• Structural Engineering and Mechanics
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• v.36 no.5
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• pp.643-667
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• 2010

The classical flexibility difference method detects damage by observing the difference of conventional deflection flexibility matrices between pre- and post-damaged states of a structure. This method is not able to identify multiple damage scenarios, and its criteria to identify damage depend upon the boundary conditions of structures. The key point behind the inability and dependence is revealed in this study. A more feasible flexibility for damage detection, the Angle-between-String-and-Horizon (ASH) flexibility, is proposed. The physical meaning of the new flexibility is given, and synthesis of the new flexibility matrix by modal frequencies and translational mode shapes is formulated. The damage indicators are extracted from the difference of ASH flexibility matrices between the pre- and post-damaged structures. One feature of the ASH flexibility is that the components in the ASH flexibility matrix are associated with elements instead of Nodes or DOFs. Therefore, the damage indicators based on the ASH flexibility are mapped to structural elements directly, and thus they can pinpoint the damaged elements, which is appealing to damage detection for complex structures. In addition, the change in the ASH flexibility caused by damage is not affected by boundary conditions, which simplifies the criteria to identify damage. Moreover, the proposed method can determine relatively the damage severity. Because the proposed damage indicator of an element mainly reflects the deflection change within the element itself, which significantly reduces the influence of the damage in one element on the damage indicators of other damaged elements, the proposed method can identify multiple damage locations. The viability of the proposed approach has been demonstrated by numerical examples and experimental tests on a cantilever beam and a simply supported beam.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.259-264
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• 1995

Recently, in order to achieve high flexibilty, monitoring and control strategies of a new type have been developed. This paper investigates the fesability of using scoustic emission signal analysis for the detection of built-up edge during machining. Results for maching SM45C steel show that the presence of a built-up edge can significantil affect the generation of acoustic emission in metal cutting. When the cutting speed comes to the conditions conducive to development of built-up edge, it is shown that the slope of curve-fitted AErms signal undergoes a change. The fesability of utilizing AErms in built-up edge sensing is sugested.

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.65-71
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• 2001

In this paper, acoustic omission technique(AE) has been applied to detect leak for heat exchanger by analyzing the characteristics of signal obtained from leak. It was confirmed that the characteristics of the signal generated by the turbulence of gas in the heat exchanger is narrow band signal having between 130-250KHz. Generally, the amplitude of leak signal is increased as the leak size increasing, but showed no significant change at frequency characteristic. Leak source location can be found by searching for the point of highest signal amplitude by comparing wi th several fired sensors.

• ETRI Journal
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• v.28 no.2
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• pp.162-174
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• 2006

Several photogrammetric and geographic information system applications such as surface matching, object recognition, city modeling, environmental monitoring, and change detection deal with multiple versions of the same surface that have been derived from different sources and/or at different times. Surface registration is a necessary procedure prior to the manipulation of these 3D datasets. This need is also applicable in the field of medical imaging, where imaging modalities such as magnetic resonance imaging (MRI) can provide temporal 3D imagery for monitoring disease progression. This paper will present a general automated surface registration procedure that can establish correspondences between conjugate surface elements. Experimental results using light detection and ranging (LIDAR) and MRI data will verify the feasibility, robustness, and accuracy of this approach.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.317-322
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• 2018

We use edge detection technique for the input image to extract the entire edges of the object in the image and then select only the edges that construct the outline of the object. By examining the positional relation between these pixels composing the outline, a simplified version of the outline of the object in the input image is generated by removing unnecessary pixels while maintaining the condition of connection of the outline. For each pixel constituting the outline, its direction is calculated by examining the positional relation with the next pixel. Then, we group the consecutive pixels with same direction into one and then change them to a line segment instead of a point. Among those line segments composing the outline of the object, a line segment whose length is smaller than a predefined minimum length of acceptable line segment is removed by merging it into one of the adjacent line segments. As a result, an outline composed of line segments of over a certain length is obtained through this process.

• Journal of Platform Technology
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• v.11 no.6
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• pp.3-12
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• 2023

In today's system operation, it is difficult to detect failures and take immediate action in the case of a shortage of manpower compared to the number of equipment or failures in vulnerable time zones, which can lead to delays in failure recovery. In addition, various algorithms exist to detect abnormal symptom data, and it is important to select an appropriate algorithm for each problem. In this paper, an ensemble-based isolation forest model was used to efficiently detect multivariate point anomalies that deviated from the mean distribution in the data set generated to predict system failure and minimize service interruption. And since significant changes in memory space usage are observed together with changes in CPU usage, the problem is solved by using LSTM-Auto Encoder for a collective anomaly in which another feature exhibits an abnormal pattern according to a change in one by comparing two or more features. did In addition, evaluation indicators are set for the performance evaluation of the model presented in this study, and then AI model evaluation is performed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.8-15
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• 2007

Recently, it is important to process multimedia data efficiently. Especially, in case of retrieval of multimedia information, technique of user interface and retrieval technique are necessary. This paper proposes a new technique which detects cuts effectively in compressed image information by MPEG. A cut is a turning point of scenes. The cut-detection is the basic work and the first-step for video indexing and retrieval. Existing methods have a weak point that they detect wrong cuts according to change of a screen such as fast motion of an object, movement of a camera and a flash. Because they compare between previous frame and present frame. The proposed technique detects shots at first using DC(Direct Current) coefficient of DCT(Discrete Cosine Transform). The database is composed of these detected shots. Features are extracted by HMMD color model and edge histogram descriptor(EHD) among the MPEG-7 visual descriptors. And detections are performed in sequence by the proposed matching technique. Through this experiments, an improved video segmentation system is implemented that it performs more quickly and precisely than existing techniques have.

• Atmosphere
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• v.33 no.1
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• pp.1-20
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• 2023

Holding the longest observation data from April 1904, Busan is one of the essential points to understand the climate variability of the Korean Peninsula without missing data since implementing the modern weather observation of the South Korea. Busan is featured by coastal areas and affected by various climate factors and fluctuations. This study aims to investigate climate variability and changes in climatic variables, extremes, and several weather indexes. The statistically significant change points in daily mean rainfall intensity and temperature were found in 1964 and 1965. Based on the change point detection, 117 years were divided into two periods for daily mean rainfall intensity and temperature, respectively. In the long-term temperature analysis of Busan, the increasing trend of the daily maximum temperature during the period of 1965~2021 was larger than the daily mean temperature and the daily minimum temperature. Applying Ensemble Empirical Mode Decomposition, daily maximum temperature is largely affected by the decadal variability compared to the daily mean and minimum temperature. In addition, the trend of daily precipitation intensity from 1964~2021 shows a value of about 0.50 mm day^-1, suggesting that the rainfall intensity has increased compared to the preceding period. The results in extremes analysis demonstrate that return values of both extreme temperatures and precipitation show higher values in the latter than in the former period, indicating that the intensity of the current extreme phenomenon increases. For Wet-Bulb Globe Temperature (effective humidity), increasing (decreasing) trend is significant in Busan with the second (third)-largest change among four stations.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.939-947
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• 2019

With the revitalization of the media market, the necessity of compression, searching, editing and copyright protection of videos is increasing. In this paper, we propose a method to detect scene change in all these fields. We propose a pre-processing, feature point extraction using SIFT, and matching algorithm for detecting the same scene change even if distortions such as resolution change, subtitle insertion, compression, and flip are added in the distribution process. Also, it is applied to filtering technology and it is confirmed that it is effective for all transformations other than considering transform.

• Communications for Statistical Applications and Methods
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• v.22 no.5
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• pp.475-485
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• 2015

Similar to regression, many measures to detect influential data points in discriminant analysis have been developed. Many follow similar principles as the diagnostic measures used in linear regression in the context of discriminant analysis. Here we focus on the impact on the predicted classification posterior probability when a data point is omitted. The new method is intuitive and easily interpretable compared to existing methods. We also propose a graphical display to show the individual movement of the posterior probability of other data points when a specific data point is omitted. This enables the summaries to capture the overall pattern of the change.