• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.21 no.45
• /
• pp.365-374
• /
• 1998

Control Chart is a powerful tool to detect that process is in control or out of control. CIM can have real effect when CIM involve automated quality control. A neural network approach is used for unnatural pattern detecting of control chart. The previous moving window method uses all unnatural pattern that is detected as moving time window. Therefore, It trains a large number of unnatural pattern and takes training time long. In this paper, the proposed method tests a small number of training unnatural pattern which modifies test data without repeating time. We shows that the proposed method has differences In training time and identification rate on the previous moving windows method. As results, we reduced training time and obtain the same identification rate.

• Journal of the Korea Society for Simulation
• /
• v.29 no.4
• /
• pp.9-19
• /
• 2020

The number of customers on Social Network Services(SNS) is rapidly increasing with the spread of smartphones. As of 2018, about 2.7 billion people of the world population (about 7.1 billion people) and more than 31.2 million people of the total population of South Korea (about 50.1 million) use SNS. There are several studies have been conducted on increasing SNS market. Most of them, however, were not quantitative but qualitative studies. This study is conducted on domestic SNS market to identify the competitive relationship among SNS platforms with great proportion in South Korea, such as Facebook, Instagram and Twitter. The objective is to suggest some hypotheses of the competitive relations, test them, and finally verify the trend of domestic SNS market. Competitive Lotka-Volterra (LV) model is used to find out the competitive relationships and Moving Window is also used to show the changes of them over time. In order to test the hypotheses on the relationships, some experiments are performed with Moving Window technique. Thus, the relations among the platforms and the changes of them over time are identified.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.18 no.1
• /
• pp.137-145
• /
• 2004

In this paper, a new algorithm for the segmentation of the multi moving objects at the 3 dimension space and the method of measuring the distance from the camera to the moving object by using stereo video monitoring system is proposed. It get the input image of left and right from the stereo video monitoring system, and the area of the multi moving objects segmented by using adaptive threshold and PRA(pixel recursive algorithm). Each of the object segmented by window mask, then each coordinate value and stereo disparity of the multi moving objects obtained from the window masks. The distance of the multi moving objects can be calculated by this disparity, the feature of the stereo vision system and the trigonometric function. From the experimental results, the error rate of a distance measurement be existed within 7.28％, therefore, in case of implementation the proposed algorithm, the stereo security system, the automatic moving robot system and the stereo remote control system will be applied practical application.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.3
• /
• pp.636-644
• /
• 2015

This research aims to suggest methods to improve object tracking performance by combining CAM shift algorithm with 8-way search window, and reduce arithmetic operation by reducing the number of frame used for tracking. CAM shift has its adverse effect in tracking methods using signature color or having difficulty in tracking rapidly moving object. To resolve this, moving search window of CAM shift makes it possible to more accurately track high-speed moving object after finding object by conducting 8-way search by using information at a final successful timing point from a timing point missing tracking object. Moreover, hardware development led to increased unnecessary arithmetic operation by increasing the number of frame produced per second, which indicates efficiency can be enhanced by reducing the number of frame used in tracking to reduce unnecessary arithmetic operation.

• Journal of the Institute of Convergence Signal Processing
• /
• v.4 no.4
• /
• pp.1-6
• /
• 2003

In this Paper, the moving image is detected by a collision preventive system. The noise of these images is reduced by a mean filter. In case of detecting a movement with a binary difference image the moving area is detected exactly by the labeling and the projective method. When the image move slowly with the tracking mode of the system, the center of the tracking window move to the previous tracking window. And the tracking windows are divided into a tracking mode and a coasting mode which are determine by the Contrast-Difference Correlation of the date obtained from a difference image. The coasting mode determine whether continue the tracking step or not comparing the coasting-time values to reducing the error by the disturbance. The coasting and tracking of these moving images are verified by the result of the simulation.

• Proceedings of the Optical Society of Korea Conference
• /
• 1998.08a
• /
• pp.102-103
• /
• 1998

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.34 no.4
• /
• pp.333-339
• /
• 2010

Identification of a steady state is the first step in developing a fault detection and diagnosis (FDD) system of a heat pump. In a complete FDD system, the steady-state detector will be included as a module in a self-learning algorithm, which enables the working system's reference model to "tune" itself to its particular installation. In this study, a steady-state detector of a residential air conditioner based on moving windows was designed. Seven representative measurements were selected as key features for steady-state detection. The optimized moving-window size and the feature thresholds were decided on the basis of a startup-transient test and no-fault steady-state test. Performance of the steady-state detector was verified during an indoor load-change test. In this study, a general methodology for designing a moving-window steady-state detector for applications involving vapor compression has been established.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.77-77
• /
• 2000

The shape of small or curved object is usually reconstructed using a single camera by moving its lens position to find a sequence of the focused images. Most conventional methods have used a window with fixed shape to test the focus measure, which resulted in a deterioration of accuracy. To solve this problem, this paper proposes a new approach of using a shape adaptive window. It estimates the shape of the object at every step and applies the same shape of window to calculate the focus measure. Focus measure is based on the variance of the pixels inside the window. This paper includes the experimental results.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.4
• /
• pp.129-135
• /
• 2016

In this paper, we propose a novel tracking algorithm called slide window tracker (SWT) suitable for maneuvering target. To efficiently estimate trajectory of moving target, we adopt a sliding piecewise linear window which includes past trace information. By adjusting the window parameters, the proposed algorithm is to reduce measurement noise and to track fast maneuvering target with little computational increment as compared to ${\alpha}-{\beta}$ tracker. Throughout the computer simulations, we verify outstanding tracking performance of the SWT algorithm in noisy linear and nonlinear trajectories. Also, we show that the SWT algorithm is not sensitive to initial model parameter selection, which gives large degree of freedom in applying the SWT algorithm to unknown time-varying measurement environments.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.11
• /
• pp.997-1004
• /
• 2012

In enterprise software projects, performance issues have become more critical during recent decades. While developing software products, many performance tests are executed in the earlier development phase against the newly added code pieces to detect possible performance regressions. In our previous research, we introduced the framework to enable automated performance anomaly detection and reduce the analysis overhead for identifying the root causes, and showed Statistical Process Control (SPC) can be successfully applied to anomaly detection. In this paper, we explain the special performance trend in which the existing anomaly detection system can hardly detect the noticeable performance change especially when a performance regression is introduced and recovered again a while later. Within the fixed number of sampling period, the fluctuation gets aggravated and the lower and upper control limit get relaxed so that sometimes the existing system hardly detect the noticeable performance change. To resolve the issue, we apply dynamically tuned sampling window size based on the performance trend, and Fuzzy theory to find an appropriate size of the moving window.