• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.829-836
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• 2005

The way to assign a splitting criterion for correct object classification is the main issue in all decisions trees. This paper describes new splitting rules for classification in order to find an optimal split point. Unlike the current splitting rules that are provided by searching all threshold values, this paper proposes the splitting rules that we based on the probabilities of pre assigned intervals. Our methodology provides that user can control the accuracy of tree by adjusting the number of intervals. In addition, we applied the proposed splitting rules to a set of image data that was retrieved by parameterized feature extraction to recognize image objects.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.3
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• pp.389-395
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• 2013

Ethernet is the most widely deployed access network protocol around the world. IEEE 802.3az WG released the EEE standard based on LPI mode to improve the energy efficiency of Ethernet. This paper proposes improved adaptive power control mechanism that can enhance energy-efficiency based on EEE from small Ethernet switch. The feature of this mechanism is that it predicts the traffic characteristic of next cycle by measuring the amount of traffic flowing in during certain period and adjusts the optimal threshold value to relevant traffic load. Performance evaluation results indicate that the proposed mechanism improves overall performance compared to traditional mechanism, since it significantly reduces energy consumption rate, even though average packet delay increases a little bit.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.738-744
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• 2016

In this paper, a robust visual odometry system has been proposed and implemented in an environment with dynamic illumination. Visual odometry is based on stereo images to estimate the distance to an object. It is very difficult to realize a highly accurate and stable estimation because image quality is highly dependent on the illumination, which is a major disadvantage of visual odometry. Therefore, in order to solve the problem of low performance during the feature detection phase that is caused by illumination variations, it is suggested to determine an optimal threshold value in the image binarization and to use an adaptive threshold value for feature detection. A feature point direction and a magnitude of the motion vector that is not uniform are utilized as the features. The performance of feature detection has been improved by the RANSAC algorithm. As a result, the position of a mobile robot has been estimated using the feature points. The experimental results demonstrated that the proposed approach has superior performance against illumination variations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.4991-4996
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• 2010

Clustering method in wireless sensor network is the technique that forms the cluster to aggregate the data and transmit them at the same time that they can use the energy efficiently. Even though cluster group model is based on clustering, it differs from previous method that reducing the total energy consumption by separating energy overload to cluster group head and cluster head. In this thesis, I calculate the optimal cluster group number and cluster number in this kind of cluster group model according to threshold of energy consumption model. By using that I can minimize the total energy consumption in sensor network and maximize the network lifetime. I also show that proposed cluster group model is better than previous clustering method at the point of network energy efficiency.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.4
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• pp.89-99
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• 2007

In this paper, an analytic model of a sleep mode operation in the IEEE 802.16e is investigated. A mobile subscriber station(MSS) goes to sleep mode after negotiations with the base station(BS) and wakes up periodically for a short interval to check whether there is downlink traffic to it. If the arrival of traffic is notified, an MSS returns to wake mode. Otherwise, it again enters increased sleep interval which is double as the previous one. In order to consider the situation more practically, we propose the sleep mode starting threshold, during which MSS should await packets before it enters the sleep mode. By modifying the M/G/l with multiple vacations model, energy consumption ratio(ECR) and average packet response time are calculated. Our analytic model provides potential guidance in determining the optimal parameters values such as sleep mode starting threshold, minimal sleep and maximal sleep window.

• Atmosphere
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• v.17 no.1
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• pp.45-53
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• 2007

In order to investigate the impacts of heat wave on human health, cluster analysis of meteorological elements (e.g., temperature, dewpoint, sea level pressure, visibility, cloud amount, and wind components) for identifying offensive synoptic air masses is employed. Meteorological data at Seoul during the past 30 years are used. The daily death data at Seoul are also employed. Occurrence frequency of heat waves which is defined by daily maximum temperature greater than the threshold temperature (i.e., $31.2^{\circ}C$) was analyzed. The result shows that the frequency and duration of heat waves at Seoul are increasing during the past 30 years. In addition, the increasing trend of the frequency and duration clearly appears in late spring and early autumn as well as summer. Factor analysis shows that 65.1% of the total variance can be explained by 4 components which are linearly independent. Eight clusters (or synoptic air masses) were classified and found to be optimal for representing the summertime air masses at Seoul, Korea. The results exhibit that cluster-mean values of meteorological variables of an offensive air mass (or cluster) are closely correlated with the observed and standardized deaths.

• The Journal of the Korea Contents Association
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• v.7 no.4
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• pp.206-212
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• 2007

To evaluate the HU value of the IV catheter fragment of CT on the accuracy and size in the peripheral vein. Pilot study of profile and table functions on PC by software was calculated of HU value of IV catheter fragment. This study demonstrates the utility of volume rendering technique to localize a small, subtle IV catheter, which can easily be reformatted of MDCT reformations. IV catheter fragment optimal image described as threshold range. Volume rendering of HU using a MDCT is an excellent method for evaluation the IV catheter fragment in three dimension.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.12
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• pp.39-42
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• 1994

An automatic multi-threshold algorithm for segmentation of 2D ultrasound images based on average filtering and the characteristics of speckle noise in 2D ultrasound image is proposed. To do this, we investigate the histogram of difference between $7{\times}7$ averaging histogram and $3{\times}3$ averaging histogram. And, we find zero crossing points in the positive portion of the differenced histogram and select middle points of the zero crossing points. We assign these selected points to characteristic points. The thresholds are the center of two characteristic points. Then we segment 2D ultrasound image by using these thresholds and extract edges from applying edge operator to optimal segmented image. Experimental results show that the segmented regions are devided accurately around the homogeneous region.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.473-480
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• 2004

This paper presents a new edge detection algorithm in color image. The proposed Adaptive morphological Wavelet-CNN algorithm is divided into two parts : The Adaptive morpholog and WCNN(Wavelet Cellular Neural Networks). It detects the optimal edge with applying this color image to WCNN algorithm, after it does level up a boundary side of a color image by using the adaptive morphology as the threshold of an input color image. Also, it is used not a conventional fixed mask edge detection method but variable mask method which is called a variable BBM. Finally, to show the feasibility of the proposed algorithm, this paper provides by simulation that the color image consists of 30.

• Journal of the Korea Society of Computer and Information
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• v.20 no.7
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• pp.9-16
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• 2015

This paper proposes the parallel design of a shot change detection algorithm using frame segmentation and moving blocks. In the proposed approach, the high parallel processing components, such as frame histogram calculation, block histogram calculation, Otsu threshold setting function, frame moving operation, and block histogram comparison, are designed in parallel for NVIDIA GPU. In order to minimize memory access delay time and guarantee fast computation, the output of a GPU kernel becomes the input data of another kernel in a pipeline way using the shared memory of GPU. In addition, the optimal sizes of CUDA processing blocks and threads are estimated through the prior experiments. In the experimental test of the proposed shot change detection algorithm, the detection rate of the GPU based parallel algorithm is the same as that of the CPU based algorithm, but the average of processing time speeds up about 6~8 times.