• Journal of the Korean Society for Precision Engineering
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• v.8 no.3
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• pp.73-81
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• 1991

There have been many studies on chatter vibration in machining but there seems to be no regulations to decide the commencing point of chatter objectively. The development of an objective method which can estimate and detect chatter commencement is very much in need for automatic manufacturing systems, dynamic performance tests for machine tools, so on. In this study, therefore, the estimation and the in-process detection of chatter have been experi- mentally investigated for the turning process. As a result, the commencing point of chatter can be decided from the behavior of the maximum amplitude of the dynamic component of cutting force, where the maximum amplitude is suddenly increasing with the chatter commencement. Then the commencing point of chatter can be estimated practically by this method before the occurrence of excessive vibration. Also, it is possible to detect the occurence of chatter vibration through the in-process measurement, by monitoring the maximum amplitude of the dynamic component of cutting force.

• Sleep Medicine and Psychophysiology
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• v.6 no.1
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• pp.26-31
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• 1999

"Attention" is not defined sufficiently. This term incorporates several dimensions or complex information processes such as alertness, spatial distribution, focused attention, sustained attention, divided attention and supervisory attentional control. In practice, however, various aspects of attention cannot be assessed separately with a single test. Moreover, a particular test is never assessing attention only, because the several intervening variables may influence the attentional component. Therefore, one can only assess a certain aspect of human behavior with special interest for its attentional component. This paper attempted to clarify various concepts of attention, reviewed signal detection theories with receiver operating characteristic(ROC) curves, and listed practical methods for assessment of attention.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.4
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• pp.76-84
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• 1998

The requirements of the accuracy, the high speed and the stability are very important factors in the defect-detection sytem for the texture. In this paper, we describe a novel scheme of the defect detection using a statistical behavior of defect patterns. Some prior knowledge as to the characteristics of flaws is that the defects are consistently distributed in the space and the noise are randomly generated. An empirical knowledge is adapted for the binarization and the determination process of defects in textured image. Since the process of the determination exclude the segmentations or delineation steps, we are able to meet the speed requirements. We show the validity of the scheme through the simulation of textured images.

• Bulletin of the Korean Chemical Society
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• v.26 no.10
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• pp.1560-1564
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• 2005

The influence of cetyltrimethylammonium bromide (CTAB) on the electrochemical behavior of bisphenol A at the carbon paste electrode (CPE) was investigated. CTAB, with a hydrophobic C-H chain, can adsorb at the CPE surface via hydrophobic interaction and then change the electrode/solution interface, and finally affects the electrochemical response of bisphenol A, confirming from the remarkable oxidation peak current enhancement. The electrode process of bisphenol A was examined, and then all the experimental parameters which affects the electrochemical response of bisphenol A, such as pH value of the supporting electrolyte, accumulation potential and time, potential scan rate and the concentration of CTAB, were examined. Finally, a sensitive and simple voltammetric method was developed for the determination of bisphenol A. Under the optimum conditions, the oxidation peak current of bisphenol A varied linearly with its concentration over the range from $2.5\;{\times}\;10^{-8}\;to\;1\;{\times}\;10^{-6}$ mol/L, and the detection limit was found to be $7.5\;{\times}\;10^{-9}$ mol/L. This method was successfully employed to determine bisphenol A in some waste plastic samples.

• Korean Journal of Optics and Photonics
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• v.14 no.6
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• pp.573-577
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• 2003

We report an effect of photon pairs on single-photon detection rates, while Hong-Ou-Handel's two-photon interference experiment is performed with photons produced in noncollinear type-I parametric down-conversion. Photon pairing behavior or spatial bunching is measured and shown to cause a decrease in the single photon counting rate. Such a dip is found to result from the fact that the single-photon timing resolution of photodetectors is much longer compared to the time interval between the two photons incident on the single-photon detector.

• Nano
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• v.13 no.10
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• pp.1850122.1-1850122.6
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• 2018

Vertically aligned $WO_3$-CuO core-shell nanorod arrays for $NH_3$ sensing are prepared. The sensor is fabricated by preparing $WO_3$-CuO nanorod arrays directly on silicon wafer with interdigital Pt electrodes. The $WO_3$-CuO nanorod arrays are characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM) and X-ray diffraction (XRD). The sensor based on the vertically aligned $WO_3$-CuO nanorod arrays exhibits ultrasensitive $NH_3$ detection, indicating p-type behavior. The optimum sensing temperature is found to be about $150^{\circ}C$. Both response and recovery time to $NH_3$ ranging from 50 ppm to 500 ppm are around 10-15 s. A possible $NH_3$ sensing mechanism of the vertically aligned hybrid nanorod arrays is proposed.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1459-1466
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• 2018

Robots which detect human and recognize action are important factors for human interaction, and many researches have been conducted. Recently, deep learning technology has developed and learning based robot's technology is a major research area. These studies require a database to learn and evaluate for intelligent human perception. In this paper, we propose a multi-modal sensor-based image database condition considering the security task by analyzing the image database to detect the person in the outdoor environment and to recognize the behavior during the running of the robot.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.67-90
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• 2019

Accurate detection, tracking and analysis of human movement using robots and other visual surveillance systems is still a challenge. Efforts are on to make the system robust against constraints such as variation in shape, size, pose and occlusion. Traditional methods of detection used the sliding window approach which involved scanning of various sizes of windows across an image. This paper concentrates on employing a state-of-the-art, hierarchical graph based method for segmentation. It has two stages: part level segmentation for color-consistent segments and object level segmentation for category-consistent regions. The tracking phase is achieved by employing SIFT keypoint descriptor based technique in a combined matching and tracking scheme with validation phase. Localization of human region in each frame is performed by keypoints by casting votes for the center of the human detected region. As it is difficult to avoid incorrect keypoints, a consensus-based framework is used to detect voting behavior. The designed methodology is tested on the video sequences having 3 to 4 persons.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.294-303
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• 2021

VANET is an upcoming technology with an encouraging prospect as well as great challenges, specifically in its security. This paper intends to survey such probable attacks and the correlating detection mechanisms that are introduced in the literature. Accordingly, administering security and protecting the owner's privacy has become a primary argument in VANETs. To furnish stronger security and preserve privacy, one should recognize the various probable attacks on the network and the essence of their behavior. This paper presents a comprehensive survey on diversified attacks and the recommended unfolding by the various researchers which concentrate on security services and the corresponding countermeasures to make VANET communications more secure.

• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.345-354
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• 2021

Recently, deep learning-based image recognition systems have been adopted to various surveillance environments, but most of them are still picture-type object recognition methods, which are insufficient for the long term temporal analysis and high-dimensional situation management. Therefore, we propose a method recognizing the specific dangerous situation generated by human in real-time, and utilizing deep learning-based object analysis techniques. The proposed method uses deep learning-based object detection and tracking algorithms in order to recognize the situations such as 'trespassing', 'loitering', and so on. In addition, human's joint pose data are extracted and analyzed for the emergent awareness function such as 'falling down' to notify not only in the security but also in the emergency environmental utilizations.