• 한국대기환경학회지
• /
• 제19권4호
• /
• pp.377-386
• /
• 2003

In order to develop a confident sampling technique, we designed and constructed a 6-port manifold MFC sampling system for collecting gaseous pollutants in air. Using this instrumentation, we tested the performance criteria of MFC system in terms of: (1) flow rate; (2) MFC-to-MFC variability; (3) tube-to-tube variability; and (4) time. It was interesting to find that the later two factors did not show any significant variations, while the former two show substantially large variations. However, as most of those variabilities are consistent enough to form systematic patterns, we were able to explain the occurrence patterns of all those MFC biases in terms of those four major variables. The overall results of our experiment suggest that one needs to use correction factor for each MFC unit under a given flow rate to maintain optimal accuracy and precision for sampling of those pollutants.

• 한국공작기계학회:학술대회논문집
• /
• 한국공작기계학회 2002년도 춘계학술대회 논문집
• /
• pp.266-272
• /
• 2002

High-speed machining is one of the most effective technology to improve productivity. Because of the high speed and hugh fried rate, high-speed machining can alive great advantages for the machining of dies and molds. This paper describes on the improvement of machining accuracy in high-speed machining. Depth of cut, feed rate and spindle revolution are control factors. The effect of the control factors on machining accuracy is discussed fur the results of surface roughness and machining error in Z-direction of the high speed machining.

• 한국정보통신학회논문지
• /
• 제14권7호
• /
• pp.1544-1550
• /
• 2010

비선형 동적 시스템을 모델링하기 위해 GMDH(Group Method of Data Handling)를 적용한 많은 연구들이 수행되어 왔다. 그러나 모델링의 정확성을 위해서는 계산량이 크게 증가한다. 그러므로 본 논문에서는 입력 데이터를 취사선택하는 기준을 점감적으로 조정함으로써 적어도 정확성을 유지하면서 전형적인 GMDH의 단점인 과도한 계산을 피할 수 있는 방법을 제안한다. 컴퓨터 시뮬레이션 결과, GMDH 알고리듬의 계산량을 성공적으로 줄일 수 있었고 에러율도 소폭 줄일 수 있었다.

• 한국멀티미디어학회논문지
• /
• 제21권8호
• /
• pp.888-896
• /
• 2018

In this paper, we report detection and recognition of vehicle logo from images captured from street CCTV. Image data includes both the front and rear view of the vehicles. The proposed method is a two-step process which combines image preprocessing and faster region-based convolutional neural network (R-CNN) for logo recognition. Without preprocessing, faster R-CNN accuracy is high only if the image quality is good. The proposed system is focusing on street CCTV camera where image quality is different from a front facing camera. Using perspective transformation the top view images are transformed into front view images. In this system, the detection and accuracy are much higher as compared to the existing algorithm. As a result of the experiment, on day data the detection and recognition rate is improved by 2% and night data, detection rate improved by 14%.

• 한국정보통신설비학회:학술대회논문집
• /
• 한국정보통신설비학회 2009년도 정보통신설비 학술대회
• /
• pp.127-130
• /
• 2009

We propose a method for detecting DDoS (Distributed Denial of Service) traffic in real-time inside the backbone network. For this purpose, we borrow the concepts of MACD (Moving Average Convergence Divergence) and RoC (Rate of Change), which are used for technical analysis in the stock market Due to the fact that the method is based on a quantitative, rather than a heuristic, detection level, DDoS traffic can be detected with greater accuracy (by reducing the false alarm ratio). Through simulation results, we show how the detection level is determined and demonstrate how much the accuracy of detection is enhanced.

• 한국기계가공학회지
• /
• 제12권5호
• /
• pp.163-169
• /
• 2013

The objective of this study is to replace labor intensive forging processes by an automated system. For achieving it, an exclusive mechanism that consists of a positioner, an arm, and a hanger is configured to handle hot forging objects. Also, a structural analysis is applied to the horizontal motion unit, which is the most highly loaded, in order to verify its validity. In addition, its possibility is also verified through identifying the performance of the proposed system before applying it to sites. As a result, the major characteristic items, such as positioning accuracy, material diameter, object traveling weight, product failure rate, and forging process rate, in this system are perfectly verified for applying it to manufacturing sites.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
• /
• pp.212-212
• /
• 2000

This study was performed to construct a hot strip speed measuring system and check over whether the measured speed can be used for improving the mass flow of the head-end part of a hot strip in the 7-stand finishing mill. Because the mass flow in hot rolling mill affects the looper operation and the thickness and width control of a strip, accurate measurement of strip speed ie important. The measured speed was compared with the roll speeds of No. 6 and No.7 stand to check the performance of the system and analyzed to find how to apply the speed. As a result, it is shown that the accuracy of the system is enough, strip thickness error can be reduced by -275∼+200$\mu\textrm{m}$ using the measured speed and the existing FSU model has low accuracy for predicting forward slip rate. A neural network was developed to calculate forward slip rate instead of FSU model. The test result of the neural network shows that the neural network is more accurate than the FSU model.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권12호
• /
• pp.6063-6079
• /
• 2019

When the length of sampling data sequence is too large, the method of gesture recognition based on traditional Dynamic Time Warping (DTW) algorithm will lead to too long calculation time, and the accuracy of recognition result is not high.Support vector machine (SVM) has some shortcomings in precision, Edit Distance on Real Sequences(EDR) algorithm does not guarantee that noise suppression will not suppress effective data.A new method based on Improved Interpolation Dynamic Time Warping (IIDTW)algorithm is proposed to improve the efficiency of gesture recognition and the accuracy of gesture recognition. The results show that the computational efficiency of IIDTW algorithm is more than twice that of SVM-DTW algorithm, the error acceptance rate is FAR reduced by 0.01%, and the error rejection rate FRR is reduced by 0.5%.Gesture recognition based on IIDTW algorithm can achieve better recognition status. If it is applied to unlock mobile phone, it is expected to become a new generation of unlock mode.

• 음성과학
• /
• 제12권4호
• /
• pp.237-245
• /
• 2005

The purpose of this study was to investigate the characteristics for cohesion in the narratives of fluent aphasics. Ten fluent aphasics and ten normal adults matched chronological-age and education level with aphasics participated in this study. Story retelling task was given to the participants individually. And all narratives they produced were recorded and transcribed for analysis. The frequency of cohesive markers and the rate of accuracy were analyzed. The result were as follows; (1) The fluent aphasics used cohesive devices significantly less than the normal adult group, and the rate of accuracy of cohesive devices used was lower than the normal adults. (2) Both groups used lexical cohesion more than pro-forms and ellipsis, and the difference of two groups was larger in lexical cohesion than pro-forms and ellipsis. (3) The fluent aphasics used lexical cohesion more accurately than pro-forms and ellipsis but the normal adults used all three cohesive markers accurately. The difference of two groups was large in pro-forms and ellipsis.

• International Journal of Advanced Culture Technology
• /
• 제7권4호
• /
• pp.283-288
• /
• 2019

Neural networks have been reborn as a Deep Learning thanks to big data, improved processor, and some modification of training methods. Neural networks used to initialize weights in a stupid way, and to choose wrong type activation functions of non-linearity. Weight initialization contributes as a significant factor on the final quality of a network as well as its convergence rate. This paper discusses different approaches to weight initialization. MNIST dataset is used for experiments for comparing their results to find out the best technique that can be employed to achieve higher accuracy in relatively lower duration.