• Journal of Ocean Engineering and Technology
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• v.35 no.4
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• pp.273-286
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• 2021

In recent years, as human casualties and property damage caused by hazardous waves have increased in the East Sea, precise wave prediction skills have become necessary. In this study, the Simulating WAves Nearshore (SWAN) third-generation numerical wave model was calibrated and optimized to enhance the accuracy of winter storm wave prediction in the East Sea. We used Source Term 6 (ST6) and physical observations from a large-scale experiment conducted in Australia and compared its results to Komen's formula, a default in SWAN. As input wind data, we used Korean Meteorological Agency's (KMA's) operational meteorological model called Regional Data Assimilation and Prediction System (RDAPS), the European Centre for Medium Range Weather Forecasts' newest 5th generation re-analysis data (ERA5), and Japanese Meteorological Agency's (JMA's) meso-scale forecasting data. We analyzed the accuracy of each model's results by comparing them to observation data. For quantitative analysis and assessment, the observed wave data for 6 locations from KMA and Korea Hydrographic and Oceanographic Agency (KHOA) were used, and statistical analysis was conducted to assess model accuracy. As a result, ST6 models had a smaller root mean square error and higher correlation coefficient than the default model in significant wave height prediction. However, for peak wave period simulation, the results were incoherent among each model and location. In simulations with different wind data, the simulation using ERA5 for input wind datashowed the most accurate results overall but underestimated the wave height in predicting high wave events compared to the simulation using RDAPS and JMA meso-scale model. In addition, it showed that the spatial resolution of wind plays a more significant role in predicting high wave events. Nevertheless, the numerical model optimized in this study highlighted some limitations in predicting high waves that rise rapidly in time caused by meteorological events. This suggests that further research is necessary to enhance the accuracy of wave prediction in various climate conditions, such as extreme weather.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.163-172
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• 2022

The purpose of this study is to present implications in the planning and design methodology for revitalization of public spaces for mixed-use residential building. For the purpose, I have taken a literature research and a site analysis with cases of 'Kyungsung Univ.·Bukyung Nat'l Univ. Station'-area in Busan City. The analysis framework was consist of spatial composition, street facilities, use behavior, and connection with the street. The result of this study is as follows; 1) It is needed to consist of an empty space practically usable in an open location that is easy to access by the general public. 2) Considering the use of people, it is needed to install street furniture that can actually be used for rest. 3) It is needed to make a plan and design that considers the access and use of the general public and the space through it. 4) It is needed to create a synergistic effect in the integration of the street and the public space and the linkage with the street through this.

• Journal of Astronomy and Space Sciences
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• v.38 no.4
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• pp.203-215
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• 2021

The auroral observation has been started at Jang Bogo Station (JBS), Antarctica by using a visible All-sky camera (v-ASC) in 2018 to routinely monitor the aurora in association with the simultaneous observations of the ionosphere, thermosphere and magnetosphere at the station. In this article, the auroral observations are introduced with the analysis procedure to recognize the aurora from the v-ASC image data and to compute the auroral occurrences and the initial results on their spatial and temporal distributions are presented. The auroral occurrences are mostly confined to the northern horizon in the evening sector and extend to the zenith from the northwest to cover almost the entire sky disk over JBS at around 08 MLT (magnetic local time; 03 LT) and then retract to the northeast in the morning sector. At near the magnetic local noon, the occurrences are horizontally distributed in the northern sky disk, which shows the auroral occurrences in the cusp region. The results of the auroral occurrences indicate that JBS is located most of the time in the polar cap near the poleward boundary of the auroral oval in the nightside and approaches closer to the oval in the morning sector. At around 08 MLT (03 LT), JBS is located within the auroral oval and then moves away from it, finally being located in the cusp region at the magnetic local noon, which indicates that the location of JBS turns out to be ideal to investigate the variabilities of the poleward boundary of the auroral oval from long-term observations of the auroral occurrences. The future plan for the ground auroral observations near JBS is presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2131-2153
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• 2022

To achieve accurate detection of tuberculosis (TB) areas in chest radiographs, we design a chest X-ray TB area detection algorithm. The algorithm consists of two stages: the chest X-ray TB classification network (CXTCNet) and the chest X-ray TB area detection network (CXTDNet). CXTCNet is used to judge the presence or absence of TB areas in chest X-ray images, thereby excluding the influence of other lung diseases on the detection of TB areas. It can reduce false positives in the detection network and improve the accuracy of detection results. In CXTCNet, we propose a channel attention mechanism (CAM) module and combine it with DenseNet. This module enables the network to learn more spatial and channel features information about chest X-ray images, thereby improving network performance. CXTDNet is a design based on a sparse object detection algorithm (Sparse R-CNN). A group of fixed learnable proposal boxes and learnable proposal features are using for classification and location. The predictions of the algorithm are output directly without non-maximal suppression post-processing. Furthermore, we use CLAHE to reduce image noise and improve image quality for data preprocessing. Experiments on dataset TBX11K show that the accuracy of the proposed CXTCNet is up to 99.10%, which is better than most current TB classification algorithms. Finally, our proposed chest X-ray TB detection algorithm could achieve AP of 45.35% and AP50 of 74.20%. We also establish a chest X-ray TB dataset with 304 sheets. And experiments on this dataset showed that the accuracy of the diagnosis was comparable to that of radiologists. We hope that our proposed algorithm and established dataset will advance the field of TB detection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4439-4455
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• 2021

Compared with two-stage object detection algorithms, one-stage algorithms provide a better trade-off between real-time performance and accuracy. However, these methods treat the intermediate features equally, which lacks the flexibility to emphasize meaningful information for classification and location. Besides, they ignore the interaction of contextual information from different scales, which is important for medium and small objects detection. To tackle these problems, we propose an image pyramid network based on dual attention mechanism (DAIPNet), which builds an image pyramid to enrich the spatial information while emphasizing multi-scale informative features based on dual attention mechanisms for one-stage object detection. Our framework utilizes a pre-trained backbone as standard detection network, where the designed image pyramid network (IPN) is used as auxiliary network to provide complementary information. Here, the dual attention mechanism is composed of the adaptive feature fusion module (AFFM) and the progressive attention fusion module (PAFM). AFFM is designed to automatically pay attention to the feature maps with different importance from the backbone and auxiliary network, while PAFM is utilized to adaptively learn the channel attentive information in the context transfer process. Furthermore, in the IPN, we build an image pyramid to extract scale-wise features from downsampled images of different scales, where the features are further fused at different states to enrich scale-wise information and learn more comprehensive feature representations. Experimental results are shown on MS COCO dataset. Our proposed detector with a 300 × 300 input achieves superior performance of 32.6% mAP on the MS COCO test-dev compared with state-of-the-art methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.599-607
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• 2021

Street-view images, which are omnidirectional scenes centered on a specific location on the road, can provide various obstacle information for the pedestrians. Pedestrian network data for the navigation services should reflect the up-to-date obstacle information to ensure the mobility of pedestrians, including people with disabilities. In this study, the object detection model was trained for the bollard as a major obstacle in Seoul using street-view images and a deep learning algorithm. Also, a process for updating information about the presence and number of bollards as obstacle properties for the crosswalk node through spatial matching between the detected bollards and the pedestrian nodes was proposed. The missing crosswalk information can also be updated concurrently by the proposed process. The proposed approach is appropriate for crowdsourcing data as the model trained using the street-view images can be applied to photos taken with a smartphone while walking. Through additional training with various obstacles captured in the street-view images, it is expected to enable efficient information update about obstacles on the road.

• Journal of Preventive Medicine and Public Health
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• v.55 no.5
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• pp.485-491
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• 2022

Objectives: Tuberculosis (TB) is a major public health concern worldwide. Social contact patterns can affect the epidemiology and risk of airborne diseases such as TB. This study was designed to investigate the social contact patterns associated with TB. Methods: In this case-control study, groups of participants with and without TB were matched by age and sex. Participants reported the nature, location, frequency, and average duration of social contacts over 1 month. The duration and number of social and spatial contacts were compared between groups using the chi-square test and the t-test. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to quantify the relationship between social contact time and TB status. Data were analyzed using Stata version 11 statistical software. A p-value of <0.05 was considered to indicate statistical significance. Results: In this study, 80 patients with TB and 172 control participants were included, and a total of 3545 social contacts were registered. Social contact with family members (OR, 1.72; 95% CI, 1.10 to 2.40), contact with a person with TB (OR, 1.53; 95% CI, 1.16 to 2.01), and contact at the participant's home (OR, 1.42; 95% CI, 1.19 to 1.82) were significantly associated with TB status. Conclusions: The duration of long-term social contact, rather than the number of contacts, may be the main contact-related factor associated with TB transmission in this population. The focus of contact-tracing efforts should be on finding and treating both family members and long-term contacts in non-household settings.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.3
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• pp.211-216
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• 2022

Steganography technology protects the existence of hidden information by embedding a secret message in a specific location on the cover medium. Security and resistance are strengthened by applying various hybrid methods based on encryption and steganography. In particular, techniques to increase chaos and randomness are needed to improve security. In fact, the case where the shuffling method is applied based on the discrete cosine transform(DCT) and the least significant bit(LSB) is an area that needs to be studied. I propose a new approach to hide the bit information of Hangul messages by integrating the selective shuffling method that can add the complexity of message hiding and applying the spatial domain technique to steganography. Inverse shuffling is applied when extracting messages. In this paper, the Hangul message to be inserted is decomposed into the choseong, jungseong and jongseong. It improves security and chaos by applying a selective shuffling process based on the corresponding information. The correlation coefficient and PSNR were used to confirm the performance of the proposed method. It was confirmed that the PSNR value of the proposed method was appropriate when compared with the reference value.

• Industry Promotion Research
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• v.7 no.4
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• pp.85-95
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• 2022

This study intends to analyze the meaning of symbolism in ancestral memorial rite arrangemen from the view that ancestral worship connecting traditional society with modernity are the transmission of ritual. It appears as a change the theory of Yin-Yang and Five Elements that became the basis and ideology about the Confucian view of life and death, an understanding of the universe structure, and a change in the four seasons. Ancestral memorial rite arrangements acknowledge the existence of ancestors. And it is understood as a ceremonial instrument which the living and the dead communicate spatially with time through the symbolic system. In addition, the four seasons, spaces of the skyground and underground were symbolized and embodied through the selection and arrangement of ancestral memorial rites. In the modern ancestral memorial rite arrangement, the factors that determine the location require Time-space analysis of the target. This is because the offering is understood not only as a functional role but also as a temporal and spatial symbolism to be expressed through the offering. In this study, it is meaningful to consider it from the perspective of inheritance of ancestral worship culture through discussions about the ideological background and symbolic system that appeared in ancestral memorial rite arrangement

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.219-230
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• 2023

Marine waste is classified according to its location into coastal waste, floating waste, and submerged waste. As awareness of environmental issues increases, research on marine submerged waste in addition to visible trash is needed. In Korea, which is surrounded by the sea on three sides, this is a study on the distribution of marine sedimentary waste by type in the West Sea of Korea. Through the study, waste synthetic resin, scrap metal, waste tires, and others appeared in the order of large amounts. As a result showing the seriousness of waste synthetic resin among sediments deposited in the West Sea, it is expected to have a huge impact not only on the marine ecosystem but also on our lives in the near future. Through this study, it is judged that it will be helpful for future collection activities by recognizing marine submerged waste that was not known because it was invisible.