• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4A
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• pp.329-335
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• 2009

The purpose of this study is to provide the efficient method and guideline of controlling the cracking in bridge deck concrete due to differential drying shrinkage. Drying shrinkage cracking is mainly influenced by the moisture diffusion coefficient that determines moisture diffusion rate inside concrete structures. In addition to the diffusion coefficient, surface coefficient of concrete surface and relative humidity of ambient air simultaneously affect the moisture evaporation from concrete inside to external air outside. Within the framework of cracking shrinkage cracking mechanism, it is necessary to conceive the numerical analysis, which involves these three influencing factors to predict and control the shrinkage cracking of concrete. In this study, moisture diffusion and stress analysis corresponding to drying shrinkage on bridge deck are performed with consideration of diffusion coefficient, surface coefficient, and relative humidity of ambient air. From the numerical results, it is found that cracking behavior due to differential drying shrinkage of bridge deck concrete shows different feature according to three influencing factors and the methodology of controlling of drying shrinkage cracks can be suggested from this study.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.315-324
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• 2023

In this paper, we propose a real-time pose estimation method for a monocular camera using a particle filter integrated with UKF (unscented Kalman filter). While conventional camera tracking techniques combine camera images with data from additional devices such as gyroscopes and accelerometers, the proposed method aims to use only two-dimensional visual information from the camera without additional sensors. This leads to a significant simplification in the hardware configuration. The proposed approach is based on a particle filter integrated with UKF. The pose of the camera is estimated using UKF, which is defined individually for each particle. Statistics regarding the camera state are derived from all particles of the particle filter, from which the real-time camera pose information is computed. The proposed method demonstrates robust tracking, even in the case of rapid camera shakes and severe scene occlusions. The experiments show that our method remains robust even when most of the feature points in the image are obscured. In addition, we verify that when the number of particles is 35, the processing time per frame is approximately 25ms, which confirms that there are no issues with real-time processing.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.3
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• pp.134-139
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• 2023

Rehabilitators perform outpatient treatment and daily rehabilitation exercises to recover physical function with the aim of quickly returning to society after surgical treatment. Unlike performing exercises in a hospital with the help of a professional therapist, there are many difficulties in performing rehabilitation exercises by the patient on a daily basis. In this paper, we propose a CNN-LSTM-based upper limb rehabilitation real-time monitoring system so that patients can perform rehabilitation efficiently and with correct posture on a daily basis. The proposed system measures biological signals through shoulder-mounted hardware equipped with EMG and IMU, performs preprocessing and normalization for learning, and uses them as a learning dataset. The implemented model consists of three polling layers of three synthetic stacks for feature detection and two LSTM layers for classification, and we were able to confirm a learning result of 97.44% on the validation data. After that, we conducted a comparative evaluation with the Teachable machine, and as a result of the comparative evaluation, we confirmed that the model was implemented at 93.6% and the Teachable machine at 94.4%, and both models showed similar classification performance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.883-896
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• 2023

As human activities in Korea are spread throughout the mountains, forest fires often affect residential areas, infrastructure, and other facilities. Hence, it is necessary to detect fire-damaged areas quickly to enable support and recovery. Remote sensing is the most efficient tool for this purpose. Fire damage detection experiments were conducted on the east coast of Korea. Because this area comprises a mixture of forest and artificial land cover, data with low resolution are not suitable. We used Sentinel-2 multispectral instrument (MSI) data, which provide adequate temporal and spatial resolution, and the k-nearest neighbor (kNN) algorithm in this study. Six bands of Sentinel-2 MSI and two indices of normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as features for kNN classification. The kNN classifier was trained using 2,000 randomly selected samples in the fire-damaged and undamaged areas. Outliers were removed and a forest type map was used to improve classification performance. Numerous experiments for various neighbors for kNN and feature combinations have been conducted using bi-temporal and uni-temporal approaches. The bi-temporal classification performed better than the uni-temporal classification. However, the uni-temporal classification was able to detect severely damaged areas.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.519-524
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• 2023

In hashing-based image retrieval, the hash code of a manipulated image is different from the original image, making it difficult to search for the same image. This paper proposes and evaluates a self-supervised deephashing model that generates perceptual hash codes from feature information such as texture, shape, and color of images. The comparison models are autoencoder-based variational inference models, but the encoder is designed with a fully connected layer, convolutional neural network, and transformer modules. The proposed model is a variational inference model that includes a SimAM module of extracting geometric patterns and positional relationships within images. The SimAM module can learn latent vectors highlighting objects or local regions through an energy function using the activation values of neurons and surrounding neurons. The proposed method is a representation learning model that can generate low-dimensional latent vectors from high-dimensional input images, and the latent vectors are binarized into distinguishable hash code. From the experimental results on public datasets such as CIFAR-10, ImageNet, and NUS-WIDE, the proposed model is superior to the comparative model and analyzed to have equivalent performance to the supervised learning-based deephashing model. The proposed model can be used in application systems that require low-dimensional representation of images, such as image search or copyright image determination.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.2
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• pp.61-68
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• 2024

The majority of high-speed railway bridges along the domestic Gyeongbu and Honam lines feature a PSC-box type structure with a span length ranging from 35 to 40m, which typically exhibits a first bending natural frequency of approximately 4 to 5Hz. When KTX high-speed trains transverse these bridges at speeds ranging from 290 to 310km/h, the vibration induced by the trains approaches the first bending natural frequency of the bridge. Furthermore, with the upcoming operation of a EMU-320 high-speed train and the anticipated increase in the speeds of these high-speed trains, there is a need to analyze the dynamic response of high-speed railway bridges. For this, based on measured responses from actual railway bridges, a numerical model was constructed using a numerical model updating technique. The dynamic response of the updated numerical model exhibited a strong agreement with the measured response from the actual railway bridges. Subsequently, this updated model was utilized to analyze the dynamic response characteristics of the bridges when KTX and EMU-320 trains operate at increased speeds. The maximum vertical displacement and acceleration at the mid-span of the bridges were also compared to those specified in the railway design standard with the increasing speed of KTX and EMU-320.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.3
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• pp.1-9
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• 2024

This study proposes a multi-scale template matching technique with image pyramids (TMI) to measure structural dynamic displacement using a vision sensor under atmospheric turbulence conditions and evaluates its displacement measurement performance. To evaluate displacement measurement performance according to distance, the three-story shear structure was designed, and an FHD camera was prepared to measure structural response. The initial measurement distance was set at 10m, and increased with an increment of 10m up to 40m. The atmospheric disturbance was generated using a heating plate under indoor illuminance condition, and the image was distorted by the optical turbulence. Through preliminary experiments, the feasibility of displacement measurement of the feature point-based displacement measurement method and the proposed method during atmospheric disturbances were compared and verified, and the verification results showed a low measurement error rate of the proposed method. As a result of evaluating displacement measurement performance in an atmospheric disturbance environment, there was no significant difference in displacement measurement performance for TMI using an artificial target depending on the presence or absence of atmospheric disturbance. However, when natural targets were used, RMSE increased significantly at shooting distances of 20 m or more, showing the operating limitations of the proposed technique. This indicates that the resolution of the natural target decreases as the shooting distance increases, and image distortion due to atmospheric disturbance causes errors in template image estimation, resulting in a high displacement measurement error.

• IMMUNE NETWORK
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• v.22 no.5
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• pp.42.1-42.20
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• 2022

Vaccination with tumor peptide epitopes associated with MHC class I molecules is an attractive approach directed at inducing tumor-specific CTLs. However, challenges remain in improving the therapeutic efficacy of peptide epitope vaccines, including the low immunogenicity of peptide epitopes and insufficient stimulation of innate immune components in vivo. To overcome this, we aimed to develop and test an innovative strategy that elicits potent CTL responses against tumor epitopes. The essential feature of this strategy is vaccination using tumor epitope-loaded nanoparticles (NPs) in combination with polyinosinic-polycytidylic acid (poly-IC) and anti-PD1 mAb. Carboxylated NPs were prepared using poly(lactic-co-glycolic acid) and poly(ethylene/maleic anhydride), covalently conjugated with anti-H-2K^b mAbs, and then attached to H-2K^b molecules isolated from the tumor mass (H-2^b). Native peptides associated with the H-2K^b molecules of H-2K^b-attached NPs were exchanged with tumor peptide epitopes. Tumor peptide epitope-loaded NPs efficiently induced tumor-specific CTLs when used to immunize tumor-bearing mice as well as normal mice. This activity of the NPs significantly was increased when co-administered with poly-IC. Accordingly, the NPs exerted significant anti-tumor effects in mice implanted with EG7-OVA thymoma or B16-F10 melanoma, and the anti-tumor activity of the NPs was significantly increased when applied in combination with poly-IC. The most potent anti-tumor activity was observed when the NPs were co-administered with both poly-IC and anti-PD1 mAb. Immunization with tumor epitope-loaded NPs in combination with poly-IC and anti-PD1 mAb in tumor-bearing mice can be a powerful means to induce tumor-specific CTLs with therapeutic anti-tumor activity.

• Journal of the Korean Society of Radiology
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• v.83 no.5
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• pp.1032-1045
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• 2022

Peripheral arterial disease (PAD) is common in elderly patients. Lower-extremity CT angiography (LE-CTA) can be useful for detecting PAD and planning its treatment. PAD can also be accurately evaluated on reconstructed monoenergetic images (MEIs) from low kiloelectron volt (keV) to high keV images using dual-energy CT. Low keV images generally provide higher contrast than high keV images but also feature more severe image noise. The noise-reduced virtual MEI reconstruction algorithm, called the Mono+ technique, was recently introduced to overcome such image noise. Therefore, this pictorial review aimed to present the imaging findings of PAD on LE-CTA and compare low and high keV images with those subjected to the Mono+ technique. We found that, in many cases, the overall and segmental image qualities were better and metal artifacts and venous contamination were decreased in the high keV images.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.173-180
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• 2024

We This study aimed to quantitatively analyze the theme of 'libertinage' and the associated issues of reason and emotion in 『Dangerous Liaisons』, a novel considered a masterpiece of libertine literature and an epistolary novel of the 18th century, using digital analysis tools. First, based on the frequency analysis of word usage using Voyant and LIWC 22, we confirmed that libertinage is manifested with keywords such as 'love' and 'time'. With Voyant's 'Contexts' feature, it was found that the letters sent by Valmont to Madame de Tourvel and those sent by Madame de Merteuil both have 'love' as the central theme. However, emotional vocabulary was higher in the former, whereas strategic vocabulary was more prevalent in the latter. Additionally, it was observed that the most frequently used word in the letters sent by Madame de Merteuil is 'time', with a higher frequency than 'love'. Thirdly, using LIWC 22, we measured the analytical thinking and emotional tone of the letters exchanged by the main characters, and analyzed how these values changed according to the chapters. Through these analyses, we confirmed that this novel, alongside Rousseau's "New Eloise," anticipates romanticism by embracing the theme of 'emotion,' which was rejected by 18th-century Enlightenment ideals.