• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.684-697
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• 2021

This study seeks to establish the structural relationship between the personal psychological risk factors of teenagers of depression, anxiety and impulsiveness and smartphone addiction (daily disability, virtual orientation, tolerance, withdrawal) and self-elasticity (vitality, optimism, curiosity, interpersonal relationships). Through this verification, the purpose of this study is to find out if the integrated model of smartphone addiction and self-elasticity and smartphone addiction among teenagers is reasonable, and to suggest ways to prevent and solve smartphone addiction among teenagers. In order to achieve this purpose, 356 teenagers in Seoul and the metropolitan area were surveyed for two months from August to September 2019 and the results were analyzed. The findings of this study are as follows. First, the "smartphone addiction factors" (depression, anxiety and impulsive) of adolescents have been shown to have negative effects on their self-elasticity (vitality, optimism, curiosity, interpersonal relationships). Second, the "smartphone addiction factors" (depression, anxiety and impulsive) of teenagers have been shown to have positive effects on the "smartphone addiction" (daily disability, virtual orientation, tolerance, withdrawal). Third, the youth's "self-elasticity (vitality, optimism, curiosity, interpersonal relationship)" was shown to have a negative impact on "smartphone addiction (daily disability, virtual orientation, tolerance, withdrawal)." The significance of this study is that it has examined personal psychological risk factors that affect smartphone addiction and suggested measures to prevent smartphone addiction among teenagers and solve related problems by micro-analyzing the effects on smartphone addiction by utilizing self-elasticity.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1635-1641
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• 2020

Air pollution is one of the most severe threats to society globally due to the rapid expansion of urbanization and industrialization. Particularly, particulate matter (PM) pollution was recently designated as a social disaster by the Korean government because of increases in public concerns and the accumulation of scientific evidence that links high levels of PM2.5 (PM smaller than 2.5 ㎛ in diameter) to a long list of adverse health effects. Atmospheric PM concentrations can also affect the indoor PM levels to which people are exposed most of the time. Thus, understanding the characteristics of indoor and ambient PM pollution based on measurements, model simulations, risk assessments, and management technologies is inevitable in establishing effective policies to mitigate social, economic, and health costs incurred by PM pollution. In this special issue, we introduce several interesting studies concerning indoor and outdoor PM from the perspective of monitoring, assessment, and management being conducted by i-SEED (School of Integrated Science for Sustainable Earth & Environmental Disaster at Pukyong National University) and SPMC (School Particulate Matter Center for Energy and Environmental Harmonization). We expect that this special issue can improve our understanding of the current and future of indoor and outdoor PM pollution, integrating the results from interdisciplinary research groups from various academic fields.

• Therapeutic Science for Rehabilitation
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• v.10 no.3
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• pp.7-22
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• 2021

Objective : The purpose of this study was to verify the effect of virtual reality interventions (VRIs) on cognitive function in individuals with stroke through a systematic literature review and meta-analysis. Methods : We reviewed randomized controlled trials (RCTs) the last 10 years using academic databases. PubMed, MEDLINE, and CINAHL were used for international studies, and DBpia, KISS, Kyoboscholar, and e-article were used for Korean studies. For the quantitative meta-analysis, subgroups of outcomes were classified into general cognitive function (G-CF), attention and memory (A&M), and executive function (EF). Results : Nine RCTs were analyzed. The total number of participants was 271 (140 in the experimental group). The effect size (Cohen's d) was estimated using a random effects model. The effect sizes of the outcome subgroups of were as follows: small to medium for G-CF (d=0.422; 95% CI: 0.101~0.742; p=0.010), small for A&M (d=0.249; 95% CI: -0.107~0.605; p=0.170), and medium for EF (d=0.666; 95% CI: 0.136~1.195; p=0.014). Conclusion : Considering the various stimuli provided by the virtual environment and the results from available research, virtual reality should be applied to interventions for integrated cognitive functions. In addition, it would be appropriate to be used as an additional intervention to traditional cognitive rehabilitation for stroke.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.2
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• pp.68-75
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• 2022

In this study, in order to directly evaluate the prestress of the PSC structure, a new sensor module based on the measurement of the deformation of concrete was proposed using hetero-core optical fibers and performance tests were performed. In a hetero-core optical fiber, optical loss occurs when a specific part of the transmission path is bent, and the amount of optical loss changes linearly according to the magnitude of the curvature. In order to confirm the measurement performance of the sensor module and the applicability of the optical fiber, the sensor module was deformed and the light passing through the optical fiber was converted into wattage and measured. It can be seen that the light passing through the optical fiber has a linearity of 0.9333 in relation to the deformation while generating the maximum deformation of 0.5 mm at a rate of 0.12 mm/min in a cylindrical concrete specimen with a diameter of 15 cm and a height of 35 cm in which the sensor module is embedded. Based on the results of this experiment, it is judged that it is possible to directly evaluate the prestress of a PSC structure by embedding a sensor module using a hetero-core optical fiber in the structure and measuring the compression deformation in concrete. It is judged that it can be used as useful data for the development of a sheath tube integrated sensor module to be applied to be applied to the girder model experiment.

• Journal of Korea Water Resources Association
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• v.55 no.5
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• pp.321-331
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• 2022

In this study, we tried to present a method for calculating the amount of regression using a watershed modeling method that can simulate the hydrological mechanism of water balance analysis and agricultural water based on watershed unit. Using the soil water assessment tool (SWAT), a watershed water balance analysis was conducted considering the simulation of paddy fields for the Manbongcheon Standard Basin (97.34 km²), which is a representative agricultural area of the Yeongsan river basin. Before evaluating return flow, the SWAT was calibrated and validated using the daily streamflow observation data at Naju streamflow gauge station (NJ). The coefficient of determination (R²), Nash-Sutcliffe Efficiency (NSE), Root-Mean-Square Error (RMSE) of NJ were 0.73, 0.70, 0.64 mm/day. Based on the calibration results for three years (2015-2017), the quick return flow and the return rate compared to the water supply amount for the irrigation period (April 1 to September 30) were calculated, and the average return flow rate was 53.4%. The proposed method of this study may be used as foundation data to optimal agricultural water supply plan for rational watershed management.

• Journal of the Korean Applied Science and Technology
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• v.38 no.2
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• pp.368-377
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• 2021

The present study aimed to evaluate the effects of radiation mutant Perilla frutescens var. crispa and Atractylodes macrocephala Koidzumi complex extract(Perilla frutescens var. crispa complex extract) on the mediators related to degenerative arthritis in a monosodium iodoacetate-induced rat model of degenerative arthritis. Perilla frutescens var. crispa complex extract was administered orally at doses of 25, 50 or 100 mg/kg/day for 2 weeks before direct injection of monosodium iodoacetate (3 mg/50 µl of 0.9% saline) into the intra-articular space of the rats' right knees. The rats subsequently received the same doses of oral Perilla frutescens var. crispa complex extract for another 4 weeks. It was evaluated that the treatment effects based on serum bio-markers, and morphological and histopathological analysis of the knee joints. Compared with those in negative control rats, the Perilla frutescens var. crispa complex extract treatments significantly reduced the serum levels of inflammation, bone metabolism markers (i.e., TNF-α, MMP-3, COX-2, PGE₂, COMP, and Aggrecan). Otherwise, it was significantly increased the production of CTX-2 in cartilage absorption mediators. In addition, the Perilla frutescens var. crispa complex extract treatments effectively preserved the knee cartilage and synovial membrane. As a result, it indicates that the Perilla frutescens var. crispa complex extract improved degenerative arthritis symptoms. Thus, the Perilla frutescens var. crispa complex can be used in food material for the management of degenerative arthritis.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.79-88
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• 2022

Modern production requires production staff who have design competence, experience and skills to work in various types of work integrated into professional activities. Possession of digital design methods significantly expands the opportunities for professional activities of qualified workers. The purpose of our study was to study the impact of pedagogical conditions on the formation of design competence of future qualified workers in a group work. We have identified a set of pedagogical conditions that promote the development of professionally oriented artistic and technical creativity of workers in the conditions of curricular and extracurricular activities, which include motivational-target, procedural-semantic, organizational-technological, and subject-oriented. It is shown that the formation of design competence is determined by motivational, informational-active and reflection criteria, which are aimed at motivational-value, cognitive, operational-active, creative, social and emotional components of this competence. The methodology of the research is highlighted, which includes the use of the following methods: determination of the personality's motivational sphere in order to identify strong and weak motives of students activity; multiple intelligence to identify students talents in the direction of practical intelligence, which is important for design competence; determining the level of creative activity to identify manifestations of students creative abilities; identifying the type of students innovative thinking in order to develop motivation for success; factor-criterion model, developed on the basis of a qualimetric approach, which is used to identify the level of design competence formation in accordance with its components. The results of the study showed that the creation of separate pedagogical conditions in the institution of vocational education and training (VET) had a positive impact on the development of design competence, which shows the potential of artistic and technical design in the development of professional creativity of future qualified workers taking into account the environmental approach.

• Smart Structures and Systems
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• v.29 no.4
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• pp.625-640
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• 2022

Maglev rail joints are vital components serving as connections between the adjacent F-type rail sections in maglev guideway. Damage to maglev rail joints such as bolt looseness may result in rough suspension gap fluctuation, failure of suspension control, and even sudden clash between the electromagnets and F-type rail. The condition monitoring of maglev rail joints is therefore highly desirable to maintain safe operation of maglev. In this connection, an online damage detection approach based on three-dimensional (3D) convolutional neural network (CNN) and time-frequency characterization is developed for simultaneous detection of multiple damage of maglev rail joints in this paper. The training and testing data used for condition evaluation of maglev rail joints consist of two months of acceleration recordings, which were acquired in-situ from different rail joints by an integrated online monitoring system during a maglev train running on a test line. Short-time Fourier transform (STFT) method is applied to transform the raw monitoring data into time-frequency spectrograms (TFS). Three CNN architectures, i.e., small-sized CNN (S-CNN), middle-sized CNN (M-CNN), and large-sized CNN (L-CNN), are configured for trial calculation and the M-CNN model with excellent prediction accuracy and high computational efficiency is finally optioned for multiple damage detection of maglev rail joints. Results show that the rail joints in three different conditions (bolt-looseness-caused rail step, misalignment-caused lateral dislocation, and normal condition) are successfully identified by the proposed approach, even when using data collected from rail joints from which no data were used in the CNN training. The capability of the proposed method is further examined by using the data collected after the loosed bolts have been replaced. In addition, by comparison with the results of CNN using frequency spectrum and traditional neural network using TFS, the proposed TFS-CNN framework is proven more accurate and robust for multiple damage detection of maglev rail joints.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.63-71
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• 2010

In modern war, Intercept Performance of SAM(Surface to Air Missile) is gaining importance as range and precision of Missile and Guided Weapon on information warfare have been improved. An aerial defence system using Surface-to-air Radar and Guided Missile is needed to be built for prediction and defense from threatening aerial attack. When developing SAM, M&S is used to free from a time limit and a space restriction. M&S is widely applied to education, training, and design of newest Weapon System. This study was conducted to develop simulator for evaluation of Intercept Performance of SAM. In this study, architecture of Intercept Performance of SAM analysis simulator for estimation of Intercept Performance of various SAM was suggested and developed. The developed Intercept Performance of SAM analysis simulator was developed by C++ and Direct3D, and through 3D visualization using the Direct3D, it shows procedures of the simulation on a user animation window. Information about design and operation of Fighting model is entered through input window of the simulator, and simulation engine consisted of Object Manager, Operation Manager, and Integrated Manager conducts modeling and simulation automatically using the information, so the simulator gives user feedback in a short time.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.103-112
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• 2009

In a nuclear power plant (NPP), periodic sensor calibrations are required to assure sensors are operating correctly. However, only a few faulty sensors are found to be calibrated. For the safe operation of an NPP and the reduction of unnecessary calibration, on-line calibration monitoring is needed. In this paper, principal component-based Auto-Associative support vector regression (PCSVR) was proposed for the sensor signal validation of the NPP. It utilizes the attractive merits of principal component analysis (PCA) for extracting predominant feature vectors and AASVR because it easily represents complicated processes that are difficult to model with analytical and mechanistic models. With the use of real plant startup data from the Kori Nuclear Power Plant Unit 3, SVR hyperparameters were optimized by the response surface methodology (RSM). Moreover the statistical techniques are integrated with PCSVR for the failure detection. The residuals between the estimated signals and the measured signals are tested by the Shewhart Control Chart, Exponentially Weighted Moving Average (EWMA), Cumulative Sum (CUSUM) and generalized likelihood ratio test (GLRT) to detect whether the sensors are failed or not. This study shows the GLRT can be a candidate for the detection of sensor drift.