• Journal of the Geological Society of Korea
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• v.54 no.5
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• pp.513-527
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• 2018

We have carried out granulometry and component analysis on pyroclastic deposits of the Maljandeung Tuff, Ulleung Island, to interpret the eruption types and prime dynamic mechanisms. It is divided into three members in the extracaldera area, each of which comprises the lithofacies of coarse tuffs and lapillistones in the lower part, and pumice deposits in upper one. The lithofacies present quantitative evidences in the granularity and component distribution patterns. As compared to the pumice deposits, the coarse tuffs and lapillistones exhibit a relative increase in both the lithic/juvenile and the crystal/juvenile ratios, and a preferential fragmentation of the juvenile fraction. The abundance of lithics and crystals in the tuffs and lapillistones can be attributed to preferential fragmentation of the aquifer-hosting rocks due to explosive evaporation of ground water, and indirect enrichment in lithics and crystals due to removal of juvenile fines from eruptive cloud. The above data exhibit that early phreatopmagmatic phase was followed by purely magmatic fragmentation phases. The coarse tuffs and lapillistones suggest phreatoplinian eruption derived from explosive interaction of magma with ground water near the conduit, while pumice deposits indicate magmatic eruption by magmatic explosion from juvenile gas pressure. In early stage, phreatoplinian eruption occurred from explosive magma/water interaction in connecting confining water with drawdown of the magma column in the conduit; Later it shifted to plinian eruption by explosive expansion of only magmatic volatiles in intercepting water influx due to higher magmatic gas pressure than confining water pressure with rising of the magma column in the conduit.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.10
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• pp.285-290
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• 2021

In the medical field, disease diagnosis and prediction research using artificial intelligence technology is being actively conducted. It is being released as a variety of products for disease diagnosis and prediction, which are most widely used in the application of artificial intelligence technology based on medical images. Artificial intelligence is being applied to diagnose diseases, to classify diseases into benign and malignant, and to separate disease regions for use in identification or reading according to the risk of disease. Recently, in connection with cloud technology, its utility as a service product is increasing. Among the diseases dealt with in this paper, liver disease is a disease with very high risk because it is difficult to diagnose early due to the lack of pain. Artificial intelligence technology was introduced based on medical images as a non-invasive diagnostic method for diagnosing these diseases. We describe the development of a web service to help the most meaningful clinical reading of liver cirrhosis patients. Then, it shows the web service process and shows the operation screen of each process and the final result screen. It is expected that the proposed service will be able to diagnose liver cirrhosis at an early stage and help patients recover through rapid treatment.

• Journal of Bio-Environment Control
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• v.28 no.4
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• pp.358-365
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• 2019

This study was conducted to estimate the dimensions of horticultural products and the mean plant height of plug seedlings using three-dimensional (3D) images. Two types of camera, a ToF camera and a stereo-vision camera, were used to acquire 3D images for horticultural products and plug seedlings. The errors calculated from the ToF images for dimensions of horticultural products and mean height of plug seedlings were lower than those predicted from stereo-vision images. A new indicator was defined for determining the mean plant height of plug seedlings. Except for watermelon with tap, the errors of circumference and height of horticultural products were 0.0-3.0% and 0.0-4.7%, respectively. Also, the error of mean plant height for plug seedlings was 0.0-5.5%. The results revealed that 3D images can be utilized to estimate accurately the dimensions of horticultural products and the plant height of plug seedlings. Moreover, our method is potentially applicable for segmenting objects and for removing outliers from the point cloud data based on the 3D images of horticultural crops.

• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.155-168
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• 2020

Open source is a key growth engine of the 4th industrial revolution, and the continuous development and use of various algorithms for image processing is expected. The purpose of this study is to examine the effectiveness of the UAS image processing open source based algorithm by comparing and analyzing the water reproduction and moving object filtering function and the time required for data processing in 3D reproduction. Five matching algorithms were compared based on recall and processing speed through the 'ANN-Benchmarks' program, and HNSW (Hierarchical Navigable Small World) matching algorithm was judged to be the best. Based on this, 108 algorithms for image processing were constructed by combining each methods of triangulation, point cloud data densification, and surface generation. In addition, the 3D reproduction and data processing time of 108 algorithms for image processing were studied for UAS (Unmanned Aerial System) images of a park adjacent to the sea, and compared and analyzed with the commercial image processing software 'Pix4D Mapper'. As a result of the study, the algorithms that are good in terms of reproducing water and filtering functions of moving objects during 3D reproduction were specified, respectively, and the algorithm with the lowest required time was selected, and the effectiveness of the algorithm was verified by comparing it with the result of 'Pix4D Mapper'.

• The Journal of Industrial Distribution & Business
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• v.12 no.1
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• pp.47-62
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• 2021

Purpose: Our purpose in this study was to examine the strategies for the development of watermelon industry using unstructured big data analysis. That is, this study was to look the change of issues and consumer's perception about watermelon using big data and social network analysis and to investigate ways to strengthen the competitiveness of watermelon industry based on that. Methodology: For this purpose, the data was collected from Naver (blog, news) and Daum (blog, news) by TEXTOM 4.5 and the analysis period was set from 2015 to 2016 and from 2017-2018 and from 2019-2020 in order to understand change of issues and consumer's perception about watermelon or watermelon industry. For the data analysis, TEXTOM 4.5 was used to conduct key word frequency analysis, word cloud analysis and extraction of metrics data. UCINET 6.0 and NetDraw function of UCINET 6.0 were utilized to find the connection structure of words and to visualize the network relations, and to make a cluster of words. Results: The keywords related to the watermelon extracted such as 'the stalk end of a watermelon', 'E-mart', 'Haman', 'Gochang', and 'Lotte Mart' (news: 015-2016), 'apple watermelon', 'Haman', 'E-mart', 'Gochang', and' Mudeungsan watermelon' (news: 2017-2018), 'E-mart', 'apple watermelon', 'household', 'chobok', and 'donation' (news: 2019-2020), 'watermelon salad', 'taste', 'the heat', 'baby', and 'effect' (blog: 2015-2016), 'taste', 'watermelon juice', 'method', 'watermelon salad', and 'baby' (blog: 2017-2018), 'taste', 'effect', 'watermelon juice', 'method', and 'apple watermelon' (blog: 2019-2020) and the results from frequency and TF-IDF analysis presented. And in CONCOR analysis, appeared as four types, respectively. Conclusions: Based on the results, the authors discussed the strategies and policies for boosting the watermelon industry and limitations of this study and future research directions. The results of this study will help prioritize strategies and policies for boosting the consumption of the watermelon and contribute to improving the competitiveness of watermelon industry in Korea. Also, it is expected that this study will be used as a very important basis for agricultural big data studies to be conducted in the future and this study will offer watermelon producers and policy-makers practical points helpful in crafting tailor-made marketing strategies.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.362-373
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• 2021

This study sought to explore the enhancement of the introduction of teaching and learning methods for Problem Based Learning (PBL) and the evaluation factors to evaluate them effectively through an understanding lecture in Cultural Content Planning. It was intended to incorporate a practical zero-volume education methodology of problem-oriented learning and sufficient leading learning to reflect storytelling in the entire process of completing a cultural content with culture, cultural content, and content planning. To this end, the role of teaching methods should be faithful to ensure that teamwork and cooperation can be done organically according to the educational field, practice and situation. Students who take classes were asked to meet demand, reflect it through surveys, apply real-world problems, and acquire the entire course. Learners had to cooperate with each other until planning cultural content and completing the results through classes, and they evaluated themselves and colleagues in teamwork until the last result was completed from creative ideas. The results were shared together and the students were able to investigate the necessary PBL evaluation factors for themselves, and the prior research and survey on the method of PBL evaluation was conducted to derive the factors of understanding of cultural content planning. The derived assessment elements were able to identify priorities between the assessment elements using basic statistics, word cloud analysis, and AHP analysis. The components of the assessment derived were communication skills, basic knowledge, reasoning process, expertise, and evaluation techniques. Through this article, I was able to lead the understanding of cultural content planning to problem-oriented learning classes and encourage students to be familiar and smooth.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.432-438
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• 2021

This dissertation's object is to confirm the drastic popularity of La Peste of Albert Camus in Korea post-corona society using big data as the mean of inductive research. Analyzing news articles concerning Camus and investigating word frequency of the book La Peste will affirm the implications La Peste has on current Korea society as the outbreak spreads. As an analysis tool, Bigkinds of Korea Press Foundation and Nuagedemots, the French version of Word Cloud were used. For the past 30 years, Albert Camus has been known in Korea as the writer of L'étranger, but after the epidemic, he earned more reputation with La Peste. Compared to L'étranger that rebelled against the world's absurdity with ennui, La peste emphasizes the importance of resistance accompanied by solidarity. La peste conveys hope by depicting disastrous situations of citizens who confront the plague by organizing a health college. The novel delivers a lot of ethical inspiration to humanity in this exceptional circumstance of COVID-19.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.7-18
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• 2021

Recently, various connected industrial parks (CIPs) architectures using new technologies such as cloud computing, CPS, big data, fifth-generation mobile communication 5G, IIoT, VR-AR, and ventilation transportation AI algorithms have been proposed in Korea. Korea's small and medium-sized enterprises do not have the upper hand in technological competitiveness than overseas advanced countries such as the United States, Europe and Japan. For this reason, Korea's small and medium-sized enterprises have to invest a lot of money in technology research and development. As a latecomer, Korean SMEs need to improve their profitability in order to find sustainable growth potential. Financially, it is most efficient for small and medium-sized Korean companies to cut costs to increase their profitability. This paper made profitability improvement by reducing costs for small and medium-sized enterprises located in CIPs in Korea a major task. VJP (Vehicle Action Program) was noted as a way to reduce costs for small and medium-sized enterprises located in CIPs in Korea. The method of achieving minimum logistics costs for small businesses through the Korean CIPs payment system was analyzed. The details of the new Korean CIPs payment system were largely divided into four types: "Business", "Data", "Technique", and "Finance". Cost Benefit Analysis (CBA) was used as a performance analysis method for CIPs payment systems.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.63-71
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• 2020

In this paper, we propose a fire detection technology using YOLOv3 and EfficientDet, the most reliable artificial intelligence detection algorithm recently, an alert service that simultaneously transmits four kinds of notifications: text, web, app and e-mail, and an AWS system that links fire detection and notification service. There are two types of our highly accurate fire detection algorithms; the fire detection model based on YOLOv3, which operates locally, used more than 2000 fire data and learned through data augmentation, and the EfficientDet, which operates in the cloud, has conducted transfer learning on the pretrained model. Four types of notification services were established using AWS service and FCM service; in the case of the web, app, and mail, notifications were received immediately after notification transmission, and in the case of the text messaging system through the base station, the delay time was fast enough within one second. We proved the accuracy of our fire detection technology through fire detection experiments using the fire video, and we also measured the time of fire detection and notification service to check detecting time and notification time. Our AI fire detection and notification service system in this paper is expected to be more accurate and faster than past fire detection systems, which will greatly help secure golden time in the event of fire accidents.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.174-192
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• 2021

The LIDAR sensor, which provides higher cognitive performance than cameras and radar, is difficult to apply to ADAS or autonomous driving because of its high price. On the other hand, as the price is decreasing rapidly, expectations are rising to improve existing autonomous driving functions by taking advantage of the LIDAR sensor. In level 3 autonomous vehicles, when a dangerous situation in the cognitive module occurs due to a sensor defect or sensor limit, the driver must take control of the vehicle for manual driving. If the driver does not respond to the request, the system must automatically kick in and implement a minimum risk maneuver to maintain the risk within a tolerable level. In this study, based on this background, a LIDAR-based LKS MRM algorithm was developed for the case when the normal operation of LKS was not possible due to troubles in the cognitive system. From point cloud data collected by LIDAR, the algorithm generates the trajectory of the vehicle in front through object clustering and converts it to the target waypoints of its own. Hence, if the camera-based LKS is not operating normally, LIDAR-based path tracking control is performed as MRM. The HAZOP method was used to identify the risk sources in the LKS cognitive systems. B, and based on this, test scenarios were derived and used in the validation process by simulation. The simulation results indicated that the LIDAR-based LKS MRM algorithm of this study prevents lane departure in dangerous situations caused by various problems or difficulties in the LKS cognitive systems and could prevent possible traffic accidents.