• Title/Summary/Keyword: Model Generalization

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Determinants on the Absence of After-school Care among Elementary Students (초등학생의 방과 후 돌봄공백 유무 및 일수의 결정요인)

  • Kim, Jikyung;Kim, Gyunhee
    • The Korean Journal of Community Living Science
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    • v.24 no.1
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    • pp.51-70
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    • 2013
  • The purpose of the study was to analyze the determinants on the absence of after-school care among elementary students. This study is based on the National Children and Youth Panel Survey(2010) data and analyzed through Binary Logit Model and Multinominal Logit Model. The Following results were obtained: First, school grades, the number of siblings, mother's education, family type by parental employment, family structure, family type by parental nativity, and family income, all affected the absence of after-school care. Second, the absence days of after-school care was affected by different factors. 1day-2days a week in absence of after-school was more likely to increase among children with more siblings and an older father. On the other hand, spending over 3-4days a week without after-school care was more likely to increase among mothers with lower education, dual-earner families, multicultural families, lower family incomes, small cities and rural areas. Based on the results of this study, we agree with the generalization and the diversification of after-school care policy for elementary school students.

Application of Multi-Frontal Method in Collaborative Engineering Environment

  • Cho, Seong-Wook;Choi, Young;Lee, Gyu-Bong;Kwon, Ki-Eak
    • International Journal of CAD/CAM
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    • v.3 no.1_2
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    • pp.51-60
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    • 2003
  • The growth of the World Wide Web and the advances in high-speed network access have greatly changed existing CAD/CAE environment. The WWW has enabled us to share various distributed product data and to collaborate in the design process. An international standard for the product model data, STEP, and a standard for the distributed object technology, CORBA, are very important technological components for the interoperability in the advanced design and manufacturing environment. These two technologies provide background for the sharing of product data and the integration of applications on the network. This paper describes a distributed CAD/CAE environment that is integrated on the network by CORBA and product model data standard STEP. Several prototype application modules were implemented to verify the proposed concept and the test result is discussed. Finite element analysis server are further distributed into several frontal servers for the implementation of distributed parallel solution of finite element system equations. Distributed computation of analysis server is also implemented by using CORBA for the generalization of the proposed method.

Application of Generalized Transmission Line Models to Mixed Ionic-Electronic Transport Phenomena

  • Ahn, Pyung-An;Shin, Eui-Chol;Kim, Gye-Rok;Lee, Jong-Sook
    • Journal of the Korean Ceramic Society
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    • v.48 no.6
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    • pp.549-558
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    • 2011
  • Application of a generalized equivalent circuit including the electrode condition for the Hebb-Wagner polarization in the frequency domain proposed by Jamnik and Maier can provide a consistent set of material parameters, such as the geometric capacitance, partial conductivities, chemical capacitance or diffusivity, as well as electrode characteristics. Generalization of the shunt capacitors for the chemical capacitance by the constant phase elements (CPEs) was applied to a model mixed conducting system, $Ag_2S$, with electron-blocking AgI electrodes and ion-blocking Pt electrodes. While little difference resulted for the electron-blocking cell with almost ideal Warburg behavior, severely non-ideal behavior in the case of Pt electrodes not only necessitates a generalized transmission line model with shunt CPEs but also requires modelling of the leakage in the cell approximately proportional to the cell conductance, which then leads to partial conductivity values consistent with the electron-blocking case. Chemical capacitance was found to be closer to the true material property in the electron-blocking cell while excessively high chemical capacitance without expected silver activity dependence resulted in the electron-blocking cell. A chemical storage effect at internal boundaries is suggested to explain the anomalies in the respective blocking configurations.

Estimating the State-of-Charge of Lithium-Ion Batteries Using an H-Infinity Observer with Consideration of the Hysteresis Characteristic

  • Xie, Jiale;Ma, Jiachen;Sun, Yude;Li, Zonglin
    • Journal of Power Electronics
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    • v.16 no.2
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    • pp.643-653
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    • 2016
  • The conventional methods used to evaluate battery state-of-charge (SOC) cannot accommodate the chemistry nonlinearities, measurement inaccuracies and parameter perturbations involved in estimation systems. In this paper, an impedance-based equivalent circuit model has been constructed with respect to a LiFePO4 battery by approximating the electrochemical impedance spectrum (EIS) with RC circuits. The efficiencies of approximating the EIS with RC networks in different series-parallel forms are first discussed. Additionally, the typical hysteresis characteristic is modeled through an empirical approach. Subsequently, a methodology incorporating an H-infinity observer designated for open-circuit voltage (OCV) observation and a hysteresis model developed for OCV-SOC mapping is proposed. Thereafter, evaluation experiments under FUDS and UDDS test cycles are undertaken with varying temperatures and different current-sense bias. Experimental comparisons, in comparison with the EKF based method, indicate that the proposed SOC estimator is more effective and robust. Moreover, test results on a group of Li-ion batteries, from different manufacturers and of different chemistries, show that the proposed method has high generalization capability for all the three types of Li-ion batteries.

An Analysis of the Relationships between the Technology Acceptance Model and Switching Costs (기술수용모형과 전환비용의 관계 분석)

  • Lee, Woong-Kyu;Kwon, Jeong-Il
    • Journal of the Korean Operations Research and Management Science Society
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    • v.37 no.1
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    • pp.89-104
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    • 2012
  • As the generalization of using computer and the internet, most people, who would decide the acceptance of new information technology (IT), may consider the current systems which have been used so far. The objective of this study was to analyze the relationships between technology acceptance model (TAM) and the switching costs which may incur during switching from the current system into another on. For this purpose, this study suggested the hypotheses, in which continuity cost and setup cost, two types of switching costs in IT adoption, would influence perceived usefulness and perceived ease of use respectively. Moreover, the moderation effects of system types, hedonic system and utilitarian system, on the relationships between switching costs and TAM, were also suggested as the hypotheses. In order to prove the validity of the hypotheses, two groups were surveyed. Before surveying, to the one group who were believed to be a user of 'Cyworld', a new blog service, Naver Blog, was introduced. Similarly, to another group, Google Docs was introduced. The analysis by Partial Least Square (PLS) approach showed that most hypotheses in this study were statistically supported.

A Study on Multi-layer Fuzzy Inference System based on a Modified GMDH Algorithm (수정된 GMDH 알고리즘 기반 다층 퍼지 추론 시스템에 관한 연구)

  • Park, Byoung-Jun;Park, Chun-Seong;Oh, Sung-Kwun
    • Proceedings of the KIEE Conference
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    • 1998.11b
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    • pp.675-677
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    • 1998
  • In this paper, we propose the fuzzy inference algorithm with multi-layer structure. MFIS(Multi-layer Fuzzy Inference System) uses PNN(Polynomial Neural networks) structure and the fuzzy inference method. The PNN is the extended structure of the GMDH(Group Method of Data Hendling), and uses several types of polynomials such as linear, quadratic and cubic, as well as the biquadratic polynomial used in the GMDH. In the fuzzy inference method, the simplified and regression polynomial inference methods are used. Here, the regression polynomial inference is based on consequence of fuzzy rules with the polynomial equations such as linear, quadratic and cubic equation. Each node of the MFIS is defined as fuzzy rules and its structure is a kind of neuro-fuzzy structure. We use the training and testing data set to obtain a balance between the approximation and the generalization of process model. Several numerical examples are used to evaluate the performance of the our proposed model.

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Hyper-Geometric Distribution Software Reliability Growth Model : Generalizatio, Estimation and Prediction (초기하분포 소프트웨어 신뢰성 성장 모델 : 일반화, 추정과 예측)

  • Park, Jung-Yang;Yu, Chang-Yeol;Park, Jae-Hong
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.9
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    • pp.2343-2349
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    • 1999
  • The hyper-geometric distribution software reliability growth model (HGDM) was recently developed and successfully applied to real data sets. The HGDM considers the sensitivity factor as a parameter to be estimated. In order to reflect the random behavior of the test-and-debug process, this paper generalizes the HGDM by assuming that the sensitivity factor is a binomial random variable. Such a generalization enables us to easily understand the statistical characteristics of the HGDM. It is shown that the least squares method produces the identical results for both the HGDM and the generalized HGDM. Methods for computing the maximum likelihood estimates and predicting the future outcomes are also presented.

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A New Design Approach for Optimization of GA-based SOPNN (GA 기반 자기구성 다항식 뉴럴 네트워크의 최적화를 위한 새로운 설계 방법)

  • Park, Ho-Sung;Park, Byoung-Jun;Park, Keon-Jun;Oh, Sung-Kwun
    • Proceedings of the KIEE Conference
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    • 2003.07d
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    • pp.2627-2629
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    • 2003
  • In this paper, we propose a new architecture of Genetic Algorithms(GAs)-based Self-Organizing Polynomial Neural Networks(SOPNN). The conventional SOPNN is based on the extended Group Method of Data Handling(GMDH) method and utilized the polynomial order (viz. linear, quadratic, and modified quadratic) as well as the number of node inputs fixed (selected in advance by designer) at Polynomial Neurons (or nodes) located in each layer through a growth process of the network. Moreover it does not guarantee that the SOPNN generated through learning has the optimal network architecture. But the proposed GA-based SOPNN enable the architecture to be a structurally more optimized networks, and to be much more flexible and preferable neural network than the conventional SOPNN. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. To evaluate the performance of the GA-based SOPNN, the model is experimented with using nonlinear system data.

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Optimization of multi-water resources in economical and sustainable way satisfying different water requirements for the water security of an area

  • Gnawali, Kapil;Han, KukHeon;Koo, KangMin;Yum, KyungTaek;Jun, Kyung Soo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.161-161
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    • 2019
  • Water security issues, stimulated by increasing population and changing climate, are growing and pausing major challenges for water resources managers around the world. Proper utilization, management and distribution of all available water resources is key to sustainable development for achieving water security To alleviate the water shortage, most of the current research on multi-sources combined water supplies depends on an overall generalization of regional water supply systems, which are seldom broken down into the detail required to address specific research objectives. This paper proposes the concept of optimization framework on multi water sources selection. A multi-objective water allocation model with four objective functions is introduced in this paper. Harmony search algorithm is employed to solve the applied model. The objective functions addresses the economic, environmental, and social factors that must be considered for achieving a sustainable water allocation to solve the issue of water security.

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An Integrated Artificial Neural Network-based Precipitation Revision Model

  • Li, Tao;Xu, Wenduo;Wang, Li Na;Li, Ningpeng;Ren, Yongjun;Xia, Jinyue
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.5
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    • pp.1690-1707
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    • 2021
  • Precipitation prediction during flood season has been a key task of climate prediction for a long time. This type of prediction is linked with the national economy and people's livelihood, and is also one of the difficult problems in climatology. At present, there are some precipitation forecast models for the flood season, but there are also some deviations from these models, which makes it difficult to forecast accurately. In this paper, based on the measured precipitation data from the flood season from 1993 to 2019 and the precipitation return data of CWRF, ANN cycle modeling and a weighted integration method is used to correct the CWRF used in today's operational systems. The MAE and TCC of the precipitation forecast in the flood season are used to check the prediction performance of the proposed algorithm model. The results demonstrate a good correction effect for the proposed algorithm. In particular, the MAE error of the new algorithm is reduced by about 50%, while the time correlation TCC is improved by about 40%. Therefore, both the generalization of the correction results and the prediction performance are improved.