• Korean Chemical Engineering Research
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• v.53 no.3
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• pp.357-363
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• 2015

The development of the environment-friendly tire that meets the standard requirements according to tire labeling system can be improved through using highly homogeneous silica immobilized zinc oxide nanoparticles. In this study, a considerable amount of nanoporous silica was essentially added into nano zinc oxide to improve the physiochemical properties of the formed composite. The introduction of nanoporous silica materials in the composite facilitates the improvement of the wear-resistance and increases the elasticity of the tread. Therefore, the introduction of nanoporous silica can replace carbon black as filler in the formation of composites with desirable properties for conventional green tire. Herein, mesoporous silica immobilized zinc oxide nanoparticle with desirable properties for rubber compounds was investigated. Composites with homogeneous dispersion were obtained in the absence of dispersants. The dispersion stability was controlled through varying the molar ratio, ageing time and mixing order of the reactants. A superior dispersion was achieved in the sample obtained using 0.03 mol of zinc precursor as it had the smallest grain size (50.5 nm) and then immobilized in silica aged for 10 days. Moreover, the specific surface area of this sample was the highest ($649m^2/g$).

• Journal of Korean Philosophical Society
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• v.142
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• pp.241-263
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• 2017

The purpose of this paper is to investigate Toegye's simhak in relation to spiritualism. In general, we call Chu Hsi's learning "lihak" (the learning of principle) while Wang Yangming's learning is described as "simhak" (the learning of mind). However, we sometimes call Toegye's learning "simhak" in spite of his respect for Chu Hsi's philosophy of li. Toegye's simhak is different from Wang Yangming's. Nonetheless, Toegye too, highlighted the existential meaning of truth. Toegye regarded simgyung (the book of mind) as one of the most important classics for self-cultivation. As is well known, Toegye's main concern was concentration on mind and heart cultivation. Toegye understood li as a spiritual being, which can actualize itself. The goal of simhak is to become a sage. For a sage, there is no contradiction between moral norm and human desire. To become a sage, Toegye developed the theory and practice of mind cultivation. Toegye's simhak has some common characteristics with Louis Lavelle's philosophy of spiritualism. Both Toegye and Louis Lavelle lay great emphasis on self reflection and spiritual life. In particular, Toegye developed the concrete method of mind cultivation. In the 21st century, human beings are confronted with spiritual crisis in many aspects. Toegye's simhak can be advanced as useful wisdom to keep one's mind in a peaceful and harmonious state.

• Journal of the Korean Society of Radiology
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• v.16 no.2
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• pp.103-113
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• 2022

In this paper, a combined ¹⁸F-FDG(fluorodeoxyglucose) and MNP(magnetic nanoparticles) contrast agent was synthesized using N-(p-maleimidophenyl) isocyanate as the crosslinker for use in simultaneous PET-MRI scans. PET-MRI images were acquired and evaluated before and after injection of the combined contrast imaging agent (¹⁸F-FDG labeled MNP) from a glioma stem cell mouse model. After setting the region of interest (ROI) on each acquired image, the area of the lesion was calculated by segmentation. As a result, the PET image was larger than the MRI. In particular, the simultaneous PET-MRI images showed accurate lesions along with the surrounding soft tissue. The mean and standard deviation values were higher in the MRI images alone than in the PET images or the simultaneous PET-MRI images, regardless of whether the contrast agent was injected. In addition, the simultaneous PET-MRI image values were higher than for the PET images. For PSNR experiments, the original image was PET Image using 18F-FDG, MRI using MNPs, and MRI without contrast medium, and the target image was simultaneous PET-MRI image using 18F-FDG labeled MNPs contrast medium. As a result, all of them appeared significantly, suggesting that the 18F-FDG labeled MNPs contrast medium is useful. Future research is needed to develop an agent that can simultaneously diagnose and treat through SPECT-MRI imaging research that can use various nuclides.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.205-212
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• 2024

This study developed a deep learning model that distinguishes the front (with garnish) and the back (without garnish) surface of the dried semi-finished product (dried bukak) for screening operation before transfter the dried bukak to oil heater using robot's vacuum gripper. For deep learning model training and verification, RGB images for the front and back surfaces of 400 dry bukak that treated by data preproccessing were obtained. YOLO-v5 was used as a base structure of deep learning model. The area, surface information labeling, and data augmentation techniques were applied from the acquired image. Parameters including mAP, mIoU, accumulation, recall, decision, and F1-score were selected to evaluate the performance of the developed YOLO-v5 deep learning model-based surface detection model. The mAP and mIoU on the front surface were 0.98 and 0.96, respectively, and on the back surface, they were 1.00 and 0.95, respectively. The results of binary classification for the two front and back classes were average 98.5%, recall 98.3%, decision 98.6%, and F1-score 98.4%. As a result, the developed model can classify the surface information of the dried bukak using RGB images, and it can be used to develop a robot-automated system for the surface detection process of the dried bukak before deep frying.

• Journal of the Korean Society of Food Science and Nutrition
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• v.34 no.7
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• pp.1000-1007
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• 2005

The aim of the present study was to examine the relationship of maternal factors such as knowledge, attitude and practice of weaning with infant feeding. The subjects were 103 mothers visiting a public health center in Gumi, Kyungbook who filled out self-administered Questionnaires. First of all, about $90\%$ of the participants recognized the importance of complementary foods and proper weaning practices. The response for the recognition of the importance of infant weaning process showed a significant difference by education levels. Concerning an appropriate time for the introduction of weaning foods, $53\%$ of mothers had commenced weaning at age $4\~6$ months, while $38\%$ had done so at age $6\~8$ months. Approximately $76\%$ of mothers fed their babies without the knowledge of age-related weaning method and type of weaning foods. There were no statistical differences in maternal weaning knowledges between levels of education and house income. Mothers with higher levels of education and family income tended to show high perception scores regarding possibility of food allergies caused by baby foods. A demand for reliable sources and education related to nutritious weaning foods and weaning practices were strong in the group with higher education. Knowledge of weaning method and baby foods were obtained by 59 of the 103 mothers from mass media, 35 from friends caring babies, and 9 obtained advice from health professionals or family. Advice from the heath professionals was not the main influence on their decision to introduce weaning foods. Although commercial baby foods are the most commonly used as first weaning foods, those with higher education groups considered commercial baby food are not nutritionally better than home-maid foods. The current findings suggest to us that to improve weaning process, mothers should be educated on the selection and preparation of nutritious, balanced weaning foods and on good weaning practices. It is advised that supportive health professionals from community public health centers should lead the education of infant feeding practices based on maternal characteristics and on basic food and nutritional knowledge.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.36 no.2
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• pp.117-125
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• 2000

The waveform and spectrum analysis of Tursiops truncatus(bottlenose dolphin) sonar signals were carried out on the basis of data collected during the dolphin show at the aquarium of Cheju Pacificland from October 1998 to February 1999. When greeting to audience, the pulse width, peak frequency and spectrum level from the five dolphins'sonar signals were 3.0ms, 4.54kHz and 125.6dB, respectively. At the time of warm-up just before the show, their figures were 5.0㎳, 5.24kHz and 127.0dB, respectively. During the performance of dolphins, with singing, peak frequency ranged 3.28∼5.78kHz and spectrum level ranged 137.0∼142.0dB. With playing ring, pulse width, peak frequency and spectrum level were 7.0㎳, 2.54kHz and 135.9dB, and when playing the ball, the values were 9.0㎳, 2.78kHz and 135.2dB, respectively. The values determined from the five dolphins during jump-up out of water were : pulse width 2.0㎳, peak frequency 4.50kHz and spectrum level 126.8dB. When they responded to trainer's instructions, the values were 2.25㎳, 248kHz and 148.7dB, respectively, and greeting to audience, the peak frequency and spectrum level were 5.84kHz and 122.5dB. During swimming under water, peak frequency and spectrum level were determined to be 10.10kHz and 126.8dB. It was found that there exited close consistencies in pulse width, frequency distribution and spectrum level between whistle sounds and dolphin's sonar signals. Accordingly, the dolphins can be easily trained by using whistle sound based on the results obtained from the waveform and spectrum of the dolphin's sonar signals.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.2
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• pp.105-111
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• 2021

Rice lodging is an annual occurrence caused by typhoons accompanied by strong winds and strong rainfall, resulting in damage relating to pre-harvest sprouting during the ripening period. Thus, rapid estimations of the area of lodged rice are necessary to enable timely responses to damage. To this end, we obtained images related to rice lodging using a drone in Gimje, Buan, and Gunsan, which were converted to 128 × 128 pixels images. A convolutional neural network (CNN) model, a deep learning model based on these images, was used to predict rice lodging, which was classified into two types (lodging and non-lodging), and the images were divided in a 8:2 ratio into a training set and a validation set. The CNN model was layered and trained using three optimizers (Adam, Rmsprop, and SGD). The area of rice lodging was evaluated for the three fields using the obtained data, with the exception of the training set and validation set. The images were combined to give composites images of the entire fields using Metashape, and these images were divided into 128 × 128 pixels. Lodging in the divided images was predicted using the trained CNN model, and the extent of lodging was calculated by multiplying the ratio of the total number of field images by the number of lodging images by the area of the entire field. The results for the training and validation sets showed that accuracy increased with a progression in learning and eventually reached a level greater than 0.919. The results obtained for each of the three fields showed high accuracy with respect to all optimizers, among which, Adam showed the highest accuracy (normalized root mean square error: 2.73%). On the basis of the findings of this study, it is anticipated that the area of lodged rice can be rapidly predicted using deep learning.

• Korean Journal of Heritage: History & Science
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• v.55 no.4
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• pp.296-312
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• 2022

This paper examines the concept and process of heritagization, as well as other measures for the value enhancement of food culture as heritage, through the case of the gastronomic meal of the French, which has a long history as a socially constructed heritage. Heritage refers to what a society perceives as worthy of being transmitted. Thus, a heritage is something that a society or group chooses to preserve and that represents its identity. In the 19th century, France began to designate and protect heritage through a policy of preserving historical monuments, and heritage became both a social construct and creation with the purpose of preserving and enhancing values. Interest in heritage spread around the world with globalization, and has grown even greater since the 1972 UNESCO Convention. This interest has progressively extended to nature, urban landscapes and intangible cultural heritage. In 2003, the UNESCO Convention for the Protection of the Intangible Cultural Heritage was adopted, and this has strengthened the interest in intangible cultural heritage worldwide. Food-related heritage has been excluded from the list due to difficulties in establishing inscription criteria and concerns about the potential commercialization of heritage. However, in 2010, the food cultures of the Mediterranean, Mexico, and France were inscribed on UNESCO's Representative List of the Intangible Cultural Heritage of Humanity, which prompted interest in food culture and efforts to inscribe the food heritage of a number of other countries, including Korea. France has a long history of interest in gastronomy as a cultural heritage and part of its national identity. Efforts to preserve and popularize gastronomy as a part of the national identity and heritage have been made at both the private level, by gourmets and associations, and at the governmental level. Through these efforts, the culture of gastronomy as a heritage has been firmly established through theoretical discussion, listing of food-related heritages, and policies. Sustainable development of the heritage is pursued through certain ongoing institutional approaches, including the City of Gastronomy network, the National Food Program, and the promotion and labeling of the Year of the French Gourmet.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.603-616
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• 2023

In this study, machine learning-based clustering and classification of residential noise in apartment buildings was conducted using frequency and temporal characteristics. First, a residential noise source dataset was constructed . The residential noise source dataset was consisted of floor impact, airborne, plumbing and equipment noise, environmental, and construction noise. The clustering of residential noise was performed by K-Means clustering method. For frequency characteristics, L_eq and L_max values were derived for 1/1 and 1/3 octave band for each sound source. For temporal characteristics, Leq values were derived at every 6 ms through sound pressure level analysis for 5 s. The number of k in K-Means clustering method was determined through the silhouette coefficient and elbow method. The clustering of residential noise source by frequency characteristic resulted in three clusters for both L_eq and L_max analysis. Temporal characteristic clustered residential noise source into 9 clusters for L_eq and 11 clusters for L_max. Clustering by frequency characteristic clustered according to the proportion of low frequency band. Then, to utilize the clustering results, the residential noise source was classified using three kinds of machine learning. The results of the residential noise classification showed the highest accuracy and f1-score for data labeled with L_eq values in 1/3 octave bands, and the highest accuracy and f1-score for classifying residential noise sources with an Artificial Neural Network (ANN) model using both frequency and temporal features, with 93 % accuracy and 92 % f1-score.