• The Journal of the Korea Contents Association
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• v.19 no.9
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• pp.262-270
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• 2019

This study aimed to develop designs for an early screening questionnaire for developmental disorders among children from multicultural families in the Republic of Korea, who are at an increased risk of developmental disorders due to cultural and language barriers. Research on early screening questionnaires for multicultural families is extremely scanty, unlike that on ordinary early detection tests designed for the same category of disorders. Worse still, there have been no attempts made at overcoming the limitations of language-based and intercultural communication that are endured by multicultural parents and social workers in the field. Given the challenges, this study confirmed through professional seminars the present status of early developmental disorder screening questionnaires and the necessity for developing specialized versions for multicultural children. Then the study identified the needs of the stakeholders by employing surveys and interviews, and obtained insights and core design elements. These preceding implementations led to the creation of an early developmental disorder screening questionnaire for multicultural families. The test kit incorporates the style of illustrations preferred by multicultural parents, as well as a system of language-specific interpretation services. Produced in a leaflet format, the questionnaire will be used at support centers for multicultural families and for disabled persons in each district for the practical purpose of early screening of developmental disorders among multicultural infants and preschool children.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.1-6
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• 2021

In the field of speech recognition, as the DNN is applied, the use of speech recognition is increasing, but the amount of calculation for parallel training needs to be larger than that of the conventional GMM, and if the amount of data is small, overfitting occurs. To solve this problem, we propose an efficient method for robust voice feature extraction and voice signal noise removal even when the amount of data is small. Speech feature extraction efficiently extracts speech energy by applying the difference in frame energy for speech and the zero-crossing ratio and level-crossing ratio that are affected by the speech signal. In addition, in order to remove noise, the noise of the speech signal is removed by removing the noise of the speech signal with an average predictive improved LMS filter with little loss of speech information while maintaining the intrinsic characteristics of speech in detection of the speech signal. The improved LMS filter uses a method of processing noise on the input speech signal by adjusting the active parameter threshold for the input signal. As a result of comparing the method proposed in this paper with the conventional frame energy method, it was confirmed that the error rate at the start point of speech is 7% and the error rate at the end point is improved by 11%.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.277-283
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• 2021

Traffic data by vehicle classification are important data used as basic data in various fields such as road and traffic design. Traffic data is collected through permanent and temporary surveys and is provided as an annual average daily traffic (AATD) in the statistical yearbook of road traffic. permanent surveys are collected through traffic collection equipment (AVC), and the AVC consists of a loop sensor that detects traffic volume and a piezo sensor that detects the number of axes. Due to the nature of the buried type of traffic collection equipment, missing data is generated due to failure of detection equipment. In the existing method, it is corrected through historical data and the trend of traffic around the point. However, this method has a disadvantage in that it does not reflect temporal and spatial characteristics and that the existing data used for correction may also be a correction value. In this study, we proposed a method to correct the missing traffic volume by calculating the axis correction coefficient through the accumulated number of axes acquired by using a piezo sensor that can detect the axis of the vehicle. This has the advantage of being able to reflect temporal and spatial characteristics, which are the limitations of the existing methods, and as a result of comparative evaluation, the error rate was derived lower than that of the existing methods. The traffic volume correction system using axis count is judged as a correction method applicable to the field system with a simple algorithm.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.429-435
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• 2021

In intracavitary radiotherapy, incorrect location of the source can cause excessive dose to normal tissue, so it is essential to evaluate the location accuracy of the source. In this study, basic research was performed on digital line dosimeter based on lead (II) oxide (PbO) to improve analog verification method. Therefore, a polycrystalline PbO unit cell dosimeter was manufactured and the measurement performance for Ir-192 sources was evaluated. As a result, the reproducibility satisfies the evaluation criteria of 1.5% with a relative standard deviation of 0.85%. Linearity showed excellent results with a linear coefficient of R² of 0.9998. In the case of distance dependence evaluation, the power function R² showed 0.9855 for PbO and 0.9974 for diode, and the overall average difference was 1.66% for PbO and 2.18% for diode. This study presents the basic detection performance of the polycrystalline PbO dosimeter for the Ir-192 source and can provide basic data in the field of radiation measurement.

• CELLMED
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• v.11 no.3
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• pp.13.1-13.9
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• 2021

Background and Objective: Nux-vomica based traditional Unani formulation, Habb-e-Azaraqi (HAZ) is an important drug used by Unani physicians since several decades. It possesses Muqawwi-i-A'sab (nervine tonic), Muharrik-i-A'sab (nervine stimulant) properties and is an effective treatment option for diseases like Laqwa (facial palsy), Falij (paralysis), Niqris (gout) and Waja'al-Mafasil (arthritis) etc. The aim of the study is to access and provide information of HAZ for its TLC, HPTLC Fingerprinting defining its clear qualitative perspective and acute oral toxicity evaluation for its safety assessment which was not done earlier, thus contributing in the field of research. Materials and Methods: The chief ingredient, nux-vomica was detoxified as per method mentioned in Unani Pharmacopeia before its use in formulation. TLC and HPTLC was developed under four detection system i.e., UV 366nm, UV 254nm, exposure to iodine vapours and after derivatization with anisaldehyde sulphuric acid. Acute toxicity studies were performed as per OECD Guidelines 425 at a limit dose of 2000 mg/kg. Observations were done for signs of toxicity, body weight, and feed consumption at regular intervals followed by haematological and biochemistry evaluation. Results: The generated data proved the authenticity and established the TLC and HPTLC profile of the formulation. Acute toxicity revealed no significant differences in HAZ-treated animals with respect to body weight gain, feed consumption, haematology, clinical biochemistry evaluation. No significant gross pathological observation was noticed in necropsy. Conclusion: Data of the present study is substantial and scientific proof of HAZ in terms of standardization and toxicity study that can be utilize in future research activities.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.340-348
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• 2021

Continuous monitoring of RGB (Red, Green, Blue) vegetation indices is important to apply remote sensing technology for the estimation of crop growth. In this study, we evaluated the performance of eight vegetation indices derived from soybean RGB images with various agronomic parameters under drought stress condition. Drought stress influenced the behavior of various RGB vegetation indices related soybean canopy architecture and leaf color. In particular, reported vegetation indices such as ExGR (Excessive green index minus excess red index), Ipca (Principal Component Analysis Index), NGRDI (Normalized Green Red Difference Index), VARI (Visible Atmospherically Resistance Index), SAVI (Soil Adjusted Vegetation Index) were effective tools in obtaining canopy coverage and leaf chlorophyll content in soybean field. In addition, the RGB vegetation indices related to leaf color responded more sensitively to drought stress than those related to canopy coverage. The PLS-DA (Partial Squares-Discriminant Analysis) results showed that the separation of RGB vegetation indices was distinct by drought stress. The results, yet preliminary, display the potential of applying vegetation indices based on RGB images as a tool for monitoring crop environmental stress.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1357-1369
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• 2022

Cloud removal is an essential image processing step for any task requiring time-series optical images, such as vegetation monitoring and change detection. This paper presents a two-stage cloud removal method that combines conditional generative adversarial networks (cGANs) with regression-based calibration to construct a cloud-free time-series optical image set. In the first stage, the cGANs generate initial prediction results using quantitative relationships between optical and synthetic aperture radar images. In the second stage, the relationships between the predicted results and the actual values in non-cloud areas are first quantified via random forest-based regression modeling and then used to calibrate the cGAN-based prediction results. The potential of the proposed method was evaluated from a cloud removal experiment using Sentinel-2 and COSMO-SkyMed images in the rice field cultivation area of Gimje. The cGAN model could effectively predict the reflectance values in the cloud-contaminated rice fields where severe changes in physical surface conditions happened. Moreover, the regression-based calibration in the second stage could improve the prediction accuracy, compared with a regression-based cloud removal method using a supplementary image that is temporally distant from the target image. These experimental results indicate that the proposed method can be effectively applied to restore cloud-contaminated areas when cloud-free optical images are unavailable for environmental monitoring.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1527-1539
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• 2022

As coastal erosion of the east coast is accelerating, the need for scientific and quantitative coastal erosion monitoring technology for a wide area increases. The traditional method for observing changes in the coast was precision monitoring based on field surveys, but it can only be applied to a small area. The airborne bathymetric Light Detection And Ranging (LiDAR) system is a technology that enables economical surveying of coastal and seabed topography in a wide area. In particular, it has the advantage of constructing topographical data for the intertidal zone, which is a major area of interest for coastal erosion monitoring. In this study, time series analysis of coastal seabed topography acquired in Aug, 2021 and Mar. 2022 on the littoral cell GW36 in Gangwon was performed using the Seahawk Airborne Bathymetric LiDAR (ABL) system. We quantitatively monitored the topographical changes by measuring the baseline length, shoreline and Digital Terrain Model (DTM) changes. Through this, the effectiveness of the ABL surveying technique was confirmed in coastal erosion monitoring.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.1
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• pp.9-16
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• 2023

Robots are expected to expand their scope of application to the military field and take on important missions such as surveillance and enemy detection in the coming future warfare. Swarm robots can perform tasks that are difficult or time-consuming for a single robot to be performed more efficiently due to the advantage of having multiple robots. Swarm robots require mutual recognition and collaboration. So they send and receive vast amounts of data, making it increasingly difficult to verify SW. Hardware-in-the-loop simulation used to increase the reliability of mission verification enables SW verification of complex swarm robots, but the amount of verification data exchanged between the HILS device and the simulator increases exponentially according to the number of systems to be verified. So communication overload may occur. In this paper, we propose a digital twin-based communication optimization technique to solve the communication overload problem that occurs in mission verification of swarm robots. Under the proposed Digital Twin based Multi HILS Framework, Network DT can efficiently allocate network resources to each robot according to the mission scenario through the Network Controller algorithm, and can satisfy all sensor generation rates required by individual robots participating in the group. In addition, as a result of an experiment on packet loss rate, it was possible to reduce the packet loss rate from 15.7% to 0.2%.

• Korean Journal of Environment and Ecology
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• v.36 no.5
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• pp.535-549
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• 2022

Damage to forests, such as broken or falling trees, has increased due to the increased intensity and frequency of abnormal climate events, such as strong winds and heavy rains. However, it is difficult to respond to them in advance based on prediction since structural defects such as cavities and bumps inside trees are difficult to identify with a visual inspection. Non-invasive sonic tomography (SoT) is a method of estimating internal defects while minimizing physical damage to trees. Although SoT is effective in diagnosing internal defects, its accuracy varies depending on the species. Therefore, it is necessary to analyze the reliability of its measurement results before applying it in the field. In this study, we measured internal defects in wood by cross-applying destructive resistance micro drilling on old Pinus densifloraSiebold & Zucc. and Ginkgo bilobaL., which are representative tree species in Korea, to verify the reliability of SoT and compared the evaluation results. The t-test for the mean values of the defect measurement between the two groups showed no statistically significant difference in pine trees and some difference in ginkgo trees. Linear regression analysis results showed a positive correlation with an increase in defects in SoT images when the defects in the drill resistance graph increased in both species.