• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.10
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• pp.865-875
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• 2012

In this paper, we optimize antenna locations for a distributed antenna system (DAS) with distributed antenna (DA) ports equipped with multiple antennas under per-DA port power constraint. Maximum ratio transmission and scaled zero-forcing beamforming are employed for single-user and multi-user DAS, respectively. Instead of maximizing the cell average ergodic sum rate, we focus on a lower bound of the expected signal-to-noise ratio (SNR) for the single-cell scenario and the expected signal-to-leakage ratio (SLR) for the two-cell scenario to determine antenna locations. For the single-cell case, optimization of the SNR criterion generates a closed form solution in comparison to conventional iterative algorithms. Also, a gradient ascent algorithm is proposed to solve the SLR criterion for the two-cell scenario. Simulation results show that DAS with antenna locations obtained from the proposed algorithms achieve capacity gains over traditional centralized antenna systems.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.9
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• pp.11-19
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• 2006

Design program was developed to determine the external shape of the supersonic axisymmetric inlet by combining conical flow solver and approximation technique of conical shock with gradient-based optimization algorithm. Inlet designs were carried out under various operation conditions through optimization with respectively two object functions which consist of pressure recovery and cowl drag and with constraints about shock position, cowl shape, and minimum throat area. New object function consisting of pressure recovery and drag of the external cowl was proposed and the optimized shapes from new object function were compared to the ones from the old object function which maximize only the pressure recovery. Through computations of inviscid and turbulent flow, was tested performance of the design program and performance estimated in design program agreed well with computation results for inlets designed under various flight conditions.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.5
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• pp.1059-1068
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• 1990

The minimum weight design for the simply-supported eccentrically stiffened plates subjected to combined loads is studied according to the stiffening configuration. The optimal programming is accomplished by formulating the design requirements in terms of a mathematical programming problem, and by using the gradient projection algorithm. The Huber type equilibrium equation is used as the governing equation for the overall buckling. The overall buckling of stiffened plates and the local buckling of the unstiffened plate between stiffeners and the stiffeners themselves are used as behavior constraints. Results of design examples for the orthogonally stiffening case compared with those of the other study support that the present study is feasible. Design examples for the symmetrically oblique stiffening case are presented and the results indicate that a significant improvement in design efficiency may be achieved through symmetrically oblique stiffening compared to the orthogonal stiffening under the combined loading condition.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.842-848
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• 2008

This paper deal with uncertainty problem by using Type-2 fuzzy logic set for nonlinear system modeling. We design Type-2 fuzzy logic system in which the antecedent and the consequent part of rules are given as Type-2 fuzzy set and also analyze the performance of the ensuing nonlinear model with uncertainty. Here, the apexes of the antecedent membership functions of rules are decided by C-means clustering algorithm and the apexes of the consequent membership functions of rules are learned by using back-propagation based on gradient decent method. Also, the parameters related to the fuzzy model are optimized by means of particle swarm optimization. The proposed model is demonstrated with the aid of two representative numerical examples, such as mathematical synthetic data set and Mackey-Glass time series data set and also we discuss the approximation as well as generalization abilities for the model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1A
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• pp.76-83
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• 2009

In this paper, we provide opportunistic scheduling schemes for elastic services in OFDMA systems with fairness constraints for each user. We adopt the network utility maximization framework in which a utility function is defined for each user to represent its level of satisfaction to the service. Since we consider elastic services whose degree of satisfaction depends on its average data rate, we define the utility function of each user as a function of its average data rate. In addition, for fair resource allocation among users, we define fairness requirements of each user by using utility functions. We first formulate an optimization problem for each fairness requirement that aim at maximizing network utility, which is defined as the sum of utilities of users. We then develop an opportunistic scheduling scheme for each fairness requirement by solving the problem using a dual approach and a stochastic sub-gradient algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.12
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• pp.1328-1336
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• 2012

Compared to terrestrial RF communications, underwater acoustic communications have several limitations such as limited bandwidth, high level of fading effects, and a large underwater propagation delay. In this paper, in order to tackle those limitations of underwater communications and to make it possible to form a large underwater monitoring systems, we propose a hierarchical underwater network architecture, which consists of underwater sensors, clusterheads, underwater/surface sink nodes, autonomous underwater vehicles (AUVs). In the proposed architecture, for the maximization of packet delivery ratio and the minimization of underwater sensor's energy consumption, a hybrid routing protocol is used. More specifically, cluster members use Tree based routing to transmit sensing data to clusterheads. AUVs on optimal trajectory movements collect the aggregated data from clusterhead and finally forward the data to the sink node. Also, in order to minimize the maximum travel distance of AUVs, an Integer Linear Programming based algorithm is employed. Performance analysis through simulations shows that the proposed architecture can achieve a higher data delivery ratio and lower energy consumption than existing routing schemes such as gradient based routing and geographical forwarding. Start after striking space key 2 times.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.416-424
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• 2017

In this study, we propose a design of digits recognition system based on RBFNNs through a comparative study of pre-processing algorithms in order to recognize digits in handwritten. Histogram of Oriented Gradient(HOG) is used to get the features of digits in the proposed digits recognition system. In the pre-processing part, a dimensional reduction is executed by using Principal Component Analysis(PCA) and (2D)2PCA which are widely adopted methods in order to minimize a loss of the information during the reduction process of feature space. Also, The architecture of radial basis function neural networks consists of three functional modules such as condition, conclusion, and inference part. In the condition part, the input space is partitioned with the use of fuzzy clustering realized by means of the Fuzzy C-Means algorithm. Also, it is used instead of gaussian function to consider the characteristic of input data. In the conclusion part, the connection weights are used as the extended type of polynomial expression such as constant, linear, quadratic and modified quadratic. By using MNIST handwritten digit benchmarking database, experimental results show the effectiveness and efficiency of proposed digit recognition system when compared with other studies.

• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.266-274
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• 2009

An abdominal aortic aneurysm occurs most commonly in older individuals (between 65 and 75), and more in men and smokers. The most important complication of an abdominal aortic aneurysm is rupture, which is most often a fatal event. An abdominal aortic aneurysm weakens the walls of the blood vessel, leaving it vulnerable to bursting open, or rupturing, and spilling large amounts of blood into the abdominal cavity. surface modeling is very useful to surgery for quantitative analysis of abdominal aortic aneurysm. the 3D representation and surface modeling an abdominal aortic aneurysm structure taken from Multi Detector Computed Tomography. The construction of the 3D model is generally carried out by staking the contours obtained from 2D segmentation of each CT slice, so the quality of the 3D model strongly defends on the precision of segmentation process. In this work we present deformable model algorithm. deformable model is an energy-minimizing spline guided by external constraint force. External force which we call Gradient Vector Flow, is computed as a diffusion of a gradient vectors of gray level or binary edge map derived from the image. Finally, we have used snakes successfully for abdominal aortic aneurysm segmentation the performance of snake was visually and quantitatively validated by experts.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.568-574
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• 2020

In this paper, we propose a method to reduce the square root computation having high computation complexity in Canny edge detection algorithm using image processing. The proposed method is to reduce the number of operation calculating gradient magnitude using pixel's continuity using make a specific pattern instead of square root computation in gradient magnitude calculating operation. Using various test images and changing number of hole pixels, we can check for calculate match rate about 97% for one hole, and 94%, 90%, 88% when the number of hole is increased and measure decreasing computation time about 0.2ms for one hole, and 0.398ms, 0.6ms, 0.8ms when the number of hole is increased. Through this method, we expect to implement low power embedded vision system through high accuracy and a reduced operation number using two-hole pixels.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.171-177
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• 2021

Through the rapid developments in machine learning, there have been diverse utilization approaches not only in industrial fields but also in daily life. Implementations of machine learning on financial data, also have been of interest. Herein, we employ machine learning algorithms to store sales data and present future applications for fintech enterprises. We utilize diverse missing data processing methods to handle missing data and apply gradient boosting machine learning algorithms; XGBoost, LightGBM, CatBoost to predict the future revenue of individual stores. As a result, we found that using median imputation onto missing data with the appliance of the xgboost algorithm has the best accuracy. By employing the proposed method, fintech enterprises and customers can attain benefits. Stores can benefit by receiving financial assistance beforehand from fintech companies, while these corporations can benefit by offering financial support to these stores with low risk.