• Journal of Digital Convergence
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• v.20 no.4
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• pp.147-157
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• 2022

This study tried to propose a smart farm technology strategy suitable for the domestic situation, focusing on the differentiation suitable for the domestic situation of ICT technology. In the case of advanced countries in the overseas agricultural industry, it was confirmed that they focused on the development of a specific stage that reflected the geographical characteristics of each country, the characteristics of the agricultural industry, and the characteristics of the people's demand. Confirmed that no enemy development is being performed. Therefore, in response to problems such as a rapid decrease in the domestic rural population, aging population, loss of agricultural price competitiveness, increase in fallow land, and decrease in use rate of arable land, this study aims to develop smart farm ICT technology in the future to create quality agricultural products and have price competitiveness. It was suggested that the smart farm should be promoted by paying attention to the excellent performance, ease of use due to the aging of the labor force, and economic feasibility suitable for a small business scale. First, in terms of economic feasibility, the ICT technology is configured by selecting only the functions necessary for the small farm household (primary) business environment, and the smooth communication system with these is applied to the ICT technology to gradually update the functions required by the actual farmhouse. suggested that it may contribute to the reduction. Second, in terms of performance, it is suggested that the operation accuracy can be increased if attention is paid to improving the communication function of ICT, such as adjusting the difficulty of big data suitable for the aging population in Korea, using a language suitable for them, and setting an algorithm that reflects their prediction tendencies. Third, the level of ease of use. Smart farms based on ICT technology for the development of the Industry6.0 (1.0(Agriculture, Forestry) + 2.0(Agricultural and Water & Water Processing) + 3.0 (Service, Rural Experience, SCM)) perform operations according to specific commands, finally suggested that ease of use can be promoted by presetting and standardizing devices based on big data configuration customized for each regional environment.

• The Journal of Korean Academy of Prosthodontics
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• v.48 no.2
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• pp.158-165
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• 2010

Purpose: The objective of the present study was to histologically evaluate durability and bone regeneration capacity of new synthetic membranes in comparison to clinically available collagen membrane. Material and methods: To the skulls of 12 rabbits, we created 4 bone defects of 6 mm in diameter on each of them. Each of defects were covered with at least one of 5 membranes; No membrane, Collagen ($Ossix^{TM}$), PLGA, HA-coated-PLGA and HA-PLGA/PLGA. After 4, 8, 12 weeks, we cut the skulls and dyed with H-E. And then, the histologic observation was done. Results: In current study, the control group which did not use the membrane showed bone regeneration at 12 weeks and covered the bone defect partially. New bones were formed through the underneath of endocranium, and the upper defect was filled with connective tissues and fats. Collagen membrane ($Ossix^{TM}$) showed new bones after 4 weeks, and they were formed through the membrane which maintained until 12 weeks. PLGA, HA-coated-PLGA, HA-PLGA/PLGA showed bone regeneration after 4 weeks and after 8 weeks, they mostly filled defects. At 12 weeks, we could find new bones and previous bones almost look alike and also, they united well. Membranes were unnoticeable after 4 weeks and were absorbed. Conclusion: Bone formation and maturation of PLGA, HA-coated-PLGA and HA-PLGA/PLGA were faster than the control group. They showed no difference on the application of HA and after 4 weeks, they were absorbed.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.73-82
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• 2021

Rural roads are the significant infrastructure for developing and managing the rural areas, hence the utilization of the remote sensing datasets for managing the rural roads is necessary for expanding the rural transportation infrastructure and improving the life quality of the rural residents. In this research, the two different methods such as image classification and image segmentation were compared for mapping the rural road based on the given high-resolution satellite image acquired in the rural areas. In the image classification method, the deep learning with the multiple neural networks was employed to the given high-resolution satellite image for generating the object classification map, then the rural roads were mapped by extracting the road objects from the generated object classification map. In the image segmentation method, the multiresolution segmentation was employed to the same satellite image for generating the segment image, then the rural roads were mapped by merging the road objects located on the rural roads on the satellite image. We used the 100 checkpoints for assessing the accuracy of the two rural roads mapped by the different methods and drew the following conclusions. The image segmentation method had the better performance than the image classification method for mapping the rural roads using the give satellite image, because some of the rural roads mapped by the image classification method were not identified due to the miclassification errors occurred in the object classification map, while all of the rural roads mapped by the image segmentation method were identified. However some of the rural roads mapped by the image segmentation method also had the miclassfication errors due to some rural road segments including the non-rural road objects. In future research the object-oriented classification or the convolutional neural networks widely used for detecting the precise objects from the image sources would be used for improving the accuracy of the rural roads using the high-resolution satellite image.

• Science of Emotion and Sensibility
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• v.22 no.1
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• pp.23-34
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• 2019

The U-Healthcare era has evolved with the development of the Internet of things (IoT) in the early stages of being connected as a society. Already, many changes such as increased well-being and the extension of human life are becoming evident across cultures. Korea entered the growing group of aging societies in 2017, and its silver industry is expected to grow rapidly by adopting the IoT of a super-connected society. In particular, the senior shift phenomenon has resulted in increased interest in the promotion of the health and well-being of the emergent silver generation which, unlike the existing silver generation, is highly active and wields great economic power. This study conducted in-depth interviews to investigate the characteristics of the new silver generation, and to develop the design for a wearable serious game that intends to boost the interest of the elderly in exercise and fitness activities according to their personalized physical training regimes as prescribed by the U-Hospital service. The usage scenario of this wearable serious game for the 'U-silver generation' is derived from social necessity. Medical professionals can utilize this technology to conduct health examinations and to monitor the rehabilitation of senior patients. The elderly can also use this tool to request checkups or to interface with their healthcare providers. The wearable serious game is further aimed at mitigating concerns about the deterioration of the physical functions of the silver generation by applying personalized exercise prescriptions. The present investigation revealed that it is necessary to merge the on / off line community activities to meet the silver generation's daily needs for connection and friendship. Further, the sustainability of the serious game must be enhanced through the inculcation of a sense of accomplishment as a player rises through the levels of the game. The proposed wearable serious game is designed specifically for the silver generation that is inexperienced in using digital devices: simple game rules are applied to a familiar interface grounded on the gourmet travels preferred by the target players to increase usability.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.481-493
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• 2023

In high-density urban areas, the urban heat island effect increases urban temperatures, leading to negative impacts such as worsened air pollution, increased cooling energy consumption, and increased greenhouse gas emissions. In urban environments where it is difficult to secure additional green spaces, rooftop greening is an efficient greenhouse gas reduction strategy. In this study, we not only analyzed the current status of the urban heat island effect but also utilized high-resolution satellite data and spatial information to estimate the available rooftop greening area within the study area. We evaluated the mitigation effect of the urban heat island phenomenon and carbon sequestration capacity through temperature predictions resulting from rooftop greening. To achieve this, we utilized WorldView-2 satellite data to classify land cover in the urban heat island areas of Busan city. We developed a prediction model for temperature changes before and after rooftop greening using machine learning techniques. To assess the degree of urban heat island mitigation due to changes in rooftop greening areas, we constructed a temperature change prediction model with temperature as the dependent variable using the random forest technique. In this process, we built a multiple regression model to derive high-resolution land surface temperatures for training data using Google Earth Engine, combining Landsat-8 and Sentinel-2 satellite data. Additionally, we evaluated carbon sequestration based on rooftop greening areas using a carbon absorption capacity per plant. The results of this study suggest that the developed satellite-based urban heat island assessment and temperature change prediction technology using Random Forest models can be applied to urban heat island-vulnerable areas with potential for expansion.

• Korean Journal of Remote Sensing
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• v.35 no.6_4
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• pp.1319-1326
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• 2019

The KARI(Korea Aerospace Research Institute) operates the government satellite information application consultation to cope with ever-increasing demand for satellite images in the public sector, and carries out various support projects including the generation and provision of mosaic images on the Korean Peninsula every year to enhance user convenience and promote the use of satellite images. In particular, the government has wanted to increase the utilization of mosaic images on the Korean Peninsula and seek to classify and update mosaic images so that users can use them in their businesses easily. However, it is necessary to test and verify whether the classification results of the mosaic images can be utilized in the field since the original spectral information is distorted during pan-sharpening and color balancing, and there is a limitation that only R, G, and B bands are provided. Therefore, in this study, the reliability of the classification result of the mosaic image was compared to the result of KOMPSAT-3 image. The study found that the accuracy of the classification result of KOMPSAT-3 image was between 81~86% (overall accuracy is about 85%), while the accuracy of the classification result of mosaic image was between 69~72% (overall accuracy is about 72%). This phenomenon is interpreted not only because of the distortion of the original spectral information through pan-sharpening and mosaic processes, but also because NDVI and NDWI information were extracted from KOMPSAT-3 image rather than from the mosaic image, as only three color bands(R, G, B) were provided. Although it is deemed inadequate to distribute classification results extracted from mosaic images at present, it is believed that it will be necessary to explore ways to minimize the distortion of spectral information when making mosaic images and to develop classification techniques suitable for mosaic images as well as the provision of NIR band information. In addition, it is expected that the utilization of images with limited spectral information could be increased in the future if related research continues, such as the comparative analysis of classification results by geomorphological characteristics and the development of machine learning methods for image classification by objects of interest.

• Korean Journal of Environmental Biology
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• v.39 no.3
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• pp.354-361
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• 2021

Understanding the phytotoxic mechanism of methyl bromide (MB), an essential fumigant during the quarantine and pre-shipment process, is urgently needed to ensure its proper use and reduce international economic losses. In a previous study, two main MB-induced toxic mechanisms such as reactive oxygen species (ROS) and auxin distribution were selected by analyzing transcriptomic analysis. In the study, a 3-week-old A. thaliana was supplied with 1 mM ROS scavengers [N-acetyl-L-cysteine (NAC) or L-glutathione (GSH)] and 1µM indole-3-acetic acid(IAA) three times every 12 h, and visual and gene expression assessments were performed to evaluate the reduction in phytotoxicity by supplements. Phytotoxic effects on the MB-4h exposed group were decreased with GSH application compared to the other single supplements and a combination of supplements at 7 days post fumigation. Among these supplements, GSH at a concentration of 1, 2, and 5mM was suppled to A. thaliana with MB-fumigation. During a long-term observation of 2 weeks after the fumigation, 5 mM GSH application was the most effective in minimizing MB-induced phytotoxic effects with up-regulation of HSP70 expression and increase in main stem length. These results indicated that ROS was a main key factor of MB-induced phytotoxicity and that GSH can be used as a supplement to reduce the phytotoxicity of MB.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.757-772
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• 2019

The purpose of this paper is to measure the clustering change and analyze empirical results, and choose the clustering ports for Busan, Incheon, and Gwangyang ports by using Artificial Neural Network, Social Network, and Tabu Search models on 38 Asian container ports over the period 2007-2016. The models consider number of cranes, depth, birth length, and total area as inputs and container throughput as output. Followings are the main empirical results. First, the variables ranking order which affects the clustering according to artificial neural network are TEU, birth length, depth, total area, and number of cranes. Second, social network analysis shows the same clustering in the benevolent and aggressive models. Third, the efficiency of domestic ports are worsened after clustering using social network analysis and tabu search models. Forth, social network and tabu search models can increase the efficiency by 37% compared to that of the general CCR model. Fifth, according to the social network analysis and tabu search models, 3 Korean ports could be clustered with Asian ports like Busan Port(Kobe, Osaka, Port Klang, Tanjung Pelepas, and Manila), Incheon Port(Shahid Rajaee, and Gwangyang), and Gwangyang Port(Aqaba, Port Sulatan Qaboos, Dammam, Khor Fakkan, and Incheon). Korean seaport authority should introduce port improvement plans by using the methods used in this paper.

• Korea Science and Art Forum
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• v.31
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• pp.21-32
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• 2017

Local festivals form the regional cultures and atmosphere of communication; they increase the demand of domestic tourism businesses and thus, have an important role in ripple effects (e.g. regional image improvement, tourist influx, job creation, regional contents development, and local product sales) and economic revitalization. IoT (Internet of Thing) technologies have been developed especially, beacon-one of the IoT services has been applied as plenty of types and forms both domestically and internationally. However, notwithstanding expansion of current digital mobile technologies, it still remains as difficult for the individual to track the information about all the local festivals and to fulfill the tourists' needs of enjoying festivals given the weak strategic approaches and advertisement activities. Furthermore, current festival-related mobile applications don't function well as delivering information and have numerous contents issues (e.g. ways of information delivery within the festival places, independent application usage for each festival, one time usage due to one time event). This research, based on the background mentioned above, aims to develop the local festival mobile application and data analysis system applying beacon technology. First of all, three algorithms were developed, namely, 'festival crowding algorithm', 'visitor stats algorithm', and 'customized information algorithm', and then beta test was followed with the developed application and data analysis system. As a result, they could form the database of visitors' types and behaviors, and provide functions and services, such as personalized information, waiting time for festival contents, and 'hot place' function. Besides, in Google Play store, they also got the titles given with more than 13,000 downloads within first three months and as the most exposed application related with festivals; and, thus, got credited with their marketability and excellence. This research follows this order: chapter 2 shows the literature review of local festival related with technology development, beacon service, and festival application. In Chapter 3, design plans and conditions are described of developing local festival mobile application and data analysis system with beacon. Chapter 4 evaluates the results of the beta performance test to verify applicability of the developed application and data analysis system, and lastly, chapter 5 explains the conclusion and suggests the future research.

• Analytical Science and Technology
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• v.31 no.5
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• pp.208-218
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• 2018

Autophagy is a cellular process whereby cytosolic materials or organelles are taken up in a double-membrane vesicle structure known as an autophagosome and transported into a lysosome for degradation. Although autophagy has been studied at the genetic, cellular, or biochemical level, systematic ultrastructural quantitative analysis of autophagosomes during the autophagy process by using transmission electron microscopy (TEM) has not yet been reported. In this study, we performed ultrastructural analysis of autophagosomes in wild-type (WT) mouse embryonic fibroblasts (MEFs) and autophagy essential gene (atg5) knockout (KO) MEFs. First, we performed ultrastructural analysis of autophagosomes in WT MEFs compared to atg5 KO MEFs in basal autophagy or starvation-induced autophagy. Although we observed phagopore, early, late autophagosomes, or autolysosomes in WT MEFs, atg5 KO MEFs had immature autophagosomes that showed incomplete closure. Upon starvation, late autophagosomes accumulated in WT MEFs while the number of immature autophagosomes significantly increased in atg5 KO MEF indicating that atg5 plays an important role in the maturation of autophagosomes. Next, we examined autophagosomes in the cell model expressing polyQ-expanded N-terminal fragment of huntingtin. Our TEM analysis indicates that the number of late autophagosomes was significantly increased in the cells expressing the mutant huntingtin, indicating that improving the fusion of autophagosome with lysosome may be effective to enhance autophagy for the treatment of Huntington's disease. Taken together, the results of our study indicate that ultrastructural and quantitative analysis of autophagosomes using TEM can be applied to various human cellular disease models, and that they will provide an important insight for cellular pathogenesis of human diseases associated with autophagy.