• Journal of the Korean Institute of Intelligent Systems
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• v.4 no.3
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• pp.32-48
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• 1994

This paper proposes the compensation algorithm of conventional shift pattern using fuzzy reasoning in automatic transmission vehicles. Recently, automatic transimssion vehicles are continually increasing because of theire ease to drive. Also users require the high performance which includes the smooth shift quality and shift scheduling that matches driver;s intentions. So the shift scheduling has been inproved significantly through the application of electronic control. But, in spite of this development, vehicles using conventional shift pattern are sometimes in discord with driver's intention on roads. In this paper, the paper, the proposed compensation algorithm makes a automatic transmission vehicle be able to select an optimal gear shifting time and position using fuzzy reasoning and make a vehicle driver feel confortable even when the vehicle runs on roads which is extremely changed. Therefore, a vehicle driver can expect to reduce the nimber of unnecessary gear shifting and expect the fuel efficiency high. To show usefulness of the proposed method, some simulation are made to compared with conventional gear shifting. Paper prosposes the compensation mehtod of conventional shift pattern using fuzzy reasoning for the purpose that a vehicle can select an optimal gerar shifting time and position in automatic vehicle. Though the conventional shift pattern has no pliability, vehicle driver can feel comfortable and can reduce the number of unnecessary gear shifting using the proposed method on variable road condition. Therefore, it can be expected the fuel efficiency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.579-582
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• 2015

The Mean-Shift is a robustness algorithm that can be used for tracking the object using the similarity of histogram distributions of target model and target candidate. However, Mean-shift using hue information has disadvantage of tracking a wrong target when the target and background has similar hue distributions. We then propose a robust Mean-Shift tracking algorithm using new image that combined upper 4bit-planes in hue and saturation, respectively.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.3
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• pp.118-126
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• 2010

The automated mechanical transmission(AMT) is composed of electronic control management(ECM) and automatic shift gear(ASG). The AMT has advantages which are high efficiency of manual transmissions(MT) and offer operation convenience similar to automatic transmissions(AT). However, it has defects that are the torque gap during gear shift transients and shift time is long. To reduce such defects, it is necessary practically to evaluate error and characteristics as developing simulation model before the control algorithm is applied. In this paper, models are composed of vehicle model and AMT shift control model. Particularly AMT shift control model consists of main clutch management model (MCM) and shift control management model(SCM). The developed models were verified by comparing the simulated and experimental results under the same operational conditions. It can also be used to evaluate shift algorithm.

• ETRI Journal
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• v.31 no.3
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• pp.282-291
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• 2009

An online mean-shift object tracking algorithm, which consists of a learning stage and an estimation stage, is proposed in this work. The learning stage selects the features for tracking, and the estimation stage composes a likelihood image and applies the mean shift algorithm to it to track an object. The tracking performance depends on the quality of the likelihood image. We propose two schemes to generate and integrate likelihood images: one based on the discrete AdaBoost (DAB) and the other based on the real AdaBoost (RAB). The DAB scheme uses tuned feature values, whereas RAB estimates class probabilities, to select the features and generate the likelihood images. Experiment results show that the proposed algorithm provides more accurate and reliable tracking results than the conventional mean shift tracking algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.8
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• pp.637-642
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• 2014

In this paper, we propose a efficient shift index searching algorithm for design of the block LDPC codes. It is combined with the message-passing based cycle search algorithm and ACE algorithm. We can determine the shift indices by ordering of priority factors which are effect on the LDPC code performance. Using this algorithm, we can construct the LDPC codes with low complexity compare to trellis-based search algorithm and save the memory for storing the parity check matrix.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2733-2737
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• 2014

Motion detection according to the movement and the change area detection method according to the background difference and the motion history image for use in a motion estimation technique using a real-time image, the motion detection method according to the optical flow, the back-projection of the histogram of the object to track for motion tracking At the heart of MeanShift center point of the object and the object to track, while used, the size, and the like due to the motion tracking algorithm CamShift, Kalman filter to track with direction. In this paper, we implemented the motion detection algorithm based on color and shape information of the object and verify.

• Journal of applied mathematics & informatics
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• v.39 no.5_6
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• pp.859-882
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• 2021

In the proposed paper, a new algorithm based on Nonlinear Feedback Shift Register (NLFSR) and modified RC4A (Rivest Cipher 4A) cipher is introduced. NLFSR is used for image pixel scrambling while modified RC4A algorithm is used for pixel substitution. NLFSR used in this algorithm is of order 27 with maximum period 2^27-1 which was found using Field Programmable Gate Arrays (FPGA), a searching method. Modified RC4A algorithm is the modification of RC4A and is modified by introducing non-linear rotation operator in the Key Scheduling Algorithm (KSA) of RC4A cipher. Analysis of occlusion attack (up to 62.5% pixels), noise (salt and pepper, Poisson) attack and key sensitivity are performed to assess the concreteness of the proposed method. Also, some statistical and security analyses are evaluated on various images of different size to empirically assess the robustness of the proposed scheme.

• Journal of Advanced Navigation Technology
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• v.23 no.1
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• pp.77-83
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• 2019

In this paper, we propose an object tracking algorithm based on color histogram and convolutional neural network model. In order to increase the tracking accuracy, we synthesize generic object tracking using regression network algorithm which is one of the convolutional neural network model-based tracking algorithms and a mean-shift tracking algorithm which is a color histogram-based algorithm. Both algorithms are classified through support vector machine and designed to select an algorithm with higher tracking accuracy. The mean-shift tracking algorithm tends to move the bounding box to a large range when the object tracking fails, thus we improve the accuracy by limiting the movement distance of the bounding box. Also, we improve the performance by initializing the tracking start positions of the two algorithms based on the average brightness and the histogram similarity. As a result, the overall accuracy of the proposed algorithm is 1.6% better than the existing generic object tracking using regression network algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2675-2690
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• 2014

We study the problem of optimal opportunistic spectrum access with unknown and heterogeneous channel dynamics in cognitive radio networks. There is neither statistic information about the licensed channels nor information exchange among secondary users in the respective systems. We formulate the problem of maximizing network throughput. To achieve the desired optimization, we propose a win-shift lose-stay algorithm based only on rewards. The key point of the algorithm is to make secondary users tend to shift to another channel after receiving rewards from the current channel. The optimality and the convergence of the proposed algorithm are proved. The simulation results show that for both heterogeneous and homogenous systems the proposed win-shift lose-stay algorithm has better performance in terms of throughput and fairness than an existing algorithm.

• Transactions of The Korea Fluid Power Systems Society
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• v.4 no.2
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• pp.7-20
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• 2007

TCU is a shift controller far automatic transmission of which major functions are to determine the shift point and manage the shifting process based on the various input signals. As the recent digital control technologies advance, it plays a key-role to improve a transmission performance and its algorithm becomes more complicated. This paper describes the development of transmission simulator fur wheel loader that enables a TCU for normal stand-alone operation by the real-time emulation of TCU interface signals. It can be utilized for the analysis of shift control algorithm implemented in a commercial TCU as well as for the development of brand new TCU.