• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.165-172
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• 2020

In this paper we propose an uses on-device-based edge computing technology and big data analysis methods through the use of on-device-based edge computing technology and analysis of big data, which are distributed computing paradigms that introduce computations and storage devices where necessary to solve problems such as transmission delays that occur when data is transmitted to central centers and processed in current general smart factories. However, even if edge computing-based technology is applied in practice, the increase in devices on the network edge will result in large amounts of data being transferred to the data center, resulting in the network band reaching its limits, which, despite the improvement of network technology, does not guarantee acceptable transfer speeds and response times, which are critical requirements for many applications. It provides the basis for developing into an AI-based facility prediction conservation analysis tool that can apply deep learning suitable for big data in the future by supporting intelligent facility management that can support productivity growth through research that can be applied to the field of facility preservation and smart factory industry with integrated hardware technology that can accommodate these requirements and factory management and control technology.

• Korean Journal of Environmental Agriculture
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• v.37 no.3
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• pp.197-206
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• 2018

BACKGROUND: The present study aimed to examine the crops capable of growing and adapting to the external environment and various stresses of reclaimed agriculture land for the development of high value-added agricultural utilization technology based on reclaimed land through standardization and empirical study of cultivation environment for cultivating crops. METHODS AND RESULTS: Two crops namely turnips and beets were selected for the salt tolerance test of soil environmental conditions on reclaimed land. Turnip and beet seedlings were planted on the soil collected at the 'Seokmun' reclaimed land. There are five treatments such as non-treatment, 1.0, 2.0 (control), 4.0 and $8.0dS{\cdot}m^{-1}$ of EC. The contents of betacyanin in beet roots was highest in control and decreased with increasing salt concentration. The GSL contents in the turnip roots waswere highest at EC 2.0 and decreased with increasing salt concentration, whereas those in turnip leaves waswere high both in the non-treated control and atthe EC 1.0-treatment. But, tThere was, however, no statistical differences among the treatments. CONCLUSION: The degree of salt tolerance of crops was examined, and the limit EC iswas expected to be $3.0{\sim}4.0dS{\cdot}m^{-1}$ as reported to date. If the soil improvement is performed and irrigation systems are used in the actual reclaimed land, the EC of supplied irrigation will be low, and desalination effecttreatment by the lower EC of the supplied irrigation on the soil will lead to more favorable soil condition of the rhizosphere and cultivation environment offor the crops than those in the port experiment. Therefore, monitoring the salinity, water content and ground water level will enable prediction of the rhizosphere environment, and setting up irrigation management and supplying irrigation will lead to crop cultivation results that are close to normal.

• The Korean Journal of Physiology and Pharmacology
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• v.23 no.2
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• pp.151-159
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• 2019

Pruritus (itching) is classically defined as an unpleasant cutaneous sensation that leads to scratching behavior. Although the scientific criteria of classification for pruritic diseases are not clear, it can be divided as acute or chronic by duration of symptoms. In this study, we investigated whether skin injury caused by chemical (contact hypersensitivity, CHS) or physical (skin-scratching stimulation, SSS) stimuli causes initial pruritus and analyzed gene expression profiles systemically to determine how changes in skin gene expression in the affected area are related to itching. In both CHS and SSS, we ranked the Gene Ontology Biological Process terms that are generally associated with changes. The factors associated with upregulation were keratinization, inflammatory response and neutrophil chemotaxis. The Kyoto Encyclopedia of Genes and Genomes pathway shows the difference of immune system, cell growth and death, signaling molecules and interactions, and signal transduction pathways. Il1a, Il1b and Il22 were upregulated in the CHS, and Tnf, Tnfrsf1b, Il1b, Il1r1 and Il6 were upregulated in the SSS. Trpc1 channel genes were observed in representative itching-related candidate genes. By comparing and analyzing RNA-sequencing data obtained from the skin tissue of each animal model in these characteristic stages, it is possible to find useful diagnostic markers for the treatment of itching, to diagnose itching causes and to apply customized treatment.

• Journal of Climate Change Research
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• v.4 no.2
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• pp.177-188
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• 2013

In this research, forest cover distribution change, forest volume and carbon stock in Yongin-city, Gyeonggi procince were estimated focused on the forest of Yongin-City using forest type map and HyTAG model in relation to climate change. Present forest volume of Yongin-city was estimated using the data from $5^{th}$ Forest Type Map and Korean National Forest Inventory (NFI). And for the future 100 years potential forest distribution by 10-year interval were estimated using HyTAG model. Forest volume was also calculated using algebraic differences form of the growth model. According to the $5^{th}$ Forest Type Map, present needleleaf forest occupied 37.8% and broadleaf forest 62.2% of forest area. And the forest cover distribution after 30 years would be changed to 0.13% of needleleaf forest and 99.97% of broadleaf forest. Finally, 60 years later, whole forest of Yongin-city would be covered by broad-leaf forest. Also the current forest carbon stocks was measured 1,773,862 tC(56.79 tC/ha) and future carbon stocks after 50 years was predicted to 4,432,351 tC(141.90 tC/ha) by HyTAG model. The carbon stocks after 100 years later was 6,884,063 tC (220.40 tC/ha). According to the HyTAG model prediction, Pinus koraiensis, Larix kaempferi, Pinus rigida, and Pinus densiflora are not suitable to the future climate of 10-year, 30-year, 30-year, and 50-year later respectively. All Quercus spp. was predicted to be suitable to the future climate.

• Korean Journal of Clinical Laboratory Science
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• v.51 no.1
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• pp.26-33
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• 2019

Recently, the rapid growth of the companion animal market has led to the development of animal disease diagnosis kits. Therefore, the utility of the introduction of biomarkers for the development of animal molecular diagnostics is being reevaluated. A good biomarker should be precise and reliable, distinguish between normal and diseased states, and differentiate between different diseases. Recently reported genetic markers, tumor markers (cell free DNA, circulating tumor cells, granzyme, and skin tumors), and others (brucellosis, programmed death recovery-1, symmetric dimethylarginine, periostin, and cysteinyl leukotrien) have been developed. The biomarkers are used for risk prediction or for the screening, diagnosis, and monitoring of disease progression. The most important criteria for related biomarkers are disease specificity. Many potential biomarkers have emerged from laboratory and test studies, but they have not been validated in independent or large-scale clinical studies. Candidate biomarkers evaluate disease associations, verify the effectiveness of biomarkers for early detection and disease progression, and incorporate them into humans and animals. In the future, it will be necessary to reevaluate the utility of well-structured biomarker-based research and study the development of kits that can be used in on-site tests in accordance with the trends introduced in the diagnosis of animal diseases.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.48-58
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• 2021

For securing technology and business competences of companies that is the engine of domestic industrial growth, government-supported policy programs for the creation of commercialization results in various forms such as 『Technology Transaction Market Vitalization』 and 『Technology Finance-based R&D Commercialization Support』 have been carried out since 2014. So far, various studies on technology valuation theories and evaluation variables have been formalized by experts from various fields, and have been utilized in the field of technology commercialization. However, Their practicality has been questioned due to the existing constraint that valuation results are assessed lower than the expectation in the evaluation sector. Even considering that the evaluation results may differ depending on factors such as the corporate situation and investment environment, it is necessary to establish a reference infrastructure to secure the objectivity and reliability of the technology valuation results. In this study, we investigate the evaluation infrastructure built by each institution and examine whether the latest artificial neural networks and deep learning technologies are applicable for performing predictive simulation of technology values based on principal variables, and predicting sales estimates and qualitative evaluation scores in order to embed onto the technology valuation system.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.3
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• pp.45-52
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• 2018

Currently, apartments have become an important research subject for the overall area of politics, economics, and culture as well as urban architectural study. However, there are few analyses of the research trends related to the current interest in the apartment research and prediction of the future changes of an apartment in politics and industry. In this study, the research information related to the apartment has classified, and the changes in the research trends have analyzed. Based on the classified data, the first thesis and dissertation related to the apartment and changes of academic notation have discovered. In addition, future interests and future research directions through Frequency of Appearance, Degree Centrality Analysis, and Betweenness Centrality Analysis of author keywords were predicted. As a result of the analysis, 'Space,' 'Residential Mobility' and 'Apartment Complex' studies were found to be important research topics throughout the entire period. 'Han Gang Apartment,' 'Small Size Apartment,' 'Civic Apartments,' 'Jamsil,' and 'Child' were newly interested topics until 70's era. '(Super) High-rise Apartment,' 'Perception,' 'Jugong Apartment,' 'Housing Environment,' 'Housewife,' 'Apartment Layout,' and 'Busan' were newly interested topics during the 80's and 90's era. 'Apartment Price,' 'Energy,' 'Remodeling,' 'Noise,' 'Resident Satisfaction,' 'Community,' and 'Apartment Lotting-out' were newly interested topics after the year 2000. New concerns for last decade are found to be 'Super High-rise Apartment', 'Remodeling', 'Indoor'(2007), 'Apartment Reconstruction Project', 'Brand', 'AHP', 'Housing Environment'(2008), 'Ventilation'(2009), 'Apartment Lotting-out'(2010), 'Economic Assessment'(2011), 'Cost'(2012), 'Green Building', 'Apartment Sales', 'Law', 'Society'(2013), 'Floor Impact Noise', 'Seoul'(2014), 'Noise'(2015), 'Hedonic Model'(2016). In addition, following research topics are expected to be active in the future: In maturity stage of the research development is going to be 'Apartment Price', 'Space', 'Management of Apartment Housing'; the hedonic model, which is research growth and development stage, is going to be '(Floor Impact) Noise', 'Community', 'Energy.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.193-198
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• 2021

Recently, interests in the 4th industry have increased the level of demand for pest control by farmers in the field of rice farming, and the interests and use of agricultural pest control drones. Therefore, the diversification of agricultural control drones that spray high-concentration pesticides and the increase of agricultural exterminators due to the acquisition of national drone certifications are rapidly developing the agricultural sector in the drone industry. In addition, as detailed projects, an effective platform is required to construct large-scale big data due to pesticide management, exterminator management, precise spraying, pest control work volume classification, settlement, soil management, prediction and monitoring of damages by pests, etc. and to process the data. However, studies in South Korea and other countries on development of models and programs to integrate and process the big data such as data analysis algorithms, image analysis algorithms, growth management algorithms, AI algorithms, etc. are insufficient. This paper proposed an online drone pest control management information platform to meet the needs of managers and farmers in the agricultural field and to realize precise AI pest control based on the agricultural drone pest control processor using drones and presented foundation for development of a comprehensive management system through empirical experiments.

• Journal of Bio-Environment Control
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• v.31 no.1
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• pp.1-7
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• 2022

Strawberry is a stand-out cultivating fruit in Korea. The optimum production of strawberry is highly dependent on growing environment. Smart farm technology, and automatic monitoring and control system maintain a favorable environment for strawberry growth in greenhouses, as well as play an important role to improve production. Moreover, physiological parameters of strawberry plant and it is surrounding environment may allow to give an idea on production of strawberry. Therefore, this study intends to build a machine learning model to predict strawberry's yield, cultivated in greenhouse. The environmental parameter like as temperature, humidity and CO₂ and physiological parameters such as length of leaves, number of flowers and fruits and chlorophyll content of 'Seolhyang' (widely growing strawberry cultivar in Korea) were collected from three strawberry greenhouses located in Sacheon of Gyeongsangnam-do during the period of 2019-2020. A predictive model, Lasso regression was designed and validated through 5-fold cross-validation. The current study found that performance of the Lasso regression model is good to predict the number of flowers and fruits, when the MAPE value are 0.511 and 0.488, respectively during the model validation. Overall, the present study demonstrates that using AI based regression model may be convenient for farms and agricultural companies to predict yield of crops with fewer input attributes.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.119-133
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• 2022

One of the most important current features of food related industry is the growth of food delivery service. Another notable food related culture is, with the advent of Youtube, the popularity of Mukbang, which refers to content that records eating. Based on these background, this study intended to focus on two things. First, we tried to see the impact of Youtube Mukbang and the sentiments of Mukbang comments on the number of related food deliveries. Next, we tried to set up the predictive modeling of chicken delivery order with machine learning method. We used Youtube Mukbang comments data as well as weather related data as main independent variables. The dependent variable used in this study is the number of delivery order of fried chicken. The period of data used in this study is from June 3, 2015 to September 30, 2019, and a total of 1,580 data were used. For the predictive modeling, we used machine learning methods such as linear regression, ridge, lasso, random forest, and gradient boost. We found that the sentiment of Youtube Mukbang and comments have impacts on the number of delivery orders. The prediction model with Mukban data we set up in this study had better performances than the existing models without Mukbang data. We also tried to suggest managerial implications to the food delivery service industry.