• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.989-995
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• 2017

As is known to all that the output of wind power generation has a character of randomness and volatility because of the influence of natural environment conditions. At present, the research of wind power prediction mainly focuses on point forecasting, which can hardly describe its uncertainty, leading to the fact that its application in practice is low. In this paper, a wind power range prediction model based on the multiple output property of BP neural network is built, and the optimization criterion considering the information of predicted intervals is proposed. Then, improved Particle Swarm Optimization (PSO) algorithm is used to optimize the model. The simulation results of a practical example show that the proposed wind power range prediction model can effectively forecast the output power interval, and provide power grid dispatcher with decision.

• 한국전산유체공학회:학술대회논문집
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• 1998.11a
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• pp.42-47
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• 1998

The pressure-based methods are very popular in CFD because it requires less computer core memory compared to other coupled or density-based solvers. Currently structured-mesh methodology based on pressure-based algorithm is quite mature to apply to the practical problems. The unstructured mesh method needs much more computer memory than the structured-mesh method. However the pressure-based method utilizing the sequential approach does not require very large memory used for unstructured-mesh density-based solvers. The present study has developed the unstructured grid pressure-based method. Cell-centered finite volume method was selected due to robustness for imposing various boundary conditions and easy implementation of higher-order upwind scheme. The predictive capability of present method has validated against several benchmark problems.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.484-492
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• 2016

Smart grid (SG) technology is now elevating the conventional power grid system to one that functions more cooperatively, responsively, and economically. When applied in an SG the demand side management (DSM) technique can improve its reliability by dynamically changing electricity consumption or rescheduling it. In this paper, we propose a new SG scheduling scheme that uses the DSM technique. To achieve effective SG management, we adopt a mixed pricing strategy based on the Rubinstein-Stahl bargaining game and a repeated game model. The proposed game-based pricing strategy provides energy routing for effective energy sharing and allows consumers to make informed decisions regarding their power consumption. Our approach can encourage consumers to schedule their power consumption profiles independently while minimizing their payment and the peak-to-average ratio (PAR). Through a simulation study, it is demonstrated that the proposed scheme can obtain a better performance than other existing schemes in terms of power consumption, price, average payment, etc.

• Computers and Concrete
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• v.34 no.4
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• pp.477-487
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• 2024

The in-situ stresses of concrete are an essential index for assessing the safety performance of concrete structures. Conventional methods for pore pressure release often face challenges in selecting drilling ring parameters, uncontrollable stress release, and unstable detection accuracy. In this paper, the parameters affecting the results of the concrete ring hole stress release method are cross-combined, and finite elements are used to simulate the combined parameters and extract the stress release values to establish a training set. The GridSearchCV function is utilized to determine the optimal hyperparameters. The mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R²) are used as evaluation indexes to train the gradient boosting decision tree (GBDT) algorithm, and the other three common algorithms are compared. The RMSE of the GBDT algorithm for the test set is 4.499, and the R² of the GBDT algorithm for the test set is 0.962, which is 9.66% higher than the R² of the best-performing comparison algorithm. The model generated by the GBDT algorithm can accurately calculate the concrete in-situ stresses based on the drilling ring parameters and the corresponding stress release values and has a high accuracy and generalization ability.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.227-230
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• 2014

LTE 3GPP standard defines several QCI (QoS Class Identifier) classes to provide differential QoS, depending on the requirements of different user applications.These QCI values have been characterized in terms of priority, packet loss and delay budget. In spite of the availability of this robust QoS framework in LTE, there is no such scheduling algorithm that has its working principle based on this framework. The responsibility of fulfilling the user requirements, while satisfying the service class requirements is left upon the cellular service provider and it is an open issue at present. To solve this problem, we have proposed a MAC scheduler, which defines the priority of different users based on their bearer specification and provides desired QoS in terms of the achieved throughput through the resource block allocation based on calculated user priority.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.619-628
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• 2012

The ZigBee network has been considered to monitor electricity usage of home appliances in the smart grid network. ZigBee, however, may suffer from a coexistence problem with wireless local area network (WLAN). In this paper, to resolve the coexistence problem between ZigBee network and WLAN, we propose a new protocol constructing a cognitive smart grid network for supporting monitoring of home appliances. In the proposed protocol, home appliances first estimates the transmission timing and channel information of WLAN by reading request to send/clear to send (RTS/CTS) frames of WLAN. Next, based on the estimated information, home appliances transmit a data at the same time as WLAN transmission. To manage the interference between WLAN and smart grid network, we propose a cognitive beamforming algorithm. The beamforming algorithm is designed to guaranteeing zero interference to WLAN while satisfying a required rate for smart metering. We also propose an energy efficient rate adaptation algorithm. By slowing down the transmission rate while satisfying an imperceptible impact of quality of service (QoS) of the receiver, the home appliance can significantly save transmit power. Numerical results show that the proposed multiple antenna technique provides reliable communications for smart metering with reduced power comparing to the simple transmission technique.

• Journal of Korea Multimedia Society
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• v.24 no.11
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• pp.1538-1551
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• 2021

The current drone flight plan creation creates a flight path point of two-dimensional coordinates on the map and sets an arbitrary altitude value considering the altitude of the terrain and the possible flight altitude. If the created flight path is a simple terrain such as a mountain or field, or if the user is familiar with the terrain, setting the flight altitude will not be difficult. However, for drone flight in a city where buildings are dense, a safer and more precise flight path generation method is needed. In this study, using high-precision spatial information, we construct a drone safety flight map with a 3D grid map structure and propose a flight path search algorithm based on it. The safety of the flight path is checked through the virtual drone flight simulation extracted by searching for the flight path based on the 3D grid map created by setting weights on the properties of obstacles and terrain such as buildings.

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.3
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• pp.201-208
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• 2015

The effects of dead-time and offset error, which cause output current distortion in single-phase grid-connected inverters are investigated this paper. Offset error is typically generated by measuring phase current, including the voltage unbalance of analog devices and non-ideal characteristics in current measurement paths. Dead-time inevitably occurs during generation of the gate signal for controlling power semiconductor switches. Hence, the performance of the grid-connected inverter is significantly degraded because of the current ripples. The current and voltage, including ripple components on the synchronous reference frame and stationary reference frame, are analyzed in detail. An algorithm, which has the proportional resonant controller, is also proposed to reduce current ripple components in the synchronous PI current regulator. As a result, computational complexity of the proposed algorithm is greatly simplified, and the magnitude of the current ripples is significantly decreased. The simulation and experimental results are presented to verify the usefulness of the proposed current ripple reduction algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.117-126
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• 2010

In order to obtain more clear x-ray images, an antiscatter grid, which can absorb the scattered rays, is employed. In the high-resolution direct digital radiography, however, the artifacts due to the grid are visible. In this paper, the grid artifacts are reduced by applying simple 1-dimensional low-pass filters in the spatial domain based on the rotated grid. Since the proposed algorithm does not use any detection scheme for the artifact frequencies and discrete Fourier transforms for 2-dimensional filters, it can simply and fast reduce the grid artifacts. The performance using the order 1 average filter is compatible to that of using 2-dimensional filters in the frequency domain.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.230-233
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• 2011

Chronic disease is linked to patient's' lifestyle. Therefore, doctor has to monitor his/her patient over time. This may involve reviewing many reports, finding any changes, and modifying several treatments. One solution to optimize the burden is using a visualizing tool over time such as a timeline-based visualization tool where all reports and medicine are integrated in a problem centric and time-based style to enable the doctor to predict and adjust the treatment plan. This solution was proposed by Bui et. al. [2] to observe the medical history of a patient. However, there was limitation of studying the diabetes patient's history to find out what was the cause of the current development in patient's condition; moreover what would be the prediction of current implication in one of the diabetes' related factors (such as fat, cholesterol, or potassium). In this paper, we propose a Grid-based Interactive Diabetes System (GIDS) to support bioinformatics analysis application for diabetes diseases. GIDS used an agglomerative clustering algorithm as clustering correlation algorithm as primary algorithm to focus medical researcher in the findings to predict the implication of the undertaken diabetes patient. The algorithm was Chronological Clustering proposed by P. Legendre [11] [12].