• Journal of the Korean GEO-environmental Society
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• v.24 no.12
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• pp.31-38
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• 2023

In this study, runoff characteristics analysis was conducted as a basic research to establish a forecasting and warning system for flood risk areas in small mountainous basins in South Korea. The Danyang 1 Bridge basin located in Danyang-gun, Chungcheongbuk-do was selected as the study basin, and the watershed characteristic factors were calculated using Q-GIS based on the digital elevation model (DEM) of the basin. In addition, nine heavy rainfall events were selected from 2020 to 2023 using hydrometeorological data provided by the National Water Resources Management Comprehensive Information System. HEC-HMS rainfall-runoff model was used to analyze the runoff characteristics of small mountainous basins, and rainfall-runoff model simulation was performed by reflecting 9 heavy rainfall events and calculated basin characteristic factors. Based on the rainfall-runoff model, parameter optimization was performed for six heavy rain events with large error rates among the simulated events, and the appropriate parameter range for the Danyang 1 Bridge basin, a small mountainous basin, was calculated to be 0.8 to 3.4. The results of this study will be utilized as foundational data for establishing flood forecasting and warning systems in small mountainous basin, and further research will be conducted to derive the range of parameters according to basin characteristics.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.40-48
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• 2023

In this paper, a sensor-based monitoring system was established to analyze the long-term behavioral characteristics of the caisson quay wall, a representative structural type in port facilities. Data was collected over a period of approximately 10 months. Based on existing literature, anomalous behaviors of port facilities were classified, and a measurement system was selected to detect them. Monitoring systems were installed on-site to periodically collect data. The collected data was transmitted and stored on a server through LTE network. Considering the site conditions, inclinometers for measuring slope and crack meters for measuring spacing and settlement were installed. They were attached to two caissons for comparison between different caissons. The correlation among measured data, temperature, and tidal level was examined. The temperature dominated the spacing and settlement data. When the temperature changed by approximately 50 degrees, the spacing changed by 10 mm, the settlement by 2 mm, and the slope by 0.1 degrees. On the other hand, there was no clear relationship with tidal level, indicating a need for more in-depth analysis in the future. Based on the characteristics of these collected database, it will be possible to develop algorithms for detecting abnormal states in gravity-type quay walls. The acquisition and analysis of long-term data enable to evaluate the safety and usability of structures in the event of disasters and emergencies.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.182-196
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• 2023

Accurate and timely estimation of crop yields is crucial for various purposes, including global food security planning and agricultural policy development. Remote sensing techniques, particularly using vegetation indices (VIs), have show n promise in monitoring and predicting crop conditions. However, traditional VIs such as the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) have limitations in capturing rapid changes in vegetation photosynthesis and may not accurately represent crop productivity. An alternative vegetation index, the near-infrared reflectance of vegetation (NIRv), has been proposed as a better predictor of crop yield due to its strong correlation with gross primary productivity (GPP) and its ability to untangle confounding effects in canopies. In this study, we investigated the potential of NIRv in estimating crop yield, specifically for corn and soybean crops in major crop-producing regions in 14 states of the United States. Our results demonstrated a significant correlation between the peak value of NIRv and crop yield/area for both corn and soybean. The correlation w as slightly stronger for soybean than for corn. Moreover, most of the target states exhibited a notable relationship between NIRv peak and yield, with consistent slopes across different states. Furthermore, we observed a distinct pattern in the yearly data, where most values were closely clustered together. However, the year 2012 stood out as an outlier in several states, suggesting unique crop conditions during that period. Based on the established relationships between NIRv peak and yield, we predicted crop yield data for 2022 and evaluated the accuracy of the predictions using the Root Mean Square Percentage Error (RMSPE). Our findings indicate the potential of NIRv peak in estimating crop yield at the county level, with varying accuracy across different counties.

• 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 Preventive Medicine and Public Health
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• v.57 no.2
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• pp.185-196
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• 2024

Objectives: Excess mortality associated with long-term exposure to fine particulate matter (PM_2.5) has been documented. However, research on the disease burden following short-term exposure is scarce. We investigated the cause-specific mortality burden of short-term exposure to PM_2.5 by considering the potential non-linear concentration-response relationship in Korea. Methods: Daily cause-specific mortality rates and PM_2.5 exposure levels from 2010 to 2019 were collected for 8 Korean cities and 9 provinces. A generalized additive mixed model was employed to estimate the non-linear relationship between PM_2.5 exposure and cause-specific mortality levels. We assumed no detrimental health effects of PM_2.5 concentrations below 15 ㎍/m³. Overall deaths attributable to short-term PM_2.5 exposure were estimated by summing the daily numbers of excess deaths associated with ambient PM_2.5 exposure. Results: Of the 2 749 704 recorded deaths, 2 453 686 (89.2%) were non-accidental, 591 267 (21.5%) were cardiovascular, and 141 066 (5.1%) were respiratory in nature. A non-linear relationship was observed between all-cause mortality and exposure to PM_2.5 at lag0, whereas linear associations were evident for cause-specific mortalities. Overall, 10 814 all-cause, 7855 non-accidental, 1642 cardiovascular, and 708 respiratory deaths were attributed to short-term exposure to PM_2.5. The estimated number of all-cause excess deaths due to short-term PM_2.5 exposure in 2019 was 1039 (95% confidence interval, 604 to 1472). Conclusions: Our findings indicate an association between short-term PM_2.5 exposure and various mortality rates (all-cause, non-accidental, cardiovascular, and respiratory) in Korea over the period from 2010 to 2019. Consequently, action plans should be developed to reduce deaths attributable to short-term exposure to PM_2.5.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.139-145
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• 2024

This paper presents the design of a voltage controlled oscillator (VCO) which is one of the key building blocks in modern wireless communication systems with small VCO gain (K_vco) variation. To compensate conventional large K_vco variation, a series varactor bank has been added to the conventional LC-tank with parallel capacitor bank array. And also, in order to achieve excellent phase noise performance while maintaining wide tuning range, a mixed coarse/fine tuning scheme(series varactor array and parallel capacitor array) is chosen. The switched varactor array bank is controlled by the same digital code for switched capacitor array without additional digital circuits. For use at a low voltage of 1.2V, the proposed current reference circuit in this paper used a current reference circuit for safety with the common gate removed more safely. Implemented in a TSMC 0.13㎛ CMOS RF technology, the proposed VCO can be tuned from 4.4GH to 5.3GHz with the K_vco (VCO gain ) variation of less than 9.6%. While consuming 3.1mA from a 1.2V supply, the VCO has -120dBc/Hz phase noise at 1MHz offset from the carrier of the 5.3 GHz.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.2
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• pp.91-111
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• 2024

Most of utility cable tunnels are constructed utilizing shield TBM as part of the underground transmission line project. The TBM chamber is the only space inside the tunnel that encounters rock and soil, and is the place with the highest frequency of accident exposure, such as collapse and collision accidents. Since there is currently no way to measure the disc cutter wear from outside the chamber, frequent inspection by workers is essential. Accordingly, in this study, in order to prevent safety accidents inside the TBM chamber and expect the effect of shortening the construction period by reducing the number of chamber openings, the concept of disk cutter wear measurement technology was established and a prototype was produced. By considering prior technology and determining that magnetic sensors are most suitable for the excavation environment, wear measurement sensor package were developed integrating magnetic sensors, wireless communication modules, power supply, external casing, and monitoring systems. To verify the performance of the prototype in an actual excavation environment, a full-scale tunnelling test was performed using a 3.6 m EPB shield TBM. Based on the full-scale tests, five prototypes were operated normally among eight prototypes. It was analyzed that sensor measurement, wireless communication, and durability performance were secured within a maximum thrust of 3,000 kN and a rotation speed of 1.5 RPM.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.835-840
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• 2023

RFID(Radio Frequency Identification) systems are attracting attention as a key component of Internet of Things technology due to the cost and energy efficiency of application services. In order to use RFID technology in the IoT application service field, it is necessary to be able to store and manage various information for a long period of time as well as simple recognition between the reader and tag of the RFID system. And in order to read and write information to tags, a performance improvement technology that is strong and reliable in poor wireless channels is needed. In particular, in the UHF(Ultra High Frequency) RFID system, since multiple tags communicate passively in a crowded environment, it is essential to improve the recognition rate and transmission speed of individual tags. In this paper, Middleton's Class A impulsive noise model was selected to analyze the performance of the RFID system in an impulsive noise environment, and FM0 encoding and Miller encoding were applied to the tag to analyze the error rate performance of the RFID system. As a result of analyzing the performance of the RFID system in Middleton's Class A impulsive noise channel, it was found that the larger the Gaussian noise to impulsive noise power ratio and the impulsive noise index, the more similar the characteristics to the Gaussian noise channel.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.1
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• pp.70-81
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• 2024

In this study, Tridimensional Hybrid Isolation System(THIS) was proposed as a vibration isolator for traffic loads, combining vertical and horizontal isolation systems. Its efficacy in improving serviceability for vertical vibration was analytically evaluated. Firstly, for the analysis, the major vibration modes of the existing apartment were identified through eigenvalue analysis for the system and pulse response analysis for the bedroom slab using commercial structural analysis software. Subsequently, a 16-story model with horizontal, vertical and rotational degrees of freedom for each slab was numerically organized to represent the achieved modes. The dynamic analysis for the measured acceleration from an adjacent ground to high-speed railway was performed by state-space equations with the stiffness and damping ratio of THIS as variables. The result indicated that as the vertical period ratio increased, the threshold period ratio where the slab response started to be suppressed varied. Specifically, when the period ratio is greater than or equal to 5, the acceleration levels of all slabs decreased to approximately 70% or less compared to the non-isolated condition. On the other hand, it was ascertained that the influence of damping ratios on the response control of THIS is inconsequential in the analysis. Finally, the improvement in vertical vibration performance of THIS was evaluated according to design guidelines for floor vibration of AIJ, SCI and AISC. It was confirmed that, after the application of THIS, the residential performance criteria were met, whereas the non-isolated structure failed to satisfy them.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.1
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• pp.82-89
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• 2024

Black ice is very difficult to recognize and reduces the friction of the road surface, causing automobile accidents. Since black ice is difficult to detect, there is a need for a system that identifies black ice in real time and warns the driver. Various studies have been conducted to prevent black ice on road surfaces, but there is a lack of research on systems that identify black ice in real time and warn drivers. In this paper, an real-time image-based analysis system was developed to identify the condition of asphalt road surface, which is widely used in Korea. For this purpose, a dataset was built for each asphalt road surface image, and then the road surface condition was identified as dry, wet, black ice, and snow using deep learning. In addition, temperature and humidity data measured on the actual road surface were used to finalize the road surface condition. When the road surface was determined to be black ice, the salt spray equipment installed on the road was automatically activated. The surface condition recognition system for the asphalt concrete pavement and black ice automatic prevention system developed in this study are expected to ensure safe driving and reduce the incidence of traffic accidents.