• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.709-716
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• 2004

This paper describes an intelligent real-time monitoring system of a semiconductor processing equipment, which determines normal or not for a wafer in processing, using multiple time-series pattern recognition. The proposed system consists of three phases, initialization, learning and real-time prediction. The initialization phase sets the weights and tile effective steps for all parameters of a monitoring equipment. The learning phase clusters time series patterns, which are producted and fathered for processing wafers by the equipment, using LBG algorithm. Each pattern has an ACI which is measured by a tester at the end of a process The real-time prediction phase corresponds a time series entered by real-time with the clustered patterns using Dynamic Time Warping, and finds the best matched pattern. Then it calculates a predicted ACI from a combination of the ACI, the difference and the weights. Finally it determines Spec in or out for the wafer. The proposed system is tested on the data acquired from etching device. The results show that the error between the estimated ACI and the actual measurement ACI is remarkably reduced according to the number of learning increases.

• Journal of the Microelectronics and Packaging Society
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• v.22 no.1
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• pp.51-54
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• 2015

An electro-plating technology on a cured isotropic conductive pattern with a hybrid Cu paste composed of resin matrix, copper, and solder powders has been developed. In a conventional technology, Ag paste was used to perform a conductive pattern on a PCB or silicon substrate. From previous research, the electrical conductive mechanism and principle of the hybrid Cu paste were concisely investigated. The isotropic conductive pattern on the PCB substrate was performed using screen-printing technology. The optimum electro-plating condition was experimentally determined by processing parameters such as the metal content of the hybrid Cu paste, applied current density, and time for the electroplating in the plating bath. The surfaces and cross-sections were observed using optical and SEM photographs. In conclusion, the optimized processing conditions for Cu electro-plating technology on the conductive pattern were a current density of $40mA/cm^2$ and a plating time of 20min on the hybrid Cu paste with a metal content of 44 vol.%. More details of the mechanical properties and processing conditions will be investigated in further research.

• The KIPS Transactions:PartD
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• v.17D no.4
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• pp.253-258
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• 2010

Traditional frequent pattern mining considers equal profit/weight value of every item. Weighted Frequent Pattern (WFP) mining becomes an important research issue in data mining and knowledge discovery by considering different weights for different items. Existing algorithms in this area are based on fixed weight. But in our real world scenarios the price/weight/importance of a pattern may vary frequently due to some unavoidable situations. Tracking these dynamic changes is very necessary in different application area such as retail market basket data analysis and web click stream management. In this paper, we propose a novel concept of dynamic weight and an algorithm DWFPM (dynamic weighted frequent pattern mining). Our algorithm can handle the situation where price/weight of a pattern may vary dynamically. It scans the database exactly once and also eligible for real time data processing. To our knowledge, this is the first research work to mine weighted frequent patterns using dynamic weights. Extensive performance analyses show that our algorithm is very efficient and scalable for WFP mining using dynamic weights.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.3 no.2
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• pp.110-114
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• 2002

The master pattern manufacturing process is one of the most important processes in jewelry industry because the process takes 20% of total jewelry manufacturing costs. The previous jewelry manufacturing process has many steps of "rough design${\leftrightarro}$ detailed drawing${\leftrightarro}$ wax pattern manufacturing ${\leftrightarro}$ lime soda flask mold manufacturing ${\leftrightarro}$ silver master pattern manufacturing ${\leftrightarro}$ mass production of wax pattern ${\leftrightarro}$ investment casting process ${\leftrightarro}$ final jewelry product." A novel process that reduces processing steps by using a rapid prototyping system (RP) has been suggested. The process is "3D CAD design ${\leftrightarro}$ DuraForm mold manufacturing by RP ${\leftrightarro}$ manufacturing master pattern by low melting alloy ${\leftrightarro}$ mass production of wax pattern ${\leftrightarro}$ investment casting process${\leftrightarro}$ final jewelry product." Molds are made with DuraForm powder, of which melting temperature is 19$0^{\circ}C$, by a selective laster sintering type RP. An alloy of Pb-Sn-Bi-Cd, of which melting temperature is $70^{\circ}C$, is casted in the DuraForm molds. Spheres and rings of diameter 20 mm are made by this process. The dimension deformation rate is less than 2%, and the post processing of the castings is convenient. The casting made by the suggested process can be used as a master pattern of jewelry products.of jewelry products.

• Design & Manufacturing
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• v.17 no.2
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• pp.22-26
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• 2023

As Light-Emitting Diodes(LEDs) continue to advance in performance, their application in automotive lamps is increasing. Automotive LEDs utilize light guides not only for aesthetics but also to control light quantity and direction. Light guides employ patterns of a few hundred micrometers(㎛) to regulate the light, and the surface roughness(Ra) of these patterns can reach tens of nanometers(nm). Given that these light guides are produced through injection molding, mold processing technology with high surface quality micro-patterns is required. This study serves as a preliminary investigation into the development of high surface quality micro-pattern processing technology. It examines the surface roughness of the workpiece based on the cutting direction of the pattern and the cutting fluid type when cutting micro-patterns on STAVAX steel using cubic Boron Nitride(cBN) tools. The experiments involved machining a step-shaped micro-pattern with a height of 60 ㎛ and a pitch of 400 ㎛ in a 22×22 mm area under identical cutting conditions, with only the cutting direction and cutting fluid type being varied. The machining results of four cases were compared, encompassing two cases of cutting direction(parallel to the pattern, orthogonal to the pattern) and two cases of cutting fluid type (flood, mist). Consequently, the Ra value was found to be the highest(Ra 128.33 nm) when machining with the flood type in parallel to the pattern, while it was the lowest(Ra 95.22 nm) when machining with the mist type orthogonal to the pattern. These findings confirm that there is a difference of up to 25.8 % in the Ra value depending on the cutting direction and cutting fluid type.

• The Journal of the Acoustical Society of Korea
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• v.27 no.2E
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• pp.51-56
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• 2008

In this paper, we propose an effective method for music summarization which automatically extracts a representative part of the music by using signal processing technology. Proposed method uses a vector quantization technique to extract several segments which can be regarded as the most important contents in the music. In general, there is a repetitive pattern in music, and human usually recognizes the most important or catchy tune from the repetitive pattern. Thus the repetition which is extracted using segment similarity is considered to express a music summary. The segments extracted are again combined to generate a complete music summary. Experiments show the proposed method captures the main theme of the music more effectively than conventional methods. The experimental results also show that the proposed method could be used for real-time application since the processing time in generating music summary is much faster than other methods.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1101-1104
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• 1995

Through welding fabrication, user can feel an surficaial and capable unsatisfaction because of welded defects, Generally speaking, these are called weld defects. For checking these defects effectively without time loss effectively, weldability estimation system setup isan urgent thing for detecting whole specimen quality. In this study, by laser vision camera, catching a rawdata on welded specimen profiles, treating vision processing with these data, qualititative defects are estimated from getting these information at first. At the same time, for detecting quantitative defects, whole specimen weldability estimation is pursued by multifeature pattern recognition, which is a kind of fuzzy pattern recognition. For user friendly, by weldability estimation results are shown each profiles, final reports and visual graphics method, user can easily determined weldability. By applying these system to welding fabrication, these technologies are contribution to on-line weldability estimation.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2E
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• pp.27-31
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• 1997

This paper proposes a new rejection algorithm which distinguishes unregistered spoken words(or non-keywords) from registered vocabulary. Two kinds of garbage models are employed in this design ; the original garbage model and a new word garbage model. The original garbage model collects all non-keyword patterns where the new word garbage model collects patterns classified by recognizing each non-keyword pattern with registered vocabulary. These two types of garbage models work together to make a robust reject decision. The first stage of processing is the classification of an input pattern through the original garbage model. In the event that the first stage of processing is ambiguous, the new word dependent garbage model is used to classify thye input pattern as either a registered or non-registered word. This paper shows the efficiency of the new word dependent garbage model. A Dynamic Multisection method is used to test the performance of the algorithm. Results of this experiment show that the proposed algorithm performs at a higher level than that of the original garbage model.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.5
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• pp.666-672
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• 2011

In this paper, we describes the development of automatic inspection system for detecting the defects on photovoltaic wafer by using machine vision. Until now, The defect inspection process was manually performed by operators. So these processes caused the produce of poorly-made articles and inaccuracy results. To improve the inspection accuracy, the inspection system is not only configured, but the image processing algorithm is also developed. The inspection system includes dimensional verification and pattern matching which compares a 2-D image of an object to a pattern image the method proves to be computationally efficient and accurate for real time application and we confirmed the applicability of the proposed method though the experience in a complex environment.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.294-294
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• 2000

In this paper, we would like to discuss the signal processing and the algorithm for ECG analysis. The ECG gives us information about the condition of the heart muscle, because myocardial abnormality or infarction is inscribed on the ECG during myocardial depolarization and repolarization. Analyzing the ECG signal, we can find heart disease, for example, arrhythmia and myocardial infarction, etc. Particularly, detecting arrhythmia is more important, because serious arrhythmia can take away the life from patients within ten minutes. The wavelet transform decomposes the ECG signal into high and low frequency component using wavelet function. Recomposing high frequency bands including QRS complex, we can detect QRS complex and eliminate the noise from the original ECG signal. To recognize the ECG signal pattern, we adopted the curve-fitting partially and statistical method. The ECG signal is divided into small parts based on QRS complex, and then, each part is approximated to the polynomials. Comparing the approximated ECG pattern with some kinds of heart disease ECG pattern, we can detect and classify the kind of heart disease.