• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.57-65
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• 1998

This paper addresses the data classification using the induction of decision trees. A weakness of other techniques of induction of decision trees is that decision trees are too large because they construct decision trees until leaf nodes have a single class. Our study include both overcoming this weakness and constructing decision trees which is small and accurate. First, we construct the decision trees using classification threshold and exception threshold in construction stage. Next, we present two stage pruning method using classification threshold and reduced error pruning in pruning stage. Empirical results show that our method obtain the decision trees which is accurate and small.

• Korean Journal of Construction Engineering and Management
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• v.18 no.6
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• pp.98-108
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• 2017

Recently, the development of middle and high-rise building technology using modular construction method has emphasized the importance of site construction error management. The modular construction method is very limited to adjust the construction error in the field because of the factory production characteristics. Therefore, in order to prevent the construction error in advance, a management plan reflecting the characteristics of the modular construction method is required, and it is important to make the decision of the construction participant at each stage. This study analyzed the factor of construction error of modular construction and suggested a decision support model for construction error management based on construction process. The result of this study is expected to be a guideline for the modular construction participant to derive the construction error management plan.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.10
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• pp.78-87
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• 1996

In this paper, a remeshing criterion has been suggested in order to order to automate the remeshing decision during finite element analysis of metal forming. In order to use for the remeshing decision, two of remeshing criteria have been investigated. One is the use of error estimates based on errors in stresses and strain rate of the finite element solution and the other is the use of geometric characterisreics of distorted elements. As a result, the strain rate error estimate in power norm based on the former is found to give more valuable information about remeshing decision than the ones based on the latter. Examples are given to demon- strate the usefulness of the suggested eroor estimate as a remeshing criterion.

• Journal of Sensor Science and Technology
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• v.23 no.1
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• pp.1-6
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• 2014

In many medical image devices, dc noise often prevents normal diagnosis. In wireless capsule endoscopy systems, multipath fading through indoor wireless links induces inter-symbol interference (ISI) and indoor electric devices generate impulsive noise in the received signal. Moreover, dc noise, ISI, and impulsive noise are also found in optical fiber communication that can be used in remote medical diagnosis. In this paper, a blind signal processing method based on the biased probability density functions of constant modulus error that is robust to those problems that can cause error propagation in decision feedback (DF) methods is presented. Based on this property of robustness to error propagation, a DF version of the method is proposed. In the simulation for the impulse response of optical fiber channels having slowly varying dc noise and impulsive noise, the proposed DF method yields a performance enhancement of approximately 10 dB in mean squared error over its linear counterpart.

• 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 Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.2035-2042
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• 1997

We consider the design of soft decision functions for each stage of multistage detection for coherent demodulation in an asynchronous code-division multiple-access(CDMA) system. In particular, the sigmoid function, which is shown to be optimal under the mean square error(MSE) criterion, andmultilevel quantizers that best approximate the sigmoid function are derived. At each stage of multistage detection, the parameters of these decision functions are adjusted depending on estimated input statistics. Computer simulation results demonstrate that multistage detectors employing these soft decision functions perform considerably better than those with hard decision.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.5
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• pp.27-33
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• 2011

In digital communication system that the Modified Constant Modulus Algorithm (MCMA) reduced the use of the adaptive equalization algorithm to combat the Inter-symbol Interference (ISI). MCMA is relatively brief operation. The major point of MCMA that it only achieves moderate convergence rate and steady state mean square error (MSE). In this paper suggest, MCMA equalization improve the performance with parallel structure. It combines Modified Constant Modulus Algorithm(MCMA) and Modified Decision Directed(MDD) algorithm. By exploiting the inherent structural relationship between the 4-QAM signal's coordinates and 16-QAM signal's coordinates, another style of cost function for Modified Constant Modulus Algorithm(MCMA) is defined and If it happen to offset of received signals and MCMA is poor performance in order to overcome this because the paper combines apply for MCMA and MDD(Modified Decision Direct) algorithm. By computer simulation, we confirmed that the proposed PMCMA-MDD algorithm has the fater convergence rate and steady mean square error than the conventional MCMA.

• Journal of Broadcast Engineering
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• v.8 no.4
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• pp.481-491
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• 2003

We present a near-optimal blind decision feedback equalizer (DFE) for Advanced Television Systems Committee digital television (DTV) receivers. By adopting a modified trellis decoder (MTD) with trace back depth of 1 for the decision device In the DFE, we obtain a hardware-efficient near-optimal blind DFE approaching to the optimal DFE which has no error propagation. The MTD uses absolute distance instead of Euclidean distance for computation of a path metric, resulting. In reduced computational complexity. Comparing to the conventional slicer, the MTD shows outstanding performance improvement of decision error probability and is comparable to the original trellis decoder using Euclidean distance. Reducing error propagation in the DFE leads to the improvement of convergence performance in terms of convergence speed and residual error. Simulation results show that the proposed blind DFE performs much better than the blind DFE with the slicer.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2451-2458
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• 1997

Adaptive channel equalization complished without resorting to a training sequence is known as blind equalization. In this paper, in order to increase the speed of the convergence and to reduce the steady-state mean squared error simulatneously, we propose the multi-stage DD(decision-direct) algorithm derived from the combination of the Sato algorithm and the decision-directed algorithm. In the starting stage, the multi-stage DD algorithm is identical to the Sato algorithm which guarantees the convergence of the equalizer. As the blind equalizer converges, the number of the level of the quantizers is increased gradally, so that the proposed algorithm operates identical to the decision-directed algorithm which leads to the low error power after the convergence. Therefore, the multi-stage DD algorithm obtains fast convergence rate and low steady state mean squared error.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.350-358
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• 2021

In modern years, the performance of the students is analysed with lot of difficulties, which is a very important problem in all the academic institutions. The main idea of this paper is to analyze and evaluate the academic performance of the college students with bipolar disorder by applying data mining classification algorithms using Jupiter Notebook, python tool. This tool has been generally used as a decision-making tool in terms of academic performance of the students. The various classifiers could be logistic regression, random forest classifier gini, random forest classifier entropy, decision tree classifier, K-Neighbours classifier, Ada Boost classifier, Extra Tree Classifier, GaussianNB, BernoulliNB are used. The results of such classification model deals with 13 measures like Accuracy, Precision, Recall, F1 Measure, Sensitivity, Specificity, R Squared, Mean Absolute Error, Mean Squared Error, Root Mean Squared Error, TPR, TNR, FPR and FNR. Therefore, conclusion could be reached that the Decision Tree Classifier is better than that of different algorithms.