• Journal of Intelligence and Information Systems
• /
• v.27 no.3
• /
• pp.75-94
• /
• 2021

The low birth rate and shortened military service period are causing concerns about selecting excellent military officers. The Republic of Korea entered a low birth rate society in 1984 and an aged society in 2018 respectively, and is expected to be in a super-aged society in 2025. In addition, the troop-oriented military is changed as a state-of-the-art weapons-oriented military, and the reduction of the military service period was implemented in 2018 to ease the burden of military service for young people and play a role in the society early. Some observe that the application rate for military officers is falling due to a decrease of manpower resources and a preference for shortened mandatory military service over military officers. This requires further consideration of the policy of securing excellent military officers. Most of the related studies have used social scientists' methodologies, but this study applies the methodology of text mining suitable for large-scale documents analysis. This study extracts words of discriminative characteristics from the Republic of Korea Air Force Non-Commissioned Officer Applicant cover letters and analyzes the polarity of pass and fail. It consists of three steps in total. First, the application is divided into general and technical fields, and the words characterized in the cover letter are ordered according to the difference in the frequency ratio of each field. The greater the difference in the proportion of each application field, the field character is defined as 'more discriminative'. Based on this, we extract the top 50 words representing discriminative characteristics in general fields and the top 50 words representing discriminative characteristics in technology fields. Second, the number of appropriate topics in the overall cover letter is calculated through the LDA. It uses perplexity score and coherence score. Based on the appropriate number of topics, we then use LDA to generate topic and probability, and estimate which topic words of discriminative characteristic belong to. Subsequently, the keyword indicators of questions used to set the labeling candidate index, and the most appropriate index indicator is set as the label for the topic when considering the topic-specific word distribution. Third, using L-LDA, which sets the cover letter and label as pass and fail, we generate topics and probabilities for each field of pass and fail labels. Furthermore, we extract only words of discriminative characteristics that give labeled topics among generated topics and probabilities by pass and fail labels. Next, we extract the difference between the probability on the pass label and the probability on the fail label by word of the labeled discriminative characteristic. A positive figure can be seen as having the polarity of pass, and a negative figure can be seen as having the polarity of fail. This study is the first research to reflect the characteristics of cover letters of Republic of Korea Air Force non-commissioned officer applicants, not in the private sector. Moreover, these methodologies can apply text mining techniques for multiple documents, rather survey or interview methods, to reduce analysis time and increase reliability for the entire population. For this reason, the methodology proposed in the study is also applicable to other forms of multiple documents in the field of military personnel. This study shows that L-LDA is more suitable than LDA to extract discriminative characteristics of Republic of Korea Air Force Noncommissioned cover letters. Furthermore, this study proposes a methodology that uses a combination of LDA and L-LDA. Therefore, through the analysis of the results of the acquisition of non-commissioned Republic of Korea Air Force officers, we would like to provide information available for acquisition and promotional policies and propose a methodology available for research in the field of military manpower acquisition.

• Journal of Korea Water Resources Association
• /
• v.53 no.12
• /
• pp.1159-1172
• /
• 2020

This study applied deep convolution neural network based on U-Net and SegNet using long period weather radar data to very short-term rainfall prediction. And the results were compared and evaluated with the translation model. For training and validation of deep neural network, Mt. Gwanak and Mt. Gwangdeoksan radar data were collected from 2010 to 2016 and converted to a gray-scale image file in an HDF5 format with a 1km spatial resolution. The deep neural network model was trained to predict precipitation after 10 minutes by using the four consecutive radar image data, and the recursive method of repeating forecasts was applied to carry out lead time 60 minutes with the pretrained deep neural network model. To evaluate the performance of deep neural network prediction model, 24 rain cases in 2017 were forecast for rainfall up to 60 minutes in advance. As a result of evaluating the predicted performance by calculating the mean absolute error (MAE) and critical success index (CSI) at the threshold of 0.1, 1, and 5 mm/hr, the deep neural network model showed better performance in the case of rainfall threshold of 0.1, 1 mm/hr in terms of MAE, and showed better performance than the translation model for lead time 50 minutes in terms of CSI. In particular, although the deep neural network prediction model performed generally better than the translation model for weak rainfall of 5 mm/hr or less, the deep neural network prediction model had limitations in predicting distinct precipitation characteristics of high intensity as a result of the evaluation of threshold of 5 mm/hr. The longer lead time, the spatial smoothness increase with lead time thereby reducing the accuracy of rainfall prediction The translation model turned out to be superior in predicting the exceedance of higher intensity thresholds (> 5 mm/hr) because it preserves distinct precipitation characteristics, but the rainfall position tends to shift incorrectly. This study are expected to be helpful for the improvement of radar rainfall prediction model using deep neural networks in the future. In addition, the massive weather radar data established in this study will be provided through open repositories for future use in subsequent studies.

• Food Science and Industry
• /
• v.53 no.1
• /
• pp.2-32
• /
• 2020

In recent years, significant importance has been given to chitooligosaccharides (COS) due to its potent notable biological applications. COS can be derived from chitosan which is commonly produced by partially hydrolyzed products from crustacean shells. In order to produce COS, there are several approaches including chemical and enzymatic methods which are the two most common choices. In this regard, several new methods were intended to be promoted which use the enzymatic hydrolysis with a lower cost and desired properties. Hence, the dual reactor system has gained more attention than other newly developed technologies. Enzymatic hydrolysis derived COS possesses important biological activities such as anticancer, antioxidant, anti-hypersentive, anti-dementia (Altzheimer's disease), anti-diabeties, anti-allergy, anti-inflammatory, etc. Results strongly suggest that properties of COS can be potential materials for nutraceutical, pharmaceutical, and cosmeceutical product development.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_3
• /
• pp.1827-1836
• /
• 2022

Disasters that occur unexpectedly are difficult to predict. In addition, the scale and damage are increasing compared to the past. Sometimes one disaster can develop into another disaster. Among the four stages of disaster management, search and rescue are carried out in the response stage when an emergency occurs. Therefore, personnel such as firefighters who are put into the scene are put in at a lot of risk. In this respect, in the initial response process at the disaster site, robots are a technology with high potential to reduce damage to human life and property. In addition, Light Detection And Ranging (LiDAR) can acquire a relatively wide range of 3D information using a laser. Due to its high accuracy and precision, it is a very useful sensor when considering the characteristics of a disaster site. Therefore, in this study, development and experiments were conducted so that the robot could perform real-time monitoring at the disaster site. Multi-sensor module was developed by combining LiDAR, Inertial Measurement Unit (IMU) sensor, and computing board. Then, this module was mounted on the robot, and a customized Simultaneous Localization and Mapping (SLAM) algorithm was developed. A method for stably mounting a multi-sensor module to a robot to maintain optimal accuracy at disaster sites was studied. And to check the performance of the module, SLAM was tested inside the disaster building, and various SLAM algorithms and distance comparisons were performed. As a result, PackSLAM developed in this study showed lower error compared to other algorithms, showing the possibility of application in disaster sites. In the future, in order to further enhance usability at disaster sites, various experiments will be conducted by establishing a rough terrain environment with many obstacles.

• Plant Journal
• /
• v.18 no.4
• /
• pp.58-65
• /
• 2023

In this study, to increase the methane content of biogas supplied from Nanji Water Regeneration Center and to purify impurities, a three-stage membrane purification process was designed and installed to demonstrate operation. The methane concentration of biomethane produced in the 2 Nm3/h purification process was set to three cases: 95%, 96.5%, and 98%, and the membrane area ratio of the membrane was 1:1, 1:2, 1:1:1, The optimum conditions for the membrane area of the separator were derived by changing to five of 1:2:1 and 1:2:2. 3 stage separation membrane process of 30 Nm3/h was installed to reflect the optimum condition of 2 Nm3/h, and biomethane production of 98% or more of methane concentration was demonstrated. As a result of the operation of the 2 Nm³/h refining device, the methane recovery rate at the 98% methane concentration was 95.6% when the membrane area ratio was 1:1 as the result of the two-stage operation of the separator, and the recovery rate of methane at 1:2 was increased to 96.8%. The methane recovery rate of the membrane three-stage operation was highest at 96.8% when the membrane area ratio was operated at 1:2:1. The carbon dioxide removal rate was 16.4 to 96.4% and the 2:2 to 95.7% film area ratio in the two-step process. In the three-step process, the film area ratio was 1:2:1 to 95.4%, and the two-step process showed higher results than the three-step process. In the 30 Nm3/h scale biogas purification demonstration operation, the methane concentration after purification was 98%, the recovery rate of methane was 97.1%, the removal rate of carbon dioxide was 95.7%, and hydrogen sulfide, the cause of corrosion, was not detected, and the membrane area ratio was 1:2:1 demonstration operation, biomethane production with a methane concentration of 98% or higher was possible.

• Korean Journal of Ecology and Environment
• /
• v.55 no.1
• /
• pp.1-9
• /
• 2022

An estuary is an area where a freshwater river or stream meets the ocean. Even before the importance of the value of estuaries was recognized, the estuary was lost because of large-scale conversion by draining, filling, damming, and dredging. In South Korea, 643 estuaries are located, and the total area is 3,248,300 ha, accounting for 32.5% of the total area of South Korea. Over 35% of Korean estuaries are closed estuaries which are only temporally connected with the sea, either permanently or periodically. Since 2008, in order to preserve the estuary ecosystem and solve major issues in the estuary by accumulating knowledge about the estuarine ecosystem, the Ministry of Environment of Republic of Korea has been conducting the "Estuarine Ecosystem Monitoring and Assessment Project". At 668 sites of 325 estuaries, epilithic diatom, benthic macroinvertebrate, fish, and vegetation are investigated, and the habitat condition of each site is evaluated using the newly developed biotic index. More than 100 researchers annually record 2,097 species of estuaries according to the standardized survey guidelines over the past 14 years and provide strictly managed data necessary for establishing estuaries conservation policies. As a result of bibliometric analysis of 1,195 research articles related to the monitoring and assessment of the estuarine ecosystem, research on pollutants such as heavy metals and sediment control have recently been conducted. "Estuarine Ecosystem Monitoring and Assessment Project" is an ecological monitoring type of long-term mandated monitoring that is usually focused on identifying trends. Although it is difficult to identify the mechanism influencing a change in an ecosystem through long-term mandated monitoring, providing empirical data for supporting evidence-based policy, decision-making, and the management of ecosystems. In order to increase the efficiency of the project, research to investigate the relationship between sediments and pollutants and organisms can be conducted at specific estuaries or sites to compensate for the shortcomings of mandatory monitoring.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_4
• /
• pp.1097-1109
• /
• 2023

Urban is an area where small-scale changes to individual buildings occur frequently. An existing urban building database requires periodic updating to increase its usability. However, there are limitations in data collection for building changes over a wide urban. In this study, we check the possibility of detecting building changes and updating a building database by using satellite images that can capture a wide urban region by a single image. For this purpose, building areas in a satellite image are first extracted by projecting 3D coordinates of building corners available in a building database onto the image. Building areas are then divided into roof and facade areas. By comparing textures of the roof areas projected, building changes such as height change or building removal can be detected. New height values are estimated by adjusting building heights until projected roofs align to actual roofs observed in the image. If the projected image appeared in the image while no building is observed, it corresponds to a demolished building. By checking buildings in the original image whose roofs and facades areas are not projected, new buildings are identified. Based on these results, the building database is updated by the three categories of height update, building deletion, or new building creation. This method was tested with a KOMPSAT-3A image over Incheon Metropolitan City and Incheon building database available in public. Building change detection and building database update was carried out. Updated building corners were then projected to another KOMPSAT-3 image. It was confirmed that building areas projected by updated building information agreed with actual buildings in the image very well. Through this study, the possibility of semi-automatic building change detection and building database update based on single satellite image was confirmed. In the future, follow-up research is needed on technology to enhance computational automation of the proposed method.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_4
• /
• pp.1135-1144
• /
• 2023

Many agricultural reservoirs in South Korea, constructed before 1970, have become aging facilities. The majority of small-scale reservoirs lack measurement systems to ascertain basic specifications and water levels, classifying them as unmeasured reservoirs. Furthermore, continuous sedimentation within the reservoirs and industrial development-induced water quality deterioration lead to reduced water supply capacity and changes in reservoir morphology. This study utilized Light Detection And Ranging (LiDAR) sensors, which provide elevation information and allow for the characterization of surface features, to construct high-resolution Digital Surface Model (DSM) and Digital Elevation Model (DEM) data of reservoir facilities. Additionally, bathymetric measurements based on multibeam echosounders were conducted to propose an updated approach for determining reservoir capacity. Drone-based LiDAR was employed to generate DSM and DEM data with a spatial resolution of 50 cm, enabling the display of elevations of hydraulic structures, such as embankments, spillways, and intake channels. Furthermore, using drone-based hyperspectral imagery, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were calculated to detect water bodies and verify differences from existing reservoir boundaries. The constructed high-resolution DEM data were integrated with bathymetric measurements to create underwater contour maps, which were used to generate a Triangulated Irregular Network (TIN). The TIN was utilized to calculate the inundation area and volume of the reservoir, yielding results highly consistent with basic specifications. Considering areas that were not surveyed due to underwater vegetation, it is anticipated that this data will be valuable for future updates of reservoir capacity information.

• Journal of the Korean Society of Radiology
• /
• v.83 no.2
• /
• pp.344-359
• /
• 2022

Purpose To develop a denoising convolutional neural network-based image processing technique and investigate its efficacy in diagnosing breast cancer using low-dose mammography imaging. Materials and Methods A total of 6 breast radiologists were included in this prospective study. All radiologists independently evaluated low-dose images for lesion detection and rated them for diagnostic quality using a qualitative scale. After application of the denoising network, the same radiologists evaluated lesion detectability and image quality. For clinical application, a consensus on lesion type and localization on preoperative mammographic examinations of breast cancer patients was reached after discussion. Thereafter, coded low-dose, reconstructed full-dose, and full-dose images were presented and assessed in a random order. Results Lesions on 40% reconstructed full-dose images were better perceived when compared with low-dose images of mastectomy specimens as a reference. In clinical application, as compared to 40% reconstructed images, higher values were given on full-dose images for resolution (p < 0.001); diagnostic quality for calcifications (p < 0.001); and for masses, asymmetry, or architectural distortion (p = 0.037). The 40% reconstructed images showed comparable values to 100% full-dose images for overall quality (p = 0.547), lesion visibility (p = 0.120), and contrast (p = 0.083), without significant differences. Conclusion Effective denoising and image reconstruction processing techniques can enable breast cancer diagnosis with substantial radiation dose reduction.

• Korean Journal of Environmental Biology
• /
• v.41 no.4
• /
• pp.482-496
• /
• 2023

Many changes in the scale and structure of the Korean rice cropping system have been made over the past few decades. Still, insufficient research has been conducted on the sustainability of this system. This study analyzed changes in the Korean rice cropping system's sustainability from a system ecology perspective using an emergy approach. For this purpose, an emergy table was created for the Korean rice cropping system in 2011, 2016, and 202, and an emergy-based indicator analysis was performed. The emergy analysis showed that the total emergy input to the rice cropping system decreased from 10,744E+18 sej year^-1 to 8,342E+18 sej year^-1 due to decreases in paddy field areas from 2011 to 2021, and the proportion of renewable resources decreased by 1.4%. The emergy input per area (ha) was found to have decreased from 13.13E+15 sej ha^-1 year^-1 in 2011 to 11.89E+15 sej ha^-1 year^-1 in 2021, and the leading cause was a decrease in nitrogen fertilizer usage and working hours. The amount of emergy used to grow 1 g of rice stayed the same between 2016 and 2021 (specific emergy: 13.3E+09 sej g^-1), but the sustainability of the rice cropping system (emergy sustainability index, ESI) continued to decrease (2011: 0.107, 2016: 0.088, and 2021: 0.086). This study provides quantitative information on the emergy input structure and characteristics of Korean rice cropping systems. The results of this study can be used as a valuable reference in establishing measures to improve the ecological sustainability of the Korean rice cropping system.