• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1309-1316
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• 2016

This paper suggests adjusting TCP for smartphones that often have small size data transmission tendency. Usage of smartphones has been risen dramatically in recent years, including frequent usage of real-time map search, public transportation search, online games, and SNS. Because the small size data transmission ends before the phase of the TCP congestion avoidance, this paper suggests an algorithm that increases the transmission speed ahead of the traffic congestion event. The algorithm reduces unnecessary delay by data size-driven adjustment of the Linux Quick ACK and Nagle's algorithm. Therefore, TCP is improved to maintain a high transmission rate steadily in small data transmission.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.337-344
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• 2004

Most of the virtual space constructed sufficiently realistic need a lot of memory space to navigate smoothly. And this kind of virtual space also requires real-time responsibility for the navigation as well as realism. In the off-line virtual system, real-time responsibility can be resolved by using large scale if secondary memory. In the web-based online virtual system, on the other hand, real-time responsibility is highly related to the latency time of network data communication. This induces the necessity of the algorithm for fast data loading. In this paper, we propose and verify the validity of the two methodology for cell leading algorithm. According to the results of computer simulation, the algorithm using hexagonal type cell promotes the real-time responsibility over 30％ than that of the rectangular type.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.68-80
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• 2016

This study proposes the traffic prediction and optimal traffic control system based on cell transmission model and genetic algorithm in cloud environment. The proposed prediction and control system consists of four parts. 1) Data preprocessing module detects and imputes the corrupted data and missing data points. 2) Data-driven traffic prediction module predicts the future traffic state using Multi-level K-Nearest Neighbor (MK-NN) Algorithm with stored historical data in SQL database. 3) Online traffic simulation module simulates the future traffic state in various situations including accident, road work, and extreme weather condition with predicted traffic data by MK-NN. 4) Optimal road control module produces the control strategy for large road network with cell transmission model and genetic algorithm. The results show that proposed system can effectively reduce the Vehicle Hours Traveled upto 60%.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.5
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• pp.61-69
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• 2015

We are in overload status of information not just in a flood of information due to the data pouring from various kinds of mobile devices, online and Social Network Service(SNS) every day. While there are many existing information already created, lots of new information has been created from moment to moment. Linkage analysis has the shortcoming in that it is difficult to find the information we want since the number of rules increases geometrically as the number of item increases with the method of finding out frequent item set where the frequency of item is bigger than minimum support in this information. In this regard, this thesis proposes WT-algorithm that represents the transaction data set as Boolean variable item and grants weight to each item by making algorithm with Quine-McKluskey used to simplify the logical function. The proposed algorithm can improve efficiency of data mining by reducing the unnecessary rules due to the advantage of simplification regardless of number of items.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.306-314
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• 2004

Some receiver(and most transmit) beamforming algorithms with an array antenna at a cellular CDMA base stations require accurate internal and external calibrations. The external calibration, which usually needs to be done only once, determines the array manifolds, i.e. the complex response of each antenna as a function of DOA(Directions of Arrival). The internal calibrations are necessary because characteristics of RF/IF circuity of each receiver chain vary differently in response to temperature or humidity changes. We propose an iterative subspace-based calibration algorithm for an asynchronous CDMA-based antenna away in the presence of unknown gain and phase error is presented. We verify the subspace-based calibration algorithms by performing the experiment using measured data. Also, we propose an efficient algorithm using the simulated annealing technique. This algorithm overcomes the problem of the initial guessing in the subspace-based approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.482-487
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• 2008

In case of flooding, the underwater flight vehicle (UFV) executes the blowing by blowing ballast tanks off using high pressure air (HPA), while it also uses control planes and a propulsion unit to reduce the overshoot depth caused by a flooding and blowing sequence. However, the conventional whole HPA blow-off method lets the body on the surface after blowing despite slight flooding. This results in the unnecessary mission failure or body exposure. Therefore, it is necessary to keep the body at the near surface by the blowing control while reducing the overshoot depth. To solve this problem, an adaptive blowing control algorithm, which is based on the decomposition method expanding the expert knowledge in depth control and the adaptive method using fuzzy basis function expansion (FBFE), is proposed. To verify the performance of the proposed algorithm, the blowing control of UFV is performed. Simulation results show that the proposed algorithm effectively solves the problems in the UFV blowing control system online.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2529-2551
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• 2022

Visual servoing (VS) based on the Kalman filter (KF) algorithm, as in the case of KF-based image-based visual servoing (IBVS) systems, suffers from three problems in uncalibrated environments: the perturbation noises of the robot system, error of noise statistics, and slow convergence. To solve these three problems, we use an IBVS based on KF, African vultures optimization algorithm enhanced extreme learning machine (AVOA-ELM), and fuzzy logic (FL) in this paper. Firstly, KF online estimation of the Jacobian matrix. We propose an AVOA-ELM error compensation model to compensate for the sub-optimal estimation of the KF to solve the problems of disturbance noises and noise statistics error. Next, an FL controller is designed for gain adaptation. This approach addresses the problem of the slow convergence of the IBVS system with the KF. Then, we propose a visual servoing scheme combining FL and KF-AVOA-ELM (FL-KF-AVOA-ELM). Finally, we verify the algorithm on the 6-DOF robotic manipulator PUMA 560. Compared with the existing methods, our algorithm can solve the three problems mentioned above without camera parameters, robot kinematics model, and target depth information. We also compared the proposed method with other KF-based IBVS methods under different disturbance noise environments. And the proposed method achieves the best results under the three evaluation metrics.

• The Journal of Korean Association of Computer Education
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• v.23 no.4
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• pp.23-33
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• 2020

Online judge provides compilation, execution, and immediate feedback on the source submitted by the learner, and ensures the accuracy and reliability of the evaluation, but it's difficult to select the language according to the level of the learner because most of them provide only textual language. In this study, a block language for online judge was developed and applied to high school classes, and the difference in self-efficacy between the block language and the textual language group was confirmed. It was found that Block language group have more ability expectation to overcome disgust experience than textual language group and Textual language group have significant decrease in ability expectation to start activity and to continue activity. It implies that Block language has an effect on self-efficacy for afterward programming activities, and methods of teaching, learning and evaluation should be devised in the case of textual language so that student's self-efficacy does not deteriorate at the initial and ongoing stage of activity. The results of this study are meaningful in that it provide various implications of methods for enhancing self-efficacy in high school class of programming.

• The Journal of Bigdata
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• v.4 no.2
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• pp.23-34
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• 2019

Recently, the crime that utilizes the digital platform is continuously increasing. About 140,000 cases occurred in 2015 and about 150,000 cases occurred in 2016. Therefore, it is considered that there is a limit handling those online crimes by old-fashioned investigation techniques. Investigators' manual online search and cognitive investigation methods those are broadly used today are not enough to proactively cope with rapid changing civil crimes. In addition, the characteristics of the content that is posted to unspecified users of social media makes investigations more difficult. This study suggests the site-based collection and the Open API among the content web collection methods considering the characteristics of the online media where the infringement crimes occur. Since illegal content is published and deleted quickly, and new words and alterations are generated quickly and variously, it is difficult to recognize them quickly by dictionary-based morphological analysis registered manually. In order to solve this problem, we propose a tokenizing method in the existing dictionary-based morphological analysis through WPM (Word Piece Model), which is a data preprocessing method for quick recognizing and responding to illegal contents posting online infringement crimes. In the analysis of data, the optimal precision is verified through the Vote-based ensemble method by utilizing a classification learning model based on supervised learning for the investigation of illegal contents. This study utilizes a sorting algorithm model centering on illegal multilevel business cases to proactively recognize crimes invading the public economy, and presents an empirical study to effectively deal with social data collection and content investigation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2346-2351
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• 2011

This paper presents the intelligent external noise analysis method for nonlinear maneuvering target. After recognizing maneuvering pattern of the target by the proposed method, we track the state of the target. The external noise can be divided into mere noise and acceleration using only the measurement. divided noise passes through the filtering step and acceleration is punched into dynamic model to compensate expected states. The acceleration is the most deterministic factor to the maneuvering. By dividing, approximating, and compensating the acceleration, we can reduce the tracking error effectively. We use the fuzzy c-means (FCM) clustering as the method to divide external noise. FCM can separate the acceleration from the noise without criteria. It makes the criteria with the data made by measurement at every sampling time. So it can show the adaptive tracking result. The proposed method proceeds the tracking target simultaneously with the learning process. Thus it can apply to the online system. The proposed method shows the remarkable tracking result on the linear and nonlinear maneuvering. Finally, some examples are provided to show the feasibility of the proposed algorithm.