• Design & Manufacturing
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• v.16 no.3
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• pp.34-38
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• 2022

Regular expression pattern matching is widely used in applications such as computer virus vaccine, NIDS and DNA sequencing analysis. Hardware-based pattern matching is used when high-performance processing is required due to time constraints. ReCPU, SMPU, and REMP, which are processor-based regular expression matching processors, have been proposed to solve the problem of the hardware-based method that requires resynthesis whenever a pattern is updated. However, these processor-based regular expression matching processors inefficiently handle repetitive operations of regular expressions. In this paper, we propose a new instruction set to improve the inefficient repetitive operations of ReCPU and SMPU. We propose REMPi, a regular expression matching processor that enables efficient iterative operations based on the REMP instruction set. REMPi improves the inefficient method of processing a particularly short sub-pattern as a repeat operation OR, and enables processing with a single instruction. In addition, by using a down counter and a counter stack, nested iterative operations are also efficiently processed. REMPi was described with Verilog and synthesized on Intel Stratix IV FPGA.

• The Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1291-1295
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• 1999

Modern functional languages provide some forms of pattern matching capability in them. However, these forms are on an ad-hoc basis and vary from languages to languages, making the user hard to understand the feature. To overcome this problem, we present a systematic approach to adding pattern matching to functional language. We extend to the core functional language with pattern matching capability and illustrate several examples of the language. We also discuss how to extend the pattern matching capability to higher-order terms.

• Laser Solutions
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• v.13 no.2
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• pp.1-5
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• 2010

A high speed laser texturing method that relies on laser scanner conditions, to form pattern shapes with micro-narrow surface detail such as dotted line features is demonstrated and analyzed. For example, this method may be used to piston ring and gear part for automotive. Data on friction characteristics of two laser patterns employed for STD61 steel will be shown. Comparison of pattern depths obtained by repetition overlapping process with laser scanner to the results on friction coefficient will be provide. It will be shown that friction characteristic in dotted line patterns can significantly depend upon interaction with the lubrication and laser pattern conditions. Laser pattern processing into a shallow depth provides only slight improvement in friction, while work into a deep shape indicates a significant improvement.

• Journal of Sensor Science and Technology
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• v.17 no.6
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• pp.406-413
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• 2008

We have been implemented simple statistical pattern recognition methods for harmful gases classification using gas sensors array fabricated by MEMS (Micro Electro Mechanical System) technology. The performance of pattern recognition method as a gas classifier is highly dependent on the choice of pre-processing techniques for sensor and sensors array signals and optimal classification algorithms among the various classification techniques. We carried out pre-processing for each sensor's signal as well as sensors array signals to extract features for each gas. We adapted simple statistical pattern recognition algorithms, which were PCA (Principal Component Analysis) for visualization of patterns clustering and MLR (Multi-Linear Regression) for real-time system implementation, to classify harmful gases. Experimental results of adapted pattern recognition methods with pre-processing techniques have been shown good clustering performance and expected easy implementation for real-time sensing system.

• Journal of Multimedia Information System
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• v.5 no.4
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• pp.221-228
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• 2018

Skin-color information is not sufficient for palmprint segmentation in complex scenes, including mobile environments. Traditional active shape model (ASM) combines gray information and shape information, but its performance is not good in complex scenes. An improved ASM method is developed for palmprint segmentation, in which Perux method normalizes the shape of the palm. Then the shape model of the palm is calculated with principal component analysis. Finally, the color likelihood degree is used to replace the gray information for target fitting. The improved ASM method reduces the complexity, while improves the accuracy and robustness.

• Journal of the Korean Society of Industry Convergence
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• v.16 no.3
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• pp.85-93
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• 2013

The MCT has been most extensively used in the machining. In particular, the ball endmill has been mainly adopted for finishing on the free- form surface. The advancement of CAD/CAM software has made it possible to develop various cutting pattern methods and to create diverse tool routes. Therefore, the current research made an attempt to find the optimal cutting pattern among the seven cutting patterns (i.e., Follow Periphery, Zig, Zig Zag, Concentric Zig, Concentric Zig Zag, Radial Zig, Radial Zig Zag) when aluminium 6000 series were machined by the ball endmill. The optimal pattern was found by comparing different shapes and surface roughness produced by the seven patterns. The current research found that each cutting pattern produced its own unique geometric features on the machined surface. It was found that the Radial Zig cutting pattern produced the lowest roughness on the flat surfaces. The Radial Zig Zag cutting pattern was found to produce the most accurate free-form surface. Finally, the most efficient cutting pattern in terms of machining time turned out to be the Follow Periphery.

• ETRI Journal
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• v.43 no.3
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• pp.483-510
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• 2021

In computational biology, desired patterns are searched in large text databases, and an exact match is preferable. Classical benchmark algorithms obtain competent solutions for pattern matching in O (N) time, whereas quantum algorithm design is based on Grover's method, which completes the search in $O(\sqrt{N})$ time. This paper briefly explains existing quantum algorithms and defines their processing limitations. Our initial work overcomes existing algorithmic constraints by proposing the quantum-based combined exact (QBCE) algorithm for the pattern-matching problem to process exact patterns. Next, quantum random access memory (QRAM) processing is discussed, and based on it, we propose the QRAM processing-based exact (QPBE) pattern-matching algorithm. We show that to find all t occurrences of a pattern, the best case time complexities of the QBCE and QPBE algorithms are $O(\sqrt{t})$ and $O(\sqrt{N})$, and the exceptional worst case is bounded by O (t) and O (N). Thus, the proposed quantum algorithms achieve computational speedup. Our work is proved mathematically and validated with simulation, and complexity analysis demonstrates that our quantum algorithms are better than existing pattern-matching methods.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.1
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• pp.119-127
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• 2000

In this study the classified researches the artificial and natural flaws in welding parts are performed using the pattern recognition technology. For this purpose the signal pattern recognition package including the user defined function was developed and the total procedure including the digital signal processing feature extraction feature selection and classifi-er selection is teated by bulk,. Specially it is composed with and discussed using the statistical classifier such as the linear discriminant function the empirical Bayesian classifier. Also the pattern recognition technology is applied to classifica-tion problem of natural flaw(i.e multiple classification problem-crack lack of penetration lack of fusion porosity and slag inclusion the planar and volumetric flaw classification problem), According to this result it is possible to acquire the recognition rate of 83% above even through it is different a little according to domain extracting the feature and the classifier.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05c
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• pp.2189-2192
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• 2003

전자정부, 전자상거래의 활성화로 디지털 문서가 빠른 속도로 유통되고 있기에 이에 대한 효과적인 보호대책이 필요한 실정이다. 본 논문에서는 Window Pattern을 이용하여 Binary Image에 저작권 정보를 삽입하는 방안을 제안한다. 삽입대상 Window Pattern을 결정하고 이러한 Pattern으로 원본 영상을 Scan하면서 픽셀 값에 변화를 주게 된다. 이렇게 되어 하나의 Pattern에 1bit의 정보의 삽입이 가능하게 되고 추출 시 원본을 필요로 하지 않으며 실용성이 높고 적용분야도 넓다.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.1-6
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• 2014

Color image processing based on smoke detection is suitable detecting target to early detection of fire smoke. A method for detecting the smoke is processed in the pre-processing movement and color. And Next, characteristics of smoke such as diffusion, texture, shape, and directionality are used to post-processing. In this paper, propose the detection method of density distribution characteristic in characteristics of smoke. the generate a candidate regions by color thresholding image in Detecting the movement of smoke to the 10Frame interval and accumulated while 1second image. then check whether the pattern of the smoke by candidate regions to applying OBTP(Object Block Ternary Pattern). every processing is Block-based processing, moving detection is decided the candidate regions of the moving object by applying an adaptive threshold to frame difference image. The decided candidate region accumulates one second and apply the threshold condition of the smoke color. make the ternary pattern compare the center block value with block value of 16 position in each candidate region of the smoke, and determine the smoke by compare the candidate ternary pattern and smoke ternary pattern.