• The Korea Journal of Herbology
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• v.28 no.6
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• pp.47-51
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• 2013

Objectives : The Illicii Veri Fructus was not only traditional medicine but also food in Asia. The aim of this study was selection of optimum solvent in the fruit of Illicii Veri Fructus because an appropriate solvent affect a medicinal effect. Methods : Illicii Veri Fructus was carried out ultrasonic-assisted extraction as various solvents. Two main compounds, p-anisaldehyde and anethole, were successfully analyzed by high performance liquid chromatography-photodiode array detector (HPLC-PDA) and carried out method validation according to ICH guideline. The optimum solvent selected by comparing with yields of two main ingredients. Results : The p-anisaldehyde and anethole were detected at approximately 8.0 min and 19.8 min, respectively. It was all below 5.0% that RSD of retention time and peak area for two main peaks. Calibration curves of two compounds were good linearity as $R^2$ >0.9999. All of the precisions and accuracy were good intra-day and inter-day as below 5.0% RSD. Limited of detection (LOD) of p-anisaldehyde and anethole were analyzed as $0.134{\mu}g/mL$ and $4.286{\mu}g$, respectively. Limited of quantification (LOQ) of two compounds were $0.407{\mu}g$ and $12.989{\mu}g$, respectively. As a result of this study, p-anisladehyde was detected as 0.209 ~ 0.467%, however anethole was not detected in the distilled water. Conclusions : Anethole was main component as 5.329 ~ 6.815% except for water extraction. Methanol extraction among various solvents was detected the highest contents of p-anisaldehyde and anethole as 0.467(${\pm}0.008$)% and 6.815(${\pm}0.220$)%, respectively.

• 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%.

• Journal of Veterinary Science
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• v.23 no.5
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• pp.74.1-74.16
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• 2022

Background: Previous studies have presented evidence to support the significant association between red meat intake and colon cancer, suggesting that heme iron plays a key role in colon carcinogenesis. Epigallocatechin-3-gallate (EGCG), the major constituent of green tea, exhibits anti-oxidative and anti-cancer effects. However, the effect of EGCG on red meat-associated colon carcinogenesis is not well understood. Objectives: We aimed to investigate the regulatory effects of hemin and EGCG on colon carcinogenesis and the underlying mechanism of action. Methods: Hemin and EGCG were treated in Caco2 cells to perform the water-soluble tetrazolium salt-1 assay, lactate dehydrogenase release assay, reactive oxygen species (ROS) detection assay, real-time quantitative polymerase chain reaction and western blot. We investigated the regulatory effects of hemin and EGCG on an azoxymethane (AOM) and dextran sodium sulfate (DSS)-induced colon carcinogenesis mouse model. Results: In Caco2 cells, hemin increased cell proliferation and the expression of cell cycle regulatory proteins, and ROS levels. EGCG suppressed hemin-induced cell proliferation and cell cycle regulatory protein expression as well as mitochondrial ROS accumulation. Hemin increased nuclear factor erythroid-2-related factor 2 (Nrf2) expression, but decreased Keap1 expression. EGCG enhanced hemin-induced Nrf2 and antioxidant gene expression. Nrf2 inhibitor reversed EGCG reduced cell proliferation and cell cycle regulatory protein expression. In AOM/DSS mice, hemin treatment induced hyperplastic changes in colon tissues, inhibited by EGCG supplementation. EGCG reduced the hemin-induced numbers of total aberrant crypts and malondialdehyde concentration in the AOM/DSS model. Conclusions: We demonstrated that EGCG reduced hemin-induced proliferation and colon carcinogenesis through Nrf2-inhibited mitochondrial ROS accumulation.

• Journal of fish pathology
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• v.35 no.1
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• pp.93-102
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• 2022

This study performed a trichlorfon (TCF) residue and pharmacokinetic analysis with Japanese eels, Anguilla japonica, to obtain baseline data to establish the maximum residue level (MRL) of TCF in A. japonica. After dipping A. japonica in 30 ppm and 150 ppm of TCF at 28℃ and 18℃, drug residue in the body was analyzed with LC-MS/MS, and these results were further analyzed with the PK solver program to obtain the pharmacokinetic parameters of TCF in the serum, muscles, and liver. The maximum concentrations (C_max) in the serum, muscles, and liver were 25.87-357.42, 129.91-1043.73, and 40.47-375.20, respectively, and the time to maximum concentration (T_max) was 0.13-1.32h, 1.17-3.34h, and 0.14-5.40h, respectively. The terminal elimination half-life (T_1/2) was 2.13-3.92h, 5.30-10.35h, and 0.65-13.81h, respectively. In the 30 mg/L concentration group, TCF was not detected in the serum of eels 96 hours after bathing, and was below the detection limit after 336 hours in muscle and liver. On the other hand, in the 150 mg/L concentration group, TCF was not detected in the serum of eels 336 hours after bathing, but was detected in muscle and liver at 336 hours. In conclusion, the results of this study would be useful in establishing the MRL of TCF in farmed A. japonica.

• The Journal of the Acoustical Society of Korea
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• v.42 no.1
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• pp.25-31
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• 2023

In order to estimate the radial speed of an underwater object so-called target with active sonar, Continuous Wave (CW) pulse is generally used, but if a target is slow and at near distance, it is not easy to estimate the radial velocity of the target due to acoustic reverberation in the ocean. In 2017, Wang et al. utilized broadband signal of two Hyperbolic Frequency Modulation (HFM) pulses, which is known as a doppler-invariant pulse, with equal frequency band and in opposite sweep directions to overcome this problem and successfully estimate the radial speed of slow-moving nearby target. They demonstrated the estimation of the radial velocity with computer simulation using the parameters of two HFM starting time differences and receiving times. However, for it uses two HFM pulses with equal frequency, cross-correlation between the two pulses negatively affect the detection performance. To mitigate this cross-correlation effect, we suggest using two different band HFM with the opposite sweep directions. In this paper, a method of radial velocity estimation is derived and simulated using two HFM pulses with the pulse length of 1 second and bandwidth of 400 Hz. Applying the suggested method, the radial velocity was estimated with approximately 6 % of relative error in the simulation.

• Journal of Service Research and Studies
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• v.12 no.2
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• pp.23-37
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• 2022

Based on the service scenario proposed by the existing Kim Tae-wan (2018) who can safely evacuate inmates with the help of a mobile application linked to a fire detection system in the event of a fire, the final purpose of this study is to develop the scenario by incorporating more realistic scenarios with mobile stimuli that can help them escape or act through the Delph In addition, to make the scenarios produced more realistic considering the structure and copper lines of a typical building, expert scenario verification and Delphi technique were applied to exclude unnecessary or impractical aspects of the existing scenarios. The results of the second Delphi survey showed that the primary psychology that could be seen at the time of the fire alarm were doubts, safety concerns and alarm, and the results of the second Delphi survey were analyzed, and the satisfaction of the content adequacy (CVR), convergence, and consensus was derived. Finally, this was applied to create a scenario in which a mobile application was assisted to evacuate the fire response phase. This study will allow the use of methods to increase the evacuation rate of those who are in the event of a fire.

• The Korean Journal of Food And Nutrition
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• v.36 no.2
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• pp.93-102
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• 2023

Centella asiatica (C. asiatica) has been widely used in food, cosmetics, and pharmaceutical industry as a functional material. In a previous study, we have investigated not only pharmacological effects such as antioxidative and anti-inflammatory effects, but also analyzed various functional ingredients. In this study, triterpenoids were analyzed using HPLC-DAD to determine marker compounds among functional ingredients. When triterpenoids were analyzed, asiaticoside from C. asiatica was determined as an optimal marker compound. Next, specificity, linearity, limited of detection (LOD), limited of quantification (LOQ), precision, accuracy, and range were evaluated using HPLC-DAD to determine asiaticoside contents in C. asiatica juice and extracts. The specificity was elucidated by chromatogram and retention time using an established analytical method. The coefficient of correlation obtained was 0.9996. LOD was 4.99 ㎍/mL and LOQ was 15.12 ㎍/mL. Intra- and inter-day precision of asiaticoside were determined to be 0.48~1.68% and 0.08~1.09%, respectively. Furthermore, the recovery rate of asiaticoside was 98.88% and the analytical range of Field-70E was determined to be 0.625~10 mg/mL. As a results of evaluating ABTS, DPPH, and FRAP antioxidative effect, Field-70E showed potent antioxidant activities. Results of this study could be used as basic data for quality standardization of C. astiatica juice and extracts.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.107-119
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• 2023

The technology that recognizes a soldier's motion and movement status has recently attracted large attention as a combination of wearable technology and artificial intelligence, which is expected to upend the paradigm of troop management. The accuracy of state determination should be maintained at a high-end level to make sure of the expected vital functions both in a training situation; an evaluation and solution provision for each individual's motion, and in a combat situation; overall enhancement in managing troops. However, when input data is given as a timer series or sequence, existing feedforward networks would show overt limitations in maximizing classification performance. Since human behavior data (3-axis accelerations and 3-axis angular velocities) handled for military motion recognition requires the process of analyzing its time-dependent characteristics, this study proposes a high-performance data-driven classifier which utilizes the long-short term memory to identify the order dependence of acquired data, learning to classify eight representative military operations (Sitting, Standing, Walking, Running, Ascending, Descending, Low Crawl, and High Crawl). Since the accuracy is highly dependent on a network's learning conditions and variables, manual adjustment may neither be cost-effective nor guarantee optimal results during learning. Therefore, in this study, we optimized hyperparameters using Bayesian optimization for maximized generalization performance. As a result, the final architecture could reduce the error rate by 62.56% compared to the existing network with a similar number of learnable parameters, with the final accuracy of 98.39% for various military operations.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.99-110
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• 2023

This study proposed a classification of malicious network traffic using the cyber threat framework(Mitre ATT&CK) and machine learning to solve the real-time traffic detection problems faced by current security monitoring systems. We applied a network traffic dataset called UNSW-NB15 to the Mitre ATT&CK framework to transform the label and generate the final dataset through rare class processing. After learning several boosting-based ensemble models using the generated final dataset, we demonstrated how these ensemble models classify network traffic using various performance metrics. Based on the F-1 score, we showed that XGBoost with no rare class processing is the best in the multi-class traffic environment. We recognized that machine learning ensemble models through Mitre ATT&CK label conversion and oversampling processing have differences over existing studies, but have limitations due to (1) the inability to match perfectly when converting between existing datasets and Mitre ATT&CK labels and (2) the presence of excessive sparse classes. Nevertheless, Catboost with B-SMOTE achieved the classification accuracy of 0.9526, which is expected to be able to automatically detect normal/abnormal network traffic.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.85-96
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• 2023

This study developed and evaluated a safe route guidance service for electric personal assistive mobility device used mainly by the mobility impaired people to improve their mobility. Thirteen underlying factors affecting the mobility of electric personal assistive mobility device have been derived through a survey with the mobility impaired people and employees in related organizations in Busan Metropolitan City. After assigning safety scores to individual factors and identifying the relevant factors along routes of interest with an object detection AI model, the safe route for electric personal assistive mobility device was provided through an optimal path-finding algorithm. As a result of comparing the general route of T-map and the recommended route of this study for the identical routes, the latter had relatively fewer obstacles and the gentler slope than the former, implicating that the recommended route is safer than the general one. As future works, it is necessary to enhance the function of a route guidance service based on the real-time location of users and to conduct spot investigations to evaluate and verify its social acceptability.