript proposes an artificial intelligence-based(AI) energy platform system that efficiently use existing energy than creating new energy than creating new energy sources. To this end, it collects public information data portal and statistics data portal and data emissions, including energy usage and greenhouse gas emissions, including energy consumption and greenhouse gas emissions.In addition, it provides strong security and personal information protection functions to overcome the limit of existing energy platform. Through the built energy platform, improving power supply and user convenience of users and users to contribute to global warming issues.In this paper, the contents to implement the contents of the system, and improvement direction from the future completion and improvement direction.

• Journal of IKEEE
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• v.23 no.1
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• pp.120-126
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• 2019

Recently, accurate prediction of power consumption based on machine learning techniques in Internet of Energy (IoE) has been actively studied using the large amount of electricity data acquired from advanced metering infrastructure (AMI). In this paper, we propose a deep learning model based on Gated Recurrent Unit (GRU) as an artificial intelligence (AI) network that can effectively perform pattern recognition of time series data such as the power consumption, and analyze performance of the prediction based on real household power usage data. In the performance analysis, performance comparison between the proposed GRU-based learning model and the conventional learning model of Long Short Term Memory (LSTM) is described. In the simulation results, mean squared error (MSE), mean absolute error (MAE), forecast skill score, normalized root mean square error (RMSE), and normalized mean bias error (NMBE) are used as performance evaluation indexes, and we confirm that the performance of the prediction of the proposed GRU-based learning model is greatly improved.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1829-1836
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• 2021

Cloud detection means determining the presence or absence of clouds in a pixel in a satellite image, and acts as an important factor affecting the utility and accuracy of the satellite image. In this study, among the satellites of various advanced organizations that provide cloud detection data, we intend to perform quantitative and qualitative comparative analysis on the difference between the cloud detection data of GK-2A/AMI, Terra/MODIS, and Suomi-NPP/VIIRS. As a result of quantitative comparison, the Proportion Correct (PC) index values in January were 74.16% for GK-2A & MODIS, 75.39% for GK-2A & VIIRS, and 87.35% for GK-2A & MODIS in April, and GK-2A & VIIRS showed that 87.71% of clouds were detected in April compared to January without much difference by satellite. As for the qualitative comparison results, when compared with RGB images, it was confirmed that the results corresponding to April rather than January detected clouds better than the previous quantitative results. However, if thin clouds or snow cover exist, each satellite were some differences in the cloud detection results.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.4
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• pp.369-375
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• 2023

In this paper, we compared and analyzed the power load patterns of dormitory buildings and office buildings to use them as basic data (demand analysis and capacity design) for the design and operation of microgrids for multi-use facilities, and the following conclusions were got. During the daytime on regular weekdays, the power consumption load pattern of office buildings was relatively large at 264.0~332.3 kWh, and during the evening hours, the power consumption load pattern of dormitory buildings was relatively large at 233.0~258.3 kWh. In the case of vacation, during the daytime on weekdays, the power consumption load pattern of office buildings was relatively large at 279.1~407.4 kWh, and in the evening, the power consumption load pattern of dormitory buildings was relatively high at 280.1~394.1 kWh. During the daytime on regular weekends, the power consumption of dormitory-type buildings was relatively high at 133.5~201.6 kWh, and it was found that the power consumption of dormitory-type buildings appeared relatively high at 187.5~252.1 kWh. During a vacation in the daytime on weekends, the power consumption of dormitory-type buildings was found to be 186.5 kWh~ and 218.6 kWh. The increase in power consumption during a vacation (December-February) compared to normal (April-June) was thought to be due to an increase in electricity demand, and the reason for the higher power consumption in dormitory buildings during the vacation was due to reduced working hours in office buildings.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1653-1661
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• 2022

In this study, the classification of cold water and normal water based on Geo-Kompsat 2A images was performed. Daily mean surface temperature products provided by the National Meteorological Satellite Center (NMSC) were used, and convolution neural network (CNN) deep learning technique was applied as a classification algorithm. From 2019 to 2022, the cold water occurrence data provided by the National Institute of Fisheries Science (NIFS) were used as the cold water class. As a result of learning, the probability of detection was 82.5% and the false alarm ratio was 54.4%. Through misclassification analysis, it was confirmed that cloud area should be considered and accurate learning data should be considered in the future.

• Proceedings of the Materials Research Society of Korea Conference
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• 1994.11a
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• pp.1-1
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• 1994

;The electronic state calculations for various types of ceramic materials have beell performed by the use of $DV-X\;{\alpha}$ cluster method. The molecular orbital levels and wave functions for model clusters have been computed to study the electronic properties ami chemical bonding of the ceramics. For ${\beta}-sialon(Si_{6-z}Al_zO_zN_{8-z})$ which is a high temperature structural material based on ${\beta}-Si_3N_4$, we have made model cluster calculations to estimate the strength of chemical bonding between atoms by the Mulliken population analysis. It is found that the covalent bonding between Si and N atoms is very strong in pure ${\beta}-Si_3N_4$, but the covalency around solute atom is considerably weakened when Si atom is substituted by AI. This tendency is enhanced by an additional substitution of oxygen atom for N. The result calculated can well explain the experimental data of changes in mechanical properties such as the reductions of Young's modulus and Vickers hardness with increment of z-value in ${\beta}-sialon$. Various model clusters for transition metal oxides which show many interesting physical and chemical properties have also been calculated. High-valent perovskite-type iron oxides EMFe0_3E(M=Ca and Sr) possess very interesting magnetic and chemical properties. In these oxides, iron exists as $Fe^{4+}$ state, but the experimental measurement of Mossba~er effect suggests that disproportionation $2Fe^{4+}=Fe^{3+}+Fe^{5+}$ takes place for $CaFe0_3$ at low temperatures. The model cluster calculations for these compounds indicated the existence of considerably strong covalent bonding of Fe-O. The calculations of hyperfine interaction at iron neucleus show very good agreement with the experimental Mossbauer measurements. The result calculated also implies that the disproportionation reaction is strongly possible by assuming the quenching of breathing phonon mode at low temperatures.tures.

• Korean Journal of Culture and Social Issue
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• v.27 no.4
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• pp.529-559
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• 2021

This study examines how people perceive and experience busyness, which is a great social pressure in the Korean society, and The socio-psychological motives that drive people's different paces of life, such as busyness or slowness, despite being in the same busy reality, were examined. Furthermore, an in-depth study was conducted on the adaptation factors in the real society according to the speed of individual life. The analysis of this study was based on an in-depth interview data of 21 unmarried men and women in their 20s and 30s, and was conducted using a phenomenological qualitative analysis method. As a result, the perception and experience of being busy had both positive and negative parts. The components of socio-psychological motivation that affect the speed of an individual's life are 'internalization of positive values of (busy/rest)', '(future/present) centric', 'selection & concentration/Inertial busyness', 'personality characteristics' were derived. In addition, 'self-selection', 'successful time management', and 'maintenance of psychological health' were derived as common factors among adaptation factors in real society, 'a sense of achievement' and 'understanding and accepting self-characteristics' were derived as discriminatory factors. became Based on these results, the value and meaning of being busy in Korean society was discussed from a social psychology perspective, and a new perspective was presented to existing studies and discussions related to the speed of life. In addition, several follow-up studies were proposed.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.311-318
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• 2016

IoT(Internet of Things areas) rich information based on the user easy access to service creation must be one of the power system of specificity due following: The IoT spread obstacle to the act be, and 'Smart Grid information of this is not easy under power plants approach the Directive on the protection measures, particularly when stringent security policies IoT technologies applied to Advanced Metering Infrastructure sector has been desired. This is a situation that occurs is limited to the application and use of IoT technologies in the power system. Power Information Network is whilst closed network operating is has a smart grid infrastructure, smart grid in an open two-way communication for review and although information security vulnerabilities increased risk of accidents increases as according to comprehensive security policies and technologies are required and can. In this paper, the IoT platform architecture design of information systems as part of the power of research and development IoT-based energy information platform aims. And to establish a standard framework for a connection to one 'Sensor-Gateway-Network-platform sensors Service' to provide power based on the IoT services and solutions. Framework is divided into "sensor-gateway" platform to link information modeling and gateways that can accommodate the interlocking standards and handling protocols variety of sensors Based on this real-time data collection, analysis and delivery platform that performs the role of the relevant and to secure technology.