• International journal of advanced smart convergence
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• v.12 no.2
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• pp.47-55
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• 2023

The automotive industry is undergoing a paradigm shift due to the convergence of IT and rapid digital transformation. Various components, including embedded structures and systems with complex architectures that incorporate IC semiconductors, are being integrated and modularized. As a result, there has been a significant increase in vehicle defects, raising expectations for the quality of automotive parts. As more and more data is being accumulated, there is an active effort to go beyond traditional reliability analysis methods and apply machine learning models based on the accumulated big data. However, there are still not many cases where machine learning is used in product development to identify factors of defects in performance and durability of products and incorporate feedback into the design to improve product quality. In this paper, we applied a prediction algorithm to the defects of automotive door devices equipped with automatic responsive sensors, which are commonly installed in recent electric and hydrogen vehicles. To do so, we selected test items, built a measurement emulation system for data acquisition, and conducted comparative evaluations by applying different machine learning algorithms to the measured data. The results in terms of R² score were as follows: Ordinary multiple regression 0.96, Ridge regression 0.95, Lasso regression 0.89, Elastic regression 0.91.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.614-630
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• 2023

Dead trees significantly impact forest production and the ecological environment and pose constraints to the sustainable development of forests. A lightweight YOLOv4 dead tree detection algorithm based on unmanned aerial vehicle images is proposed to address current limitations in dead tree detection that rely mainly on inefficient, unsafe and easy-to-miss manual inspections. An improved logarithmic transformation method was developed in data pre-processing to display tree features in the shadows. For the model structure, the original CSPDarkNet-53 backbone feature extraction network was replaced by MobileNetV3. Some of the standard convolutional blocks in the original extraction network were replaced by depthwise separable convolution blocks. The new ReLU6 activation function replaced the original LeakyReLU activation function to make the network more robust for low-precision computations. The K-means++ clustering method was also integrated to generate anchor boxes that are more suitable for the dataset. The experimental results show that the improved algorithm achieved an accuracy of 97.33%, higher than other methods. The detection speed of the proposed approach is higher than that of YOLOv4, improving the efficiency and accuracy of the detection process.

• Korean Journal of Cognitive Science
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• v.21 no.4
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• pp.447-458
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• 2010

Time expressions are a very important form of information in different types of data. Thus, the recognition of a time expression is an important factor in the field of information extraction. However, most previously designed systems consider only a specific domain, because time expressions do not have a regular form and frequently include different ellipsis phenomena. We present a two-level recognition method consisting of extraction and transformation phases to achieve generality and portability. In the extraction phase, time expressions are extracted by atomic time units for extensibility. Then, in the transformation phase, omitted information is restored using basis time and prior knowledge. Finally, every complete atomic time unit is transformed into a normalized form. The proposed system can be used as a general-purpose system, because it has a language- and domain-independent architecture. In addition, this system performs robustly in noisy data like SMS data, which include various errors. For SMS data, the accuracies of time-expression extraction and time-expression normalization by using the proposed system are 93.8% and 93.2%, respectively. On the basis of these experimental results, we conclude that the proposed system shows high performance in noisy data.

• Journal of Biosystems Engineering
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• v.26 no.1
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• pp.21-28
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• 2001

Major deficiencies of current automation scheme including various robots for bioproduction include the lack of task adaptability and real time processing, low job performance for diverse tasks, and the lack of robustness of take results, high system cost, failure of the credit from the operator, and so on. This paper proposed a scheme that could solve the current limitation of task abilities of conventional computer controlled automatic system. The proposed scheme is the man-machine hybrid automation via tele-operation which can handle various bioproduction processes. And it was classified into two categories. One category was the efficient task sharing between operator and CCM(computer controlled machine). The other was the efficient interface between operator and CCM. To realize the proposed concept, task of the object identification and extraction of 3D coordinate of an object was selected. 3D coordinate information was obtained from camera calibration using camera as a measurement device. Two stereo images were obtained by moving a camera certain distance in horizontal direction normal to focal axis and by acquiring two images at different locations. Transformation matrix for camera calibration was obtained via least square error approach using specified 6 known pairs of data points in 2D image and 3D world space. 3D world coordinate was obtained from two sets of image pixel coordinates of both camera images with calibrated transformation matrix. As an interface system between operator and CCM, a touch pad screen mounted on the monitor and remotely captured imaging system were used. Object indication was done by the operator’s finger touch to the captured image using the touch pad screen. A certain size of local image processing area was specified after the touch was made. And image processing was performed with the specified local area to extract desired features of the object. An MS Windows based interface software was developed using Visual C++6.0. The software was developed with four modules such as remote image acquisiton module, task command module, local image processing module and 3D coordinate extraction module. Proposed scheme shoed the feasibility of real time processing, robust and precise object identification, and adaptability of various job and environments though selected sample tasks.

• Journal of Advanced Navigation Technology
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• v.27 no.3
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• pp.306-313
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• 2023

Realistic and graphics-based virtual reality content is based on 360-degree videos, and viewport extraction through the viewer's intention or automatic recommendation function is essential. This paper designs a viewport extraction system based on multiple object tracking in 360-degree videos and proposes a parallel computing structure necessary for multiple viewport extraction. The viewport extraction process in 360-degree videos is parallelized by composing pixel-wise threads, through 3D spherical surface coordinate transformation from ERP coordinates and 2D coordinate transformation of 3D spherical surface coordinates within the viewport. The proposed structure evaluated the computation time for up to 30 viewport extraction processes in aerial 360-degree video sequences and confirmed up to 5240 times acceleration compared to the CPU-based computation time proportional to the number of viewports. When using high-speed I/O or memory buffers that can reduce ERP frame I/O time, viewport extraction time can be further accelerated by 7.82 times. The proposed parallelized viewport extraction structure can be applied to simultaneous multi-access services for 360-degree videos or virtual reality contents and video summarization services for individual users.

• Sim-seong Yeon-gu
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• v.38 no.1
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• pp.161-200
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• 2023

The fairy tale 'The King's Ass's Ears' is a simple story about a king and a barber. The king's 'Ass's ears' is discovered by the barber, who becomes sick due to his inability to reveal the secret. He eventually confesses the secret in a deep pit and covers it with soil, but a reed grows in that spot and reveals the secret when it sways in the wind. This fairy tale is registered in Stith Thompson's narrative type AT 782 as 'King Midas and His Ass's Ears', corresponding to a well-known story of King Gyeongmun in Korea, as it is published in elementary textbooks. When something becomes conscious, its automatic mechanical tendency leads to obsolete and rigid. To avoid rigidity in our conscious life, we need continuous renewal via contact with the flow of mental events in our unconscious. From the aspect of analytical psychology, the King's 'Ass's ears' enables irrational contact with the fundamental emotions lost in the flow of life. The barber symbolizes spiritual transformation, and the reed swaying in the wind symbolizes the revelation of secretive knowledge associated with the divine. The king can hear the sound of all creation and become one with it, which was the will of the divine. The Self, as the psychic totality of an individual and paradoxically also represents the regulating center of the collective unconscious, continually seeks to merge and transform with the lost primal layer of humanity, which has now become distant and discarded due to the development of human consciousness.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.40 no.4
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• pp.319-327
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• 2004

The Electronic compass made as a pilot model in this research is comprised of a three axis magnetic sensor, an accustar clinometer, and a fiber optic gyro sensor. The results confirming the output character, performance, and the accuracy of the deviation corrects of each sensor are as follows: 1) As for the output character of the three axis magnetic sensor, the magnetic field showed a cosine curve on the X axis, a - sine curve on the Y axis, and constant figures on the Z sensor. The horizontal component H and the vertical component V of the terrestrial magnetism calculated from the output voltage were 33.2${\mu}$T and 23.95${\mu}$T respectively. 2) When the fiber optic gyro sensor is fixed on the electromotive rotation transformation and has made a clockwise rotation with the speed of 10/sec, 20/sec, and 30/sec, the relationship between the output and the rotation angle of the fiber optic gyro sensor showed proportionally constant values. 3) When the magnetic field was induced with a magnet, the deviation before the correction was significant at a high of 25. However, the deviation after the correction using Poisson correction was in the 2 range, significantly lower than before the correction. It was confirmed that automatic deviation corrects are possible with the electronic compass made as a pilot model in this research.

• Journal of the Korean Society of Marine Environment & Safety
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• v.14 no.2
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• pp.119-125
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• 2008

The aim of this study was to determine the characteristics of wave transformation in the shallow water of the Nakdong River estuary due to variations in air pressure, air temperature, wind speed, and wind direction. We analyzed the correlation between weather factors and wind waves in offshore regions near Geoje Island and the Nakdong River estuary in April and May 2007. The weather and wind wave data were obtained from the automatic ocean observation buoy near Geoje Island operated by the Korean Meteorological Administration (KMA). For the estuary region, the wind wave information was the result of field observations, and weather data were obtained from the Busan Meteorological Station. Field observations of water waves in April and May showed that the maximum wave height decreased by about 2.2 m. M oreover, wave height decreased significantly by about 1.3 m due to the reduction in wave energy caused by the water waves propagating from Geoje buoy to the Nakdong River estuary. We conclude that offshore or wind waves coming into the Nakdong River estuary showed considerable height variation due to the prevailing weather conditions, especially wind speed and direction. In particular, headwinds tended to decrease the wave size in inverse proportion to the wind speed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2597-2602
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• 2015

With the development of economy and improving of people's living standards, people dietary needs will be achieved from subsistence to high nutrition and from high nutrition to healthy transformation. Mushroom as a kind of highly nutritious, low fat, rich vitamin food has a great interest among the people. This makes the mushroom into a new sunrise industry and it gradually from pure manual cultivation develops toward the fully automatic factory. In the process of mushroom factory production, regulation of environmental factors directly affects the yield and quality of mushroom. In related to the methods of mushroom cultivation, the recent technologies apply the new technology such as sensors and IT convergence services. And then cultivating mushroom is managed effectively. This paper in order to solve the above problems and construct an effective mushroom growth environment using technology such as humidity sensor construct an environment that can automatically adjust the humidity. This environment has important significance to improve the level of automation mushroom production, increase yield per unit area and quality of mushroom, increase economic efficiency of mushroom production, and enhance the competitiveness of mushroom production.

• International Journal of Contents
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• v.10 no.4
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• pp.1-10
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• 2014

In this paper, we propose a method to build an accurate initial trimap for the GrabCut algorithm without the need for human interaction. First, we identify a rough candidate for the label region of a bottle by applying a saliency map to find a salient area from the image. Then, the Hough Transformation method is used to detect the left and right borders of the label region, and the k-means algorithm is used to localize the upper and lower borders of the label of the bottle. These four borders are used to build an initial trimap for the GrabCut method. Finally, GrabCut segments accurate regions for the label. The experimental results for 130 wine bottle images demonstrated that the saliency map extracted a rough label region with an accuracy of 97.69% while also removing the complex background. The Hough transform and projection method accurately drew the outline of the label from the saliency area, and then the outline was used to build an initial trimap for GrabCut. Finally, the GrabCut algorithm successfully segmented the bottle label with an average accuracy of 92.31%. Therefore, we believe that our method is suitable for product label recognition systems that automatically segment product labels. Although our method achieved encouraging results, it has some limitations in that unreliable results are produced under conditions with varying illumination and reflections. Therefore, we are in the process of developing preprocessing algorithms to improve the proposed method to take into account variations in illumination and reflections.