• Korean Journal of Clinical Pharmacy
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• v.29 no.1
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• pp.56-60
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• 2019

Oseltamivir is an antiviral medication prescribed to prevent and treat influenza A and B. A case from a community pharmacy in Korea was reported for an adverse event associated with oseltamivir administration. A 20-month-old boy had psychiatric symptoms after receiving 2 doses of oseltamivir. Therefore, an evaluation of whether the psychiatric symptoms were caused by oseltamivir was required. To determine whether the adverse event resulted from the administrated medication or other factors, three tools were used: the Naranjo scale, the Korean causality assessment algorithm (Ver.2), and the World Health Organization-Uppsala Monitoring Center (WHO-UMC) criteria. The psychiatric symptoms occurred after oseltamivir administration, and were attenuated after oseltamivir termination. A possible cause of the psychiatric symptoms is high fever, but information on the body temperature of the patient was not sufficient. Therefore, it was unclear whether there were other nonpharmacological causes of adverse drug reaction. For these reasons, in terms of causality, the results evaluated by the three tools represented, "possible", "probable", and "probable/likely", respectively.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.4
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• pp.373-379
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• 2019

In this study, image-based flock monitoring and density evaluation were conducted for broiler chicks welfare. Image data were captured by using a mono camera and region of broiler chicks in the image was detected using converting to HSV color model, thresholding, and clustering with filtering. The results show that region detection was performed with 5% relative error and 0.81 IoU on average. The detected region was corrected to the actual region by projection into ground using coordinate transformation between camera and real-world. The flock density of broiler chicks was estimated using the corrected actual region, and it was observed with an average of 80%. The developed algorithm can be applied to the broiler chicks house through enhancing accuracy of region detection and low-cost system configuration.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.2
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• pp.79-85
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• 2019

The mission tasks of polar exploration utilizing unmanned systems such as glacier monitoring, ecosystem research, and inland exploration have been expanded. To facilitate unmanned exploration mission tasks, precise and robust navigation systems are required. However, limitations on the utilization of satellite navigation system are present due to satellite orbital characteristics at the polar region located in a high latitude. The orbital inclination of global positioning system (GPS), which was developed to be utilized in mid-latitude sites, was designed at $55^{\circ}$. This means that as the user is located in higher latitudes, the satellite visibility and vertical precision become worse. In addition, the use of satellite-based wide-area augmentation system (SBAS) is also limited in higher latitude regions than the maximum latitude of signal reception by stationary satellites, which is $70^{\circ}$. This study proposes a local-area augmentation system that additionally utilizes Global Navigation Satellite System (GLONASS) considering satellite navigation system environment in Polar Regions. The orbital inclination of GLONASS is $64.8^{\circ}$, which is suitable in order to ensure satellite visibility in high-latitude regions. In contrast, GLONASS has different system operation elements such as configuration elements of navigation message and update cycle and has a statistically different signal error level around 4 m, which is larger than that of GPS. Thus, such system characteristics must be taken into consideration to ensure data integrity and monitor GLONASS signal fault. This study took GLONASS system characteristics and performance into consideration to improve previously developed fault detection algorithm in the local-area augmentation system based on GPS. In addition, real GNSS observation data were acquired from the receivers installed at the Antarctic King Sejong Station to analyze positioning accuracy and calculate test statistics of the fault monitors. Finally, this study analyzed the satellite visibility of GPS/GLONASS-based local-area augmentation system in Polar Regions and conducted performance evaluations through simulations.

• Geophysics and Geophysical Exploration
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• v.22 no.2
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• pp.72-79
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• 2019

Underwater object detection method adopting electrical resistivity technique was proposed recently, and the need of advanced data processing algorithm development counteracting various marine environmental conditions was required. In this paper, we present an improved water tank experiment system and its operation results, which can provide efficient test and verification. The main features of the system are as follows: 1) All the processes enabling real time process for not only simultaneous gathering of object images but also the electrical field measurement and visualization are carried out at 5 Hz refresh rates. 2) Data acquisition and processing for two detection lines are performed in real time to distinguish the moving direction of a target object. 3) Playback and retest functions for the saved data are equipped. 4) Through the monitoring screen, the movement of the target object and the measurement status of two detection lines can be intuitively identified. We confirmed that the enhanced physical modeling system works properly and facilitates efficient experiments.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.4
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• pp.93-102
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• 2019

As interest in wellness grows, There is a lot of research about monitoring individual health using wearable devices. Accordingly, a variety of methods have been studied to distinguish exercise from daily activities using wearable devices. Most of these existing studies are machine learning methods. However, there are problems with over-fitting on individual person's learning, data discontinuously recognition by independent segmenting and fake activity. This paper suggests a detection method for exercise activity based on the physiological response principle of heart rate up and down during exercise. This proposed method calculates activity intensity and heart rate from triaxial and photoplethysmography sensor to determine a heart rate recovery, then detects exercise by estimating activity intensity or detecting a heart rate rising state. Experimental results show that our proposed algorithm has 98.64% of averaged accuracy, 98.05% of averaged precision and 98.62% of averaged recall.

• Phonetics and Speech Sciences
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• v.13 no.1
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• pp.73-79
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• 2021

This study investigated the change in lip movement during speech according to aging. For the study, 15 elderly women with an average of 69 years and 15 young women with an average of 22 years were selected. To measure the movement of the lips, the ratio between the minimum point and the maximum point of movement when pronouncing a double vowel was analyzed in pixel units using image analysis software. For clinical utility, the software was produced by applying an automated algorithm and compared with the results of handwork. This study found that the range of the width and length of lips in double vowel tasks was smaller for the elderly than that of the young. A strong positive correlation was found between manual and automated methods, indicating that both methods are useful for extracting lip contours. Based on the above results, it was found that the range of the lips decreased when ignited as aging progressed. Therefore, monitoring the condition of lip performance by simply measuring the movement of lips before aging progresses, and performing exercises to maintain lip range, will prevent pronunciation problems caused by aging.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.1058-1063
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• 2020

This paper presents a new insulation resistance calculation technique to prevent electric shock and fire accidents due to the dielectric breakdown in the primary insulation section of the IT ground system. The solar power generation market is growing rapidly due to the recent expansion of renewable energy and energy storage systems, but as the insulation is destroyed and fire accidents frequently occur, a device for monitoring the insulation resistance state is indispensable to the IT grounding method. Compared to the conventional algorithm that use a method of multiplying a time constant to a fixed coefficient, the proposed insulation resistance calculation method has a fast response time and high accuracy over a wide insulation resistance range by applying a different coefficient according to the values of the insulation impedance. The proposed dynamic time constant based insulation resistance calculation technique reduces the response time by up to 39.29 seconds and improves the error rate by 20.11%, compared to the conventional method.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.615-625
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• 2021

The coastal areas around Palau Island and Tonga Island, near the Pacific equator, consist of coral reefs, mangrove and seaweed. In particular, understanding the optical properties of sea surface water in coral reef habitats helps improve the accuracy of remote sensing based habitat mapping and identify tropical ecosystem characteristics. Here, we collected spectral characteristics of sea surface water of Palau Island and Tonga Island and analyzed the concentration of suspended matters, absorption coefficient, and remote sensing reflectance to understand the seawater characteristics of the coral reef habitats. Based on the results of the suspended matter concentration analysis, we developed and verified an empirical algorithm to derive the concentration from satellite data using remote sensing reflectance of three bands, 555, 625, 660 nm, showed a high determinant coefficient, 0.98. In conclusion, coral reef habitats in tropical regions are characterized by CASE-I water in terms of the marine optics with oligotrophic properties, and require monitoring using continuous collection and analysis of field data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.8-19
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• 2021

The air pollution problem caused by industrialization in recent years is attracting great attention to both the country and the people. Domestic wide-area air pollution information is provided to the public through public data nationally, but regional air pollution information with different environmental variables is very insufficient. Therefore, in this study, we design and implement an air pollution analysis and prediction system based on regional environmental variables that can more accurately analyze and predict regional air pollution phenomena. In particular, the proposed system accurately analyzes and provides regional atmospheric information based on environmental data measured locally and public big data, and predicts and presents future regional atmospheric information using artificial intelligence algorithms. Furthermore, through the proposed system, it is expected that local air pollution can be prevented by accurately identifying the cause of regional air pollution.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.21-28
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• 2021

In this study, we propose a deep learning-based NILM technique using actual measured power data for 5 kinds of home appliances and verify its effectiveness. For about 3 weeks, the active power of the central power measuring device and five kinds of home appliances (refrigerator, induction, TV, washing machine, air cleaner) was individually measured. The preprocessing method of the measured data was introduced, and characteristics of each household appliance were analyzed through spectogram analysis. The characteristics of each household appliance are organized into a learning data set. All the power data measured by the central power measuring device and 5 kinds of home appliances were time-series mapping, and training was performed using a LSTM neural network, which is excellent for time series data prediction. An algorithm that can disaggregate five types of energies using only the power data of the main central power measuring device is proposed.