• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.7
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• pp.1618-1631
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• 1994

In this paper, in-process chatter detection methodology which utilizes nondimensional characteristic variables is introduced. To obtain nondimensional chatter detection indexes which are constant regardless of the cutting conditions during machining with the same tool and workpiece material, both the cutting forces and accelerations are measured and processed in time and frequency domain. The indexes are calculated from the present and past value of the acceleration and cutting force signals in time and frequency domain. The chatter is identified when these chatter detection indexes are bigger than the threshold which is decided by preliminary experiments. The experiment shows that these indexes works very well in-process chatter detection.

• Journal of Welding and Joining
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• v.17 no.2
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• pp.53-60
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• 1999

Conventionally, CCD camera and vision sensor using the projected pattern of light is generally used to inspect the weld bead defects. But with this method, a lot of time is needed for image preprocessing, stripe extraction and thinning, etc. In this study, laser vision sensor using the scanning beam of light is used to shorten the time required for image preprocessing. The software for deciding whether the weld bead is in proper shape or not in real time is developed. The criteria are based upon the classification of imperfections in metallic fusion welds(ISO 6520) and limits for imperfections(ISO 5817).

• Journal of the Korean Vacuum Society
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• v.17 no.1
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• pp.58-66
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• 2008

The KSTAR Current Lead System(CLS) with network based real-time distributed control system is implemented using an EPICS as a middle-ware software. The current lead system transfers current from magnet power supplies to superconducting magnet system and simultaneously supply the coolant to maintain superconducting state. To control the CLS at main control room an EPICS IOC server is installed in local control area. Using this server, it is able to be controlled and monitored the system in main control room through operator interface(OPI) which uses "caget" to read status and "caput" to write command with a unique name called PV. The EPICS IOC is developed using "ether-ip" driver to communicate with PLC. Also we achieved satisfactory results in operation and stability aspects from a long period commissioning test.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4439-4455
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• 2021

Compared with two-stage object detection algorithms, one-stage algorithms provide a better trade-off between real-time performance and accuracy. However, these methods treat the intermediate features equally, which lacks the flexibility to emphasize meaningful information for classification and location. Besides, they ignore the interaction of contextual information from different scales, which is important for medium and small objects detection. To tackle these problems, we propose an image pyramid network based on dual attention mechanism (DAIPNet), which builds an image pyramid to enrich the spatial information while emphasizing multi-scale informative features based on dual attention mechanisms for one-stage object detection. Our framework utilizes a pre-trained backbone as standard detection network, where the designed image pyramid network (IPN) is used as auxiliary network to provide complementary information. Here, the dual attention mechanism is composed of the adaptive feature fusion module (AFFM) and the progressive attention fusion module (PAFM). AFFM is designed to automatically pay attention to the feature maps with different importance from the backbone and auxiliary network, while PAFM is utilized to adaptively learn the channel attentive information in the context transfer process. Furthermore, in the IPN, we build an image pyramid to extract scale-wise features from downsampled images of different scales, where the features are further fused at different states to enrich scale-wise information and learn more comprehensive feature representations. Experimental results are shown on MS COCO dataset. Our proposed detector with a 300 × 300 input achieves superior performance of 32.6% mAP on the MS COCO test-dev compared with state-of-the-art methods.

• Journal of KIISE
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• v.42 no.1
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• pp.54-67
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• 2015

Nowadays, studies on the fusion of Semantic Web technologies are being carried out to promote the interoperability and value of sensor data in an IoT environment. To accomplish this, the semantic translation of sensor data is essential for convergence with service domain knowledge. The existing semantic translation technique, however, involves translating from static metadata into semantic data(RDF), and cannot properly process real-time and large-scale features in an IoT environment. Therefore, in this paper, we propose a technique for translating large-scale streaming sensor data generated in an IoT environment into semantic data, using real-time and parallel processing. In this technique, we define rules for semantic translation and store them in the semantic repository. The sensor data is translated in real-time with parallel processing using these pre-defined rules and an ontology-based semantic model. To improve the performance, we use the Apache Storm, a real-time big data analysis framework for parallel processing. The proposed technique was subjected to performance testing with the AWS observation data of the Meteorological Administration, which are large-scale streaming sensor data for demonstration purposes.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.1-7
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• 2011

The depth camera measures range information of the scene in real time using Time-of-Flight (TOF) technology. Measured depth data is then regularized and provided as a depth image. This depth image is utilized with the stereo or multi-view image to generate high-resolution depth map of the scene. However, it is required to correct noise and distortion of TOF depth image due to the technical limitation of the TOF depth camera. The corrected depth image is combined with the color image in various methods, and then we obtain the high-resolution depth of the scene. In this paper, we introduce the principal and various techniques of sensor fusion for high-quality depth generation that uses multiple camera with depth cameras.

• Journal of the Korea Convergence Society
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• v.7 no.1
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• pp.9-15
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• 2016

In this paper, we describe the design of a high speed data acquisition system(DAS) with STM32 processor based on Cortex-M4. The system is used for the sensor devices to collect raw data on production lines at factory and send them to the servo computer in real time. The system is designed for multi functions with universal asynchronous receiver and transmitter(UART), analog to digital converter(ADC), digital to analog converter(DAC), and general purpose input output(GPIO). those are well tested for various data acquisition and high speed motor control in real time.

• International Journal of Advanced Culture Technology
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• v.4 no.4
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• pp.81-86
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• 2016

In this paper, we propose a simple and effective vision-based tracking controller design for autonomous object tracking using multicopter. The multicopter based automatic tracking system usually unstable when the object moved so the tracking process can't define the object position location exactly that means when the object moves, the system can't track object suddenly along to the direction of objects movement. The system will always looking for the object from the first point or its home position. In this paper, PID control used to improve the stability of tracking system, so that the result object tracking became more stable than before, it can be seen from error of tracking. A computer vision and control strategy is applied to detect a diverse set of moving objects on Raspberry Pi based platform and Software defined PID controller design to control Yaw, Throttle, Pitch of the multicopter in real time. Finally based series of experiment results and concluded that the PID control make the tracking system become more stable in real time.

• Journal of the Korean Society of Costume
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• v.60 no.3
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• pp.110-122
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• 2010

The purpose of this study is to analyze the expressional traits and internal meanings of fake design in the 2000s' fashion, based on study of art and design area. For achieving the purpose, this study performed related research works and a demonstrative analysis of fashion collection photographs. The scope of this study is from 2000 to 2009. The results are as follows. Fake design uses trompe-l'oeil which is an art technique related to the meanings of 'deceive or fool the eye'. This eye-deceiving technique has been used for a long time in the art, and particularly noticed as one of techniques of Surrealism. Art works using trompe-l'oeil express familiar and unreasonable world at the same time, and also the fusion of reality and fabrication. Fake design in design area of the 2000s makes people take daily life in unfamiliar way by unusualness and breaking the boundary between real and fake. By fake design, people can enjoy fun and a sense of freedom with amusement rather than unpleasant of being deceived. Fake design in the fashion of the 2000s uses eye-deceiving technique and also focuses on the concept of 'fake'. The expressional traits were categorized as realistic expression, surrealistic expression and fake value expression. The internal meanings were analyzed as breaking boundary between real and fake, rediscover dailiness, new attitude to traditional thinking. In conclusion, fake design in the fashion of the 2000s gives playfulness, fun, feeling of release and will be pursued continually.

• Journal of Broadcast Engineering
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• v.21 no.5
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• pp.782-791
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• 2016

The object segmentation algorithm from the background could be used for object recognition and tracking, and many applications. To segment objects, this paper proposes a method that refer to several initial frames with real-time processing at fixed camera. First we suggest the probability model to segment object and background and we enhance the performance of algorithm analyzing the color consistency and focus characteristic of camera for several initial frames. We compensate the segmentation result by using human skeleton characteristic among extracted objects. Last the proposed method has the applicability for various mobile application as we minimize computing complexity for real-time video processing.