• Journal of KIISE
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• v.43 no.8
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• pp.919-926
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• 2016

In a wireless network, TCP causes the performance degradation because of mistaking packet loss, which is caused by characteristics of wireless link and throughput oscillation due to change of devices connected on a limited bandwidth. Delay based TCP is not affected by packet loss because it controls window size by using the RTT. Therefore, it can solve the problem of unnecessary degradation of the rate caused by misunderstanding reason of packet loss. In this paper, we propose an algorithm for improving the remaining problems by using delay based TCP. The proposed scheme can change throughput adaptively by adding the RTT, which rapidly reflects the network conditions to BaseRTT. It changes the weight of RTT and the increases and decreases window size based on the remaining amount of the buffer. The simulation indicated that proposed scheme can alleviate the throughput oscillation problem, as compared to the legacy TCP Vegas.

• Journal of Broadcast Engineering
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• v.5 no.1
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• pp.102-112
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• 2000

The previous video structuring techniques are mainly limited to shot or shot group level. However, the shot level structure couldn't provide semantics within a video. So, researches on high level structuring are going on for getting over the drawbacks of shot level structure, recently. To overcome the drawbacks of shot level structure, we propose video scene segmentation technique based on color and motion features. For considering various color distribution, each shot is divided into sub-shots based on color feature. A key frame is extracted from each sub-shot. The motion feature in a shot is extracted from MPEG-1 video's motion vector. Moreover adaptive weights based on motion's property in search range are applied to color and motion features. The experiment results of proposed technique show the excellence in view of the over-segmentation and the reflection of semantics, comparing with those of previous techniques. The proposed technique decomposes video into meaningful hierarchical structure and provides video browsing or retrieval based on scene.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.57-65
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• 2010

In this paper, we propose a new real-time algorithm detecting the flame and smoke in digital CCTV images. Because the forest fire causes the enormous human life and damage of property, the early management according to the early sensing is very important. The proposed algorithm for monitoring forest fire is classified into the flame sensing and detection of smoke. The flame sensing algorithm detects a flame through the conditional test at YCbCr color model from the single frame. For the detection of smoke, firstly the background range is set by using differences between current picture and the average picture among the adjacent frames in the weighted value, and the pixels which get out of this range and have a gray-scale are detected in the smoke area. Because the proposed flame sensing algorithm is stronger than the existing algorithms in the change of the illuminance according to the quantity of sunshine, and the smoke detection algorithm senses the pixel of a gray-scale with the smoke considering the amount of change for unit time, the effective early forest fire detection is possible. The experimental results indicate that the proposed algorithm provides better performance than existing algorithms.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.632-639
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• 2007

This paper presents a wavelet-based watermarking algorithm to securely hide biometric features such as face and fingerprint and effectively extract them with less distortion of the concealed data. To hide the biometric features, we proposed a determination method of insert location based on wavelet transform and adaptive weight method according to the image characteristics. The hidden features are effectively extracted by applying the inverse wavelet transform to the watermarked image. To show the effectiveness, we analyze the various performance such as PSNR and correlation of watermark features before and after applying watermarking. Also, we evaluate the effect of watermaking algorithm with respect to biometric system such as recognition rate. Recognition rate shows 98.67% for multimodal biometric systems consisted of face and fingerprint. From these, we confirm that the proposed method makes it possible to effectively hide and extract the biometric features without lowering recognition rate.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.139-146
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• 2002

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement learning is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to choose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement learning is different from supervised learning in the sense that there is no presentation of input-output pairs as training examples. Furthermore, model-free reinforcement learning algorithms like Q-learning do not require defining or learning any models of the surrounding environment. Nevertheless these algorithms can learn the optimal policy if the agent can visit every state-action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem, we suggest Adaptive Mediation-based Modular Q-Learning (AMMQL) as an improvement of the existing Modular Q-Learning (MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state space effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. In this paper we use the AMMQL algorithn as a learning method for dynamic positioning of the robot soccer agent, and implement a robot soccer agent system called Cogitoniks.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.5
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• pp.465-473
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• 2002

Images are easily corrupted by noise during the data transmission, data capture and data processing. A technical method of noise analyzing and adaptive filtering for reducing of quantum noise in radiography is presented. By adjusting the characteristics of the filter according to local statistics around each pixel of the image as moving windowing, it is possible to suppress noise sufficiently while preserve edge and other significant information required in reading. We have proposed adaptive weighted median(AWM) filters based on local statistics. We show two ways of realizing the AWM filters. One is a simple type of AWM filter, whose weights are given by a simple non-linear function of three local characteristics. The other is the AWM filter which is constructed by homogeneous factor(HF). Homogeneous factor(HF) from the quantum noise models that enables the filter to recognize the local structures of the image is introduced, and an algorithm for determining the HF fitted to the detection systems with various inner statistical properties is proposed. We show by the experimented that the performances of proposed method is superior to these of other filters and models in preserving small details and suppressing the noise at homogeneous region. The proposed algorithms were implemented by visual C++ language on a IBM-PC Pentium 550 for testing purposes, the effects and results of the noise filtering were proposed by comparing with images of the other existing filtering methods.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.3
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• pp.312-319
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• 2011

In this paper, a new linearization algorithm for DPD(Digital PreDistorter) is suggested. This new algorithm uses DFP(Davidon-Fletcher-Powell) method. This algorithm is more accurate than that of the existing algorithms, and this method renew the best-fit value in every routine with out setting the initial value of step-size. In modeling power amplifier, the memory polynomial model which can model the memory effect of the power amplifier is used. And the overall structure of linearizer is based on an indirect learning architecture. In order to verify for performance of proposed algorithm, we compared with LMS(Least Mean-Squares), RLS(Recursive Least squares) algorithm.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.10
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• pp.529-538
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• 2007

Fair Queueing algorithms based on Generalized Processor Sharing (GPS) not only guarantee sessions with service rate and delay, but also provide sessions with instantaneous fair sharing. This fair sharing distributes server capacity to currently backlogged sessions in proportion to their weights without regard to the amount of service that the sessions received in the past. From a long-term perspective, the instantaneous fair sharing leads to a different quality of service in terms of delay and bandwidth to sessions with the same weight depending on their traffic pattern. To minimize such long-term unfairness, we propose a delay-bandwidth normalization model that defines the concept of value of service (VoS) from the aspect of both delay and bandwidth. A model and a packet-by-packet scheduling algorithm are proposed to realize the VoS concept. Performance comparisons between the proposed algorithm and algorithms based on fair queueing and service curve show that the proposed algorithm provides better long-term fairness among sessions and that is more adaptive to dynamic traffic characteristics without compromising its service rate and delay guarantees.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.24-35
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• 2012

In this paper, we propose a dynamic lane control scheme with a traffic predictor module and a rate controller for reconciling with commercial optical PHY modules in energy efficient optical Ethernet systems. The commercial high speed optical Ethernet system capable of 40/100Gbps employs 4 or 10 multiple optical transceivers over WDM or multiple optical links. Each of the transceivers is always turned on even if the link is idle. To save energy, we propose the dynamic lane control scheme. It allows that several links may be entirely turned off in a low traffic load and frames are handled on the remaining active links. To preserve the byte order even if the number of active links may be changed, we propose a rate controller to be sat on the reconciliation sublayer. The main role of the controller is to insert null byte streams into the xGMII of inactive lanes. For the PHY module, the null input streams corresponding to inactive lanes will be disregarded on inactive PMDs. It is very handy to implement the rate controller module with MAC in FPGA without any modification of commercial PHYs. It is very crucial to determine the number of active links based on the fluctuated traffic load, we provide a simple traffic predictor based on both the current transmission buffer size and the past one with different weighting factors for adapting to the traffic load fluctuation. Using the OMNET++ simulation framework, we provide several performance results in terms of the energy consumption.

• Nuclear Engineering and Technology
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• v.19 no.4
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• pp.233-241
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• 1987

Difficulties are encountered when the behavior of complex systems (i.e., fuel failure probability) that have unreliable deterministic models is predicted. For more realistic prediction of the behavior of complex systems with limited observational data, the present study was undertaken to devise an approach of combining predictions from the deterministic model and actual observational data. Predictions by this method of combining are inferred to be of higher reliability than separate predictions made by either model taken independently. A systematic method of hierarchical pattern discovery based on the method developed in the SPEAR was used for systematic search of weighting factors and pattern boundaries for the present method. A sample calculation was performed for prediction of CANDU fuel failures that had occurred due to power ramp during refuelling process. It was demonstrated by this sample calculation that there exists a region of feature space in which fuel failure probability from the PROFIT model nearly agree with that from observational data.