• Journal of the Institute of Convergence Signal Processing
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• v.7 no.4
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• pp.161-168
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• 2006

In this paper, we propose a method for the pattern inspection of LCD module using the color compensation and pattern matching. The pattern matching is generally used for the inspection method of LCD module at the industry. LCD module has many defections such as the brightness difference of the back light, the optic feature of liquid crystal, the difference of the light penetrated by driving LCD and the color difference by the lighting. The conventional method without the color compensation can not solve these defections and decreases the efficiency of inspecting LCD module. The method proposed to inspect defective badness through the pattern matching after it compensated color difference of the LCD occurred by the various causes. At first, it revises with setting by standard tone of color with the LCD pattern of the reference image. And It perform the preprocessing and pattern matching algorithm on the compensated image. In experiment, we confirmed that this algorithm is useful to detect some defections of LCD module. The proposed methods was easy to detect the faulty product.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.71-77
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• 2011

CEP(Complex Event Processing) is a technique to find complex event pattern in a massive information system. Based on CEP technique, an abuse pattern monitoring method has been developed to provide an real-time detection. In the method, the events occurred by game-play are observed to be against the rules using CEP. User abuse patterns are pre-registered in CEP engine. And CEP engine monitors user abuse after aggregating the game data transferred by game logging server. This article provides the performance analysis results of the abuse pattern monitoring method using real game DB. We results that the method proposed in previous study is effective to monitor abusing users.

• Journal of the Korean Institute of Oriental Medical Informatics
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• v.18 no.1
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• pp.1-63
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• 2012

Objective : "Huatuoxuanmenneizhaotu" is a Huatuo's about 5~6 century works are estimated to be voted for. Scored the first Anatomical Pictures. Expand your knowledge on the anatomy of the later set the foundation. This books is part of two volumes, which is largely divided into six parts. We have concern on the content and features. Method : Through "Huatuoxuanmenneizhaotu" text translation, we will try to categorize two ways : classifying 1) The first volume of Chapter 1, Pictures 2) The second volume divided into four parts, Chapter 2, Viscera Disease and Chapter 3, Viscera metastasize and Chapter 4, Viscera and Bowel each for metastasize, explained. Result : In consideration against Disease symptom classification, Medicine classification, processing of medicinals examine. Viscera Disease symptom each wind pattern(風證), qi pattern(氣證), heat pattern(熱證), cold pattern(冷證), deficiency pattern(虛證) was classified as. Same method were explained as Viscera into Viscera, as Viscera into Bowel. Viscera Disease also not mentioned in the Bowel Disease symptoms were found to be viewed. Conclusion : These results explain "HuatuoXuanmenNeizhaotu" were really diverse and various.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.4
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• pp.391-406
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• 2014

The performance of General-Purpose computation on Graphics Processing Units (GPGPU) is heavily dependent on the memory access behavior. This sensitivity is due to a combination of the underlying Massively Parallel Processing (MPP) execution model present on GPUs and the lack of architectural support to handle irregular memory access patterns. Application performance can be significantly improved by applying memory-access-pattern-aware optimizations that can exploit knowledge of the characteristics of each access pattern. In this paper, we present an algorithmic methodology to semi-automatically find the best mapping of memory accesses present in serial loop nest to underlying data-parallel architectures based on a comprehensive static memory access pattern analysis. To that end we present a simple, yet powerful, mathematical model that captures all memory access pattern information present in serial data-parallel loop nests. We then show how this model is used in practice to select the most appropriate memory space for data and to search for an appropriate thread mapping and work group size from a large design space. To evaluate the effectiveness of our methodology, we report on execution speedup using selected benchmark kernels that cover a wide range of memory access patterns commonly found in GPGPU workloads. Our experimental results are reported using the industry standard heterogeneous programming language, OpenCL, targeting the NVIDIA GT200 architecture.

• Proceedings of the KOSOMBE Conference
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• v.1993 no.11
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• pp.81-84
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• 1993

Artificial Heart Valve is the one of the most important artificial organ which has been implanted to many patients. The most important problems related to the artificial heart valve prosthesis are thrombosis and hemolysis. Usual method to test against this problem in vivo experiment, which is complex and hard work. Nowadays the request for In vitro Artificial Heart Valve testing system is increasing. Several papers has announced us flow pattern of Artificial Heart Valve is highly correlated with thrombosis and hemolysis. They usually gel flow pattern by LDA, it is also hard work and has narrow measuring region. In this reason we have determined to develop PTV(Particle Tracking Velocimetry). By using High-speed camera and image processing technique, flow pattern could be relatively easily obtained. Parachute and Bileaflet Artificial Heart Valve designed by SNU were testified.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.645-654
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• 2019

The purpose of this study was to collect and analyze personal bio data and social network services (SNS) data, derive user preference and user life pattern, and propose intuitive and precise user modeling. This study not only tried to conduct eye tracking experiments using various smart devices to be the ground of the recommendation system considering the attribute of smart devices, but also derived classification preference by analyzing eye tracking data of collected bio data and SNS data. In addition, this study intended to combine and analyze preference of the common classification of the two types of data, derive final preference by each smart device, and based on user life pattern extracted from final preference and collected bio data (amount of activity, sleep), draw the similarity between users using Pearson correlation coefficient. Through derivation of preference considering the attribute of smart devices, it could be found that users would be influenced by smart devices. With user modeling using user behavior pattern, eye tracking, and user preference, this study tried to contribute to the research on the recommendation system that should precisely reflect user tendency.

• The Journal of Korean Academy of Sensory Integration
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• v.14 no.2
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• pp.22-32
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• 2016

Objective : The purpose of study is to investigate the correlation between sensory processing pattern and depression and anxiety of university students. Methods : A designed questionnaire for this study has been distributed to university students for about a month (10th to 29th of August, 2016). The questionnaire is consisted of 5 items for personal characteristics, 60 items for adult/adolescent sensory profile, 21 items from the Beck depression scale-2, and 21 items from the Beck anxiety scale. The data has been collected from 174 university students and analyzed by SPSS version 22.0 for descriptive statistics, cross-tabulation analysis, and Pearson correlation. Results : For depression, there is significant positive correlation with low registration, sensory sensitivity, and sensory avoiding among the sensory processing patterns. For anxiety, all sensory processing patterns are significantly correlated with it. Conclusion : Based on the result of this study, it is recommended for academic staffs or health care professionals to consider the impact of sensory processing patterns on psychological function when they develop an educational program for university students or plan a treatment for young clients.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.9
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• pp.4130-4135
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• 2013

This paper is a special-purpose machine studies for processing various patterns on the surface of the stone. We have developed a special-purpose machine that can be applied in various patterns upon the surface treatment of the stone with the water jet. The special-purpose machine is Configured of Transfer mechanism, motion controller, multi-nozzle mechanism, ultra high pressure water control system and S/W. We conducted a performance evaluation experiments of the pattern. We have developed a special-purpose machine with a precision of machining error ${\pm}0.5mm$ and pattern processing of various types.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3315-3337
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• 2012

Crowded scenes analysis is a challenging topic in computer vision field. How to detect diverse motion patterns in crowded scenarios from videos is the critical yet hard part of this problem. In this paper, we propose a novel approach to mining motion patterns by utilizing motion information during both long-term period and short interval simultaneously. To capture long-term motions effectively, we introduce Motion History Image (MHI) representation to access to the global perspective about the crowd motion. The combination of MHI and optical flow, which is used to get instant motion information, gives rise to discriminative spatial-temporal motion features. Benefitting from the robustness and efficiency of the novel motion representation, the following motion pattern mining is implemented in a completely unsupervised way. The motion vectors are clustered hierarchically through automatic hierarchical clustering algorithm building on the basis of graphic model. This method overcomes the instability of optical flow in dealing with time continuity in crowded scenes. The results of clustering reveal the situations of motion pattern distribution in current crowded videos. To validate the performance of the proposed approach, we conduct experimental evaluations on some challenging videos including vehicles and pedestrians. The reliable detection results demonstrate the effectiveness of our approach.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.91-96
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• 2022

At the current camera-based technology level, sensor-based basic life pattern recognition technology has to suffer inconvenience to obtain accurate data, and commercial band products are difficult to collect accurate data, and cannot take into account the motive, cause, and psychological effect of behavior. the current situation. In this paper, radar technology for life pattern recognition is a technology that measures the distance, speed, and angle with an object by transmitting a waveform designed to detect nearby people or objects in daily life and processing the reflected received signal. It was designed to supplement issues such as privacy protection in the existing image-based service by applying it. For the implementation of the proposed system, based on TI IWR1642 chip, RF chipset control for 60GHz band millimeter wave FMCW transmission/reception, module development for distance/speed/angle detection, and technology including signal processing software were implemented. It is expected that analysis of individual life patterns will be possible by calculating self-management and behavior sequences by extracting personalized life patterns through quantitative analysis of life patterns as meta-analysis of living information in security and safe guards application.