• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2663-2674
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• 2014

For cognitive radio sensor networks (CRSNs) that use underlay-based spectrum access, the location of the primary user (PU) plays an important role in the power control of the secondary users (SUs), because the SUs must keep the minimum interference level required by the PU. Received signal strength (RSS)-based localization schemes provide low-cost implementation and low complexity, thus it is suitable for the PU localization in CRSNs. However, the RSS-based localization schemes have a high localization error because they use an inexact path loss exponent (PLE). Thus, applying a RSS-based localization scheme into the PU localization would cause a high interference to the PU. In order to reduce the localization error and improve the channel reuse rate, we propose a RSS-based PU localization scheme that uses distance calibration for CRSNs using underlay model-based spectrum access. Through the simulation results, it is shown that the proposed scheme can provide less localization error as well as more spectrum utilization than the RSS-based PU localization using the mean and the maximum likelihood calibration.

• Journal of Power Electronics
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• v.18 no.2
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• pp.533-546
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• 2018

This study proposes a comprehensive mathematical model that includes coil-system circuit and loss models for power converters in wireless power transfer (WPT) systems. The proposed model helps in understanding the performance of WPT systems in terms of coil-to-coil efficiency, overall efficiency, and output power capacity and facilitates system performance optimization. Three methods to achieve constant output power for variable-load systems are presented based on system performance analysis. An optimal method can be selected for a specific WPT system by comparing the efficiencies of the three methods calculated with the proposed model. A two-coil 1 kW WPT system is built to verify the proposed mathematical model and constant output power control methods. Experimental results show that when the load resistance varies between 5 and $25{\Omega}$, the system output power can be maintained at 1 kW with a maximum error of 6.75% and an average error of 4%. Coil-to-coil and overall efficiencies can be maintained at above 90% and 85%, respectively, with the selected optimal control method.

• Journal of Korean Public Health Nursing
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• v.27 no.2
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• pp.357-371
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• 2013

Purpose: The purpose of this study was to investigate the effects of health education based on the health belief model (HBM) to the prevention of noise-induced hearing loss (NIHL) in middle school students. Methods: A pretest-posttest nonequivalent control group was designed for the purpose of this study. A total of 212 students (134 in the experimental group and 78 in the control group) of two middle schools in Seoul were enrolled for the study. Health education of two 45-minutes sessions over two weeks were provided. The data were analyzed by descriptive statistics, Chi-square test, t-test, ANCOVA and repeated measures ANOVA with Bonferroni post-hoc test, using the SPSS version 21.0. Results: There were significant differences between experimental group and control group with reference to perceived susceptibility (F=7.862, p=.006), perceived severity (F=8.291, p=.004), perceived benefits (F=20.311, p<.001), and perceived barriers (F=5.628, p=.019) after health education were provided. We also observed sustained health education effects of perceived susceptibility, perceived severity, perceived benefits, and perceived barriers in the experimental group for up to 4 weeks after health education were provided. Conclusion: The health education to prevent NIHL based on the HBM improved the health beliefs of the middle school students. Health education on the HBM for the prevention of NIHL should be provided at the level of middle school.

• Convergence Security Journal
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• v.24 no.3
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• pp.3-11
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• 2024

Information security is crucial not only for protecting against external cyber-attacks but also for identifying and blocking internal data leakage risks in advance. To this end, many companies and institutions implement digital rights management(DRM) document security solutions, which encrypt files to prevent content access if leaked, and data loss prevention(DLP) solutions, which control devices such as USB ports on computing equipment to prevent data leaks. At a time when efforts to prevent internal data leaks are crucial, there is a growing need for control policies such as device control and the identification of information assets in standalone network environments, which could otherwise fall into unmanaged domains. In this study, we propose a Generation-Distribution-Application model for device control policies that are uniquely applied to standalone information assets that are not connected to internal networks. To achieve this, we developed an authentication technique linked with the asset management system, where information assets are automatically registered upon acquisition. This system allows for precise identification of information assets and enables flexible device control, and we have designed and implemented a system based on these principles.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1156-1170
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• 2019

In recent years, the problem of data drifted of the smart grid due to manual operation has been widely studied by researchers in the related domain areas. It has become an important research topic to effectively and reliably find the reasonable data needed in the Supervisory Control and Data Acquisition (SCADA) system has become an important research topic. This paper analyzes the data composition of the smart grid, and explains the power model in two smart grid applications, followed by an analysis on the application of each parameter in density-based spatial clustering of applications with noise (DBSCAN) algorithm. Then a comparison is carried out for the processing effects of the boxplot method, probability weight analysis method and DBSCAN clustering algorithm on the big data driven power grid. According to the comparison results, the performance of the DBSCAN algorithm outperforming other methods in processing effect. The experimental verification shows that the DBSCAN clustering algorithm can effectively screen the power grid data, thereby significantly improving the accuracy and reliability of the calculation result of the main grid's theoretical line loss.

• Journal of Biosystems Engineering
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• v.19 no.1
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• pp.22-32
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• 1994

The combine harvester is considered as an important but complicated and costly machine. The appropriate size of combine has to be developed to use efficiently in Korea. But the combine is such a complicated machine that a complete design model to develop a new type is impossible without understanding the relationship between each factor. The combine capacity is generally limited by the cleaning shoe performance. So a design model for a cleaning shoe has to be developed first for the complete combine design. The objective of this research was to develop a cleaning model of head-feeding combine to predict grain separation from chaff and broken straw on a sieve. A developed physically based model can explain the situation which can happen during separation process. A test apparatus based on the field going machine was developed. The test materials were paddy rice and barley. The data obtained were analyzed by the hand and the video camera. The developed model was verified as an adequate model through the test with $R^2$ of 0.934 and 0.837. The model can be used to evaluate design and operation alternatives of combine and also applied to the automatic control of separation unit of combine with a loss monitering sensors.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.720-723
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• 2005

Ship motion is a complex controlled process with several hydrodynamic parameters that vary in wide ranges with respect to ship load condition, speed and surrounding conditions (such as wind, current, tide, etc.). Therefore, to effectively control ships in a designed track is always an important task for ship masters. This paper presents an effective adaptive autopilot ships that ensure the optimal accuracy, economy and stability characteristics. The PID control methodology is modified and parameters of a PID controller is designed to satisfy conditions for an optimal objective function that comprised by heading error, resistance and drift during changing course, and loss of surge velocity or fuel consumption. Designing of the controller for course changing process is based on the Model Reference Adaptive System (MRAS) control theory, while as designing of the automatic course keeping process is based on the Self Tuning Regulator (STR) control theory. Simulation (using MATLAB software) in various disturbance conditions shows that in comparison with conventional PID autopilots, the designed autopilot has several notable advantages: higher course turning speed, lower swing of ship bow even in strong waves and winds, high accuracy of course keeping, shorter time of rudder actions smaller times of changing rudder direction.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.6
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• pp.65-73
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• 2008

The purpose of this study is development of universal engine model for integrated Hybrid Electric Vehicle (HEV) simulator and a optimization of engine model. The engine model of this study is based on the MATLAB Simulink for universal and include engine fuel economy technologies for HEV. Various engine fuel economy technologies for HEV is estimated by commercial engine 1-D simulation program - WAVE. And, the 1-D simulation model of base version is compared with engine experiment result. The analyzed engine technologies with 1-D simulation are Dual-CVVT, Atkinson-Cycle and Cylinder-Deactivation System. There are improvement of fuel economy and power performance with Dual-CVVT model at part load and full load, pumping loss reduction with Cylinder-Deactivation System at idle and regeneration. Each estimated technologies are analyzed by 1-D simulation on all operation region for base data to converse simulink. The simulink based engine model maintains a signal with ECU for determination of engine operation point.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2499-2522
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• 2017

Multi-hop networks are a low-setup-cost solution for enlarging an area of network coverage through multi-hop routing. Carrier sense multiple access with collision avoidance (CSMA/CA) is frequently used in multi-hop networks. Multi-hop networks face multiple problems, such as a rise in contention for the medium, and packet loss under heavy-load, saturated conditions, which consumes more bandwidth due to re-transmissions. The number of re-transmissions carried out in a multi-hop network plays a major role in the achievable quality of service (QoS). This paper presents a statistical, analytical model for the end-to-end delay of contention-based medium access control (MAC) strategies. These strategies schedule a packet before performing the back-off contention for both differentiated heterogeneous data and homogeneous data under saturation conditions. The analytical model is an application of Markov chain theory and queuing theory. The M/M/1 model is used to derive access queue waiting times, and an absorbing Markov chain is used to determine the expected number of re-transmissions in a multi-hop scenario. This is then used to calculate the expected end-to-end delay. The prediction by the proposed model is compared to the simulation results, and shows close correlation for the different test cases with different arrival rates.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.5
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• pp.35-44
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• 2011

In a spark ignition engine, a variable valve lift (VVL) system has been developed for high fuel efficiency and low power loss. However, changes in valve lift cause deviations of cylinder air charge which lead to individual cylinder equivalence ratio maldistribution. In this study, in order to reduce the maldistribution, we propose individual cylinder equivalence ratio estimation and control algorithms. The estimation algorithm calculates the equivalence ratio of each cylinder by using a mathematical engine model which includes air charging, fuel film, exhaust gas, and universal exhaust gas oxygen sensor (UEGO) dynamics at various valve lifts. Based on the results of estimated equivalence ratio, the injection quantity of each cylinder is adjusted to control the individual cylinder equivalence ratio. Estimation and control performance are validated by engine experiments. Experimental results represented that the equivalence ratio maldistribution and variation are decreased by the proposed algorithms.