• Korean Journal of Remote Sensing
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• v.35 no.3
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• pp.457-470
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• 2019

Automatic Target Recognition (ATR) using Synthetic Aperture Radar (SAR) has been attracted attention in the fields of surveillance, reconnaissance, and national security due to its advantage of all-weather and day-and-night imaging capabilities. However, there have been some difficulties in automatically identifying targets in real situation due to various observational and environmental conditions. In this paper, ATR problems in Extended Operating Conditions (EOC) were investigated. In particular, we considered partial occlusions of the target (10% to 50%) and differences in the depression angle between training ($17^{\circ}$) and test data ($30^{\circ}$ and $45^{\circ}$). To simulate various occlusion conditions, SARBake algorithm was applied to Moving and Stationary Target Acquisition and Recognition (MSTAR) images. The ATR accuracies were evaluated by using the template matching and Adaboost algorithms. Experimental results on the depression angle showed that the target identification rate of the two algorithms decreased by more than 30% from the depression angle of $45^{\circ}$ to $30^{\circ}$. The accuracy of template matching was about 75.88% while Adaboost showed better results with an accuracy of about 86.80%. In the case of partial occlusion, the accuracy of template matching decreased significantly even in the slight occlusion (from 95.77% under no occlusion to 52.69% under 10% occlusion). The Adaboost algorithm showed better performance with an accuracy of 85.16% in no occlusion condition and 68.48% in 10% occlusion condition. Even in the 50% occlusion condition, the Adaboost provided an accuracy of 52.48%, which was much higher than the template matching (less than 30% under 50% occlusion).

• Science of Emotion and Sensibility
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• v.23 no.4
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• pp.105-116
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• 2020

The purpose of this study is to progress the limitations and disadvantages of existing safety clothing by applying high technology to current safety clothing that is produced and distributed only with fluorescent fabrics and retroreflective materials. Therefore, the industrial suspender-type safety belt and engineering technology are introduced, designed, and fabricated to help save a life in an emergency. First, the suspender-type safety belt to be developed is designed to emit light by LED attached to the film, and the body of the belt-wearer is recognized from a distance through retroreflection from the flashing LED. It aims to support people's safety by preventing accidents during roadside work, rescue activities, and sports activities at night. Second, with the development of advanced devices when the user is in an unconscious state due to distress or falls into an unconscious state due to distress or accident, the tilt sensor of the control unit attached to the belt automatically detects the angle of the human body and generates light and sound. It is intended to further enhance the utilization by mounting a sensing and signaling device that generates a distress signal and shaping it in the form of a belt attached to a vest that can be easily detached from the outside of the garment. When the wearer falls due to an accident, the tilt sensor of this belt detects the angle change and then the controller generates a high-frequency sound and repeated LED blinking signals at the same time. In the case of conventional safety vests, it is almost impossible to detect that the person is wearing a vest when there is no ambient light, but in case of the safety belts in this study, the sound and light signals of the safety belt enable us to find the wearer within 100 meters even when there is no ambient light.

• Economic and Environmental Geology
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• v.54 no.2
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• pp.233-245
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• 2021

Many studies on the microstructures in rocks have been conducted using experimental methods with various equipment as well as natural rock studies to see the development of microstructures and understand their mechanisms. Grain boundary migration of mineral aggregates in rocks could cause grain growth or grain size changes during metamorphism or deformation as one of the main recrystallization mechanisms. This study suggests improved ways regarding the analog material experiments with reformed equipment to see sequential observations of these grain boundary migration. It can be more efficient than the existing techniques and carry out an appropriate microstructure analysis. This reformed equipment was implemented to enable optical manipulation by mounting polarizing plates capable of rotating operation on a stereoscopic microscope and a deformation rig capable of experimenting with analog materials. The equipment can automatically control the temperature and strain rate of the deformation rig by microcontrollers and programming and can take digital photomicrographs with constant time intervals during the experiment to observe any microstructure changes. The composite images synthesized using images by rotated polarizing plates enable us to see more accurate grain boundaries. As a rock analog material, norcamphor(C7H10O) was used, which has similar birefringence to quartz. Static grain growth and simple shear deformation experiments were performed using the norcamphor to verify the effectiveness of the equipment. The static grain growth experiments showed the characteristics of typical grain growth behavior. The number of grains decreases and the average grain size increases over time. These case experiments also showed a clear difference between the growth curves with three temperature conditions. The result of the simple shear deformation experiment under the medium temperature-low strain rate showed no significant change in the average grain size but presented the increased elongation of grain shapes in the direction of about 53° regarding the direction perpendicular to the shearing direction as the shear strain increases over time. These microstructures are interpreted as both the plastic deformation and the internal recovery process in grains are balanced by the deformation under the given experimental conditions. These experiments using the reformed equipment represent the ability to sequentially observe changing the microstructure during experiments as desired in the tests with the analog material during the entire process.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.17-32
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• 2021

Speaker recognition is generally divided into speaker identification and speaker verification. Speaker recognition plays an important function in the automatic voice system, and the importance of speaker recognition technology is becoming more prominent as the recent development of portable devices, voice technology, and audio content fields continue to expand. Previous speaker recognition studies have been conducted with the goal of automatically determining who the speaker is based on voice files and improving accuracy. Speech is an important sociolinguistic subject, and it contains very useful information that reveals the speaker's attitude, conversation intention, and personality, and this can be an important clue to speaker recognition. The final ending used in the speaker's speech determines the type of sentence or has functions and information such as the speaker's intention, psychological attitude, or relationship to the listener. The use of the terminating ending has various probabilities depending on the characteristics of the speaker, so the type and distribution of the terminating ending of a specific unidentified speaker will be helpful in recognizing the speaker. However, there have been few studies that considered speech in the existing text-based speaker recognition, and if speech information is added to the speech signal-based speaker recognition technique, the accuracy of speaker recognition can be further improved. Hence, the purpose of this paper is to propose a novel method using speech style expressed as a sentence-final ending to improve the accuracy of Korean speaker recognition. To this end, a method called sentence sequencing that generates vector values by using the type and frequency of the sentence-final ending appearing in the utterance of a specific person is proposed. To evaluate the performance of the proposed method, learning and performance evaluation were conducted with a actual drama script. The method proposed in this study can be used as a means to improve the performance of Korean speech recognition service.

• Journal of agriculture & life science
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• v.53 no.6
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• pp.23-33
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• 2019

In accordance with a change in the management information system containing the management record and planning for the entire national forest in South Korea by an amendment of the relevant law (The national forest management planning and methods, Korea Forest Service), in this study, average, the maximum, and the minimum values for DBH were presented while only average values were required before the amendment. In this regard, there is a need for an estimation algorithm by which all the existing values for DBH established before the revision can be converted to the highest and the lowest ones. The purpose of this study is to develop an estimation equation to automatically show the minimum and the maximum values for DBH for 12 main tree species from the data in the national forest management information system. In order to develop the estimation equation for the minimum and the maximum values for DBH, there was exploited the 6,858 fixed sample plots of the fifth and the sixth national forest inventory between in 2006 and 2015. Two estimation models were applied for DBH-tree age and DHB-tree height using such growth variables as DBH, tree age, and height, to draw the estimation equation for the maximum and the minimum values for DBH. The findings showed that the most suitable model to estimate the minimum and the maximum values for DBH was Dmin=a+bD+cH, Dmax=a+bD+cH with the variables of DBH and height. Based on these optimal models, the estimation equation was devised for the minimum and the maximum values for DBH for the 12 main tree species.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.679-687
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• 2021

The purpose of the present study was to document the standardization and management process of interface terminology regarding the chief complaints, diagnoses, and procedures, including surgery in a four-hospital consortium. The process was proposed, discussed, modified, and finalized in 2016 by the Terminology Standardization Committee (TSC), consisting of personnel from four hospitals. A request regarding interface terminology was classified into one of four categories: 1) registration of a new term, 2) revision, 3) deleting an old term and registering a new term, and 4) deletion. A request was processed in the following order: 1) collecting testimonies from related departments and 2) voting by the TSC. At least five out of the seven possible members of the voting pool need to approve of it. Mapping to the reference terminology was performed by three independent medical information managers. All processes were performed online, and the voting and mapping results were collected automatically. This process made the decision-making process clear and fast. In addition, this made users receptive to the decision of the TSC. In the 16 months after the process was adopted, there were 126 new terms registered, 131 revisions, 40 deletions of an old term and the registration of a new term, and 1235 deletions.

• Ecology and Resilient Infrastructure
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• v.8 no.1
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• pp.32-43
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• 2021

Multichannel automated chamber systems (MCACs) were developed for the continuous monitoring of soil CO2 efflux in forest ecosystems. The MCACs mainly consisted of four modules: eight soil chambers with lids that automatically open and close, an infrared CO2 analyzer equipped with eight multichannel gas samplers, an electronic controller with time-relay circuits, and a programmable logic datalogger. To examine the stability and reliability of the developed MCACs in the field during all seasons with a high temporal resolution, as well as the effects of temperature and soil water content on soil CO2 efflux rates, we continuously measured the soil CO2 efflux rates and micrometeorological factors at the Nam-san experimental site in a Quercus mongolica forest floor using the MCACs from January to December 2010. The diurnal and seasonal variations in soil CO2 efflux rates markedly followed the patterns of changes in temperature factors. During the entire experimental period, the soil CO2 efflux rates were strongly correlated with the temperature at a soil depth of 5 cm (r2 = 0.92) but were weakly correlated with the soil water content (r2 = 0.27). The annual sensitivity of soil CO2 efflux to temperature (Q10) in this forest ranged from 2.23 to 3.0, which was in agreement with other studies on temperate deciduous forests. The annual mean soil CO2 efflux measured by the MCACs was approximately 11.1 g CO2 m-2 day-1. These results indicate that the MCACs can be used for the continuous long-term measurements of soil CO2 efflux in the field and for simultaneously determining the impacts of micrometeorological factors.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1445-1462
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• 2022

Compact Advanced Satellite 500-4 (CAS500-4), which is scheduled to be launched in 2025, is a mid-resolution satellite with a 5 m resolution developed for wide-area agriculture and forest observation. To utilize satellite images, it is important to establish a precision sensor model and establish accurate geometric information. Previous research reported that a precision sensor model could be automatically established through the process of matching ground control point (GCP) chips and satellite images. Therefore, to improve the geometric accuracy of satellite images, it is necessary to improve the GCP chip matching performance. This paper proposes an improved GCP chip matching scheme for improved precision sensor modeling of mid-resolution satellite images. When using high-resolution GCP chips for matching against mid-resolution satellite images, there are two major issues: handling the resolution difference between GCP chips and satellite images and finding the optimal quantity of GCP chips. To solve these issues, this study compared and analyzed chip matching performances according to various satellite image upsampling factors and various number of chips. RapidEye images with a resolution of 5m were used as mid-resolution satellite images. GCP chips were prepared from aerial orthographic images with a resolution of 0.25 m and satellite orthogonal images with a resolution of 0.5 m. Accuracy analysis was performed using manually extracted reference points. Experiment results show that upsampling factor of two and three significantly improved sensor model accuracy. They also show that the accuracy was maintained with reduced number of GCP chips of around 100. The results of the study confirmed the possibility of applying high-resolution GCP chips for automated precision sensor modeling of mid-resolution satellite images with improved accuracy. It is expected that the results of this study can be used to establish a precise sensor model for CAS500-4.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.925-938
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• 2022

Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.

• Korean Chemical Engineering Research
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• v.60 no.3
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• pp.347-355
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• 2022

The safety valve (PSV) is a safety device that automatically releases a spring when the pressure generated by various causes reaches the set pressure, and is restored to a normal state when the pressure falls below a certain level. Periodic inspection and monitoring of safety valves are essential so that they can operate normally in abnormal conditions such as pressure rise. However, as the current safety inspection is performed only at a set period, it is difficult to ensure the safety of normal operation. Therefore, evaluation items were developed by finding failure modes and causative factors of safety valves required for safety management. In addition, it is intended to provide decision-making information for securing safety by deriving the priority of items. To this end, a Delphi survey was conducted three times to derive evaluation factors that were judged to be important in relation to the Failure Mode Cause Factor (FMCFs) of the safety valve (PSV) targeting 15 experts. As a result, 6 failure modes of the safety valve and 22 evaluation factors of its sub-factors were selected. In order to analyze the priorities of the evaluation factors selected in this way, the hierarchical structure was schematized, and the hierarchical decision-making method (AHP) was applied to the priority calculation. As a result of the analysis, the failure mode priorities of FMCFs were 'Leakage' (0.226), 'Fail to open' (0.201), 'Fail to relieve req'd capacity' (0.152), 'Open above set pressure' (0.149), 'Spuriously' 'open' (0.146) and 'Stuck open' (0.127) were confirmed in the order. The lower priority of FMCFs is 'PSV component rupture' (0.109), 'Fail to PSV size calculation' (0.068), 'PSV Spring aging' (0.065), 'Erratic opening' (0.059), 'Damage caused by improper installation and handling' (0.058), 'Fail to spring' (0.053), etc. were checked in the order. It is expected that through efficient management of FMCFs that have been prioritized, it will be possible to identify vulnerabilities of safety valves and contribute to improving safety.