• Journal of Practical Agriculture & Fisheries Research
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• v.23 no.2
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• pp.63-70
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• 2021

In order to compare and investigate the growth rates of each of the various soils, the soil mixing ratios were varied to four soils (Pitmos, Pearlite, Masato, General Soil, and Cocopeat). Ten were selected for each soil ratio and the average length and weight were compared. As a result, in the ratio of No. 1 pitmos 6.5: Perlite 2: Masato 1.5, it was measured as 16.36cm, 0.60g. In the ratio of No. 2 pitmos 10, 13.74cm, 0.41g. In the ratio of No. 3 general clay 10, it was measured as 12.43cm, 0.26g. 4 general clay 8, 0.39g. The growth rate of each soil was measured to be superior to that of other soil growth environments in the ratio of pitmos 6.5: pearlite 2: masato 1.5 soil. For ginseng plant analysis, 30 ginseng plants grown in the average length and weight of each soil at a ratio of 6.5: pearlite 2: masato 1.5 and relatively low-result general soil were selected and analyzed. As a result, 1,040ppm of nitrite nitrogen(NO₃-N) was higher in ginseng plants grown in general soil. There was no significant difference in phosphoric acid(P), potassium(K), and magnesium(Mg). Ginseng is characterized by poor growth when it exceeds 300ppm by combining ammonia tae (NH₄-N) and nitrate tae (NO₃-N) nitrogen. In addition, nitric acid produced in a part of this nitrite makes the pH reaction of the soil acidic, and the nitrite remaining in the soil evaporates into gas.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.204-210
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• 2016

This paper presents an experimental analysis of the growth and oxidation processes of soot particles generated in an isooctane diffusive laminar flame due to incomplete combustion. The effects of iron-based diagnostics were employed to measure the elastic scattering light from soot particles in a flame at different flame heights, and the differential scattering coefficients were calculated through a calibration process. The growth and oxidation of soot particles in flame was investigated by comparing differential scattering coefficients, and the soot volume fraction was seen to decrease in the soot oxidation process. In the same manner, the differential scattering coefficients were calculated for iron-based fuel-additive seeded flame, and these coefficients were revealed to be smaller than those obtained in the fuel-additive unseeded flame. In addition, transmission through the radial direction of the flame was measured, and transmission in the soot oxidation regime was approximately 5% higher for the seeded flame. The propensity of the data coincided well with the differential scattering coefficients, and it can be concluded that the iron component of the fuel additive plays a crucial role as a catalyst, which eventually enhanced soot particle oxidation.

• Journal of Digital Convergence
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• v.18 no.3
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• pp.171-177
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• 2020

Under the influence of the Fourth Industrial Revolution, there are many tries to promote productivity enhancement and competitiveness by adapting smart farm technology that converges ICT technologies in agriculture. This smart farming technology is emerging as a new paradigm for future growth in agriculture. The development of real-time cultivation environment monitoring and automatic control system is needed to implement smart farm. Furthermore, the development of intelligent system that manages cultivation environment using monitoring data of the growth of crops is required. In this paper, a fast and efficient development method for implementing a cloud-based smart farm management system using a highly compatible and scalable web platform is proposed. It was verified that the proposed method using the web platform is effective and stable system implementation through the operation of the actual implementation system.

• Korean Journal of Agricultural Science
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• v.46 no.2
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• pp.381-393
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• 2019

A smart farm is a system that combines information and communication technology (ICT), internet of things (IoT), and agricultural technology that enable a farm to operate with minimal labor and to automatically control of a greenhouse environment. Machine learning based on recently data-driven techniques has emerged with big data technologies and high-performance computing to create opportunities to quantify data intensive processes in agricultural operational environments. This paper presents research on the application of machine learning technology to diagnose the growth status of crops and predicting the harvest time of strawberries in a greenhouse according to image processing techniques. To classify the growth stages of the strawberries, we used object inference and detection with machine learning model based on deep learning neural networks and TensorFlow. The classification accuracy was compared based on the training data volume and training epoch. As a result, it was able to classify with an accuracy of over 90% with 200 training images and 8,000 training steps. The detection and classification of the strawberry maturities could be identified with an accuracy of over 90% at the mature and over mature stages of the strawberries. Concurrently, the experimental results are promising, and they show that this approach can be applied to develop a machine learning model for predicting the strawberry harvesting time and can be used to provide key decision support information to both farmers and policy makers about optimal harvest times and harvest planning.

• Journal of Convergence for Information Technology
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• v.9 no.4
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• pp.78-87
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• 2019

The study examined how job satisfaction and pay level can affect on old salary workers over time using longitudinal data and longitudinal data analysis. The KLoSA 6-period panel data was used which contains alternate year from 2006 to 2016. In addition, Gender and Age is also considered as moderating variables. As result, the initial value and the slope of pay level influenced the initial value and the slope of job satisfaction, vice versa. It implicates the two factors of pay level and job satisfaction are interrelated. Based on the results of this study, limitations and suggestions were discussed for further research.

• International Journal of Knowledge Content Development & Technology
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• v.12 no.1
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• pp.17-34
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• 2022

This informetrics study was conducted to find out the distribution of articles and authors that published in African Journal of Library, Archives and Information Studies [AJLAIS]) from 2009 to 2018; considering the year-wise growth of research articles; authorship pattern and collaboration ratio; subject and geographical distributions of authors; and authors' productivity level. A descriptive informetrics research design was adopted. Quota sampling technique was used to select all the articles published within the ten-year period. Data collected through a self-designed checklist was analyzed using frequency count and percentage. The findings revealed that 141 articles, contributed by 266 authors were published by AJLAIS during the period. An annual average growth of 1.20% was recorded. Overall year-wise authorship pattern revealed that majority of articles (62.41%) published in AJLAIS were multiple authored. Also, articles on Informetrics and ICT dominated the journal. Some subject areas not covered were identified such as: indexing and serial collections management. Average collaborative index across the 10-year period for the journal was 0.62. South Africa and Nigeria were the two major prolific contributors to AJLAIS, just as evidence-based research papers of survey type (65.25%) were the most common to the journal. There should be increased numbers of articles in each edition over the coming years, and awareness should be created by the publishers to familiarize the researchers with the publishing requirements of the journal. Also, LIS researchers should concentrate more on areas usually left untouched by previous studies. The study is original as no other similar study was found on publication pattern of articles in AJLAIS covering a ten year period of 2009-2018. The findings of the study will also serve as a feedback mechanism for the Publisher of the Journal and LIS researchers on how to improve the journal and LIS research in general.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.198-221
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• 2021

After large-scale reforestation in the 1960s and 1970s, forests in Korea have gradually been aging. Net ecosystem CO₂ exchange of old-growth forests is theoretically near zero; however, it can be a CO₂ sink or source depending on the intervention of disturbance or management. In this study, we report the CO₂ budget dynamics of the Gwangneung deciduous old-growth forest (GDK) in Korea and examined the following two questions: (1) is the preserved GDK indeed CO₂ neutral as theoretically known? and (2) can we explain the dynamics of CO₂ budget by the common mechanisms reported in the literature? To answer, we analyzed the 15-year long CO₂ flux data measured by eddy covariance technique along with other biometeorological data at the KoFlux GDK site from 2006 to 2020. The results showed that (1) GDK switched back-and-forth between sink and source of CO₂ but averaged to be a week CO₂ source (and turning to a moderate CO₂ source for the recent five years) and (2) the interannual variability of solar radiation, growing season length, and leaf area index showed a positive correlation with that of gross primary production (GPP) (R²=0.32~0.45); whereas the interannual variability of both air and surface temperature was not significantly correlated with that of ecosystem respiration (RE). Furthermore, the machine learning-based model trained using the dataset of early monitoring period (first 10 years) failed to reproduce the observed interannual variations of GPP and RE for the recent five years. Biomass data analysis suggests that carbon emissions from coarse woody debris may have contributed partly to the conversion to a moderate CO₂ source. To properly understand and interpret the long-term CO₂ budget dynamics of GDK, new framework of analysis and modeling based on complex systems science is needed. Also, it is important to maintain the flux monitoring and data quality along with the monitoring of coarse woody debris and disturbances.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.85-92
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• 2014

In recent years, the government has pushed ahead with the convergence and innovation of science technology and information technology in order to realize the creative economy. So, a creative economy ecosystem has been set up to realize the creative economy for small businesses growth and small business happiness. According to proliferation of mobile area taking the lead in the recent IT transition, development of various convergence technologies related to mobile such as mobile Apps, SNS, and big data have been promoted. For realizing government's creative economy, systematic raising plan to create newly value-added market and occupation being considered with developing technology for mobile convergence based on imagination and creativity of small businesses is proposed in this paper.

• Journal of Sensor Science and Technology
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• v.27 no.5
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• pp.352-356
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• 2018

This paper relates to a technology for monitoring a liquefied gas storage tank in the special gas field where demand is increasing owing to the continuous growth of related fields such as the semiconductor, display, and ICT convergence electronics industries. We have proposed a system for real - time monitoring using wireless sensor network technology, and implemented a system consisting of a sensor unit, transmitter module, and receiver module to be attached to a liquefied gas storage tank. The system was applied to LCO2 tanks among various liquefied gas storage tanks to verify the feasibility. The storage tanks employed in the experiments has capacities of 16,179 l and was 1,920 mm in inner diameter. Furthermore, the density was 1.03 g/l. The measured data were compared with reference data on the remaining gas level versus the $CO_2$ height of the surface, expressed using a conventional water meter, provided by an existing storage tank supplier. The experimental results show that the data is similar to the standard data provided by the tank supplier, and has a high accuracy and reliability within an error range of 0.03%.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.4
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• pp.247-261
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• 2017

O2O service that combine online with offline service has been rapidly increasing and O2O service is the new trend that merges online commerce with traditional markets in various fields. The purpose of this study is to investigate influences of University Student's Perceived O2O application characteristics on O2O services satisfaction and continuous use intention. For this purpose, questionnaires including O2O application characteristics scale, customer perceived O2O satisfaction scale and O2O use intention scale were administered to 241 college students in Seoul. Regression analysis revealed that O2O application Characteristics showed influences of O2O service satisfaction. The O2O application charac*teristics showed influences of continuous use of intention of O2O services, O2O services satisfaction showed partial influence continuous use intention of O2O service. The result of this study is expected to provide implication as an initial study O2O service which is spreading with the growth of mobile ICT. Ultimately, the results of this study provide a number of theoretical and practical implications.