• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1071-1083
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• 2005

By estimating probability distributions of the good solutions in the current population, some researchers try to find the optimal solution more efficiently. Particularly, finite mixtures of distributions have a very useful role in dealing with complex problems. However, it is difficult to choose the number of components in the mixture models and merge superior partial solutions represented by each component. In this paper, we propose a new continuous evolutionary optimization algorithm with distribution estimation by variational Bayesian mixtures of factor analyzers. This technique can estimate the number of mixtures automatically and combine good sub-solutions by sampling new individuals with the latent variables. In a comparison with two probabilistic model-based evolutionary algorithms, the proposed scheme achieves superior performance on the traditional benchmark function optimization. We also successfully estimate the parameters of S-system for the dynamic modeling of biochemical networks.

• Journal of Digital Convergence
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• v.18 no.8
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• pp.231-242
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• 2020

The thesis presents a system that continuously collects the human body's physiological vital information at rest with sensors and ICT information technology and predicts diabetes using the collected information. it shows the artificial neural network machine learning method and essential basic variable values. The study method analyzed the correlation between heart rate measurements of BCG and ECG sensors in 20 DM- and 15 DM+ subjects. Artificial Neural Network (ANN) machine learning program was used to predictability of diabetes. The input variables are time domain information of HRV, heart rate, heart rate variability, respiration rate, stroke volume, minimum blood pressure, highest blood pressure, age, and sex. ANN machine learning prediction accuracy is 99.53%. Thesis needs continuous research such as diabetic prediction model by BMI information, predicting cardiac dysfunction, and sleep disorder analysis model using ANN machine learning.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1886-1900
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• 2018

This paper proposes a confronting feedback control structure and controllers for positive output elementary super lift Luo converters (POESLLCs) working in discontinuous conduction mode (DCM). The POESLLC offers the merits like high voltage transfer gain, good efficiency, and minimized coil current and capacitor voltage ripples. The POESLLC working in DCM holds the value of not having right half pole zero (RHPZ) in their control to output transfer function unlike continuous conduction mode (CCM). Also the DCM bestows superlative dynamic response, eliminates the reverse recovery troubles of diode and retains the stability. The proposed control structure involves two controllers respectively to control the voltage (outer) loop and the current (inner) loop to confront the time-varying ON/OFF characteristics of variable structured systems (VSSs) like POESLLC. This study involves two different combination of feedback controllers viz. the proportional integral controller (PIC) plus sliding mode controller (SMC) and the fuzzy logic controller (FLC) plus SMC. The state space averaging modeling of POESLLC in DCM is reviewed first, then design of PIC, FLC and SMC are detailed. The performance of developed controller combinations is studied at different working states of the POESLLC system by MATLAB-Simulink implementation. Further the experimental corroboration is done through implementation of the developed controllers in PIC 16F877A processor. The prototype uses IRF250 MOSFET, IR2110 driver and UF5408 diodes. The results reassured the proficiency of designed FLC plus SMC combination over its counterpart PIC plus SMC.

• Journal of Multimedia Information System
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• v.5 no.4
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• pp.235-244
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• 2018

Potential maximum soil moisture retention (S) is a dominant parameter in the Soil Conservation Service (SCS; now called the USDA Natural Resources Conservation Service (NRCS)) runoff Curve Number (CN) method commonly used in hydrologic modeling for event-based flood forecasting (SCS, 1985). Physically, S represents the depth [L] soil could store water through infiltration. The depth of soil moisture retention will vary depending on infiltration from previous rainfall events; an adjustment is usually made using a factor for Antecedent Moisture Conditions (AMCs). Application of the method for continuous simulation of multiple storms has typically involved updating the AMC and S. However, these studies have focused on a time step where S is allowed to vary at daily or longer time scales. While useful for hydrologic events that span multiple days, this temporal resolution is too coarse for short-term applications such as flash flood events. In this study, an approach for deriving a time-variable potential maximum soil moisture retention curve (S-curve) at hourly time-scales is presented. The methodology is applied to the Napa River basin, California. Rainfall events from 2011 to 2012 are used for estimating the event-based S. As a result, we derive an S-curve which is classified into three sections depending on the recovery rate of S for soil moisture conditions ranging from 1) dry, 2) transitional from dry to wet, and 3) wet. The first section is described as gradually increasing recovering S (0.97 mm/hr or 23.28 mm/day), the second section is described as steeply recovering S (2.11 mm/hr or 50.64 mm/day) and the third section is described as gradually decreasing recovery (0.34 mm/hr or 8.16 mm/day). Using the S-curve, we can estimate the hourly change of soil moisture content according to the time duration after rainfall cessation, which is then used to estimate direct runoff for a continuous simulation for flood forecasting.

• Journal of Dental Rehabilitation and Applied Science
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• v.26 no.1
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• pp.59-68
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• 2010

Recently, dental implants extensively inserted on edentulous area show highly clinical success rate. However, clinicians cannot exclude the possibility of failure and it often unexpectively occures. Many possible factors associated with failure of dental implants have been reported but controversy exists over the extent to them. In this study, we collected 212 patients who had been inserted 358 dental implants on mandibular premolar and molar area from 2005 to 2006. The survival rate of fixtures was recorded according to age of patients, implantation site, implant system, diameter and length of fixtures. Multi-variable analysis using SPSS chi-square test was operated to verify relation of each factors and survival rates. Accumulative survival rate was 98.3% for 3 years. Only diameter of fixtures was related to the implant survival rate. This may be thought that wider fixtures had been chosen to rescue implants or used in sites of poor bone quality. Further continuous study will be needed for direct guidance associated with survival rate of implants.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.4
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• pp.75-89
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• 2019

In the case of SMEs, entrepreneurship that organizes only core functions with the minimum number of people is increasing, and a responsibility management system focusing on core functions is emphasized, so that the interest in innovation behavior and survival strategy of enterprises is getting bigger. However, in the case of SMEs, it is not easy to pursue continuous innovation due to lack of capital and lack of professional manpower. The purpose of this study is to investigate the effect of SME on innovation behavior by selecting exploratory study and literature study for SMEs. The data for this study were 545 out of the total 600 copies distributed to employees in SMEs. The data were analyzed using SPSS 21.0 and amos18.0. First, product diversification, strategy formulation, and R & D have a significant effect on innovation behavior, and market diversification has no effect on innovation behavior. Second, working variables such as product diversification, market diversification, strategy formulation, and R & D do not control the influence of innovative behavior on innovation behavior. Third, the rank variable, which is the controlling variable, controls the magnitude of the effect of product diversification, market diversification, strategy formulation, and R & D on innovation behavior. As a result, corporate managers should lead the organization in order to promote product diversification, market diversification strategy, R & D and innovation activities. After discussing the conclusions and implications of this study, this study presented the direction of the research for the follow-up study.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.241-241
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• 2012

Semiconductor industry has been taking the advantage of improvements in process technology in order to maintain reduced device geometries and stringent performance specifications. This results in semiconductor manufacturing processes became hundreds in sequence, it is continuously expected to be increased. This may in turn reduce the yield. With a large amount of investment at stake, this motivates tighter process control and fault diagnosis. The continuous improvement in semiconductor industry demands advancements in process control and monitoring to the same degree. Any fault in the process must be detected and classified with a high degree of precision, and it is desired to be diagnosed if possible. The detected abnormality in the system is then classified to locate the source of the variation. The performance of a fault detection system is directly reflected in the yield. Therefore a highly capable fault detection system is always desirable. In this research, time series modeling of the data from an etch equipment has been investigated for the ultimate purpose of fault diagnosis. The tool data consisted of number of different parameters each being recorded at fixed time points. As the data had been collected for a number of runs, it was not synchronized due to variable delays and offsets in data acquisition system and networks. The data was then synchronized using a variant of Dynamic Time Warping (DTW) algorithm. The AutoRegressive Integrated Moving Average (ARIMA) model was then applied on the synchronized data. The ARIMA model combines both the Autoregressive model and the Moving Average model to relate the present value of the time series to its past values. As the new values of parameters are received from the equipment, the model uses them and the previous ones to provide predictions of one step ahead for each parameter. The statistical comparison of these predictions with the actual values, gives us the each parameter's probability of fault, at each time point and (once a run gets finished) for each run. This work will be extended by applying a suitable probability generating function and combining the probabilities of different parameters using Dempster-Shafer Theory (DST). DST provides a way to combine evidence that is available from different sources and gives a joint degree of belief in a hypothesis. This will give us a combined belief of fault in the process with a high precision.

• Journal of Biomedical Engineering Research
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• v.24 no.4
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• pp.319-328
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• 2003

The purpose of this paper is to develop a medical laser system using the semiconductor diode laser in order to photodynamic cancel therapy as a light source. The ideal light source for photodynamic therapy would be a homogeneous nondiverging light with variable spot size and specific wavelength with stability. After due consideration in this point, in this paper, we used a diode laser resonator of 635nm wavelength. The development laser system have a statistical laser out beam with accuracy control using the constant current control of method and clinic-friendly with compact. In order to protect the diode resonator from the over-current, the rush-current and electrical fault, we specially designed. The most importance therapeutic factor are the radiation mode for cancer therapy. So we developed the radiation mode of CW(Continuous Wave), long pulse, short pulse, and burst pulse and can adjust the exposure time from several milli-second to several minute. The experimental result shows that laser beam power was increased linear from 10mW to 300mW according to the increasing input current and the increasing exposure time. The developed new compact diode laser system have a stability of output power and specific wavelength with easy control and transportable for many applications of PDT.

• The Korean Journal of Petroleum Geology
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• v.5 no.1_2 s.6
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• pp.36-47
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• 1997

This study presents multi-variable sequence model for a broader application of sequence concept proposed by Exxon group. The concept of the multi-variable model is based on the fact that internal organization and boundary type of the sequences are determined by three varying factors including 3rd-order cycles of eustasy, and tectonic movement and sediment influx with 2nd-order changes. Instead of Exxon group's systems tracts, this model adopts parasequence sets as the fundamental building blocks of the sequence, because they are descriptive stratigraphic units simply defined by internal stacking pattern, reflecting interactions of accommodation and sediment influx. Seven sequence types which vary in number and type of internal parasequence sets are formulated as associations of four types of accommodation development and three grades of sediment influx. In the southwestern margin of Ulleung Basin, the multi-variable sequence analysis of shelf-slope sequence shows systematic changes in stratal patterns and the numbs, of constituent parasequence sets (i.e. sequence type). These changes are interpreted to reflect temporal and spatial changes in type and rate of tectonic movement and sediment influx, as a result of back-arc opening and closing. During the back-arc opening, rapid subsidence, continuous rise of relative sea level, and high sediment influx gave rise to sequences dominantly of single progradational parasequence set. In the early stage of back-arc closing accompanied by local contractional deformation, different types of sequences contemporaneously formed depending on the spatial changes in tectonically-controlled accommodation and influx rates. During the subsequent slow back-arc subsidence, rise-dominated relative sea-level cycle was coupled with moderate to high sedimentation rate to have resulted in sequences consisting of $2~3$ parasequence sets.

• Journal of Distribution Science
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• v.12 no.12
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• pp.101-106
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• 2014

Purpose - This study reviews the achievements of a pilot project for the revitalization of a commercial district performed for three years after its establishment in 2011. The project for the revitalization of the commercial district was performed to create a new local community space in connection with the traditional market and nearby districts. Although it was a pilot project, the project for the revitalization of the commercial district has been performed for almost three years. Therefore, this seems a proper time to conduct an interim evaluation of the project. This study aims to review and evaluate how the government support policy is influential for the revitalization of the commercial district. In other words, this research aims to identify what projects positively affected consumers' intention to revisit the downtown commercial area among the commercial district revitalization projects-promotion events, promotion activities, education, merchants cooperation system, IT projects, cultural events, and residents' communication. Research design, data, and methodology - This study designated seven management improvement projects affecting commercial district revitalization based on preceding studies. The survey of the degree of satisfaction on seven management improvement projects was executed targeting consumers who visited the commercial areas. Additionally, visitors' revisit intentions regarding currently visited commercial areas were also investigated. Therefore, revisit intention was set as a dependent variable and the satisfaction degrees of the respective management improvement projects were set as the independent variables. A total of 1,209 consumers were examined in six districts in the country. Result - Multiple regression analysis results showed that cultural events, education, the merchants' cooperation system, and IT projects brought statistically significant effects to the revisit intentions of consumers. In contrast, promotion events, resident communication projects, and promotion activities did not affect the revisit intentions of consumers. Particularly, the residents' communication project did not show significant influence because of consumers' recognition that it is similar to a cultural event. Conclusion - The following implications for the revitalization of business districts in the urban central area are drawn. From a general perspective, the businesses of culture, education, and cooperative system among seven businesses play positive roles regarding the intention to revisit so that the project is required to be promoted periodically through unique performances differentiated for each district, the merchant training reinforced for professionalism, and the expansion of joint events of merchants. Moreover, the sales promotion project and public relations activity are shown to be not influential to the intention to revisit. Therefore, while short-term sales promotion such as one-time gift events are required, sales promotion and public relation activities to induce revisits by mileage savings and accumulated gift presentation to attract long-term customers are required. The IT business is positively influential to the intention of revisit. Therefore, detailed information on the revitalized commercial district should be provided and additional functions such as discount coupons for continuous utilization should be included in the mobile app and the website.