• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.600-602
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• 2022

2차원 이미지 또는 영상을 통한 자세 추정의 경우, 영상 내에서 발생할 수 있는 탐지 오류, 피사체 잘림, 폐색(Occlusion) 등으로 인해 자세 추정 정확도가 감소할 수 있다. 본 논문에서는 4장 이상의 다양한 각도로 촬영한 이미지를 NeRF(Neural Radiance Fields)를 통해 이미지 합성(Image synthesis)을 진행하여 3차원 모델을 생성한다. 이후 DeepLabCut을 사용하여 관절 좌표와 골격(Skeleton)을 구축한다. 구축한 골격을 인공지능에 학습시킨 뒤 2차원 영상에서의 관절 좌표 인식, 골격 구축, 자세 추정을 진행한다. 2차원 영상 테스트 데이터를 통해, 3차원 모델을 사전 학습한 인공지능 모델과 기존 2차원 이미지를 사용하여 학습한 인공지능 모델의 자세 추정 정확도를 비교한다.

• Asia Marketing Journal
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• v.26 no.2
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• pp.104-128
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• 2024

More consumers are choosing pro-consumption for social change, but scholars know little about why and how consumers engage in pro-consumption behaviors. A newly emerged pro-consumption behavior called "Don-jjul," which appeared during the COVID-19 pandemic in South Korea, refers to compensating businesses that have engaged in altruistic actions by boosting their sales. This study used Latent Dirichlet Allocation (LDA) of topic modeling, sentiment analysis, and in-depth interviews to investigate the perceptions, motivations, and emotions regarding Don-jjul. As a result, the study revealed pro-consumers' perceptions of Don-jjul as "collective pro-consumption for contributing to social well-being." Don-jjul has two main motives: "supporting underdogs with difficulties" and "compensating good businesses economically." We also found two ambivalent emotions evoked by Don-jjul: "respect for good business owners" and "concerns regarding the misuse of Don-jjul." The results contribute to pro-consumption research for social well-being, providing business opportunities for retailers and CSR managers with a deep understanding of pro-consumers.

• Food Science and Preservation
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• v.21 no.5
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• pp.676-687
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• 2014

This study investigated the quality changes in cabbage brined with deep sea water salt and in a commercial brined cabbage product. The subject cabbages were separated into two groups: those manufactured in the Lab (ML) and the commercial brined cabbage product (CP). Each group had three brining treatments: with sun-dried salt (S, CS), refined salt (R, CR), and deep sea water salt (D, CD). The salinity level of the ML group was 2.1~2.3%, higher than that of the CP group (1.1~1.5%). The total plate count (TPC) was detected as 5.0 log CFU/g with the S, R, and D treatments at Day 7, but the growth rate of the TPC with the CS, CR, and CD treatments was faster than that with the S, R, and D treatments (6.9~7.7 log CFU/g). A lactic acid bacteria (LAB) level of 5.0~6.6 log CFU/g was also detected in the S, R, and D samples, but only 7.0~7.6 log CFU/g was detected in the CP groups at Day 14. The instrumental hardness levels of the cabbage brined with the deep sea water salts (D and CD) were 3,971 g and 3,932.4 g, respectively, which were significantly higher than those of the samples that were salted with sun-dried salt and refined salt (p<0.05). As for the sensory attributes, S, D, and CD maintained their marketability scores until the end of the storage period for all the properties. CD presented the highest total free amino acid (478.9 mg%), glutamic acid (107.0 mg%), citric acid (428 mg%), and sodium (189 ppm) contents.

• Journal of the Korean earth science society
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• v.24 no.5
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• pp.440-448
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• 2003

We have performed 3-D geomagnetic induction Modeling considering with anomalous conductive structures to interpret the conductive anomaly proposed by previous studies on the Korean Peninsula. The results of modeling coincide well with the observed induction arrow. we confirm the fact that Imjin River Belt and Ogcheon Belt presumed in the model are reasonable. In the western-middle area of the peninsula (YIN, ICHN) the induction arrows seem to reflect the existence for the Imjin River Belt and the induction arrows in western-south area (HNS, CHY, DZN, MWN) is likely to reflect the effect of the Ogcheon Belt. The difference arrows, calculated by subtracting the sea effect from observed induction arrow in the western area of the peninsula at the period of 60-minutes, show little difference with the observed induction arrows. Especially, the difference arrows in YIN, ICHN also show a similar pattern to those at the periods longer than 10-minutes. These results strongly suggest that the Imjin River Belt and the Ogcheon Belt extend down to the deep part of the crust in spite of the limitation of our model.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.45 no.3
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• pp.307-317
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• 2019

To develop sustainable new natural anti-aging ingredients from Korean native plants, we investigated the cultivation potential of Nymphoides indica using the eco-friendly aquaponics system, and tested the anti-aging effects from N. indica extracts. N. indica could be grown in aquaponics system using floating leaved deep water culture method, and propagated through rhizome propagation. It was confirmed that the nitrate ($80{\mu}g/mL$), potassium ($63.5{\mu}g/mL$) and water temperature ($25^{\circ}C$) greatly affected the cultivation of the N. indica. In addition, synergistic effects were found when two major components (3,7-di-O-methylquercetin-4'-O-${\beta}$-glucoside & sweroside) were present at more than about $5{\mu}g/mL$. The extract had a significant effect on the recovery of skin cells damaged by environmental pollutant such as $benzo[{\alpha}]pyrene$, ammonium nitrate, formaldehyde. It also suppressed $PGE_2$, $TNF-{\alpha}$ and COX-2, and inhibited the production of MMP-1. Taken together, the results suggested that the standardized extracts of N. indica cultivated in the aquaponics has considerable potential as a new cosmetics ingredient with an anti-aging effect.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

• Journal of the Korea Convergence Society
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• v.10 no.3
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• pp.1-6
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• 2019

In modern society, lifestyle and individuality are important, and personalized lifestyle and patterns are emerging. The number of people with articulation diseases is increasing due to wrong living habits. In addition, as the number of households increases, there is a case where emergency care is not received at the appropriate time. We need information that can be managed by ourselves through accurate analysis according to the individual's condition for health and disease management, and care appropriate to the emergency situation. It is effectively used for classification and prediction of data using CNN in deep learning. CNN differs in accuracy and processing time according to the data features. Therefore, it is necessary to improve processing speed and accuracy for real-time healthcare. In this paper, we propose motion monitoring using Mask R-CNN for articulation disease management. The proposed method uses Mask R-CNN which is superior in accuracy and processing time than CNN. After the user's motion is learned in the neural network, if the user's motion is different from the learned data, the control method can be fed back to the user, the emergency situation can be informed to the guardian, and appropriate methods can be taken according to the situation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1266-1271
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• 2022

Cats have strong wildness so they have a characteristic of hiding diseases well. The disease may have already worsened when the guardian finds out that the cat has a disease. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia, polyuria, and frequent urination more quickly. In this paper, 1) Efficient version of DeepLabCut for pose estimation, 2) YOLO v4 for object detection, 3) LSTM is used for behavior prediction, and 4) BoT-SORT is used for object tracking running on an artificial intelligence device. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the server system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.165-167
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• 2022

The proportion of cat cats among companion animals has been increasing at an average annual rate of 25.4% since 2012. Cats have strong wildness compared to dogs, so they have a characteristic of hiding diseases well. Therefore, when the guardian finds out that the cat has a disease, the disease may have already worsened. Symptoms such as anorexia (eating avoidance), vomiting, diarrhea, polydipsia, and polyuria in cats are some of the symptoms that appear in cat diseases such as diabetes, hyperthyroidism, renal failure, and panleukopenia. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia (drinking a lot of water), polyuria (a large amount of urine), and frequent urination (urinating frequently) more quickly. In this paper, 1) Efficient version of DeepLabCut for posture prediction running on an artificial intelligence server, 2) yolov4 for object detection, and 3) LSTM are used for behavior prediction. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the main server system.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.2 no.2
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• pp.125-137
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• 1997

To study the vertical variation of heavy metal and Rare Earth Element (REE) contents in deep-sea sediments, eighteen cores were sampled from the Korea Deep-sea Environmental Study (KODES)-96 area in the C-C zone (Clarion-Clipperton fracture zone), northeast equatorial Pacific. Sediment columns can be divided into three units based on sediment colors and geochemical characters; uppermost Unit I with brown color, middle Unit II with pale brown color and smaller Ni/Cu ratio than the ratio in Unit I, and lowermost Unit III with dark (brown) colors and higher contents of Mn, Ni, Cu, and REEs than those in Unit I and II. Unit II can be divided more into two layers of upper Unit IIa and lower Unit IIb. Unit IIb is characterized by high contents of Cu, 3+REEs (REEs except Ce), smectite, and severely deteriorated fossil tests. Unit III can also be divided into two units; upper Unit IIIa with dark brown color, and lower Unit IIIb with black color and enriched Mn and Fe. The KODES area was located near from the East Pacific Rise (EPR) When Unit III Sediments were deposited, considering the hiatus between Unit II and III (Quaternary-Tertiary boundary) and the spreading rate (10 cm/yr) and direction (north southern west) of the Pacific plate from the EPR. High contents of Mn and Fe in Unit IIIb may be related with hydrothermal influence from the EPR. Meanwhile, Unit IIb (about 2~3 Ma) and Unit III (11~30 Ma) layers were probably formed near (or under) the equatorial high productivity zone, and accordingly received a lot of organic materials. As a result, Cu and 3+REEs, closely associated with organic materials, are enriched in smectite and/or Ca-P composites (fish bone debrise, biogenic apatite) after decomposition and reprecipitation on the sea floor. Higher contents of Cu and 3+REEs in Unit IIb and III are suggested to be the result of abundant supply of organic substances in the equatorial high productivity zone.