• Journal of Sasang Constitutional Medicine
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• v.22 no.4
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• pp.20-29
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• 2010

1. Objectives Our goal is to observe the feasibility of constitution discrimination from computing quantitative roughness index from dynamic friction coefficients and their gradients with the measurement device of skin friction with 3-Axis load cell sensor. 2. Methods In the traditional Korean medicine, skin diagnosis is one of the examination methods to discriminate Sasang constitution since it was known that Tae-eumin has rough skin, and Soyangin has smooth one. It is based on the skin roughness on the back of one's hand for the discrimination. The measurement device of skin friction with 3-axis load cell sensor has been developed in order to provide quantitative skin roughness through dynamic friction coefficients. The effective interval of the coefficients is obtained from the automatic sampling algorithm to use their curvature and slope. Then, Fisher's discriminant function of them makes the discrimination. 3. Results The success rate of extracting the effective interval was about 90% and the discriminant accuracy between Tae-eumin and Soyangin was 70% and 68% for men and women, respectively. The entire methods showed the possibility to distinguish between Tae-eumin and Soyangin by using stochastic properties of roughness index, which can make the entire system to include the measurement, the computation of the roughness index and the discrimination of constitution automatical. 4. Conclusions The measurement device, the automatic sampling algorithm of dynamic friction coefficients and the constitution discrimination algorithm were developed, respectively, and their combination can become the serial and automatic procedure for quantitative and objective skin diagnosis, which mimics the movement of the Oriental medical doctors' skin diagnosis. It can be applied to healthcare as well as the diagnosis of constitution in a u-Health system soon.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.71-77
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• 2015

This paper suggested dynamic application framework based data collecting and monitoring technique using wireless sensor network. The development of application for wireless measurement node firmware program integrates with various sensors and performs control. Collecting data of the user application is downloaded from the node onboard process wirelessly. In addition, the user application can change the temperature initial value of the nodes, which enables dynamic sampling of the measurement nodes. Therefore, dynamic sampling control of the nodes can reduce the power consumptions of sensors compared to existing wired data monitoring.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.1013-1020
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• 2021

This study examines the role of dynamic socio-emotional capabilities to increase proactive stakeholder engagement in family businesses. The research sample includes all furniture enterprises scattered in Jepara Regency sub-districts as many as 3,945 companies. The sampling in this research is purposive; as many as 210 respondents, 181 could be used. The sampling unit is the owners and managers, considering that most company owners are also company managers. This study examines how learning and supply chain management in the family business can be integrated to enable a set of resources and capabilities provided by the family to be developed to build closer relationships with stakeholders. The findings showed the importance of a family business's supply chain management perspective in the relationship between dynamic socio-emotional capabilities to mediate organizational learning to proactive stakeholder engagement significantly. Based on this study's results, companies can build dynamic socio-emotional capabilities through organizational learning to increase proactive stakeholder engagement. Dynamic socio-emotional capabilities proved to play a role as a mediator for organizational learning by family companies for proactive stakeholder engagement.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.2
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• pp.141-146
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• 2009

Support vector machine is a classification algorithm based on statistical learning theory. It has shown many results with good performances in the data mining fields. But there are some problems in the algorithm. One of the problems is its heavy computing cost. So we have been difficult to use the support vector machine in the dynamic and online systems. To overcome this problem we propose to use stratified sampling of statistical sampling theory. The usage of stratified sampling supports to reduce the size of training data. In our paper, though the size of data is small, the performance accuracy is maintained. We verify our improved performance by experimental results using data sets from UCI machine learning repository.

• Journal of Power Electronics
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• v.13 no.3
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• pp.349-361
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• 2013

As a result of the advantages such as high efficiency, continuous current and high stability margin, push-pull converter with continuous current (PPCWCC) is competitive for battery discharge regulator (BDR) which plays an important role in power conditioning unit (PCU). Leakage inductance yields current spike in low-ripple current of PPCWCCs. The operating modes are added due to leakage inductance. Therefore the steady state performance is affected, which is embodied in the spike of low-ripple current. PPCWCCs which are suitable for BDR can be separated into three types by current spike characteristics. Three representative topologies IIs1, IIcb2 and Is3 are analyzed in order to investigate the factors on the magnitude and duration of spike. Equivalent current sampling method (ECSM) which eliminates the sampling time delay and achieves excellent dynamic performance is adopted to prevent the spike disturbance on current sampling. However, ECSM reduces the sampling accuracy and telemetry accuracy due to neglecting the spike. In this paper, ECSM used in PPCWCCs is summarized. The current sampling error is analyzed in quality and quantity, which provides the foundation for offsetting and enhancing the telemetry accuracy. Finally, current sampling error rate of three topologies is compared by experiment results, which verify the theoretical analysis.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.2
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• pp.128-133
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• 2010

This paper presents a method for estimating the parameters of dynamic models for induction motor dominating loads. Using particle swarm optimization, the method finds the adequate set of parameters that best fit the sampling data from the measurement for a period of time, minimizing the error of the outputs, active and reactive power demands and satisfying the steady-state error criterion.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.723-729
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• 2005

Traditional statistical process control(SPC) applied to discrete part industry in the form of control charts can look for and eliminate assignable causes by process monitoring. On the other hand, engineering process control(EPC) applied to the process industry in the form of feedback control can maintain the process output on the target by continual adjustment of input variable. This study presents controlling and monitoring rules adopted variable sampling interval(VSI) to change sampling intervals in a predetermined fashion on the predicted process levels for integrated EPC and SPC systems. Twelve rules classified by EPC schemes(MMSE, constrained PI, bounded or deadband adjustment policy) and type of sampling interval combined with EWMA chart of SPC are proposed under IMA(1,1) disturbance model and zero-order (responsive) dynamic system. The properties of twelve control rules under three patterns of process change(sudden shift, drift and random shift) are evaluated and discussed through simulation and control rules for integrated VSI EPC and SPC systems are recommended.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1235-1238
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• 1987

In this paper, a new focusing method, to be called the sampled delay focusing (SDF), is proposed. This method improves the lateral resolution in ultrasound imaging system. In SDF, the analog delay lines are no longer necessary because sampling sum process can replace the conventional delay sum process. Also, this method offers continuous dynamic focusing on the resolution pixel basis if the maximum delay time is less than the sampling interval. Second order sampling is adopted in order to extend the sampling interval.

• International Journal of Control, Automation, and Systems
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• v.5 no.5
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• pp.515-525
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• 2007

In this paper, we develop a co-design methodology of stochastic optimal controllers and network parameters that optimizes the overall quality of control (QoC) in networked control systems (NCSs). A new dynamic model for NCSs is provided. The relationship between the system stability and performance and the sampling frequency is investigated, and the analysis of co-design of control and network parameters is presented to determine the working range of the sampling frequency in an NCS. This optimal sampling frequency range is derived based on the system dynamics and the network characteristics such as data rate, time-delay upper bound, data-packet size, and device processing time. With the optimal sampling frequency, stochastic optimal controllers are designed to improve the overall QoC in an NCS. This co-design methodology is a useful rule of thumb to choose the network and control parameters for NCS implementation. The feasibility and effectiveness of this co-design methodology is verified experimentally by our NCS test bed, a ball magnetic-levitation (maglev) system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.63
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• pp.33-43
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• 2001

To estimate the reliability of a large and complex network with a small variance, we propose two dynamic Monte Carlo sampling methods: the sequential minimal cut set (SMCS) and the sequential minimal path set (SMPS) methods. These methods do not require all minimal cut sets or path sets to be given in advance and do not simulate all arcs at each trial, which can decrease the valiance of network reliability. Based on the proposed methods, we develop the importance sampling estimators, the total hazard (or safety) estimator and the hazard (or safety) importance sampling estimator, and compare the performance of these simulation estimators. It is found that these estimators can significantly reduce the variance of the raw simulation estimator and the usual importance sampling estimator. Especially, the SMCS algorithm is very effective in case that the failure probabilities of arcs are low. On the contrary, the SMPS algorithm is effective in case that the success Probabilities of arcs are low.