• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.859-865
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• 2018

A construction of infrastructures and base station on the moon could be undertaken by linking with the regions where construction materials and energy could be supplied on site. It is necessary to detect craters on the lunar surface and gather their topological information in advance, which forms permanent shaded regions (PSR) in which rich ice deposits might be available. In this study, an effective method for automatic detection of lunar craters on the moon surface is taken into consideration by employing a latest version of deep-learning algorithm. A training of a deep-learning algorithm is performed by involving the still images of 90000 taken from the LRO orbiter on operation by NASA and the label data involving position and size of partly craters shown in each image. the Faster RCNN algorithm, which is a latest version of deep-learning algorithms, is applied for a deep-learning training. The trained deep-learning code was used for automatic detection of craters which had not been trained. As results, it is shown that a lot of erroneous information for crater's positions and sizes labelled by NASA has been automatically revised and many other craters not labelled has been detected. Therefore, it could be possible to automatically produce regional maps of crater density and topological information on the moon which could be changed through time and should be highly valuable in engineering consideration for lunar construction.

• Korean Journal of Heritage: History & Science
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• v.46 no.1
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• pp.346-361
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• 2013

Since the Ming Castle located in Nanjing was designated by the Government of China as a cultural property in 1988, the Nanjing city government has been conserving the castle according to its plan and thus restoring the historical and cultural values of Nanjing. The project is still in progress, and in this regard, a series of logistics have formulated and a lot of discussions have taken place. Likewise, Korea has been carrying out multidirectional policies to conserve and utilize castles lying throughout the country, appreciating the historical and cultural resources of castles lying throughout the country, and at the same time gets down to designation as the World Heritage. This study focused on how Nanjing, not only a castle city but also a historical city, had established a principle and legal foundation regarding the protection of the Ming Castle, especially on how the problems, which might continually arise in a process where a scheme reached a working stage, had been solved. The problem-solving process is expected to have great implications for Korea in a similar situation. Hereat, this study analyzed the project plans formulated seasonally and gathered data on practical operation by conducting interviews with hands-on workers. The results showed that Nanjing had carried out policies to utilize the castles as tourism resources by harmonizing cityscape and ecological environment, but that it well conserved castles without damaging cultural assets. The stereoscopic protection system for the Ming Castle, based on the consideration of historical and cultural environments, may provide practical and useful data for Korea's administration mapping out for a castle conservation policy and designation as the UNESCO World Heritage.

• The Journal of the Convergence on Culture Technology
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• v.5 no.3
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• pp.197-202
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• 2019

In the era of the fourth revolution, interest in content production using proven engines in the broadcasting sector, such as Vizrt, is growing. The new visual effects required in the 5G era are critical to content production training. Vizrt has a good production time utility and affordability for broadcast and media content. In this paper, we are going to use this to present a practical case of the theorem and application of the basic training course in the production of virtual content, and to present the basic training direction. In the introduction, the graphic algorithm analyzed and studied the characteristics and environmental factors of the Vizrt engine. In this paper, the production process was studied separately, and the work carried out through engine implementation was presented. The VS Studio Foundation was provided as a practical production case at each stage. The Vizrt engine operator process is important in graphic approach and application, and through the results of the lecture, the method of understanding and implementing algorithms for virtual reality perspective suitable for basic learning was studied. Based on practice, the research method of main theory was to create Vizrt contents specialized in 5G contents work in each sector and to implement graphic production in new areas from contents image. Through this study, we came to the conclusion of the basic training method through virtual reality content work based on Vizrt by practicing content creation according to the subject. It also proposes the effect of creating Vizrt content and the direction of building Vizrt basic training courses.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.29 no.4
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• pp.179-186
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• 2019

In this study, we investigated the structural properties of $Ga_2O_3$ thin films and the photo-electrical properties of metal-semiconductor-metal (MSM) photodetectors deposited by Ti/Au electrodes. $Ga_2O_3$ thin films were grown at different temperatures using metal organic chemical vapor deposition (MOCVD). The crystal phase of $Ga_2O_3$ changed from ${\varepsilon}$-phase to ${\beta}$-phase depending on the growth temperature. The crystal structure of ${\varepsilon}-Ga_2O_3$ was confirmed by X-ray diffraction (XRD) analysis and the formation mechanism of crystal structure was discussed by scanning electron microscopy (SEM) images. From the results of current-voltage (I-V) and time-dependent photoresponse characteristics under the illumination of external lights, we confirmed that the MSM photodetector fabricated by ${\varepsilon}-Ga_2O_3$ showed much better photocurrent characteristics in the 266 nm UV range than in the visible range.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.161-170
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• 2019

Multi-product mass production small and medium enterprise factories have a wide variety of products and a large number of products, wasting manpower and expenses for inventory management. In addition, there is no way to check the status of inventory in real time, and it is suffering economic damage due to excess inventory and shortage of stock. There are many ways to build a real-time data collection environment, but most of them are difficult to afford for small and medium-sized companies. Therefore, smart factories of small and medium enterprises are faced with difficult reality and it is hard to find appropriate countermeasures. In this paper, we implemented the contents of extension of existing inventory management method through character extraction on label with barcode and QR code, which are widely adopted as current product management technology, and evaluated the effect. Technically, through preprocessing using OpenCV for automatic recognition and classification of stock labels and barcodes, which is a method for managing input and output of existing products through computer image processing, and OCR (Optical Character Recognition) function of Google vision API. And it is designed to recognize the barcode through Zbar. We propose a method to manage inventory by real-time image recognition through Raspberry Pi without using expensive equipment.

• Journal of the Korean Academy of Esthetic Dentistry
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• v.27 no.2
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• pp.82-96
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• 2018

3D printing is a process of producing 3d object from a digital file in STL format by joining, bonding, sintering or polymerizing small volume elements by layer. The various type of 3d printing is classified according to the additive manufacturing strategies. Among the types of 3D printer, SLA(StereoLithography Apparatus) and DLP(Digital Light Processing) 3D printer which use polymerization by light source are widely used in dental office. In the previous study, a full-arch scale 3d printed model is less precise than a conventional stone model. However, in scale of quadrant arch, a 3d printed model is significantly precise than a five-axis milled model. Using $3^{rd}$ Party dental CAD program, full denture, provisional crowns and diagnostic wax-up model are fabricated by 3d printer in dental office. In Orthodontics, based on virtual setup model, indirect bracket bonding tray can be generated by 3d printer. And thermoforming clear aligner can be fabricated on the 3d printed model. 3D printed individual drilling guide enable the clinician to place the dental implant on the proper position. The development of layer additive technology enhance the quality of 3d printing object and shorten the operating time of 3D printing. In the near future, traditional dental laboratory process such as casting, denture curing will be replaced by digital 3D printing.

• Journal of IKEEE
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• v.25 no.2
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• pp.243-251
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• 2021

In this paper, we propose a measurement technique of indoor location based on markerless applicable to AR. The proposed technique has the following originality. The first is to extract feature points and use them to generate local patches to enable faster computation by learning and using only local patches that are more useful than the surroundings without learning the entire image. Second, learning is performed through deep learning using the convolution neural network structure to improve accuracy by reducing the error rate. Third, unlike the existing feature point matching technique, it enables indoor location measurement including left and right movement. Fourth, since the indoor location is newly measured every frame, errors occurring in the front side during movement are prevented from accumulating. Therefore, it has the advantage that the error between the final arrival point and the predicted indoor location does not increase even if the moving distance increases. As a result of the experiment conducted to evaluate the time required and accuracy of the measurement technique of indoor location based on markerless applicable to AR proposed in this paper, the difference between the actual indoor location and the measured indoor location is an average of 12.8cm and a maximum of 21.2cm. As measured, the indoor location measurement accuracy was better than that of the existing IEEE paper. In addition, it was determined that it was possible to measure the user's indoor location in real time by displaying the measured result at 20 frames per second.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1339-1348
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• 2020

Phytoplankton controls marine ecosystems in terms of nutrients, photosynthetic rate, carbon cycle, etc. and the degree of its influence on the marine environment depends on their physical size. Many studies have been attempted to identify marine phytoplankton size classes using the remote sensing techniques. One of successful approach was the three-component model which estimates the chlorophyll concentrations of three phytoplankton size classes (micro-phytoplankton; >20 ㎛, nano-; 2-20 ㎛ and pico-; <2 ㎛) as a function of total chlorophyll. Here, we examined the applicability of Geostationary Ocean Colour Imager (GOCI) to the mapping of the phytoplankton size class distribution in the East Sea. A fit of the three-component model to a biomarker pigment dataset collected in the study area for some years including a large harmful algal bloom period has been carried out to derive size-fractioned chlorophyll concentration (CHL). The tuned three-component model was applied to the hourly GOCI images to identify the fractions of each phytoplankton size class for the entire CHL. Then, we investigated the distribution of phytoplankton community in terms of the size structure in the East Sea during the harmful Cochlodinium polykrikoides blooms in the summer of 2013.

• Journal of the Korea Society of Computer and Information
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• v.26 no.8
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• pp.23-30
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• 2021

In this study, we present a comparative analysis of major autoencoder(AE)-based anomaly detection methods for quality determination in the manufacturing process and a new anomaly discrimination criterion. Due to the characteristics of manufacturing site, anomalous instances are few and their types greatly vary. These properties degrade the performance of an AI-based anomaly detection model using the dataset for both normal and anomalous cases, and incur a lot of time and costs in obtaining additional data for performance improvement. To solve this problem, the studies on AE-based models such as AE and VAE are underway, which perform anomaly detection using only normal data. In this work, based on Convolutional AE, VAE, and Dilated VAE models, statistics on residual images, MSE, and information entropy were selected as outlier discriminant criteria to compare and analyze the performance of each model. In particular, the range value applied to the Convolutional AE model showed the best performance with AUC PRC 0.9570, F1 Score 0.8812 and AUC ROC 0.9548, accuracy 87.60%. This shows a performance improvement of an accuracy about 20%P(Percentage Point) compared to MSE, which was frequently used as a standard for determining outliers, and confirmed that model performance can be improved according to the criteria for determining outliers.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.577-582
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• 2021

Recently, with the development of AR, VR, and smart device technologies, the demand for services based on non-face-to-face environments is also increasing in the fitness industry. The non-face-to-face online home training service has the advantage of not being limited by time and place compared to the existing offline service. However, there are disadvantages including the absence of exercise equipment, difficulty in measuring the amount of exercise and chekcing whether the user maintains an accurate exercise posture or not. In this study, we develop a standard exercise program that can compensate for these shortcomings and propose a new non-face-to-face home training application by using a deep learning-based body posture estimation image processing algorithm. This application allows the user to directly watch and follow the trainer of the standard exercise program video, correct the user's own posture, and perform an accurate exercise. Furthermore, if the results of this study are customized according to their purpose, it will be possible to apply them to performances, films, club activities, and conferences