• Journal of Auto-vehicle Safety Association
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• v.14 no.3
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• pp.48-59
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• 2022

A V2X system can be a candidate as a means to increase the stability of autonomous vehicles. In particular, in order to implement a Level 4 or higher autonomous driving system, the application of the V2X system is essential. Wireless communication technologies applicable to the V2X system include WAVE and C-V2X. Currently, the V2X service most used by autonomous driving systems is a service that provides signal phase and timing information and since real-time characteristic is a very important, verification of this service must be done. In this paper, we measured the time delay characteristics for providing signal phase and timing information using WAVE and LTE communication, and proposed a TOD-based signal phase and timing information generation method without using V2X communication system. To analyze the time delay characteristics, RTT (Round Trip Time) was measured as a result of the measurement. Average RTT using WAVE communication was 5.84ms and was 104.15ms with LTE communication. As a result of measuring the error between the signal phase and timing information generated based on TOD and the actual traffic light state, it was measured to be -0.284~3.784sec.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.4
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• pp.11-18
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• 2022

A physically unclonable function (PUF) is a circuit that generates random numbers by exploiting natural variation. Since it utilizes variations, which cannot be fully controlled, it can be used to generate true random numbers, but environment change may distort the output. In this paper, we propose a PUF with a confidence signal. We designed a PUF that exploits the difference of the time constant of the circuit and verified that different PUFs generate distinct outputs and the same PUF keeps generating similar outputs regardless of the temperature change. Compared to the existing technique, which employs an error correction code, the proposed technique offers the same level of reliability at the 700 times smaller overhead.

• Genomics & Informatics
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• v.20 no.2
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• pp.22.1-22.9
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• 2022

The rise of newer coronavirus disease 2019 (COVID-19) variants has brought a challenge to ending the spread of COVID-19. The variants have a different fatality, morbidity, and transmission rates and affect vaccine efficacy differently. Therefore, the impact of each new variant on the spread of COVID-19 is of interest to governments and scientists. Here, we proposed mathematical SEIQRDVP and SEIQRDV3P models to predict the impact of the Omicron variant on the spread of the COVID-19 situation in South Korea. SEIQEDVP considers one vaccine level at a time while SEIQRDV3P considers three vaccination levels (only one dose received, full doses received, and full doses + booster shots received) simultaneously. The omicron variant's effect was contemplated as a weighted sum of the delta and omicron variants' transmission rate and tuned using a hyperparameter k. Our models' performances were compared with common models like SEIR, SEIQR, and SEIQRDVUP using the root mean square error (RMSE). SEIQRDV3P performed better than the SEIQRDVP model. Without consideration of the variant effect, we don't see a rapid rise in COVID-19 cases and high RMSE values. But, with consideration of the omicron variant, we predicted a continuous rapid rise in COVID-19 cases until maybe herd immunity is developed in the population. Also, the RMSE value for the SEIQRDV3P model decreased by 27.4%. Therefore, modeling the impact of any new risen variant is crucial in determining the trajectory of the spread of COVID-19 and determining policies to be implemented.

• Korean Journal of Schizophrenia Research
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• v.23 no.1
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• pp.15-28
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• 2020

Objectives: This study investigated the relationship between clock-drawing test (CDT) performance and neuropsychological functions in patients with chronic schizophrenia. Methods: Thirty-one patients with schizophrenia and 30 healthy controls participated in this study. The CDT was administered in three conditions and analyzed using both quantitative and qualitative scoring systems. Comprehensive neuropsychological tests were administered. Results: The results of the quantitative analysis showed that the schizophrenia group performed significantly worse in all three conditions of the CDT compared with the control group. However, no significant differences were observed between the two groups, when the IQ and educational level were controlled. The qualitative analysis showed that the schizophrenia group exhibited significantly more errors in "graphic difficulty" compared with the control group. In addition, CDT quantitative scores were significantly correlated with visuospatial function, memory, attention and executive functions in patients with schizophrenia. Conversely, each qualitative error type was correlated with specific cognitive domains. Furthermore, "graphic difficulty" and "spatial/planning deficit" were identified as predictors of depression symptoms in patients with schizophrenia. Conclusion: The present study demonstrated that the CDT is useful for assessing cognitive dysfunctions in patients with schizophrenia, while qualitative analyses provide more specific information about cognitive deficits compared with quantitative analyses.

• Structural Engineering and Mechanics
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• v.82 no.2
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• pp.245-258
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• 2022

Many Structural Health Monitoring (SHM) methods have been proposed for structural damage diagnosis and prognosis. However, SHM for pinched hysteretic structures can be problematic due to the high level of nonlinearity. The model-free hysteresis loop analysis (HLA) has displayed notable robustness and accuracy in identifying damage for full-scaled and scaled test buildings. In this paper, the performance of HLA is compared with seven other SHM methods in identifying lateral elastic stiffness for a six-story numerical building with highly nonlinear pinching behavior. Two successive earthquakes are employed to compare the accuracy and consistency of methods within and between events. Robustness is assessed across sampling rates 50-1000 Hz in noise-free condition and then assessed with 10% root mean square (RMS) noise added to responses at 250 Hz sampling rate. Results confirm HLA is the most robust method to sampling rate and noise. HLA preserves high accuracy even when the sampling rate drops to 50 Hz, where the performance of other methods deteriorates considerably. In noisy conditions, the maximum absolute estimation error is less than 4% for HLA. The overall results show HLA has high robustness and accuracy for an extremely nonlinear, but realistic case compared to a range of leading and recent model-based and model-free methods.

• Journal of People, Plants, and Environment
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• v.24 no.5
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• pp.529-544
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• 2021

Background and objective: A great deal of previous research has highlighted the value of educational and cultural facilities embedded in housing prices, by taking a large spatial area as the focus, such as the city or district level. However, few studies have investigated the extent to which educational and cultural facilities influence the formation of housing prices from an accessibility perspective. This study aims to identify the value of educational and cultural facilities embedded in the housing prices in Seoul Metropolitan City with a focus on the concept of the residents' neighbourhood and accessibility. Methods: To this end, this research used a spatial regression model with educational and cultural facilities as the independent variables and housing prices as the dependent variable. The model assessed the accessibility of cultural and educational facilities by considering geographic effects. Results: The findings are as follows. First, the spatial error model was found to be the best fit for multi-unit housing, while the spatial lag model was more appropriate for single-unit housing and apartments. Second, private educational facilities and art museums had positive effects on single- and multi-unit housing prices, while historical sites had a negative effect. Finally, private educational facilities positively influenced apartment prices, whereas public libraries and urban park areas had a negative effect. Conclusion: These findings indicate that the accessibility of educational and cultural facilities reflects residents' preferences and needs, which will ultimately influence housing prices.

• Journal of Marine Bioscience and Biotechnology
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• v.14 no.2
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• pp.69-75
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• 2022

The micro-Kjeldahl method, a common technique for analyzing crude proteins, is time-consuming and dangerous due to the employment of reagents such as sulfuric acid and sodium hydroxide. However, a Fourier transform near-infrared (FT-NIR) spectrophotometer analysis can be completed in under a minute after simple pre-processing if data has been gathered using sufficient reference material in advance. Furthermore, the use of safe reagents in this technique ensures the safety of the experimenter and the environment. In addition, a portable FT-NIR spectrophotometer enables real-time measurement at processing or distribution sites and has recently gained popularity. The standard errors of calibration and regression (r²) for the calibration result for estimating the crude protein content of dried laver were 0.9775 and 1.2526, respectively. The standard error of prediction was 1.1814, and the r² was 0.9303 in the validation results, which was a good level. In the present study, a method for predicting the crude protein content of dried laver using an FT-NIR spectrophotometer in the range of 29%-40% crude protein content has been reported.

• Journal of Korea Game Society
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• v.22 no.1
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• pp.33-42
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• 2022

In online games, interactions with other players may threaten player satisfaction. Therefore, matching players of similar skill levels is important for players' experience. However, with the current evaluation method which is only based on the final result of the game, newbies and returning players are difficult to be matched properly. In this study, we propose a method to improve matchmaking quality. We build machine learning models to predict the MMR of players and derive the basis of the prediction. The error of the best model was 40.4% of the average MMR range, confirming that the proposed method can immediately place players in a league close to their current skill level. In addition, the basis of predictions may help players to accept the result.

• Journal of Sensor Science and Technology
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• v.31 no.2
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• pp.96-101
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• 2022

As the elderly population gradually increases, the risk of fatal fall accidents among the elderly is increasing. One way to cope with a fall accident is to determine the fall direction before impact using a wearable inertial measurement unit (IMU). In this context, a previous study proposed a method of classifying fall directions using a support vector machine with sensor velocity, acceleration, and tilt angle as input parameters. However, in this method, the IMU signals are processed through several processes, including a Kalman filter and the integration of acceleration, which involves a large amount of computation and error factors. Therefore, this paper proposes a machine learning-based method that classifies the fall direction before impact using IMU raw signals rather than processed data. In this study, we investigated the effects of the following two factors on the classification performance: (1) the usage of processed/raw signals and (2) the selection of machine learning techniques. First, as a result of comparing the processed/raw signals, the difference in sensitivities between the two methods was within 5%, indicating an equivalent level of classification performance. Second, as a result of comparing six machine learning techniques, K-nearest neighbor and naive Bayes exhibited excellent performance with a sensitivity of 86.0% and 84.1%, respectively.

• Earthquakes and Structures
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• v.25 no.3
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• pp.161-175
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• 2023

High-damping rubber bearings (HDRB) are commonly used as seismic isolation devices to protect civil engineering structures from earthquakes. However, the nonlinear hysteresis characteristics of the HDRB, such as their dependence on material properties and hardening phenomena, make predicting their behavior during earthquakes difficult. This study proposes a hysteretic model that can accurately predicts the behavior of shear deformation considering the nonlinearity when designing the seismic isolation structures using HDR bearings. To model the hysteretic characteristics of the HDR, dynamic loading tests were performed by applying sinusoidal and random waves on scaled-down specimens. The test results show that the nonlinear characteristics of the HDR strongly correlate with the shear strain experienced in the past. Furthermore, when shear deformation occurred above a certain level, the hardening phenomenon, wherein the stiffness increased rapidly, was confirmed. Based on the experimental results, the dynamic characteristics of the HDR, equivalent stiffness, equivalent damping ratio, and strain energy were quantitatively evaluated and analyzed. In this study, an improved bilinear HDR model that can reproduce the dependence on shear deformation and hardening phenomena was developed. Additionally, by proposing an objective parameter-setting procedure based on the experimental results, the model was devised such that similar parameters could be set by anyone. Further, an actual dynamic analysis could be performed by modeling with minimal parameters. The proposed model corresponded with the experimental results and successfully reproduced the mechanical characteristics evaluated from experimental results within an error margin of 10%.