• Korean Journal of Child Studies
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• v.33 no.6
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• pp.71-84
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• 2012

The purpose of this study is to analyze the relationship between decision making abilities young children and their self-directed learning abilities. A survey was carried out using 160 young children in the J region. The collected data were analyzed by Pearson correlation and multiple regression techniques using the SPSS statistics program. The conclusions are as follows : First, decision making abilities in young children exhibited a positive correlation with their self-directed learning abilities. Second, decision making abilities in young children were an influential variable in terms of their self-directed learning abilities. As a result, decision making abilities in young children were an important variable in predicting their self-directed learning abilities.

• Journal of Fisheries and Marine Sciences Education
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• v.27 no.4
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• pp.901-911
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• 2015

This article starts with a review of the e-self directed learning, future time perspective and decision making, especially in relation to the career myths. In particular, we empirically analyzed the factors affecting the future time perspective and the decision making on the characteristics of career myths(e.g. relatedness of the test myths, the supreme myth and the family myths). Hence the main purpose of this article is to suggest an empirical model explaining how these factors affect e-self directed learning to future time perspective and decision making. Furthermore, we suggested an expanded model about future time perspective, decision making and especially in relation to the career myths. We founded that the e-self directed learning significantly affect the future time perspective and the decision making, also the future time perspective affect the test myths and family myths except the supreme myths and the decision making significantly affect the career myths(i.e., the test myths, the supreme myth, the family myths).

• Journal of Advanced Navigation Technology
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• v.16 no.6
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• pp.982-987
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• 2012

In this paper, the SNR estimation error of Decision Directed SNR estimation method in AWGN is investigated, which uses samples received in reference decision region. In communication system receiver, when SNR estimation scheme using error vectors between ideal sample points and received sample points of reference region is adopted, the samples contain incorrectly received samples due to AWGN. Consequently, the mean of estimated reference constellation point is shifted and Decision Directed SNR estimation is inaccurately performed. These effects are explained by modified probability density function and difference between actual SNR and estimated SNR is theoretically derived and quantatively analyzed. It is proved that SNR estimation error obtained through computer simulation is matched up with derived one, and SNR estimation performance is enhanced significantly by adopting suggested correction scheme.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.3
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• pp.73-80
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• 2010

Complex-valued blind algorithms which are based on constant modulus error and Euclidian distance (ED) between two probability density functions show relatively poor performance in spite of the advantages of information theoretic learning since the inherent characteristics of the constant modulus error prevent the algorithm from coping with the symbol phase rotation caused by the complex channels. In this paper, we show that the symbol phase rotation problem can be avoided and the advantages of information theoretic learning can be preserved by introducing decision-directed mode to the blind algorithm whenever the equalizer output power lies in the neighborhood of multi-modulus levels. Simulation results through MSE convergence and constellation comparison for severely distorted complex channels show significantly enhanced performance of symbol-point concentration and no phase rotation problems caused by the complex channel models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2C
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• pp.234-241
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• 2009

TETRA Enhanced Data Service (TEDS), which is an upgrade version of narrow-band ETSI TETRA Release 1 system, can support high speed packet data services in frequency selected fading channel. The performance of M-QAM transceivers employed in the TEDS is significantly affected by the accuracy of channel estimation. In this paper, we consider the design of a decision-directed channel estimation scheme robust to fast fading by estimating the channel by means of a per-survivor processing (PSP) method. The performance of the proposed channel estimation scheme is verified by computer simulation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.2
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• pp.78-85
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• 2002

We introduce a rotational decision-directed joint algorithm of blind equalization coupled with carrier recovery for 32-QAM demodulation with high symbol rate. The proposed carrier recovery, which we call a rotational decision-directed carrier recovery(RDDCR), removes the residual phase difference by rotating the decision boundary for the kth received symbol by the frequency detector output of the (k-1)th received symbol. Since the RDDCR includes the function of PLL loop filter by rotating the decision boundary, it gives a simpler demodulator structure. The rotational decision-directed blind equalization(RDDBE) with the rotated decision boundary based on the Stop-and-Go Algorithm(SGA) operated during tracking the frequency offset by the RDDCR and removes intersymbol interference due to multipaths and channel noise. Test results show that symbol error rate of $10^{-3}$ is obtained before the forward error correction when SNR equals 15dB with 150KHz of carrier frequency offset and two multipaths, which is the channel condition for 32-QAM receiver.

• The Journal of Information Technology
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• v.2 no.1
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• pp.103-113
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• 1999

In this paper, we propose th soft decision-directed sto-and-go algorithm combining a concept of the stop-and-go algorithm with soft decision-directed algorithm. The proposed algorithm has an enhanced equalization performance according to using the more confidential error signal than two algorithms. By computer simulation, it is confirmed that the proposed algorithm has the performance superiority in terms of residual ISI and convergence speed compared with the adaptive blind equalization algorithm of CMA, Modified CMA(MCMA), Stop-and Go algorithm and simplified 50ft decision-directed algorithm.

• English Language & Literature Teaching
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• v.12 no.4
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• pp.159-183
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• 2006

The purpose of this study is to investigate Korean primary school English teachers' beliefs on self-directed teaching and learning for facilitating student's self-directed learning. A survey was conducted, using 315 primary school teachers as participants. According to different school areas, sex, English teaching careers, and types of English teaching like classroom teachers or English specialist teachers, beliefs on teachers' self-directed teaching were studied based on class planning, class process, utilization of human resources, development and utilization of teaching materials and class evaluation. The results of this study are as follows: first, differences were not shown except class planning according to teachers from different school areas. Second, sex and beliefs of teachers' self-directed teaching had nothing in common. Third, differences were shown in class planning and class process, according to English teaching careers. Finally, according to types of English teaching, differences were shown in class process and development and utilization of teaching materials. The study suggests that it is necessary to conduct other studies for observing primary English classrooms focusing on teacher's self-directed decision-making.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4007-4024
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• 2020

It is tremendously important to construct decision trees to use as a tool for knowledge representation from a given decision table. However, the usual algorithms may split the decision table based on each value, which is not efficient for numerical attributes. The methodology of this paper is to split the given decision table into binary groups as like the CART algorithm, that uses binary split to work for both categorical and numerical attributes. The difference is that it uses split for each attribute established by the directed acyclic graph in a dynamic programming fashion whereas, the CART uses binary split among all considered attributes in a greedy fashion. The aim of this paper is to study the effect of binary splits in comparison with each value splits when building the decision trees. Such effect can be studied by comparing the number of nodes, local and global misclassification rate among the constructed decision trees based on three proposed algorithms.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.10
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• pp.1012-1015
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• 2011

The decision-directed blind equalization algorithm is often used due to its simplicity and good convergence property when the eye pattern is open. However, in a channel where the eye pattern is closed, the decision-directed algorithm is not guaranteed to converge. Hence, a modified Bussgang-type algorithm using a hyperbolic tangent function for zero-memory nonlinear(ZNL) function has been proposed and applied to avoid this problem by Filho et al. But application of this algorithm includes the calculation of hyperbolic tangent function and its derivative or a look-up table which may need a large amount of memory due to channel variations. To reduce the computational and/or hardware complexity of Filho's algorithm, in this paper, an improved method for the decision-directed algorithm is proposed. In the proposed scheme, the ZNL function and its derivative are respectively set to be the original signum function and a narrow rectangular pulse which is an approximation of Dirac delta function. It is shown that the proposed scheme, when it is combined with decision-directed algorithm, reduces the computational complexity drastically while it retains the convergence and steady-state performance of the Filho's algorithm.