• Journal of the Korea Society of Computer and Information
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• v.22 no.11
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• pp.1-7
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• 2017

In this paper, we introduce three monitoring filtering techniques which reduce the overheads of dynamic data race detection. It is well known that detecting data races dynamically in multi-threaded programs is quite hard and troublesome task, because the dynamic detection techniques need to monitor all execution of a multi-threaded program and to analyse every conflicting memory and thread operations in the program. Thus, the main drawback of the dynamic analysis for detecting data races is the heavy additional time and space overheads for running the program. For the practicality, we also empirically compare the efficiency of three monitoring filtering techniques. The results using OpenMP benchmarks show that the filtering techniques are practical for dynamic data race detection, since they reduce the average runtime overhead to under 10% of that of the pure detection.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.1-2
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• 2016

다중 스레드 기반 병렬 프로그램에서의 자료경합 탐지는 동시에 수행되는 스레드 간의 비결정적인 상호작용 때문에 탐지하기 어려운 것으로 잘 알려져 있다. 동적 분석기술을 사용하여 자료경합을 탐지할 경우 프로그램 수행의 감시와 충돌하는 모든 메모리 연산의 분석을 위해 추가적인 오버헤드가 발생한다는 단점이 있다. 이러한 동적 분석의 추가적인 오버헤드를 줄이는 방법으로 감시 필터링 기술이 소개되고 있으며, 본 논문에서는 동적 자료경합 탐지를 위한 감시 필터링 기술 중 OpenMP 디렉티브 병렬 프로그램에 적용 가능한 두 기술을 대상으로 실용성과 효율성을 실험적으로 비교한다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.715-722
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• 2012

A structural health monitoring (SHM) technique for locating impact position in a composite plate is presented in this paper. The technique employs a single sensor and spatial focusing properties of time reversal (TR) and inverse filtering (IF). We first examine the focusing effect of back-propagated signal at the impact position and its surroundings through simulation. Impact experiments are then carried out and the localization images are found using the TR and IF signal processing, respectively. Both techniques provide accurate impact location results. Compared to existing techniques for locating impact or acoustic emission source, the proposed methods have the benefits of using a single sensor and not requiring knowledge of material properties and geometry of structures. Furthermore, it does not depend on a particular mode of dispersive Lamb waves that is frequently used in the SHM of plate-like structures.

• Proceedings of the Korean Society for Information Management Conference
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• 1997.08a
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• pp.37-53
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• 1997

The huge size of Internet does not allow ordinary information seekers to search information with ease. Now, it is almost impossible to navigate the ocean of information without effective search tools. Web search engine has been the most effective technology for information retrieval on WWW. But recently, the need for new search tools on WWW or Internet has increased drastically. Currently, there are many on-going researches on the related topics. In this survey, we categorize the new search tools into four types: monitoring systems, filtering systems, browsing assistant systems, recommending systems. These example systems are examined. We are especially interested in WWW information filtering. It is studied how to apply the information filtering techniques to WWW, The application is not so straightforward like Email, Newswire filtering systems. As a result of this study, a simple WWW information filtering system is proposed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.374-379
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• 2016

On-line process monitoring schemes are designed to give early warnings of process faults. In the artificial intelligence and machine learning fields, reliable approaches have been utilized, such as kernel-based nonlinear techniques. This work presents a kernel-based empirical monitoring scheme with a small sample problem. The measurement data of normal operations are easy to collect, whereas special events or faults data are difficult to collect. In such situations, noise filtering techniques can be helpful in enhancing the process monitoring performance. This can be achieved by the preprocessing of raw process data and eliminating unwanted variations of data. In this work, the performance of several monitoring schemes was demonstrated using three-dimensional batch process data. The results showed that the monitoring performance was improved significantly in terms of the detection success rate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.538-543
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• 2016

For a good product quality and plant safety, it is necessary to implement the on-line monitoring and diagnosis schemes of industrial processes. Combined with monitoring systems, reliable diagnosis schemes seek to find assignable causes of the process variables responsible for faults or special events in processes. This study deals with the real-time diagnosis of complicated industrial processes from the intelligent use of multivariate statistical techniques. The presented diagnosis scheme consists of a classification-based diagnosis using nonlinear representation and filtering of process data. A case study based on the simulation data was conducted, and the diagnosis results were obtained using different diagnosis schemes. In addition, the choice of future estimation methods was evaluated. The results showed that the performance of the presented scheme outperformed the other schemes.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.311-314
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• 1995

This paper presents a method for measuring tool wear parameters based on two dimensional image information. The tool wear images were obtained from an ITV camera with magnifying and lighting devices, and were analyzed using image processing techniques such as thresholding, noise filtering and boundary tracing. Thresholding was used to transform the captured gray scale image into a binary image for rapid sequential image processing. The threshold level was determined using a novel technique in which the brightness histograms of two concentric windows containing the tool wear image were compared. The use of noise filtering and boundary tracing to reduce the measuring errors was explored. Performance tests of the measurement precision and processing speed revealed that the direct method was highly effective in intermittent tool wear monitoring.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.351-361
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• 2003

As the launches of a series of remote sensing satellites, there are various multiresolution and multi-spectral images available nowadays. This diversity in remotely sensed image data has created a need to be able to integrate data from different sources. The C-band imaging radar of ERS-2 due to its high sensitivity to coastal wetlands holds tremendous potential in mapping and monitoring coastal wetland features. This paper investigates the advantages of using ERS-2 SAR data combined with IRS-ID LISS-3 data for mapping complex coastal wetland features of Tamil Nadu, southern India. We present a methodology in this paper that highlights the mapping potential of different combinations of filtering and integration techniques. The methodology adopted here consists of three major steps as following: (i) speckle noise reduction by comparative performance of different filtering algorithms, (ii) geometric rectification and coregistration, and (iii) application of different integration techniques. The results obtained from the analysis of optical and microwave image data have proved their potential use in improving interpretability of different coastal wetland features of southern India. Based visual and statistical analyzes, this study suggests that brovey transform will perform well in terms of preserving spatial and spectral content of the original image data. It was also realized that speckle filtering is very important before fusing optical and microwave data for mapping coastal mangrove wetland ecosystem.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2001.04a
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• pp.58-65
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• 2001

It is essential to know exactly what the response of the seismograph is inclusive of characteristic of the seismic sensors before using it for detailed seismic study. This is because the recorded earthquake data can be more or less affected by the overall system and need to be corrected properly to the analysis`s best to obtain the right results. In this respect, two basic earthquake data processing techniques are introduced and applied, for validation purpose, to real data from KEPRI seismic monitoring system which were established for determining the site-specific characteristics of the earthquakes around the Nuclear Power Plants. One is conventional instrumental correction technique for velocity data and the other is for removing acausal ringing originate from using linear phase FIR filter. These techniques are all implemented in the time domain using digital filtering process and shows the desired results when applied to real earthquake data.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.2
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• pp.152-159
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• 2013

A structural health monitoring(SHM) technique for locating impact position in a composite plate is presented in this paper. The technique employs a single sensor and spatial focusing properties of time reversal(TR) and inverse filtering(IF). We first examine the focusing effect of back-propagated signal at the impact position and its surroundings through simulation. Impact experiments are then carried out and the localization images are found using the TR and IF signal processing, respectively. Both techniques provide accurate impact location results. Compared to existing techniques for locating impact or acoustic emission source, the proposed methods have the benefits of using a single sensor and not requiring knowledge of material properties and geometry of structures. Furthermore, it does not depend on a particular mode of dispersive Lamb waves that is frequently used in the SHM of plate-like structures.