• Proceedings of the IEEK Conference
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• summer
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• pp.442-446
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• 2004

This paper propose scene change detection algorithm using coefficient of forward prediction macro-block, backward prediction macro-block, and intra-coded macro-block on getting motion estimation. Proposed method detect scene change with correlation according picture type forward two picture or forward and backward two picture on video sequences. Proposed algorithm is high accuracy and can detect all scene change on video, and detect to occur scene change on P, B, I-picture.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2C
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• pp.172-180
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• 2003

This paper propose a new change detection algorithm based on macro block unit for selective video coding scheme. The conventional method badly decides a macro block of unchanged region into a changed macro block due to a noise of the difference images. To solve the problem of the conventional method, we propose a new test statistic which is robust to the noise of the difference image. As shown in experimental results(Fig. 1∼3), the proposed algorithm shows more accurate segmentation results than the conventional method. Also, because the proposed detection method reduces the average numbers of changed macro block per frame to 55∼60% than the conventional method, it can improve the performance of the selective video coding at lower bit rates.

• Korean Journal of Clinical Laboratory Science
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• v.53 no.2
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• pp.188-192
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• 2021

The persistent increase of aspartate aminotransferase (AST) due to the presence of a macro-AST can confuse diagnostic or therapeutic decisions in many clinical situations. In this study, we report a case of isolated and persistent AST-elevation without any clinical sign of dysfunction in organs such as the liver, skeletal muscle, cardiac muscle, etc. Despite various investigations, no definite cause for the elevation of AST could be found. With the help of polyethylene glycol (PEG) precipitation, we showed that macro-AST formation was responsible for the elevation of the AST titer in this case. Early recognition of macro-AST by PEG precipitation can prevent diagnostic confusion and unnecessary and even invasive tests.

• Korean Journal of Optics and Photonics
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• v.12 no.4
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• pp.289-293
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• 2001

A metal capillary splice fiber-optic sensor was fabricated for use as an intensity-based macro-bending sensor. As the radius of curvature due to the macro-bending decreases, the angular misalignment of the fiber ends inside the metal capillary increases, i.e., the coupling efficiency of the fiber splice is reduced. Thus, macro-bending can be detected by the measurement of the reduction of transmitted power. The detectable range of macro-bending. was measured approximately from 20 mm to 85 mm. The center wavelengths of the fiber Bragg gratings are 1543.3 nm and 1549.5 nm, respectively. The maximum bending loss of this sensor was measured about -11.92 dB. Using this metal capillary spliced fiber sensor and fiber Bragg gratings, macro-bending detection has been demonstrated, and it is shown to have potential for multi-point macro-bending sensors. nsors.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.500-503
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• 2005

Many researches on intelligent system have been performed and various intelligent algorithms have been developed, which are effective under an assumed specific environment and purpose. But in an real environment, the performance of these algorithms can be largely degraded. In this Paper, we Proposed an Evolvable and Reconfigurable(ERI) Architecture based on intelligent Macro Core(IMC) so that various and new algorithms can be easily added incrementally and construct the reconfigured intelligent system easily. We apply the proposed ERI Architecture to face detection and recognition system to show its usefulness.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.823-827
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• 2005

Many researches on intelligent system have been performed and various intelligent algorithms have been developed, which are effective under an assumed specific environment and purpose. But in an real environment, the Performance of these algorithms can be largely degraded. In this paper, we proposed an Evolvable and Reconfigurable(ERI) Architecture based on intelligent Macro Core(IMC) so that various and new algorithms can be easily added incrementally and construct the reconfigured intelligent system easily. We apply the proposed ERI Architecture to face detection and recognition system to show its usefulness.

• Smart Structures and Systems
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• v.19 no.4
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• pp.393-402
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• 2017

Many vibration-based global damage detection methods attempt to extract modal parameters from vibration signals as the main structural features to detect damage. The local flexibility method is one promising method that requires only the first few fundamental modes to detect not only the location but also the extent of damage. Generally, the mode shapes in the lateral degree of freedom are extracted from lateral vibration signals and then used to detect damage for a beam structure. In this study, a new approach which employs the mode shapes in the rotary degree of freedom obtained from the macro-strain vibration signals to detect damage of a beam structure is proposed. In order to facilitate the application of mode shapes in the rotary degree of freedom for beam structures, the local flexibility method is modified and utilized. The proposed rotary approach is verified by numerical and experimental studies of simply supported beams. The results illustrate potential feasibility of the proposed new idea. Compared to the method that uses lateral measurements, the proposed rotary approach seems more robust to noise in the numerical cases considered. The sensor configuration could also be more flexible and customized for a beam structure. Primarily, the proposed approach seems more sensitive to damage when the damage is close to the supports of simply supported beams.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1123-1129
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• 2015

Macro(automatic hunting) of mobile game is a program that touch the screen by defined rules like a game bot in PC online games, and it is used by make various ways like android application or windows application program. This gives honest users deprivation and make to lose their interest. Finally they would leave the game and gradually game life would be shorten. Although many studies to prevent these problems in PC online game are conducted, applying mobile game to PC's way is difficult because mobile games are limited to use the network and device performance is different with PC. In this paper, we propose a framework for macro detection by using the touch event information. A touch event on the mobile game is a necessary control command to the game. Because macro touches the screen with the same pattern, there is a difference between normal user's behavior and macro's operation. In mobile games that casual games are mostly, Touch event is the best difference that identify normal user against macro for a short period of time. As a result of detecting macros used in real mobile game by using the proposed framework it showed 100% accuracy and 0% false positive rate.

• Journal of KIISE
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• v.44 no.10
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• pp.1105-1111
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• 2017

Influence maximization (IM) is the problem of finding a seed set composed of k nodes that maximizes the influence spread in social networks. However, one of the biggest problems of existing solutions for IM is that it takes too much time to select a k-seed set. This performance issue occurs at the micro and macro levels. In this paper, we propose a fast hybrid method that addresses two issues at micro and macro levels. Furthermore, we propose a path-based community detection method that helps to select a good seed set. The results of our experiment with four real-world datasets show that the proposed method resolves the two issues at the micro and macro levels and selects a good k-seed set.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.141-148
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• 2011

Most of the previous works on scene change detection algorithm focus on the detection of abrupt rather than gradual changes. In general, gradual scene change detection algorithms require heavy computation. Some of those approaches don't consider the error factors such as flashlights, camera or object movements, and special effects. Many scenes change detection algorithms based on the histogram show better performances than other approaches, but they have computation load problem. In this paper, we proposed a scene change detection algorithm with fast and accurate performance using the vertical and horizontal blocked slice images and their macro block informations. We apply graph cut partitioning algorithm for clustering and partitioning of video sequence using generated spatio-temporal histogram. When making spatio-temporal histogram, we only use the central block on vertical and horizontal direction for performance improvement. To detect camera and object movement as well as various special effects accurately, we utilize the motion vector and type information of the macro block.