• Journal of the Korea Organic Resources Recycling Association
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• v.19 no.3
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• pp.44-53
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• 2011

Siloxane, organo-silicon compound, is used in the various forms of products such as cosmetics and detergents due to its quality physical chemistry attributes. Siloxane included in landfill gas which is caused in the process of decomposing of such products after landfill has imposed negative impacts on the operation of landfill gas utility facilities. The objective of this study was to investigate the siloxane production characteristics depending on the features of various landfill site in Korea so that the analysis was made on the landfilling age and landfill waste by in terms of its concentration, structure and composition. As for the concentration of siloxane depending on time passage, 12 landfill sites were reviewed by landfilling age. As for production attributes change of siloxane by landfill wastes, the source of wastes, physical production ration and siloxane concentration were compared in 6 landfills. The average concentration of total-siloxane within LFG is $6.75mg/m^3$ and cyclic-siloxane out of it occupies over 93%. By element, D4 and D5 in order take the highest proportion regardless of total-siloxane concentration and landfilling age. Even though this study is not able to verify the different impact of each kind of wastes on the generation of siloxane, it is confirmed that total-siloxane and cyclic-siloxane decrease in line with the increase of landfilling age as it does in the first order decay model for landfill gas.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.5
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• pp.533-541
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• 2021

Retaining walls have been used to prevent slope failure through resistance of earth pressure in railway, road, nuclear power plant, dam, and river infrastructure. To calculate dynamic earth pressure and determine the characteristics for seismic behavior, many researchers have analyzed the nonlinear response of ground and structure based on various numerical analyses (FLAC, PLAXIS, ABAQUS etc). In addition, seismic fragility evaluation is performed to ensure safety against earthquakes for structures. In this study, we used the FLAC2D program to understand the seismic response of the inverted T-type wall with a backfill slope, and evaluated seismic fragility based on relative horizontal displacements of the wall. Nonlinear site response analysis was performed for each site (S2 and S4) using the seven ground motions to calculate various seismic loadings reflecting site characteristics. The numerical model was validated based on other numerical models, experiment results, and generalized formula for dynamic active earth pressure. We also determined the damage state and damage index based on the height of retaining wall, and developed the seismic fragility curves. The damage probabilities of the retaining wall for the S4 site were computed to be larger than those for the S2 site.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1517-1526
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• 2021

With the recent global and domestic development of Earth observation satellites, the applications of satellite images have been widened. Research for improving the geometric accuracy of satellite images is being actively carried out. This paper studies the possibility of automated ground control point (GCP) generation for CAS-4 satellite, to be launched in 2025 with the capability of image acquisition at 5 m ground sampling distance (GSD). In particular, this paper focuses to check whether GCP chips with 25 cm GSD established for CAS-1 satellite images can be used for CAS-4 and to check whether optimalspatial resolution for matching between CAS-4 images and GCP chips can be determined to improve matching performance. Experiments were carried out using RapidEye images, which have similar GSD to CAS-4. Original satellite images were upsampled to make satellite images with smaller GSDs. At each GSD level, up-sampled satellite images were matched against GCP chips and precision sensor models were estimated. Results shows that the accuracy of sensor models were improved with images atsmaller GSD compared to the sensor model accuracy established with original images. At 1.25~1.67 m GSD, the accuracy of about 2.4 m was achieved. This finding lead that the possibility of automated GCP extraction and precision ortho-image generation for CAS-4 with improved accuracy.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1669-1683
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• 2021

AI intelligent agriculture and digital agriculture are important for the science of agriculture. Leaf chlorophyll contents(LCC) are one of the most important indicators to determine the growth status of vegetable crops. In this study, a support vector machine (SVM) regression model was produced using an unmanned aerial vehicle-based RGB camera and a multispectral (MSP) sensor for onions and garlic, and the LCC estimation applicability of the RGB camera was reviewed by comparing it with the MSP sensor. As a result of this study, the RGB-based LCC model showed lower results than the MSP-based LCC model with an average R² of 0.09, RMSE 18.66, and nRMSE 3.46%. However, the difference in accuracy between the two sensors was not large, and the accuracy did not drop significantly when compared with previous studies using various sensors and algorithms. In addition, the RGB-based LCC model reflects the field LCC trend well when compared with the actual measured value, but it tends to be underestimated at high chlorophyll concentrations. It was possible to confirm the applicability of the LCC estimation with RGB considering the economic feasibility and versatility of the RGB camera. The results obtained from this study are expected to be usefully utilized in digital agriculture as AI intelligent agriculture technology that applies artificial intelligence and big data convergence technology.

• Journal of Korean Home Economics Education Association
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• v.33 no.1
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• pp.151-167
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• 2021

This study reports on the development of a dietary education program for Korean young adults in single-person households. The 7th National Health and Nutrition Survey (2016-2018) was used to compare and analyze the dietary behavior of single-person households and multi-person households, and an online survey was conducted on 350 young adults (age 19-39 years) living in Seoul. According to the analysis, single-person households had higher rates of breakfast and eating out than multi-person households, and significantly lower average intake of energy and nutrients (p<0.05). In particular, in the case of single-person households, the lower the frequency of cooking at home, the higher the rate of breakfast and the higher the frequency of eating out and delivery food (p<0.05). Based on the survey, a dietary education program for young adults single-person households was developed by applying the DESIGN six-step procedure and social cognitive theory as a conceptual model. The first session consisted of the health and economic benefits of home-cooked meals, the second session of the importance of the breakfast and the effect of exercise in life, the third session of the importance of balanced nutrition and the principles of a healthy diet, the fourth session of food safety and storage, and the fifth session of social dining. Each session was composed of a combination of theoretical lectures to motivate 'more making and eating healthy home-cooked meals' and cooking practice for improving behavioral performance.

• Korean Chemical Engineering Research
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• v.59 no.3
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• pp.417-428
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• 2021

The combustion characteristics of anthracite, which follow a complex process with low reactivity, must be considered through the dynamic behavior of circulating fluidized bed (CFB) boilers. In this study, computational fluid dynamics (CFD) simulation was performed to analyze the combustion characteristics of anthracite in a pilot scale 0.1 MW_th Oxy-fuel circulating fluidized bed (Oxy-CFB) boiler. The 0.1MW_th Oxy-CFB boiler is composed of combustor (0.15 m l.D., 10 m High), cyclone, return leg, and so on. To perform CFD analysis, a 3D simulation model reactor was designed and used. The anthracite used in the experiment has an average particle size of 1,070 ㎛ and a density of 2,326 kg/m³. The flow pattern of gas-solids inside the reactor according to the change of combustion environment from air combustion to oxygen combustion was investigated. At this time, it was found that the temperature distribution in air combustion and oxygen combustion showed a similar pattern, but the pressure distribution was lower in oxygen combustion. addition, since it has a higher CO₂ concentration in oxygen combustion than in air combustion, it can be expected that carbon dioxide capture will take place actively. As a result, it was confirmed that this study can contribute to the optimized design and operation of a circulating fluidized bed reactor using anthracite.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.41-49
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• 2021

All application programs, including malware, call the Application Programming Interface (API) upon execution. Recently, using those characteristics, attempts to detect and classify malware based on API Call information have been actively studied. However, datasets containing API Call information require a large amount of computational cost and processing time. In addition, information that does not significantly affect the classification of malware may affect the classification accuracy of the learning model. Therefore, in this paper, we propose a method of extracting a essential feature set after reducing the dimensionality of API Call information by applying various feature selection methods. We used CICAndMal2020, a recently announced Android malware dataset, for the experiment. After extracting the essential feature set through various feature selection methods, Android malware classification was conducted using CNN (Convolutional Neural Network) and the results were analyzed. The results showed that the selected feature set or weight priority varies according to the feature selection methods. And, in the case of binary classification, malware was classified with 97% accuracy even if the feature set was reduced to 15% of the total size. In the case of multiclass classification, an average accuracy of 83% was achieved while reducing the feature set to 8% of the total size.

• International Area Studies Review
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• v.13 no.3
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• pp.287-308
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• 2009

This article examines the distributional characteristics of the return of Chinese stock market indices. The majority of previous empirical researches have tended to focus upon the simple stock market index. However, this study focuses on the four indices which represent the characteristics of each stock market index. The empirical findings indicate that the returns of the four chinese indices are not normally distributed at conventional levels. The Ljimg-Box -statistics indicate the returns of the index of A shares are not serially autocorrelated. However, the returns of the index of B shares are serially autocorrelated. The empirical findings also indicate returns of the four chinese indices are not serially autocorrelated. The statistics of Regression Specification Error Test and ARCH indicate the returns of all four indices are not serially linear. The findings also indicate that E- GARCH model is the most fittest model for the returns of the four chinese indices and the forecast error can be reduced by using student t distribution rather normal distribution.

• Journal of vocational education research
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• v.37 no.5
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• pp.55-78
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• 2018

The purpose of this study is to investigate the recognition of the professionalism required for strengthening the effective career guidance capacity of the secondary career teachers who are required to prepare for the coming fourth industrial revolution era. Based on these research objectives, we derived the required roles(8), the required competencies(20), and the contents(23) for enhancing professionalism by the required competencies, based on this, the questionnaire was composed and 217 respondents were collected and analyzed. First, the t-test was conducted to confirm the statistically significant difference between the current level and the important level of each content item by each role. As a result, it was found that in all roles except role of 'administrator' The t-value is statistically significant and the t-value distribution is high. Second, the demand value calculation and the priority ranking using the Borich demand calculation formula were found, and as a result, the directionality between the t value and the Borich demand was in agreement. Third, as a result of prioritizing using the Locus for Focus model, the contents of all 5 (middle school 7, high school 2) education contents were given priority. Fourth, three middle schools and five high schools were derived from the subordinate. Finally, we confirmed the relevance of the contents of education to actual educational necessity. Although this study has many limitations and limitations due to the fact that there are few prior data due to the segmentation of the subject related to the 4th Industrial Revolution and career guidance, it is necessary to develop educational training program I hope to be able to use it as basic data of various follow-up studies and make some suggestions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.9-15
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• 2019

Large global online shopping malls, such as Amazon, offer services in English or in the language of a country when their products are sold. Since many customers purchase products based on the product reviews, the shopping malls actively utilize the sentimental analysis technique in judging preference of each product using the large amount of review data that the customer has written. And the result of such analysis can be used for the marketing to look the potential shoppers. However, it is difficult to apply this English-based semantic analysis system to different languages used around the world. In this study, more than 500,000 data from Amazon fine food reviews was used for training a deep learning based system. First, sentiment analysis evaluation experiments were carried out with three models of English test data. Secondly, the same data was translated into seven languages (Korean, Japanese, Chinese, Vietnamese, French, German and English) and then the similar experiments were done. The result suggests that although the accuracy of the sentimental analysis was 2.77% lower than the average of the seven countries (91.59%) compared to the English (94.35%), it is believed that the results of the experiment can be used for practical applications.