• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.32 no.4
• /
• pp.88-94
• /
• 2004

The electrical design of the Ka-band antenna for the domestic Communications and Broadcasting Satellite (CBS) is described. The antenna has the offset Gregorian structure and is installed on the Earth-facing panel of the satellite. The electrical performance specifications for the antenna were determined from the required EIRP and G/T through the payload level performance analysis. This paper utilized the reflector shaping technology for the trade-off among the major performance parameters, resulting in compliance of all the parameters. The designed antenna shows 37.95 dBi EOC (End of Coverage) gain and 28.7 dB sidelobe isolation for transmit band, and 37.49 dBi EOC gain and 31.1 dB sidelobe isolation for receive band, The electrical performances of the antenna have been verified via the electrical testing of a manufactured EQM (Engineering Qualification Model) antenna.

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

• KIPS Transactions on Computer and Communication Systems
• /
• v.12 no.3
• /
• pp.103-110
• /
• 2023

With the spread of the Internet, anonymous communities emerged along with the activation of communities for communication between people, and many users are doing harm to others, such as posting aggressive posts and leaving comments using anonymity. In the past, administrators directly checked posts and comments, then deleted and blocked them, but as the number of community users increased, they reached a level that managers could not continue to monitor. Initially, word filtering techniques were used to prevent malicious writing from being posted in a form that could not post or comment if a specific word was included, but they avoided filtering in a bypassed form, such as using similar words. As a way to solve this problem, deep learning was used to monitor posts posted by users in real-time, but recently, the community uses words that can only be understood by the community or from a human perspective, not from a general Korean word. There are various types and forms of characters, making it difficult to learn everything in the artificial intelligence model. Therefore, in this paper, we proposes a preprocessing technique in which each character of a sentence is imaged using a CNN model that learns the consonants, vowel and spacing images of Korean word and converts characters that can only be understood from a human perspective into characters predicted by the CNN model. As a result of the experiment, it was confirmed that the performance of the LSTM, BiLSTM and CNN-BiLSTM models increased by 3.2%, 3.3%, and 4.88%, respectively, through the proposed preprocessing technique.

• Journal of Korean Neurosurgical Society
• /
• v.47 no.6
• /
• pp.446-453
• /
• 2010

Objective : The purpose of this study was to analyze the biomechanical effects of three different constrained types of an artificial disc on the implanted and adjacent segments in the lumbar spine using a finite element model (FEM). Methods : The created intact model was validated by comparing the flexion-extension response without pre-load with the corresponding results obtained from the published experimental studies. The validated intact lumbar model was tested after implantation of three artificial discs at L4-5. Each implanted model was subjected to a combination of 400 N follower load and 5 Nm of flexion/extension moments. ABAQUS$^{TM}$ version 6.5 (ABAQUS Inc., Providence, RI, USA) and FEMAP version 8.20 (Electronic Data Systems Corp., Plano, TX, USA) were used for meshing and analysis of geometry of the intact and implanted models. Results : Under the flexion load, the intersegmental rotation angles of all the implanted models were similar to that of the intact model, but under the extension load, the values were greater than that of the intact model. The facet contact loads of three implanted models were greater than the loads observed with the intact model. Conclusion : Under the flexion load, three types of the implanted model at the L4-5 level showed the intersegmental rotation angle similar to the one measured with the intact model. Under the extension load, all of the artificial disc implanted models demonstrated an increased extension rotational angle at the operated level (L4-5), resulting in an increase under the facet contact load when compared with the adjacent segments. The increased facet load may lead to facet degeneration.

• KIEE International Transactions on Power Engineering
• /
• v.5A no.4
• /
• pp.396-402
• /
• 2005

In an electricity market with imperfect competition, participants devise bidding plans and transaction strategies to maximize their own profits. The market price and the quantity are concerned with the operation reserve as well as the bidding system and demand curves in an electricity market. This paper presents a market model combined by an energy market and an operating reserve market. The competition of the generation producers in the combined market is formulated as a gaming of selecting bid parameters such as intersections and slopes in bid functions. The Nash Equilibrium (NE) is analyzed by using bi-level optimization; maximization of Social Welfare (SW) and maximization of the producers' profits.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.55 no.9
• /
• pp.392-398
• /
• 2006

Maintenance scheduling of generating units (MSU) has strategic dimension in an oligopolistic market. Strategic MSU of gencos can affect a market power through capacity withdrawal which is related to bidding strategy in an generation wholesale market. This paper presents a combined framework that models the interrelation between competitive bidding and strategic MSU. The combined game model is represented as some sub-optimization problems of a market operator (MO) and gencos, that should be solved through bi-level optimization scheme. The gradient method with dual variables is also adopted to calculate a Nash Equilibrium (NE) by an iterative update technique in this paper. Illustrative numerical example shows that NE of a supply function equilibrium is obtained properly by using proposed solution technique. The MSU made by MO is compared with that by each genco and that under perfect competition market.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.38 no.3
• /
• pp.41-54
• /
• 2001

This paper propose an active rule and its semantic model integrating active rule system into temporal database. Most of previous works have been focused on condition action(CA) rule for temporal relations. However, proposed active rule model supports full SQL:3 trigger functionalitics including transition variable and table as well as tuple-level and statement-level active rules in E CA granularity. A bi-temporal concept of active rule and valid time event are also proposed newlv.

• Structural Engineering and Mechanics
• /
• v.85 no.4
• /
• pp.469-484
• /
• 2023

A deep recursive bidirectional Cuda Deep Neural Network Long Short Term Memory (Bi-CuDNNLSTM) layer is recruited in this paper to predict the entire force time histories, and the corresponding hysteresis and backbone curves of reinforced concrete (RC) bridge piers using experimental fast and slow cyclic tests. The proposed stacked Bi-CuDNNLSTM layers involve multiple uncertain input variables, including horizontal actuator displacements, vertical actuators axial loads, the effective height of the bridge pier, the moment of inertia, and mass. The functional application programming interface in the Keras Python library is utilized to develop a deep learning model considering all the above various input attributes. To have a robust and reliable prediction, the dataset for both the fast and slow cyclic tests is split into three mutually exclusive subsets of training, validation, and testing (unseen). The whole datasets include 17 RC bridge piers tested experimentally ten for fast and seven for slow cyclic tests. The results bring to light that the mean absolute error, as a loss function, is monotonically decreased to zero for both the training and validation datasets after 5000 epochs, and a high level of correlation is observed between the predicted and the experimentally measured values of the force time histories for all the datasets, more than 90%. It can be concluded that the maximum mean of the normalized error, obtained through Box-Whisker plot and Gaussian distribution of normalized error, associated with unseen data is about 10% and 3% for the fast and slow cyclic tests, respectively. In recapitulation, it brings to an end that the stacked Bi-CuDNNLSTM layer implemented in this study has a myriad of benefits in reducing the time and experimental costs for conducting new fast and slow cyclic tests in the future and results in a fast and accurate insight into hysteretic behavior of bridge piers.

• The Journal of the Acoustical Society of Korea
• /
• v.25 no.8
• /
• pp.389-394
• /
• 2006

Mid-Frequency bistatic reverberation level is modeled using ray theoretic algorithms. The algorithm assumes multiple forward/backward scatter along with reciprocity in the Propagation paths. The environments modeled are assumed to be range independent in bathymetry, bottom scattering and surface scattering. Mid-Frequency bistatic scattering algorithm is used as a scattering model. A comparison of predicted reverberation versus time with measured data is presented to verify the bistatic reverberation model. The result demonstrates that it is possible to obtain reasonable reverberation Predictions in experimental site.

• Journal of Korean Society of Transportation
• /
• v.26 no.5
• /
• pp.175-184
• /
• 2008

Uncertainties are unavoidable in engineering applications. In this paper we propose an alpha reliable multi-variable network design problem under demand uncertainty. In order to decide the optimal capacity enhancement, three performance measures based on 3E(Efficiency, Equity, and Environmental) are considered. The objective is to minimize the total budget required to satisfy alpha reliability constraint of total travel time, equity ratio, and total emission, while considering the route choice behavior of network users. The problem is formulated as the chance-constrained model for application of alpha confidence level and solved as a lexicographic optimization problem to consider the multi-variable. A simulation-based genetic algorithm procedure is developed to solve this complex network design problem(NDP). A simple numerical example ispresented to illustrate the features of the proposed NDP model.