• International Journal of Safety
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• v.1 no.1
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• pp.28-35
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• 2002

Kullback Discrimination Information (KDI) is one of the pattern recognition methods. KDI defined as a measure of the mutual dissimilarity computed between two time series was studied for detection and classification of bearing flaking on outer-race and inner-races. To model the damages, the bearings in normal condition, outer-race flaking condition and inner-races flaking condition were provided. The vibration sensor was attached by the bearing housing. This produced the total 25 pieces of data each condition, and we chose the standard data and measure of distance between standard and tested data. It is difficult to detect the flaking because similar pulses come out when balls pass the defection point. The detection and classification method for inner and outer races are defected by KDI and nearest neighbor classification rule is proposed and its high performance is also shown.

• The KIPS Transactions:PartA
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• v.16A no.2
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• pp.55-60
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• 2009

Race conditions in current Java programs must be detected because it may cause unexpected result by non-deterministic executions. For detecting such races during program execution, execution flows of all threads and all access events can be monitored. It is difficult for previous race detection techniques to monitor all threads and access events in actuality because these techniques analyze the files traced during program execution or modify original source programs and then monitor these programs. This paper presents a transparent scalable monitoring tool to detect races using JDI(Java Debug Interface) where JDI is 100% pure java interface to provide in JDPA(Java Platform Debugger Architecture) and is able to provide information corresponding to events occurred in run-time of programs. This tool thus can monitor execution flows of all threads and all access events without program modification. We prove transparency of the presented tool and grasp the efficiency of it using a set of published benchmark programs. As a result of this, the suggested tool can monitor all threads and accesses of these programs without their modification, and their monitoring time is increased to more than 20 times.

• The KIPS Transactions:PartA
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• v.9A no.4
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• pp.525-534
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• 2002

Race conditions, races in short, need to be detected for debugging parallel programs, because the races result in unintended non-deterministic executions. To detect the races in an execution of program, previous techniques use a centralized data structure which may incur serious bottleneck in generating concurrency information, or show inefficient time complexity which depends on the degree of nested parallelism in comparing any two of them. We propose a new labeling scheme in this paper, which is scalable in generating the concurrency information without bottleneck by using private data structure, and improves time complexity into constant in checking concurrency. The scalability and time efficiency therfore makes on-the-fly race detection efficient not only for programs with either shared-memory or message-passing, but also for programs with mixed model of the two.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.12
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• pp.1287-1294
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• 2004

Hub bearings not only sustain the body of a cat, but permit wheels to rotate freely. Excessive radial or axial load and many other reasons can cause defects to be created and grown in each component. Therefore, nitration and noise from unwanted defects in outer-race, inner-race or ball elements of a Hub bearing are what we want to detect as early as possible. How early we can detect the faults has to do with how the detection algorithm finds the fault information from measured signal. Fortunately, the bearing signal has Periodic impulse train. This information allows us to find the faults regardless how much noise contaminates the signal. This paper shows the basic signal processing idea and experimental results that demonstrate how good the method is.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.593-596
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• 2004

Hub bearings not only sustain the body of a car, but permit wheels to rotate freely. Excessive radial or axial load and many other reasons can cause defects to be created and grown in each component. Therefore, vibration and noise from unwanted defects in outer-race, inner-race or ball elements of a Hub bearing are what we want to detect as early as possible. How early we can detect the faults has to do with how the detection algorithm finds the fault information from measured signal. Fortunately, the bearing signal has periodic impulse train. This information allows us to find the faults regardless how much noise contaminates the signal. This paper shows the basic signal processing idea and experimental results that demonstrate how good the method is.

• The Plant Pathology Journal
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• v.34 no.6
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• pp.506-513
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• 2018

Clubroot is one of the most economically important diseases of the Brassicaceae family. Clubroot disease is caused by the obligate parasite Plasmodiophora brassicae, which is difficult to study because it is nonculturable in the laboratory and its races are genetically variable worldwide. In Korea, there are at least five races that belongs to four pathotype groups. A recent study conducted in Korea attempted to develop molecular markers based on ribosomal DNA polymorphism to detect P. brassicae isolates, but none of those markers was either race-specific or pathotype-specific. Our current study aimed to develop race- and isolate-specific markers by exploiting genomic sequence variations. A total of 119 markers were developed based on unique variation exists in genomic sequences of each of the races. Only 12 markers were able to detect P. brassicae strains of each isolate or race. Ycheon14 markers was specific to isolates of race 2, Yeoncheon and Hoengseong. Ycheon9 and Ycheon10 markers were specific to Yeoncheon isolate (race 2, pathotype 3), ZJ1-3, ZJ1-4 and ZJ1-5 markers were specific to Haenam2 (race 4) isolate, ZJ1-35, ZJ1-40, ZJ1-41 and ZJ1-49 markers were specific to Hoengseong isolate and ZJ1-56 and ZJ1-64 markers were specific to Pyeongchang isolate (race 4, pathotype 3). The PCR-based sequence characterized amplified region (SCAR) markers developed in this study are able to detect five Korean isolates of P. brassicae. These markers can be utilized in identifying four Korean P. brassicae isolates from different regions. Additional effort is required to develop race- and isolate-specific markers for the remaining Korean isolates.

• The Plant Pathology Journal
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• v.39 no.5
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• pp.494-503
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• 2023

Xanthomonas campestris pv. campestris (Xcc) is a plant pathogen of Brassica crops that causes black rot disease throughout the world. At present, 11 physiological races of Xcc (races 1-11) have been reported. The conventional method of using differential cultivars for Xcc race detection is not accurate and it is laborious and time-consuming. Therefore, the development of specific molecular markers has been used as a substitute tool because it offers an accurate and reliable result, particularly a quick diagnosis of Xcc races. Previously, our laboratory has successfully developed race-specific molecular markers for Xcc races 1-6. In this study, specific molecular markers to identify Xcc race 7 have been developed. In the course of study, whole genome sequences of several Xcc races, X. campestris pv. incanae, X. campestris pv. raphani, and X. campestris pv. vesicatoria were aligned to identify variable regions like sequence-characterized amplified regions and insertions and deletions specific to race 7. Primer pairs were designed targeting these regions and validated against 22 samples. The polymerase chain reaction analysis revealed that three primer pairs specifically amplified the DNA fragment corresponding to race 7. The obtained finding clearly demonstrates the efficiency of the newly developed markers in accurately detecting Xcc race 7 among the other races. These results indicated that the newly developed marker can successfully and rapidly detect Xcc race 7 from other races. This study represents the first report on the successful development of specific molecular markers for Xcc race 7.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.7
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• pp.267-275
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• 2007

Message races should be detected for debugging message-passing parallel programs because they can cause non-deterministic executions. Specially, it is important to detect the first race in each process because the first race can cause the occurrence of the other races in the same process. The previous techniques for detecting the first races require more than two monitored runs of a program or analyze a trace file which size is proportional to the number of messages. In this paper we introduce an on-the-fly technique to detect the first race in each process without generating any trace file. In the experiment we test the accuracy of our technique with some benchmark programs and it shows that our technique detects the first race in each process in all benchmark programs.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.173-176
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• 2002

This paper describes an implementation of fast face detection algorithm. This algorithm can robustly detect human faces with unknown sizes and positions in complex backgrounds. This paper provides a powerful face detection algorithm using skin color segmenting. Skin Color is modeled by a Gaussian distribution in the HSI color space among different persons within the same race, Oriental. The main feature of the Algorithm is achieved face detection robust to illumination changes and a simple adaptive thresholding technique for skin color segmentation is employed to achieve robust face detection.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.7-8
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• 2019

자료경합은 두 개 이상의 스레드가 같은 공유메모리에 적절한 동기화 없이 접근하고, 적어도 한 개의 접근사건이 쓰기일 때 발생할 수 있는 동시성 오류이다. 자료경합은 프로그래머가 의도하지 않은 비결정적인 수행결과를 초래하여, 항공기 소프트웨어와 같은 고신뢰성이 요구되는 프로그램에서 치명적인 오류를 발생시켜 인적 물적 손해로 이어질 수 있다. 자료경합 탐지기법은 이러한 문제를 사전에 탐지하여 수정하는데 사용되어진다. 하지만 GPGPU 프로그램에서의 자료경합은 CPU 병행프로그램에서보다 복잡한 실행구조를 가지고 있어 스레드 및 메모리 계층, 스케줄링, 동기화 기법 등의 많은 변수가 존재한다. 이로 인해 실세계 프로그램에 자료경합 탐지기법을 적용하여 검증 시 이러한 변수들을 반영하여 실험하는데 많은 노력이 소요된다. 본 논문은 실세계 프로그램에서의 자료경합을 대표하는 4가지 패턴의 합성프로그램으로 이루어지고 실행 시 스레드 및 메모리 계층, 스레드 구조, 메모리 사용량 및 동기화 방안을 지정할 수 있는 벤치마크 모음을 제시한다.