• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.85-92
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• 2021

Ambient Air Vaporizer (AAV) is an essential facility in the process of generating natural gas that uses air in the atmosphere as a medium for heat exchange to vaporize liquid natural gas into gas-state gas. AAV is more economical and eco-friendly in that it uses less energy compared to the previously used Submerged vaporizer (SMV) and Open-rack vaporizer (ORV). However, AAV is not often applied to actual processes because it is heavily affected by external environments such as atmospheric temperature and humidity. With insufficient operational experience and facility operations that rely on the intuition of the operator, the actual operation of AAV is very inefficient. To address these challenges, this paper proposes an artificial intelligence-based model that can intelligent AAV operations based on operational big data. The proposed artificial intelligence model is used deep neural networks, and the superiority of the artificial intelligence model is verified through multiple regression analysis and comparison. In this paper, the proposed model simulates based on data collected from real-world processes and compared to existing data, showing a 48.8% decrease in power usage compared to previous data. The techniques proposed in this paper can be used to improve the energy efficiency of the current natural gas generation process, and can be applied to other processes in the future.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.371-379
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• 2022

The environment in Kosovo is a topic of concern for the citizens and the state because of the temperatures that affect the health of the citizens and the climate around the world. Kosovo's climate is related to its geographical position. Stretching in the middle latitude, Kosovo's climate depends on the amount of heat coming from the Sun, the proximity of the Adriatic Sea, the Vardar valley, the openness to the north. In order to better understand the climatic features of Kosovo, one must know the elements of the climate such as: sunshine, temperature, precipitation, atmospheric pressure, winds. The Meteorological Institute of Kosovo is responsible for measuring temperatures in Kosovo since 2014 and until now 12 meteorological stations have been operationalized with automatic measurement and real-time data transfer to the central system for data collection and archiving. The hydrometeorological institute lacks an application for measuring temperatures in all the countries of Kosovo. Software applications are generally built to suit the requirements of different governments and clients in order to enable easier management of the jobs they operate on. One of the forms of application development is the development of mobile applications based on android. The purpose of the work is to create a mobile application based on the Android operating system that aims to display information about the weather, this type of application is necessary and important for users who want to see the temperature in different places in Kosovo, but also the world. This type of application offers many options such as maximum temperature, minimum temperature, humidity, and air pressure. The built application will have real and accurate data; this will be done by comparing the results with other similar applications. Such an application is necessary for everyone, especially for those people whose daily work is dependent on the weather or even for those who decide to spend their vacations, such as summer or winter. In this paper, comparisons are also made within android applications for tablets, televisions and smart watches.

• ETRI Journal
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• v.44 no.4
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• pp.573-587
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• 2022

The agricultural sector is completely different from other sectors since it completely relies on various natural and climatic factors. Climate changes have many effects, including lack of annual rainfall and pests, heat waves, changes in sea level, and global ozone/atmospheric CO₂ fluctuation, on land and agriculture in similar ways. Climate change also affects the environment. Based on these factors, farmers chose their crops to increase productivity in their fields. Many existing agricultural ontologies are either domain-specific or have been created with minimal vocabulary and no proper evaluation framework has been implemented. A new agricultural ontology focused on subdomains is designed to assist farmers using Jaccard relative extractor (JRE) and Naïve Bayes algorithm. The JRE is used to find the similarity between two sentences and words in the agricultural documents and the relationship between two terms is identified via the Naïve Bayes algorithm. In the proposed method, the preprocessing of data is carried out through natural language processing techniques and the tags whose dimensions are reduced are subjected to rule-based formal concept analysis and mapping. The subdomain ontologies of weather, pest, and soil are built separately, and the overall agricultural ontology are built around them. The gold standard for the lexical layer is used to evaluate the proposed technique, and its performance is analyzed by comparing it with different state-of-the-art systems. Precision, recall, F-measure, Matthews correlation coefficient, receiver operating characteristic curve area, and precision-recall curve area are the performance metrics used to analyze the performance. The proposed methodology gives a precision score of 94.40% when compared with the decision tree(83.94%) and K-nearest neighbor algorithm(86.89%) for agricultural ontology construction.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.1
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• pp.102-112
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• 2023

This research mainly focuses on the transport and dispersion of chemical agent plume according to the Lagrangian Puff Model and Lagrangian Particle Model of NBC_RAMS(Nuclear, Biological, Chemical Reporting And Modeling S/W System). NBC_RAMS was developed with the purposes of estimating the fate of Chemical, Biological, and Radioactive(CBR) agent plumes and evaluating damages in the Republic of Korea. First, it calculates the local weather pattern, i.e. wind speed, wind direction, and temperature, by considering the effects of land uses and topography. The plume behaviors are calculated by adopting the Lagrangian Puff Model(LPFM) or Lagrangian Particle Model(LPTM). In this research, we assumed a virtual chemical agent exposure event in a stable atmospheric condition during the summer season. The plume behaviors were estimated by both LPFM and LPTM on the used area(urbanized and dry area) and the agricultural land. The higher heat flux in the used area led to stronger winds and further downward movement moving of the chemical agent than the farmland. The lateral dispersion of the chemical plume was emphasized in the Lagrangian Puff Model because it adopted Gaussian distribution.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.spc
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• pp.31-38
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• 2023

In this study, in order to develop a method to efficiently inject essential nutrients necessary for plant growth into wood chips, which are simply used as soil covering materials in the agriculture, landscaping and horticultural industries, the atmospheric pressure dipping method and the vacuum pressure impregnating method are used to improve the plant nutrients injectability and impregnation amount were comparatively analyzed. Nutrient ingredients and 8 major heavy metal contents of wood chips injected with nutrients were analyzed, and soil covering effects were examined by covering wood chips injected with nutrients on soil. Comparing the dipping method and the vacuum pressure impregnation method, it took about 48 hours or more to inject 1,500 g or more of the nutrient aqueous solution into 1 kg of wood chips in the dipping method, but the vacuum pressure impregnation method could be impregnated in about 5 minutes. Components of the impregnated nutrients were detected in proportion to the diluted concentration. As a result of covering the wood chips developed in this study on soil, they showed weakly acidic pH, and the heat insulation and moisturizing effects during the winter season were evaluated to be superior to those of uncovered soil. In the future, wood chips impregnated with nutrients are expected to contribute to the more efficient use of waste wood resources and the long-term supply of nutrients essential for plant growth, reducing excessive use of chemical fertilizers and reducing costs.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.20 no.1
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• pp.39-48
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• 2024

Research reactors are operated under ambient temperature and atmospheric pressure, which is much less severe conditions compared to those in typical nuclear power plants. Due to the high temperature, heat resistant materials such as austenite stainless steel should be used for the reactors in typical nuclear power plants. Whereas, as the effect of temperature is low for research reactors, materials with high resistance to neutron irradiation, such as zircaloy and beryllium, are used. Therefore, these conditions should be considered when performing integrity assessment for research reactors. In this study, a computational technique through finite element (FE) analysis was developed considering the operating conditions and materials of research reactor when conducting integrity assessment. Neutron irradiation analysis techniques using thermal expansion analysis were proposed to consider neutron irradiation growth and swelling in zirconium alloys and beryllium. A user subroutine program that can calculate the strain rate induced by neutron irradiation creep was developed for use in the commercial analysis program Abaqus. To validate the proposed technique and the user subroutine, FE analysis results were compared with hand-calculation results, and showed good agreement. Consequently, developed technique and user subroutine are suitable for evaluating structural integrity of research reactors.

• Journal of the Korean Vacuum Society
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• v.22 no.2
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• pp.55-65
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• 2013

Sterilization of Neurospora crassa has been investigated in this research by using a surface air plasma with dielectric barrier discharged (DBD) structure under atmospheric pressure. The sinusoidal alternating current has been used in this experiment with discharge voltage of 1.4~2.3 kV. The phase difference between the voltage and current signals are found to be almost 80 degree due to the capacitive property of dielectric barrier. Temperature on the biomaterials has been minimized by radiating the heat with the air cooling system. It is noted that the substrate temperature remains under 37 degree for plasma exposure time of 10 minutes with operation of cooler system. It is found that the ozone, $O_3$, has been measured to be about 25~30 ppm within 1 cm region and to be about 5 ppm at the 150 cm downstream region away from the suface plasma. It is also noted that the nitric oxide, NO, and nitric dioxide, $NO_2$, are not nearly detected. Germination rate and mitochodrial activity of Neurospora crassa immersed in the deionized water have been found to be drastically decreased as the plasma treatment time and its electrical power are increased in this experiment. Here, the mitochondrial activity has been analyzed by MTT (3-(4,5-dimethy lthiazol-2yl)-2,5-diphenyl-2H-tetrazolium bromide) assay. However, sterilization of Neurospora crassa immersed in the Vogel's minimal media has been found to be low by plasma treatment, which is caused by surrounding background solution. This research shows the sterilization possibility of Neurospora crassa by using the noncontated surface DBD plasma, which is different from the plasma jet. This is mainly attibuted to the reactive species generated by the surface plasma, since they play a major role for inhibition of micobes such as Neurospora crassa.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

• The Korean Journal of Quaternary Research
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• v.20 no.1 s.26
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• pp.51-66
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• 2006

The climate of the last glacial maximum (LGM) in northeast Asia is simulated with an atmospheric general circulation model of NCAR CCM3 at spectral truncation of T170, corresponding to a grid cell size of roughly 75 km. Modern climate is simulated by a prescribed sea surface temperature and sea ice provided from NCAR, and contemporary atmospheric CO2, topography, and orbital parameters, while LGM simulation was forced with the reconstructed CLIMAP sea surface temperatures, sea ice distribution, ice sheet topography, reduced $CO_2$, and orbital parameters. Under LGM conditions, surface temperature is markedly reduced in winter by more than $18^{\circ}C$ in the Korean west sea and continental margin of the Korean east sea, where the ocean exposed to land in the LGM, whereas in these areas surface temperature is warmer than present in summer by up to $2^{\circ}C$. This is due to the difference in heat capacity between ocean and land. Overall, in the LGM surface is cooled by $4{\sim}6^{\circ}C$ in northeast Asia land and by $7.1^{\circ}C$ in the entire area. An analysis of surface heat fluxes show that the surface cooling is due to the increase in outgoing longwave radiation associated with the reduced $CO_2$ concentration. The reduction in surface temperature leads to a weakening of the hydrological cycle. In winter, precipitation decreases largely in the southeastern part of Asia by about $1{\sim}4\;mm/day$, while in summer a larger reduction is found over China. Overall, annual-mean precipitation decreases by about 50% in the LGM. In northeast Asia, evaporation is also overall reduced in the LGM, but the reduction of precipitation is larger, eventually leading to a drier climate. The drier LGM climate simulated in this study is consistent with proxy evidence compiled in other areas. Overall, the high-resolution model captures the climate features reasonably well under global domain.

• Atmosphere
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• v.23 no.3
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• pp.283-291
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• 2013

This study investigates the changes in the atmosphere-ocean interactions over the South China Sea (SCS) by analyzing their variables in the period of 1979~2011 during the boreal summer (June-July-August). It is found that a simultaneous correlation coefficient between sea surface temperature (SST) and precipitation over SCS during summer is significantly changed before and after the late-1990s. That is, the variation of precipitation over SCS is negatively (positively) correlated with the SST variations before (after) the late-1990s. Our further correlation analysis indicates that the atmospheric forcing of the SST is dominant before the late-1990s accompanying with wind-evaporation feedback and cloud-radiation feedback. After the late-1990s, in contrast, the SST forcing of the atmosphere through the latent heat flux from the ocean to the atmosphere is dominant. It is found that the change in the relationship of atmosphere-ocean interactions over SCS are associated with the changes in the relationship with Northeast Asian summer precipitation. In particular, a simultaneous correlation coefficient between the precipitation over SCS and Northeast Asia becomes stronger during after the late-1990s than before the late-1990s. We argue that the increase of the SST forcing of the atmosphere over SCS may lead a direct relationship of precipitation variations between SCS and Northeast Asia after the late-1990s.