• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4B
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• pp.218-225
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• 2005

Although Snoop protocol can enhance TCP throughput efficiently in a wired-cum-wireless environment, it has a problem in performing local packet retransmissions under a burst error-prone wireless link. AT-Snoop protocol is proposed to cope with this Snoop protocol's problem by adopting adaptive timer. In this paper, TCP throughputs of AT-Snoop protocol have been analyzed with varying wireless link conditions and the ways of setting parameters of AT-Snoop protocol for higher TCP throughput are found out through computer simulations. From the simulation results, AT-Snoop protocol's two parameters, local retransmission threshold value and local retransmission timeout value, are closely related with the fading changing rate. To get higher TCP throughput, local retransmission threshold value and local retransmission timeout value should be set to a little bit larger values than average WSRTT(Wireless Smoothed Round Trip Time) and mean bad period of the wireless link, respectively.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.329-338
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• 2003

Object tracking in a real time image is one of Interesting subjects in computer vision and many practical application fields past couple of years. But sometimes existing systems cannot find object by recognize background noise as object. This paper proposes a method of object detection and tracking using adaptive background image in real time. To detect object which does not influenced by illumination and remove noise in background image, this system generates adaptive background image by real time background image updating. This system detects object using the difference between background image and input image from camera. After setting up MBR(minimum bounding rectangle) using the internal point of detected object, the system tracks object through this MBR. In addition, this paper evaluates the test result about performance of proposed method as compared with existing tracking algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.7
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• pp.1373-1379
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• 2007

A modified adaptive switching median filter for impulse noise removal, which has the noise detection step and the noise filtering step, is proposed in this paper. In the noise detection step, we use the detection threshold which is earned by calculating the intensity differences between pixels nearby with each other in localized window, to determine whether the pixels in the image are noise or not. Then in the noise filtering step, we will only remove the corrupted pixels and remain the good pixels. By the noise detection result, we can easily get the local noise density of the image, and use it to consider the filtering mask size and the times of filtering iteration according to different localized noise corruptions. For Setting the simulation result, we compared the proposed method to conventional median filters with several test images corrupted by various impulse noise densities. We also use the peak signal-to-noise ratio (PSNR) to evaluate restoration performance, the simulation results demonstrate that the proposed method shows better results than other median-based type filters.

• Journal of the Korea Computer Graphics Society
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• v.29 no.1
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• pp.1-11
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• 2023

Deep-learning-based image segmentation is one of the most widely employed lane detection approaches, and it requires a post-process for extracting the key points on the lanes. A general approach for key-point extraction is using a fixed threshold defined by a user. However, finding the best threshold is a manual process requiring much effort, and the best one can differ depending on the target data set (or an image). We propose a novel key-point extraction algorithm that automatically adapts to the target image without any manual threshold setting. In our adaptive key-point extraction algorithm, we propose a line-level normalization method to distinguish the lane region from the background clearly. Then, we extract a representative key point for each lane at a line (row of an image) using a kernel density estimation. To check the benefits of our approach, we applied our method to two lane-detection data sets, including TuSimple and CULane. As a result, our method achieved up to 1.80%p and 17.27% better results than using a fixed threshold in the perspectives of accuracy and distance error between the ground truth key-point and the predicted point.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.1
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• pp.62-74
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• 2002

The tracking of a reference temperature trajectory in a polymerization batch reactor is a common problem and has critical importance because the quality control of a batch reactor is usually achieved by implementing the trajectory precisely. In this study, only energy balances around a reactor are considered as a design model for control synthesis, and material balances describing concentration variations of involved components are treated as unknown disturbances, of which the effects appear as time-varying parameters in the design model. For the synthesis of a tracking controller, a method combining the input-output linearization of a time-variant system with the parameter estimation is proposed. The parameter estimation method provides parameter estimates such that the estimated outputs asymptotically follow the measured outputs in a specified way. Since other unknown external disturbances or uncertainties can be lumped into existing parameters or considered as another separate parameters, the method is useful in practices exposed to diverse uncertainties and disturbances, and the designed controller becomes robust. And the design procedure and setting of tuning parameters are simple and clear due to the resulted linear design equations. The performances and the effectiveness of the proposed method are demonstrated via simulation studies.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.122-127
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• 2001

Lasting machines for shoe manufacturing are continuously developed with the aid of automation and Computer Aided Manufacturing (CAM). Although automation and CAM techniques have tremendously reduced the labor in shoe manufacturing field, there still remain some parts manufactured by experts. In order to enhance the capability and efficiency of machines for labor-free shoe manufacturing, CAD data of a shoe last is indispensable. While CAD datarization takes the fundamental role in the shoe design as well as the shoe manufacturing, there has been little research for the CAD datarization of a shoe last. In this paper, a new procedure for CAD datarization of a shoe last using finite element patches is proposed and some data for the control part of the shoe lasting machine are extracted and interpolated from the CAD data. The outer line of a shoe-last sole is interpolated by a tension spline method and bonding lines are extracted from the shoe CAD data. Finally, initial setting data for the lasting machine are extracted from the last CAD data and initial setup parts of the lasting machine.

• Ocean Systems Engineering
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• v.6 no.3
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• pp.217-231
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• 2016

This paper presents a new approach for underwater image analysis using the bi-dimensional empirical mode decomposition (BEMD) technique and the phase congruency information. The BEMD algorithm, fully unsupervised, it is mainly applied to texture extraction and image filtering, which are widely recognized as a difficult and challenging machine vision problem. The phase information is the very stability feature of image. Recent developments in analysis methods on the phase congruency information have received large attention by the image researchers. In this paper, the proposed method is called the EP model that inherits the advantages of the first two algorithms, so this model is suitable for processing underwater image. Moreover, the receiver operating characteristic (ROC) curve is presented in this paper to solve the problem that the threshold is greatly affected by personal experience when underwater image edge detection is performed using the EP model. The EP images are computed using combinations of the Canny detector parameters, and the binaryzation image results are generated accordingly. The ideal EP edge feature extractive maps are estimated using correspondence threshold which is optimized by ROC analysis. The experimental results show that the proposed algorithm is able to avoid the operation error caused by manual setting of the detection threshold, and to adaptively set the image feature detection threshold. The proposed method has been proved to be accuracy and effectiveness by the underwater image processing examples.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.337-352
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• 2005

In this paper, a fuzzy logic implementation of the random early detection (RED) mechanism [1] is presented. The main objective of the proposed fuzzy controller is to reduce the loss probability of the RED mechanism without any change in channel utilization. Based on previous studies, it is clear that the performance of RED algorithm is extremely related to the traffic load as well as to its parameters setting. Using fuzzy logic capabilities, we try to dynamically tune the loss probability of the RED gateway. To achieve this goal, a two-input-single-output fuzzy controller is used. To achieve a low packet loss probability, the proposed fuzzy controller is responsible to control the $max_{p}$ parameter of the RED gateway. The inputs of the proposed fuzzy controller are 1) the difference between average queue size and a target point, and 2) the difference between the estimated value of incoming data rate and the target link capacity. To evaluate the performance of the proposed fuzzy mechanism, several trials with file transfer protocol (FTP) and burst traffic were performed. In this study, the ns-2 simulator [2] has been used to generate the experimental data. All simulation results indicate that the proposed fuzzy mechanism out performs remarkably both the traditional RED and Adaptive RED (ARED) mechanisms [3]-[5].

• Korean Journal of Adult Nursing
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• v.19 no.2
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• pp.191-206
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• 2007

Purpose: This qualitative study aimed to understand the experiences of reorganization of everyday lives among the women with chronic health problem. Methods: In this study, the approach and its process of sociology of everyday lives were adopted. Data for the study came from 6 informants and 9 family members of the informants by interview and participant-observation from January, 2004 to May, 2006. Qualitative content analyzing methods were adopted. Results: Informants' everyday lives were reorganized as follows. During the experiences of shock from unpleasant and unclear symptoms of their body, their sight fixed on the body part. Their time also fixed on a point of present. They started to wander from medical care to folk and lay care. After they were informed that the health problem could not be treated completely, they reduced the world of everyday life and protected themselves from the chaotic unfamiliar world by setting -a- side duties as a family member and severing unessential social relationship. As they achieved a skill for managing their health problem, they gained their former pattern of everyday lives as a woman, a family member, and a social member. Finally, they created a new life world. Conclusion: We need more study on the development of an adaptive strategy by the informants, to intervene in the crisis of everyday life.

• International Journal of Precision Engineering and Manufacturing
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• v.5 no.4
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• pp.61-68
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• 2004

Necessity to address engineering system uncertainties in design processes has long been acknowledged. To obtain quality of product, a safety factor is traditionally used by many design engineers due to its easy of use and comprehension. However, the safety factor approach often yields either conservative or unreliable designs, since it ignores the type of probability distribution and the mechanism of uncertainty propagation from the input to the output. For a consistent reliability-based design, two fundamental issues must be investigated thoroughly. First, the design-decision process that clearly identifies a mechanism of uncertainty propagation under system uncertainties needs to be developed, which must be an efficient and accurate process. To identify the mechanism more effectively, an adaptive probability analysis is proposed by adaptively setting probability levels through a posteriori error estimation. The second is to develop the design process that not only yields a high quality design but also a cost-effective optimum design from manufacturing point of view. As a result, a response surface methodology is specially developed for RBDO, thus enhancing numerical challenges of efficiency and complicatedness. Side crashworthiness application is used to demonstrate the integrated design process for product and manufacturing process design.