• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.71-80
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• 2024

In this study, a proposed ensemble learning technique aims to enhance the semantic segmentation performance of images captured by Unmanned Aerial Vehicles (UAVs). With the increasing use of UAVs in fields such as urban planning, there has been active development of techniques utilizing deep learning segmentation methods for land cover segmentation. The study suggests a method that utilizes prominent segmentation models, namely U-Net, DeepLabV3, and Fully Convolutional Network (FCN), to improve segmentation prediction performance. The proposed approach integrates training loss, validation accuracy, and class score of the three segmentation models to enhance overall prediction performance. The method was applied and evaluated on a land cover segmentation problem involving seven classes: buildings,roads, parking lots, fields, trees, empty spaces, and areas with unspecified labels, using images captured by UAVs. The performance of the ensemble model was evaluated by mean Intersection over Union (mIoU), and the results of comparing the proposed ensemble model with the three existing segmentation methods showed that mIoU performance was improved. Consequently, the study confirms that the proposed technique can enhance the performance of semantic segmentation models.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.245-257
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• 2023

The representative crop in the Republic of Korea, rice, is cultivated over extensive areas every year, which resulting in reduced resistance to pests and diseases. One of the major rice diseases, rice blast disease, can lead to a significant decrease in yields when it occurs on a large scale, necessitating early detection and effective control of rice blast disease. Drone-based crop monitoring techniques are valuable for detecting abnormal growth, but frequent image capture for potential rice blast disease occurrences can consume significant labor and resources. The purpose of this study is to early detect rice blast disease using remote sensing data, such as drone and satellite images, along with weather data. Satellite images was helpful in identifying rice cultivation fields. Effective detection of paddy fields was achieved by utilizing vegetation and water indices. Subsequently, air temperature, relative humidity, and number of rainy days were used to calculate the risk of rice blast disease occurrence. An increase in the risk of disease occurrence implies a higher likelihood of disease development, and drone measurements perform at this time. Spectral reflectance changes in the red and near-infrared wavelength regions were observed at the locations where rice blast disease occurred. Clusters with low vegetation index values were observed at locations where rice blast disease occurred, and the time series data for drone images allowed for tracking the spread of the disease from these points. Finally, drone images captured before harvesting was used to generate spatial information on the incidence of rice blast disease in each field.

• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.4
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• pp.324-331
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• 2023

In this study, the hydration and carbonation properties of circulating fluidized bed boiler (CFBC) ash with different free-CaO contents were investigated. In addition, the possibility of utilizing CFBC ash with a high free-CaO content as a cementitious material was investigated by carbonation curing as a pretreatment. The CFBC ash with high free-CaO content exhibited rapid setting behavior and low early compressive strength when mixed with cement. For CFBC ash with high free-CaO content, carbon dioxide capture increased with the duration of carbonization curing. In addition, the free-CaO value decreased together, indicating that the free-CaO reacted with carbon dioxide. When the CFBC ash with high free-CaO content was pretreated by carbonation, no fresh set appeared, and the initial compressive strength was improved. From the results of this study, it is confirmed that CFBC ash with high free-CaO content has a high potential to be utilized as a cementitious material through proper carbonation curing.

• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.4
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• pp.440-448
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• 2023

Utilizing admixture, which is one of the raw material replacement method in the cement industry, is expected to be easily and quickly put to practical use as it is relatively more accessible than other methods. Among cement admixtures, limestone powder is reported to be able to improve cement performance through nucleation effects, chemical effects, and filler effects, so it is a material expected to be suitable as a cement admixture. Meanwhile, as high-quality limestone is depleted around the world, the use of limestone with clay or high magnesia (MgO) content is becoming increasingly inevitable. Therefore, in this study, we attempted to evaluate the suitability of limestone cement as a admixture by measuring the basic properties of limestone cement mixed with limestone of different qualities commonly used in Korea. As a result, the effect of alite reaction promotion was confirmed regardless of the chemical composition of the limestone binder. However, the dilution effect depending on the substitution amount was greater than the chemical composition. It is believed that normal-grade limestone can be used as a mixture as long as the limestone content in cement is within 15 % in this scope of study. In the future, we plan to evaluate the impact of the chemical composition of the limestone mixture through additional experiments depending on the chemical composition of cement.

• Journal of The Korean Association For Science Education
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• v.43 no.6
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• pp.563-572
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• 2023

This study aimed to analyze cases of online class design by pre-service science teachers to identify the teaching strategies employed for online classes. For this purpose, the real-time online class lesson plans of 12 pre-service science teachers, who had experienced education utilizing online teaching tools for a semester, were collected and analyzed. The pre-service science teachers considered all the elements that were essential in traditional face-to-face class designs, including prerequisites, statements of learning objectives, stimulating motivation, teaching and learning methods, wrapping up, teacher-student interaction, and assessment. They devised teaching strategies that could overcome the limitations of online teaching and were not feasible in face-to-face classes for each element. Additionally, they were considering new instructional strategies tailored to the online teaching environment, such as creating a conducive environment for using online teaching tools and strategies related to checking the online teaching environment. However, for statements of learning objectives, stimulating motivation, and wrapping up, most of the pre-service science teachers predominantly utilized teaching strategies from traditional face-to-face classes, especially those involving the presentation of visual materials through online tools. Student-centered approaches were rarely implemented in stimulating motivation or wrapping up. These findings imply that one semester of exposure to the utilization of online teaching tools may be insufficient in teacher education. Thus, there is a need for a continuous and expanded educational program on the utilization of online teaching tools as part of pre-service teacher education.

• Korean Journal of Ecology and Environment
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• v.56 no.4
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• pp.363-374
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• 2023

The limitation in deriving the species richness representing the entire country of South Korea lies in its relatively short history of species field observations and the scattered observation data, which has been collected by various organizations in different fields. In this study, a comprehensive compilation of the observation data for plants held by agencies under the Ministry of Environment was conducted, enabling the construction of a time series dataset spanning over 100 years. The data integration was carried out using minimal criteria such as species name, observed location, and time (year) followed by data verification and correction processes. Based on the integrated plant species data, the comprehensive collection of plant species in South Korea has occurred predominantly since 2000, and the number of plant species explored through these surveys appears to be converging recently. The collection of species survey data necessary for deriving national-level biodiversity information has recently begun to meet the necessary conditions. Applying the Chao 2 method, the species richness of indigenous plants estimated at 3,182.6 for the 70-year period since 1951. A minimum cumulative period of 7 years is required for this estimation. This plant species richness from this study can be a baseline to study future changes in species richness in South Korea. Moreover, the integrated data with the estimation method for species richness used in this study appears to be applicable to derive regional biodiversity indices such as for local government units as well.

• Journal of the Korean Geotechnical Society
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• v.39 no.10
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• pp.41-48
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• 2023

The presence of abnormalities in the subgrade of roads poses safety risks to users and results in significant maintenance costs. In this study, we aimed to experimentally evaluate the temperature distributions in abnormal areas of subgrade materials using infrared cameras and analyze the data with machine learning techniques. The experimental site was configured as a cubic shape measuring 50 cm in width, length, and depth, with abnormal areas designated for water and air. Concrete blocks covered the upper part of the site to simulate the pavement layer. Temperature distribution was monitored over 23 h, from 4 PM to 3 PM the following day, resulting in image data and numerical temperature values extracted from the middle of the abnormal area. The temperature difference between the maximum and minimum values measured 34.8℃ for water, 34.2℃ for air, and 28.6℃ for the original subgrade. To classify conditions in the measured images, we employed the image analysis method of a convolutional neural network (CNN), utilizing ResNet-101 and SqueezeNet networks. The classification accuracies of ResNet-101 for water, air, and the original subgrade were 70%, 50%, and 80%, respectively. SqueezeNet achieved classification accuracies of 60% for water, 30% for air, and 70% for the original subgrade. This study highlights the effectiveness of CNN algorithms in analyzing subgrade properties and predicting subsurface conditions.

• Economic and Environmental Geology
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• v.56 no.5
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• pp.533-545
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• 2023

In this study, an investigation was conducted on the features, events, and processes (FEP) that could impact the long-term safety of the natural barriers constituting high-level radioactive waste geological repositories. The FEP list was developed utilizing the IFEP list 3.0 provided by the Nuclear Energy Agency (NEA) as foundational data, supplemented by geological investigations and research findings from leading countries in this field. A total of 49 FEPs related to the performance of the natural barrier were identified. For each FEP, detailed definitions, classifications, impacts on long-term safety, significance in domestic conditions, and feasibility of quantification were provided. Moreover, based on the compiled FEP list, three scenarios that could affect the long-term safety of the disposal facility were developed. Geological factors affecting the performance of the natural barrier in each scenario were selected and their relationships were visualized. The constructed FEP list and the visualization of interrelated factors in various scenarios are anticipated to provide essential information for selecting and organizing factors that must be considered in the development of mathematical models for quantitatively evaluating the long-term safety of deep geological repositories. In addition, these findings could be effectively utilized in establishing criteria related to the key performance of natural barriers for the confirmation of repository sites.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.5
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• pp.44-56
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• 2023

This research explores the enhancement of park operation and management by analyzing the changing demands of park users. While traditional methods depended on surveys, there has been a recent shift towards utilizing social media data to understand park usage trends. Notably, most research has focused on text data from social media, overlooking the valuable insights from image data. Addressing this gap, our study introduces a novel method of assessing park usage using social media image data and then applies it to actual city park evaluations. A unique image analysis tool, built on Visual Question Answering (VQA) deep learning technology, was developed. This tool revealed specific city park details such as user demographics, behaviors, and locations. Our findings highlight three main points: (1) The VQA-based image analysis tool's validity was proven by matching its results with traditional text analysis outcomes. (2) VQA deep learning technology offers insights like gender, age, and usage time, which aren't accessible from text analysis alone. (3) Using VQA, we derived operational and management strategies for city parks. In conclusion, our VQA-based method offers significant methodological advancements for future park usage studies.

• Journal of Korea Port Economic Association
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• v.39 no.3
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• pp.47-60
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• 2023

A thorough inventory of ship emissions, particularly ship's emission of in-port area is necessary to identify significant sources of exhaust gases such as NOx, SOx, PM, and CO₂ and trends in emission levels over time, and reduce their serious effects on the environment and human health. Therefore, the goal of this study is to assess the volume of emissions from ships in Mokpo port, which serves as a gateway to the southwest coast of Korea, using a bottom-up methodology and data from the automatic identification system (AIS) and the Korean Port Management Information System (Port-MIS). In this work, an analysis of ship movement utilizing AIS data and an actual set of data on ship specification were gathered. By examining ship movement using AIS data, We also proposed a new approach for identifying cruising/maneuvering mode. Finally, the results were classified by ship operating mode, by exhaust gas, by ship type, and by berth, which provides a thorough and in-depth analysis of the air pollution caused by ships in Mokpo port.