• 비파괴검사학회지
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• 제7권2호
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• pp.35-41
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• 1988

The optimum test conditions of measuring the crack height were determined for the two-probe ultrasonic diffraction method. The applicability and the accuracy of the two-probe ultrasonic diffraction method on the inclined artificial cracks and the fatigue cracks were evaluated. It us possible to measure the height of the normal and inclined artificial cracks with the maximum error of ${\pm}\;0.5mm$ with the two-probe ultrasonic diffraction method. It was found, however, that the accuracy of this method in meaasuring the height of the fatigue crack depends on the degree of closure of the crack tip. It was desirable to choose a refraction angle as small as possible, but the angle should not be so small that the distortion of the lateral waveform became appreciable.

• 한국정밀공학회지
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• 제17권5호
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• pp.124-130
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• 2000

For measuring out the submicron order straightness, a precision measuring device is developed in this paper. The device is constructed with a hydrostatic feed table and a capacitive type sensor which is mounted to the feed table. Straightness is acquired as substracting the motion error of feed table from the measured profile with probe. Motion error of feed table is simultaneously compensated upto 0.120${\mu}{\textrm}{m}$ of linear motion error and 0.20arcsec of angular motion error using the active controlled capillary. Reversal method and strai호t-edge is used fur estimating the measuring accuracy and from the experimental result, it is verified that the device has the measuring accuracy 0.030m. Also, through the practical application on the measurement of ground surface, it is confirmed that the device is very effective to measure the submicron order straightness.

• 항공우주기술
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• 제6권2호
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• pp.219-228
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• 2007

구름 검출 시 사용되는 인자들에 따른 Landmark 정합의 정밀도 변화를 추정하기 위한 시험을 수행하였다. 본 시험을 위해서 MTSAT-1R의 7개 영상을 이용하였으며, Landmark 정합의 정밀도는 대략 0.1 화소 이하로 추정됨을 확인할 수 있었다.

• Journal of Computing Science and Engineering
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• 제11권3호
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• pp.100-108
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• 2017

In the field of Internet of Things (IoT), smarter embedded devices offer functions via web services. The Quality-of-Service (QoS) prediction is a key measure that guarantees successful IoT service applications. In this study, a collaborative filtering method is presented for predicting response time of IoT service due to time-awareness characteristics of IoT. First, a calculation method of service response time similarity between different users is proposed. Then, to improve prediction accuracy, initial similarity values are adjusted and similar neighbors are selected by a similarity threshold. Finally, via a densified user-item matrix, service response time is predicted by collaborative filtering for current active users. The presented method is validated by experiments on a real web service QoS dataset. Experimental results indicate that better prediction accuracy can be achieved with the presented method.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2013년도 춘계학술대회
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• pp.141-143
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• 2013

현재 나와 있는 휴대용 방사선 검출장치들은 기능적으로 제약이 크다. 이러한 단점을 해결하고자 안드로이드 플랫폼 기반의 휴대용 방사선 검출장치에 관한 연구가 이루어졌다. 연구초기 단계인 만큼 방사선 측정은 가능하지만, 정확도가 나와 있는 제품들만큼 높지 못하다. 이러한 안드로이드 플랫폼 기반의 휴대용 방사선 검출장치는 온도에 따라 오차가 발생하게 된다. 이와 같은 온도에 따른 오차를 제거하기 위해 온도에 따른 보상 알고리즘을 구현하여 정확도를 향상하고자 한다.

• Journal of Information Processing Systems
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• 제12권4호
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• pp.644-660
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• 2016

The real-time detection of malware remains an open issue, since most of the existing approaches for malware categorization focus on improving the accuracy rather than the detection time. Therefore, finding a proper balance between these two characteristics is very important, especially for such sensitive systems. In this paper, we present a fast portable executable (PE) malware detection system, which is based on the analysis of the set of Application Programming Interfaces (APIs) called by a program and some technical PE features (TPFs). We used an efficient feature selection method, which first selects the most relevant APIs and TPFs using the chi-square ($KHI^2$) measure, and then the Phi (${\varphi}$) coefficient was used to classify the features in different subsets, based on their relevance. We evaluated our method using different classifiers trained on different combinations of feature subsets. We obtained very satisfying results with more than 98% accuracy. Our system is adequate for real-time detection since it is able to categorize a file (Malware or Benign) in 0.09 seconds.

• 소성∙가공
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• 제5권4호
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• pp.343-352
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• 1996

One of the preferred methods that can be used to verify the results of finite element analysis is to measure surface strains of the deformed part for purpose of direct comparison with simulation results. Instead of using the usual manual method the vision-based measurement method is capable of determining surface geometry and strain from the deformed grid pattern automatically with the help of a computer. To obtain strain distribution over an area, the coordinates of such a surface grid are determined from the multiple video images by applying the photogrammetry principle. Methods to improve the overall accuracy of the vision-based strain measurement system are explored and the possible accuracies that can be attained by such a measurement method are discussed. A major emphasis is placed on the initial grid application method its accuracy and ease of subsequent image processing. Finite element analyses of limiting dome height(LDH) test are carried out and the results of them are compared with exsperimen-tal data.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.366-370
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• 2002

A kinematic ball bar measurement system can analyze the various errors of a machine tool easily and rapidly in a procedure and can measure many types of equipment such as chip mounter, PCB router, precision stage, etc. In this paper, the thermally induced errors are loused among various errors of a chip mounter because it affects the accuracy of the machine very much. Linear regression technique is adapted for the thermal error modeling. While the measurement and calibration of a chip mounter is difficult in general, this developed system is not only easy to apply for it but also improves the accuracy by 4 times or more.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2007년도 학술발표회 논문집
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• pp.1592-1596
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• 2007

Accuracy of flood forecasting is an important non-structural measure on the flood control and mitigation. Hence, combination of horologic model with real time error correction became an important issue. It is one of the efficient ways to improve the forecasting precision. In this work, an approach based on Kalman Filter (KF) is proposed to continuously revise state estimates to promote the accuracy of flood forecasting results. The case study refers to the Wi River in Korea, with the flood forecasting results of Xinanjiang model. Compared to the results, the corrected results based on the Kalman filter are more accurate. It proved that this method can take good effect on hydrologic forecasting of Wi River, Korea, although there are also flood peak discharge and flood reach time biases. The average determined coefficient and the peak discharge are quite improved, with the determined coefficient exceeding 0.95 for every year.

• 말소리와 음성과학
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• 제1권3호
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• pp.109-115
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• 2009

Many isolated word recognition systems may generate non-similar words for recognition candidates because they use only acoustic information. In this paper, we investigate several techniques which can exclude non-similar words from N-best candidate words by applying Levenstein distance measure. At first, word distance method based on phone and syllable distances are considered. These methods use just Levenstein distance on phones or double Levenstein distance algorithm on syllables of candidates. Next, word similarity approaches are presented that they use characters' position information of word candidates. Each character's position is labeled to inserted, deleted, and correct position after alignment between source and target string. The word similarities are obtained from characters' positional probabilities which mean the frequency ratio of the same characters' observations on the position. From experimental results, we can find that the proposed methods are effective for removing non-similar words without loss of system performance from the N-best recognition candidates of the systems.