• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.397-402
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• 2003

This paper proposes an efficient fixed-point (FP) algorithm for improving performances of the independent component analysis (ICA) based on neural networks. The proposed algorithm is the FP algorithm based on Newton method for ICA using the adaptive learning parameters. The purpose of this algorithm is to improve the separation speed and performance by using the learning parameters in Newton method, which is based on the first order differential computation of entropy optimization function. The learning rate and the moment are adaptively adjusted according to an updating state of inverse mixing matrix. The proposed algorithm has been applied to the fingerprints and the images generated by random mixing matrix in the 8 fingerprints of 256${\times}$256-pixel and the 10 images of 512$\times$512-pixel, respectively. The simulation results show that the proposed algorithm has the separation speed and performance better than those using the conventional FP algorithm based on Newton method. Especially, the proposed algorithm gives relatively larger improvement degree as the problem size increases.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1804-1807
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• 1997

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learnign architecture. It is proposed a learning controller consisting of two neural networks-fuzzy based on independent reasoning and a connecton net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Journal of Power System Engineering
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• v.2 no.3
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• pp.74-82
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• 1998

This paper presents a new approach to the design of speed and azimuth control of a mobile robot with two drive wheels. The proposed control scheme uses a Gaussian function as a unit function in the neural-fuzzy network and back propagation algorithm to train the neural-fuzzy network controller in the framework of the specialized learning architecture. It is proposed to a learned controller with two neural-fuzzy networks based on an independent reasoning and a connection net with fixed weights to simplify the neural-fuzzy network. The performance of the proposed controller can be seen by the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• ETRI Journal
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• v.40 no.5
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• pp.634-642
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• 2018

Projection spectral analysis is investigated and refined in this paper, in order to unify principal component analysis and independent component analysis. Singular value decomposition and spectral theorems are applied to nonsymmetric correlation or covariance matrices with multiplicities or singularities, where projections and nilpotents are obtained. Therefore, the suggested approach not only utilizes a sum-product of orthogonal projection operators and real distinct eigenvalues for squared singular values, but also reduces the dimension of correlation or covariance if there are multiple zero eigenvalues. Moreover, incremental learning strategies of projection spectral analysis are also suggested to improve the performance.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.3
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• pp.36-45
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• 2011

An agent in collaborative e-learning has independent function for learners in any circumstance, status and task by the reasonable and general means for social learning. In order to perform it well, communication among agents requires standardized and regular information technology method. This study suggests data model as a communication tool for various agents. Therefore this study shows various agents types for collaborative learning, designation of rule for data model that enable to communicate among agents and data element of agent communication data model. A multi-agent e-learning system using like this standardized data model should able to exchange the message that is needed for communication among agents who can take charge of their independent tasks. This study should contribute to perform collaborative e-learning successfully by the application of communication data model among agents for social learning.

• The Journal of the Korea Contents Association
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• v.19 no.8
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• pp.556-564
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• 2019

The purpose of this study is to examine the effects of team based learning on academic achievement, problem solving skill, and communication ability in high risk pregnant nursing. This experimental study is designed for a equivalent control group. The program was put into practice 1 times a week for 8 weeks. The number of subjects in this research consists of 120, where 60 of the experimental group participated in team based learning program and 60 of the control group didn't do. The data was analyzed by ${\chi}^2-test$, Fisher's exact test, independent t-test, and paired t-test. The effects of team based learning approaches on learning outcomes in high risk pregnant nursing are as follows: The problem solving skill of the experimental group has been significantly more elevated than that of the control group. The experimental group has made increase in communication ability. This study has significance in that it identified the availability of the team based learning program and that it would be useful teaching and learning method to achieve learning outcomes.

• Journal of Industrial Convergence
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• v.20 no.10
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• pp.225-232
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• 2022

This study purpose was to identify the effect of simulation education based on Blended Learning on Nursing students' Knowledge, performance, Learning satisfaction to ACLS. Methods was nonequivalent control group pretest-posttest design. The participants were 88 students 4 grade from the Department of Nursing at C University. The study period was from September 1 to December 31, 2021, and Data were analyzed with X² test, independent t-test using SPSS 22.0 program. The research results show that the experimental group showed significantly higher performance(t=-9.843, p=.001) and learning satisfaction(t=-3.484, p<.001) for ACLS compared with the control group. In conclusion, it was suggested that ACLS simulation education based on Blended Learning is an effective teaching method to improve nursing students' performance and learning satisfaction.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.31-42
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• 2024

Different industries mostly rely on quality certification for promoting their products or brands. Although getting quality certification, specifically by human experts is a tough job to do. But the field of machine learning play a vital role in every aspect of life, if we talk about quality certification, machine learning is having a lot of applications concerning, assigning and assessing quality certifications to different products on a macro level. Like other brands, wine is also having different brands. In order to ensure the quality of wine, machine learning plays an important role. In this research, we use two datasets that are publicly available on the "UC Irvine machine learning repository", for predicting the wine quality. Datasets that we have opted for our experimental research study were comprised of white wine and red wine datasets, there are 1599 records for red wine and 4898 records for white wine datasets. The research study was twofold. First, we have used a technique called backward elimination in order to find out the dependency of the dependent variable on the independent variable and predict the dependent variable, the technique is useful for predicting which independent variable has maximum probability for improving the wine quality. Second, we used a robust machine learning algorithm known as "XGBoost" for efficient prediction of wine quality. We evaluate our model on the basis of error measures, root mean square error, mean absolute error, R2 error and mean square error. We have compared the results generated by "XGBoost" with the other state-of-the-art machine learning techniques, experimental results have showed, "XGBoost" outperform as compared to other state of the art machine learning techniques.

• Journal of Information Technology Applications and Management
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• v.21 no.4
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• pp.141-156
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• 2014

This study intended to evaluate the viability of cyber education in terms of learning satisfaction and learning achievement. The study integrated two research streams such as social presence model and learning environment model. Where the learning environment model emphasizes the components of learning aids, social presence model considers more deeply the relationships among peers and with instructors. These two research streams have been considered relatively independently. The study integrated these ideas and measured their reliabilities and validities. The results demonstrate that the two constructs are relevantly independent and both of these constructs are very important considerations for the success of cyber education. The study concludes that cyber education 2.0 requires more social presence factors than the learning environment factors such as technological development or new equipments.

• IE interfaces
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• v.23 no.3
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• pp.205-212
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• 2010

The learning curve model is a mathematical form which represents the relationship between the manufacturing experience and its effectiveness. The semiconductor manufacturing is widely known as an appropriate example for the learning effect due to its complicated manufacturing processes. In this paper, I propose a new compound learning curve model for semiconductor products in which the general learning curve model and the growth curve are composed. The dependent variable and the effective independent variables of the model were abstracted from the existing learning curve models and selected according to multiple regression processes. The simulation results using the historical DRAM data show that the proposed compound learning curve model is one of adequate models for describing learning effect of semiconductor products.