• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.7
• /
• pp.1347-1353
• /
• 2011

While most of the existing protection schemes have been designed with local information around individual components, these local schemes are not considered capable of protecting the modern electric power gird with growing complexity. Recent blackouts in North America and Europe have renewed the emphasis on coordinated protection and control actions to avoid systemwide blackouts, utilizing all of the available grid information. Thus, this paper proposes a new methodology, Agent-based Colored Petri Net (ACPN) modeling for systematically representing, modeling and analyzing information flows and interactions among the entities of the electric power grid. The paper demonstrates its efficacy and accuracy by investigating an ACPN model of a wide area protection system for a typical power grid. The proposed modeling and analysis schemes may further provide a framework to help assure reliability and interoperability of diverse smart grid components.

• International journal of advanced smart convergence
• /
• v.11 no.1
• /
• pp.127-133
• /
• 2022

This study aims to find out the associative relationship between dementia and comorbidities. To conduct this study, we used KNHDIS(Korea National Hospital Discharge In-depth Injury Survey) data from 2009 to 2018 provided by the KDCA(Korean Disease Control and Prevention Agency) annually. We used MySQL for data preprocessing and R for data analysis. As a result of applying the Apriori algorithm criteria of support(≥0.01), confidence(≥ 0.6), and lift(>1), seventeen rules related to dementia were discovered. The diseases associated with dementia were diabetes mellitus, hypertension, disorders of lipoprotein metabolism, glomerular disorders in diabetes mellitus, renal diseases, cardiovascular disease, cerebrovascular disease, and other urinary system disorders. This study can be utilized as primary data for the care of patients with dementia and provides implications for improving effective dementia prevention policies.

• Smart Structures and Systems
• /
• v.15 no.3
• /
• pp.555-576
• /
• 2015

The large number of long-span bridges constructed in China motivates the applications of structural health monitoring (SHM) technology. Many bridges have been equipped with sophisticated SHM systems in the mainland of China and in Hong Kong of China. Recently, SHM technology has been extended to field test systems. In this view, SHM can serve as a tool to develop the methods of life-cycle performance design, evaluation, maintenance and management of bridges; to develop new structural analysis methods through validation and feedback from SHM results; and to understand the behavior of bridges under natural and man-made disasters, rapidly assess the damage and loss of structures over large regions after disasters, e.g., earthquake, typhoon, flood, etc. It is hoped that combining analytical methods, numerical simulation, small-scale tests and accelerated durability tests with SHM could become the main engine driving the development of bridge engineering. This paper demonstrates the above viewpoint.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.11a
• /
• pp.840-845
• /
• 2004

Development of the linear motors is recently required to control a high-speed and high-resolution in the high-integrated and speed process industry. This paper presents vibration analyses as well as measurement standards of the newly developed linear motors through analyzing the vibration characteristics of the advanced products. Vibration experiments are conducted for identifying vibration level during operation. They are also included in the modal test to analyze dynamic characteristics. Analytic data using Finite Element Method (FEM) are compared with the results of the modal. The FEM and experiments make it possible to understand these characteristics. Further, through computer simulation for the behavior of moving part to be vibration source, the best acceleration pattern of moving part movement can be verified to achieve effective moving part positioning and reduce the vibration due to moving part movement.

• International journal of advanced smart convergence
• /
• v.8 no.2
• /
• pp.39-46
• /
• 2019

Human mobility estimation plays a key factor in a lot of promising applications including location-based recommendation systems, urban planning, and disease outbreak control. We study the human mobility estimation problem in the case where recent locations of a person-of-interest are unknown. Since matrix decomposition is used to perform latent semantic analysis of multi-dimensional data, we propose a human location estimation algorithm based on matrix factorization to reconstruct the human movement patterns through the use of information of persons with correlated movements. Specifically, the optimization problem which minimizes the difference between the reconstructed and actual movement data is first formulated. Then, the gradient descent algorithm is applied to adjust parameters which contribute to reconstructed mobility data. The experiment results show that the proposed framework can be used for the prediction of human location and achieves higher predictive accuracy than a baseline model.

• International journal of advanced smart convergence
• /
• v.11 no.4
• /
• pp.253-259
• /
• 2022

This study aims to investigate the antecedent of consumer personal preventive equipment purchase behaviour by extending the HBM model after the pandemic. Pandemic related studies have focused on the effect of perceived susceptibility and perceived severity on consumer preventive behaviour, little studies have investigated the antecedents of consumer perceived risk. This study filled the gaps in the previous studies. This study tested all proposed hypotheses among users who have purchase the self-preventive behaviour. In final 253 valid data were collected through online survey for statistics analysis. This study found that consumer's health consciousness significantly impacted consumer's perceived severity of COVID-19 and perceived risk. Perceived risk positively impacted consumer self-preventive equipment purchase intention. In contrast, perceived susceptibility did not significantly consumer perceived risk. Based on these results, the theoretical implication will be offered on the study of health-related studies and will be given insight for disease control center to effectively manage consumer self-preventive behaviour.

• Smart Structures and Systems
• /
• v.21 no.6
• /
• pp.727-740
• /
• 2018

Tuned mass dampers (TMDs) are passive damping devices widely employed to mitigate the pedestrian-induced vibrations on footbridges. The TMD design must ensure an adequate performance during the overall life-cycle of the structure. Although the TMD is initially adjusted to match the natural frequency of the vibration mode which needs to be controlled, its design must further take into account the change of the modal parameters of the footbridge due to the modification of the operational and environmental conditions. For this purpose, a motion-based design optimization method is proposed and implemented herein, aimed at ensuring the adequate behavior of footbridges under uncertainty conditions. The uncertainty associated with the variation of such modal parameters is simulated by a probabilistic approach based on the results of previous research reported in literature. The pedestrian action is modelled according to the recommendations of the Synpex guidelines. A comparison among the TMD parameters obtained considering different design criteria, design requirements and uncertainty levels is performed. To illustrate the proposed approach, a benchmark footbridge is considered. Results show both which is the most adequate design criterion to control the pedestrian-induced vibrations on the footbridge and the influence of the design requirements and the uncertainty level in the final TMD design.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.3
• /
• pp.283-289
• /
• 2015

In this paper, a GNSS interference detection algorithm based on an adaptive fading Kalman filter is proposed to detect a spoofing signal which is one of the threatening GNSS intentional interferences. To detect and mitigate the spoofing signal, the fading factor of the filter is used as a detection parameter. For simulation, the effect of the spoofing signal is modeled by the ramp type bias error of the pseudorange to emulate a smart spoofer and the change of the fading factor value according to ramp type bias error is quantitatively analyzed. In addition, the detection threshold is established to detect the spoofing signal by analyzing the change of the error covariance and the effect of spoofing is mitigated by controlling the Kalman gain of the filter. To verify the performance analysis of the proposed algorithm, various simulations are implemented. Through the results of simulations, we confirmed that the proposed algorithm works well.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.11 no.4
• /
• pp.13-21
• /
• 2001

Electrorheological(ER) fluid is a kind of smart material with variable shear stress and dynamic viscosity under various electric field intensity. Electric field can control the damping characteristics of ER damper. The objective of this study is the analysis of the performance of ER damper and its application to shock absorber. Idealized nonlinear Bingham plastic shear flow model is used to predict the velocity profile between electrodes. Cylindrical dashpot ER damper with moving electrode is constructed and tested under various electric fields. The analytic and experimental results for damping force are compared and discussed. Drop test system using ER damper is prepared to identify transient vibration characteristics. The rebound is eased as the applied electric field increases. When semi-active control algorithm is applied, rebound phenomenon disappears and vibration energy level decays faster than the case of zero electric field.

• The Journal of Korean Physical Therapy
• /
• v.33 no.3
• /
• pp.162-167
• /
• 2021

Purpose: A hyperextended knee is described as knee pain associated with an impaired knee extensor mechanism. Additionally, a hyperextended knee may involve reduced position sense of the knee joint that decreases the individual's ability to control end-range knee extension movement. The purpose of this study was to investigate the effects of visual biofeedback information for plantar pressure distribution on knee joint angle and lower extremity muscle activities in participants with hyperextended knees. Methods: Twenty-three participants with hyperextended knees were recruited for the study. Surface electromyography signals were recorded for the biceps femoris, rectus femoris, gastrocnemius, and tibialis anterior muscle activities. The plantar pressure distribution was displayed and measured using a pressure distribution measuring plate. Knee joint angle kinematic parameters were recorded using a motion analysis system. The visual biofeedback condition was the point at which the difference between the forefoot and backfoot plantar foot pressure on the monitor was minimized. The Wilcoxon signed-rank test was used to determine the significance between the visual biofeedback condition and the preferred condition. Results: The knee joint angle was significantly decreased in the visual biofeedback condition compared to that in the preferred condition (p<0.05). The rectus femoris and gastrocnemius muscle activities were significantly different between the visual biofeedback and preferred conditions (p<0.05). Conclusion: The results of this study showed that visual biofeedback of information about plantar pressure distribution is effective for correcting hyperextended knees.