• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.215-217
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• 2014

본 논문에서는 ns-3 기반의 IEEE 802.15.4 모의 성능 평가에 대해 기술한다. IT 기술의 발달과 함께 차세대 전력망인 '스마트 그리드'가 대두되고 있다. 이에 따라 무선 센서들 간의 통신을 위해 IEEE 802.15.4 표준 기술이 채택되고 있다. IEEE 802.15.4 표준에는 beacon-enabled mode 와 non beacon-enabled mode 두 가지 채널 접근 기법이 존재하지만 특정 기법의 용도와 목적에 대해서는 구체적으로 명시되지 않는다. 따라서 본 논문에서는 스마트 그리드 환경에서 IEEE 802.15.4 의 두 채널 접근 기법의 성능을 시험하고 beacon-enabled mode 와 non beacon-enabled mode 간의 성능 분석을 통해 beacon-enabled mode 의 효용성에 대하여 연구한다.

• Communications for Statistical Applications and Methods
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• v.27 no.6
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• pp.589-602
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• 2020

The development of smart grids has enabled the easy collection of a large amount of power data. There are some common patterns that make it useful to cluster power consumption patterns when analyzing s power big data. In this paper, clustering analysis is based on distance functions for time series and clustering algorithms to discover patterns for power consumption data. In clustering, we use 10 distance measures to find the clusters that consider the characteristics of time series data. A simulation study is done to compare the distance measures for clustering. Cluster validity measures are also calculated and compared such as error rate, similarity index, Dunn index and silhouette values. Real power consumption data are used for clustering, with five distance measures whose performances are better than others in the simulation.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.130-138
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• 2023

The Smart grids are considered as multi-disciplinary power systems where the communication networks are highly employed. This paper presents optimal wide area measurement system (WAMS) configuration in Nordic power system. The transition from SCADA to WAMS becomes now trend in all power systems to ensure higher reliability and data visibility. The optimization applied in this research considered the geographical regions of the Nordic power system. The research considered all the devices of WAMS namely phasor measurement units (PMUs), phasor data concentrators (PDCs) and communication links. The study also presents two scenarios for optimal WAMS namely base case and N-1 contingency as different operating conditions. The result of this research presents technical and financial results for WAMS configuration in a real power system. The optimization results are performed using MATLAB 2017a software application.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.993-996
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• 2011

최근 그린 IT 에 대한 관심이 점차 고조되면서, 이 사업의 일환으로 저탄소, 녹색 성장을 위한 지능형 전력망인 스마트 그리드의 도입이 발 빠르게 진행되고 있다. 스마트 그리드를 통해 전력 공급자와 소비자의 양방향 통신으로 에너지 효율의 최적화가 가능하지만, 동시에 사이버 공격에 의한 개인정보의 노출위험에 대한 우려도 제기되고 있는 상황이다. 데이터의 안전한 전송을 위해 다양한 암호화 방식이 제안되고 있으며, 본 논문에서는 기밀성에만 초점을 맞춘 Homomorphic 암호화의 허점을 보완하기 위하여 additive Homomorphic 방식을 기반으로 하여 데이터 무결성을 보장 할 수 있는 새로운 방식을 제안하였다. 이 메커니즘을 통해 데이터는 최종 목적지까지 안전하게 도달했으며, 위조 및 변조 되지 않았다는 것을 보장받을 수 있다.

• Journal of computational fluids engineering
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• v.21 no.4
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• pp.1-10
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• 2016

The analysis of characteristics of turbulent flow and thermal boundary layer for natural convection caused by fire along vertical wall is performed. The 4m-high vertical copper plate is heated and kept at a uniform surface temperature of $60^{\circ}C$ and the surrounding fluid (air) is kept at $16.5^{\circ}C$. The flow and temperature is solved by large eddy simulation(LES) of FDS code(Ver.6), in which the viscous-sublayer flow is calculated by Werner-Wengle wall function. The whole analyzed domain is assumed as turbulent region to apply wall function even through the laminar flow is transient to the turbulent flow between $10^9$<$Gr_z$<$10^{10}$ in experiments. The various grids from $7{\times}7{\times}128$ to $18{\times}18{\times}128$ are applied to investigate the sensitivity of wall function to $x^+$ value in LES simulation. The mean velocity and temperature profiles in the turbulent boundary layer are compared with experimental data by Tsuji & Nagano and the results from other LES simulation in which the viscous-sublayer flow is directly solved with many grids. The relationship between heat transfer rate($Nu_z$) and $Gr_zPr$ is investigated and calculated heat transfer rates are compared with theoretical equation and experimental data.

• The Korean Journal of Physiology and Pharmacology
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• v.25 no.6
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• pp.585-592
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• 2021

Cisplatin has been reported to cause side effects such as muscle wasting in humans and rodents. The physiological mechanisms involved in preventing muscle wasting, such as the regulation of AKT, PGC1-α, and autophagy-related factor FOXO3a by MuRF 1 and Atrogin-1, remain unclear following different types of exercise and in various skeletal muscle types. Eight-week-old male Wistar rats (n = 34) were assigned to one of four groups: control (CON, n = 6), cisplatin injection (1 mg/kg) without exercise (CC, n = 8), cisplatin (1 mg/kg) + resistance exercise (CRE, n = 9) group, and cisplatin (1 mg/kg) + aerobic exercise (CAE, n = 11). The CRE group performed progressive ladder exercise (starting with 10% of body weight on a 1-m ladder with 2-cm-interval grids, at 85°) for 8 weeks. The CAE group exercised by treadmill running (20 m/min for 60 min daily, 4 times/week) for 8 weeks. Compared with the CC group, the levels of the autophagy-related factors BNIP3, Beclin 1, LC3-II/I ratio, p62, and FOXO3a in the gastrocnemius and soleus muscles were significantly decreased in the CRE and CAE groups. The CRE and CAE groups further showed significantly decreased MuRF 1 and Atrogin-1 levels and increased phosphorylation of AKT, FOXO3a, and PGC1-α. These results suggest that both ladder and aerobic exercise directly affected muscle wasting by modulating the AKT/PGC1-α/FOXO3a signaling pathways regardless of the skeletal muscle type.

• Smart Media Journal
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• v.8 no.2
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• pp.9-15
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• 2019

Since the computational complexity for hologram generation increases exponentially with respect to the size of the point cloud, parallel processing using CUDA and/or OpenCL library based on multiple GPUs has recently become popular. The CUDA kernel for parallelization needs to consist of threads, blocks, and grids properly in accordance with the number of cores and the memory size in the GPU. In addition, in case of multiple GPU environments, the distribution in grid-by-grid, in block-by-block, or in thread-by-thread is needed according to the number of GPUs. In order to evaluate the performance of CGH generation, we compared the computational speed in CPU, in single GPU, and in multi-GPU environments by gradually increasing the number of points in a point cloud from 10 to 1,000,000. We also present a memory structure design and a calculation method required in the CUDA-based parallel processing to accelerate the CGH (Computer Generated Hologram) generation operation in multiple GPU environments.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.93-104
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• 2024

Demand response is a strategy that encourages customers to adjust their consumption patterns at times of peak demand with the aim to improve the reliability of the power grid and minimize expenses. The integration of renewable energy sources into smart grids poses significant challenges due to their intermittent and unpredictable nature. Demand response strategies, coupled with reinforcement learning techniques, have emerged as promising approaches to address these challenges and optimize grid operations where traditional methods fail to meet such kind of complex requirements. This research focuses on investigating the application of reinforcement learning algorithms in demand response for renewable energy integration. The objectives include optimizing demand-side flexibility, improving renewable energy utilization, and enhancing grid stability. The results emphasize the effectiveness of demand response strategies based on reinforcement learning in enhancing grid flexibility and facilitating the integration of renewable energy.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.3
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• pp.51-65
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• 2024

Accurate electrical load forecasting is important to the effective operation of power systems in smart grids. With the recent development in machine learning, artificial intelligence-based models for predicting power demand are being actively researched. However, since existing models get input variables as numerical features, the accuracy of the forecasting model may decrease because they do not reflect the semantic relationship between these features. In this paper, we propose a scheme for short-term load forecasting by using features extracted through the large language models for input data. We firstly convert input variables into a sentence-like prompt format. Then, we use the large language model with frozen weights to derive the embedding vectors that represent the features of the prompt. These vectors are used to train the forecasting model. Experimental results show that the proposed scheme outperformed models based on numerical data, and by visualizing the attention weights in the large language models on the prompts, we identified the information that significantly influences predictions.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.612-620
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• 2017

Relay coordination in power system is a complex problem and so far, meta-heuristic algorithms and other methods as an alternative approach may not properly deal with large scale relay coordination due to their huge time consuming computation. In some cases the relay coordination could be unachievable. As the urgency for a proper approach is essential, in this paper an innovative and simple relay coordination method is introduced that is able to be applied on optimization algorithms for relay protection coordination. The objective function equation of operating time of relays are divided into two separate functions with less constraints. As the analytical results show here, this equivalent method has a remarkable speed with high accuracy to coordinate directional relays. Two distribution systems including directional overcurrent relays are studied in DigSILENT software and the collected data are examined in MATLAB. The relay settings of this method are compared with particle swarm optimization and genetic algorithm. The analytical results show the correctness of this mathematical and practical approach. This fast coordination method has a proper velocity of convergence with low iteration that can be used in large scale systems in practice and also to provide a feasible solution for protection coordination in smart grids as online or offline protection coordination.