• Journal of Korea Trade
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• v.23 no.6
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• pp.66-92
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• 2019

Purpose - Foreign Exchange Rates (FER) have been one of the most significant factors for both Korean exporters and the economy of Korea. The purpose of this study is to evaluate whether exporters with a high level of Exchange Rate Elasticity of Sales (ERES) make the use of earnings management for Income Smoothing (IS). Design/methodology - Income smoothing was obtained using the methodology suggested by Leuz, Nanda and Wysocki (2003). Accruals-based Earnings Management (AEM) was estimated using Discretionary Accruals (DA) calculated by the operant Jones Model developed by Dechow, Sloan and Sweeney (1995). Real Earnings Management (REM) was obtained using the methodologies suggested by Roychowdhury (2006) and Cohen and Zarowin (2010). Data were 2,402 firm years of public listed companies on the KRX, which were not in the financial industry and had a settlement of accounts in December for the period from 2013 to 2017. Findings - Results of the evaluation are as follows. First, companies with higher levels of ERES have relatively lower levels of smoothing of reported income. This might be because a fluctuation in sales caused by an exchange rate fluctuation has a direct impact on the volatility of the reported income. Second, companies with high levels of both ERES and IS have a positive correlation with both AEM and REM. This might be because companies with high levels of IS engage in earnings management to smooth reported income. Specifically, it is possible to assume that for smoothing the reported income, not only AEM but also REM is practiced. Third, companies with high levels of ERES but low levels of IS have a negative correlation with both AEM and REM. This could be interpreted as companies exhibiting low levels of IS due to higher levels of ERES tend to control IS. In addition, such results were supported by firms relying highly on exporting, and are consequently sensitive to exchange rate fluctuation. Therefore, it may conclude that companies with high levels of ERES make the use of earnings management as a means of IS. Originality/value - This study can find its significance from the fact that it is the first study, empirically verifying that companies of Korea, where exportation is a large part, use both AEM and REM as a means for smoothing reported income upon facing exchange rate fluctuations. In addition, it is highly expected that the results of this study could be useful for participants of financial markets when making IS-related decisions.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.59-68
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• 2021

As artificial intelligence(AI) technologies, which have made rapid growth recently, began to be applied to the marine environment such as ships, there have been active researches on the application of CNN-based models specialized for digital videos. In E-Navigation service, which is combined with various technologies to detect floating objects of clash risk to reduce human errors and prevent fires inside ships, real-time processing is of huge importance. More functions added, however, mean a need for high-performance processes, which raises prices and poses a cost burden on shipowners. This study thus set out to propose a method capable of processing information at a high rate while maintaining the accuracy by applying Quantization techniques of a deep learning model. First, videos were pre-processed fit for the detection of floating matters in the sea to ensure the efficient transmission of video data to the deep learning entry. Secondly, the quantization technique, one of lightweight techniques for a deep learning model, was applied to reduce the usage rate of memory and increase the processing speed. Finally, the proposed deep learning model to which video pre-processing and quantization were applied was applied to various embedded boards to measure its accuracy and processing speed and test its performance. The proposed method was able to reduce the usage of memory capacity four times and improve the processing speed about four to five times while maintaining the old accuracy of recognition.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.279-286
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• 2021

Recently, We are carrying out a policy of physical distancing of at least 1m from each other to prevent the spreading of COVID-19 disease in public places. In this paper, we propose a method for measuring distances between people in real time and an automation system that recognizes objects that are within 1 meter of each other from stereo images acquired by drones or CCTVs according to the estimated distance. A problem with existing methods used to estimate distances between multiple objects is that they do not obtain three-dimensional information of objects using only one CCTV. his is because three-dimensional information is necessary to measure distances between people when they are right next to each other or overlap in two dimensional image. Furthermore, they use only the Bounding Box information to obtain the exact coordinates of human existence. Therefore, in this paper, to obtain the exact two-dimensional coordinate value in which a person exists, we extract a person's key point to detect the location, convert it to a three-dimensional coordinate value using Stereo Vision and Camera Calibration, and estimate the Euclidean distance between people. As a result of performing an experiment for estimating the accuracy of 3D coordinates and the distance between objects (persons), the average error within 0.098m was shown in the estimation of the distance between multiple people within 1m.

• Journal of Bio-Environment Control
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• v.28 no.3
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• pp.212-217
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• 2019

Bacterial wilt caused by Ralstonia solanacearum is a major disease that affects tomato plants widely. R. solanacearum is a soil born pathogen which limits the disease control measures. Therefore, breeding of resistant tomato variety to this disease is important. To identify the susceptible variety, degree of disease resistance has to be determined. In this study, micro sap flow sensor is used for accurate prediction of resistant degree. The sensor is designed to measure sap flow and water use in stems of plants. Using this sensor, the susceptibility to bacterial wilt disease can be identified two to three days prior to the onsite of symptoms after innoculation of R. solanacearum. Thus, this find of diagnosis approach can be utilized for the early detection of bacterial wilt disease.

• Journal of Nutrition and Health
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• v.52 no.2
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• pp.157-167
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• 2019

Purpose: This study examined the antioxidant and cancer cell growth inhibitory activities of an ethanol extract and different solvent fractions of Mesembryanthemum crystallinum L. (ice plant). Methods: The ice plant was freeze-dried, extracted with 99.9% ethanol, and then fractionated with hexane, ethyl acetate, butanol, and water. The total polyphenol content (TPC), total carotenoid content (TCC), 2,2-diphenyl-1-picrylhydrazyl radical-scavenging activity (RSA), and ferric reducing antioxidant power (FRAP) were measured. Assays using 2',7'-dichlorofluorescin-diacetate and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide were performed to measure the intracellular reactive oxygen species (ROS) and cell growth, respectively. Annexin V/propidium iodide staining and cell cycle analysis were performed for the detection of apoptosis and cell cycle arrest. Results: TPC, TCC, RSA, and FRAP of the ethanol extract (EE) were 3.7 mg gallic acid equivalent/g, $13.2{\mu}g/g$, 21.0% (at a concentration of 5 mg/mL), and 21.0% (at a concentration of 5 mg/mL), respectively. Among the different solvent fractions, the butanol fraction (BF) showed the highest TPC (5.4 mg gallic acid equivalent/g), TCC ($86.6{\mu}g/g$), RSA (34.9% at 5 mg/mL), and FRAP (80.8% at 5 mg/mL). Treatment of HCT116 human colon cancer cells with EE and BF at concentrations of 250 and $500{\mu}g/mL$ reduced the levels of intracellular ROS. Concomitantly, EE and BF resulted in the dose-dependent inhibition of cell growth (at the concentrations of 125, 250, and $500{\mu}g/mL$ for 24 ~ 48 h) and the induction of apoptosis (at the concentrations of 250 and $500{\mu}g/mL$ for 48 h) in HCT116 cells. An increased G2/M cell population was also found in the BF-treated cells. Conclusion: These results suggest that ice plant possesses antioxidant and growth inhibitory activities in colon cancer cells.

• Journal of Energy Engineering
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• v.27 no.4
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• pp.103-110
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• 2018

In this paper, we introduce evaluation method of time series prediction model with new approach of Mean Absolute Percentage Error(hereafter MAPE) and Symmetric Mean Absolute Percentage Error(hereafter sMAPE). There are some problems using MAPE and sMAPE. First MAPE can't evaluate Zero observation of dataset. Moreover, when the observed value is very close to zero it evaluate heavier than other methods. Finally it evaluate different measure even same error between observations and predicted values. And sMAPE does different evaluations are made depending on whether the same error value is over-predicted or under-predicted. And it has different measurement according to the each sign, even if error is the same distance. These problems were solved by Maximum Mean Absolute Percentage Error(hereafter mMAPE). we used the absolute maximum of observed value as denominator instead of the observed value in MAPE, when the value is less than 1, removed denominator then solved the problem that the zero value is not defined. and were able to prevent heavier measurement problem. Also, if the absolute maximum of observed value is greater than 1, the evaluation values of mMAPE were compared with those of the other evaluations. With Beijing PM2.5 temperature data and our simulation data, we compared the evaluation values of mMAPE with other evaluations. And we proved that mMAPE can solve the problems that we mentioned.

• Analytical Science and Technology
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• v.34 no.1
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• pp.23-35
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• 2021

In order to measure the volatile organic compounds (VOCs) of a sample which is too large to use commercially available chamber, a stainless steel vacuum chamber (VC) (with an internal diameter of 205 mm and a height of 50 mm) was manufactured and the temperature of the chamber was controlled using an oven. After concentrating the volatiles of the sample in the chamber by helium gas, it was made possible to remove residual volatile substances present in the chamber under reduced pressure ((2 ± 1) × 10-2 mmHg). The chamber was connected to a purge & trap (P&T) using a 6 port valve to concentrate the VOCs, which were analyzed by gas chromatography-mass spectrometry (GC-MS) after thermal desorption (VC-P&T-GC-MS). Using toluene, the toluene recovery rate of this device was 85 ± 2 %, reproducibility was 5 ± 2 %, and the detection limit was 0.01 ng L-1. The method of removing VOCs remaining in the chamber with helium and the method of removing those with reduced pressure was compared using Korean drinking water regulation (KDWR) VOC Mix A (5 μL of 100 ㎍ mL-1) and butylated hydroxytoluene (BHT, 2 μL of 500 ㎍ mL-1). In case of using helium, which requires a large amount of gas and time, reduced pressure ((2 ± 1) × 10-2 mmHg) only during the GC-MS running time, could remove VOCs and BHT to less than 0.1 % of the original injection concentration. As a result of analyzing volatile substances using VC-P&T-GC-MS of six types of cell phone case, BHT was detected in four types and quantitatively analyzed. Maintaining the chamber at reduced pressure during the GC-MS analysis time eliminated memory effect and did not affect the next sample analysis. The volatile substances in a cell phone case were also analyzed by dynamic headspace (HT3) and GC-MS, and the results of the analysis were compared with those of VC-P&T-GC-MS. Considering the chamber volume and sample weight, the VC-P&T configuration was able to collect volatile substances more efficiently than the HT3. The VC-P&T-GC-MS system is believed to be useful for VOCs measurement of inhomogeneous large sample or devices used inside clean rooms.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.1-9
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• 2022

Localization systems can be used with various circumstances like measuring population movement and rescue technology, even in security technology (like infiltration detection system). Vision sensors such as camera often used for localization is susceptible with light and temperature, and can cause invasion of privacy. In this paper, we used ultra-wideband radar technology (which is not limited by aforementioned problems) and machine learning techniques to measure the number and location of occupants in other indoor spaces behind the wall. We used four different algorithms and compared their results, including extremely randomized tree for four different situations; detect the number of occupants in a classroom, split the classroom into 28 locations and check the position of occupant, select one out of the 28 locations, divide it into 16 fine-grained locations, and check the position of occupant, and checking the positions of two occupants (existing in different locations). Overall, four algorithms showed good results and we verified that detecting the number and location of occupants are possible with high accuracy using machine learning. Also we have considered the possibility of service expansion using the oneM2M standard platform and expect to develop more service and products if this technology is used in various fields.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.179-189
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• 2022

Ice and water droplets rise and fall above the freezing altitude under the effects of strong updrafts and downdrafts, grow into hail, and then fall to the ground in the form of balls or irregular lumps of ice. Although such hail, which occurs in a local area within a short period of time, causes great damage to the agricultural and forestry sector, there is a paucity of domestic research toward predicting hail. The objective of this study was to introduce Land-Atmosphere Modeling Package (LAMP) hail prediction and measure its performance for 50 hail events that occurred from January 2020 to July 2021. In the study period, the frequency of occurrence was high during the spring and during afternoon hours. The average duration of hail was 15 min, and the average diameter of the hail was 1 cm. The results showed that LAMP predicted hail events with a detection rate of 70%. The hail prediction performance of LAMP deteriorated as the hail prediction time increased. The radar reflectivity of actual cases of hail indicated that the average maximum reflectivity was greater than 40 dBZ regardless of altitude. Approximately 50% of the hail events occurred when the reflectivity ranged from 30~50 dBZ. These results can be used to improve the hail prediction performance of LAMP in the future. Improved hail prediction performance through LAMP should lead to reduced economic losses caused by hail in the agricultural and forestry sector through preemptive measures such as net coverings.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.2
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• pp.85-92
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• 2023

Respiratory infections such as COVID-19 mainly occur within enclosed spaces. The presence or absence of abnormal symptoms of respiratory infectious diseases is judged through initial symptoms such as fever, cough, sneezing and difficulty breathing, and constant monitoring of these early symptoms is required. In this paper, image matching correction was performed for the RGB camera module and the thermal imaging camera module, and the temperature of the thermal imaging camera module for the measurement environment was calibrated using a blackbody. To detection the target recommended by the standard, a deep learning-based object recognition algorithm and the inner canthus recognition model were developed, and the model accuracy was derived by applying a dataset of 100 experimenters. Also, the error according to the measured distance was corrected through the object distance measurement using the Lidar module and the linear regression correction module. To measure the performance of the proposed model, an experimental environment consisting of a motor stage, an infrared thermography temperature screening system and a blackbody was established, and the error accuracy within 0.28℃ was shown as a result of temperature measurement according to a variable distance between 1m and 3.5 m.