• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.9
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• pp.1719-1729
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• 1994

In this paper, an adaptive CAC(Connection Admission Control) method is proposed. The adaptive CAC uses traffic estimates derived from both traffic parameter specified by user and cell flow measurements. Traffic estimation using user-specified parameters is performed at every moment of connection request or connection release by recursive formula which makes real-time calculation possible. Traffic estimation using cell flow measurement is carried out when the number of connected calls does not change during a measurement reflection period-renewal period. The most import ant thing for the traffic estimation using cell flow measurement is the determination of the length of a renewal period to trace a real traffic flow with an allowable time lag and the measurement reflection ratio(MRR) both to reduce the portion of overestimation and to avoid underestimation of real traffic flow. To solve these problems, the adaptive CAC updates renewal period and MRR adaptively according to the number of connections and the elapsed time after last connection or release respectively. Performance analysis for the proposed method is evaluated in several aspects for the cases of both homogeneous and heterogeneous bursty traffic. Numerical examples show the adaptive CAC method has the better performance compared with conventional CAC method based on burst model from the both utilization and QOS point of view.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.4
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• pp.1908-1914
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• 2013

In this paper, we introduce a design method for a broadband planar quasi-Yagi antenna (QYA) for terrestrial digital television (DTV) reception. The coplanar strip line which feeds the driver dipole is connected to a microstrip line and is terminated by short circuit. By appending a wide strip-type rectangular director at a location close to the driver dipole, broadband impedance matching and gain enhancement in a high frequency region are obtained. The gain characteristics in a low frequency region are improved by adding a reflector formed by a truncated ground plane. To reduce the antenna size, the strip-type dipole and reflector are modified to half bow-tie (V)-shaped elements. The effects of various parameters on the antenna characteristics are examined. An antenna, as a design example for the proposed antenna, is designed for the operation in the frequency band of 470-806 MHz for terrestrial DTV. The optimized antenna is fabricated on an FR4 substrate and the experimental results show that the antenna has a good performance such as a frequency band of 450-848 MHz for a VSWR < 2, gain > 4.1 dBi, and front-to-back ratio > 10.4 dB.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.846-851
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• 2005

In this paper, we propose Genetic Algorithms(GAs)-based Optimized Polynomial Neural Networks(PNN). The proposed algorithm is based on Group Method of Data Handling(GMDH) method and its structure is similar to feedforward Neural Networks. But the structure of PNN is not fixed like in conventional neural networks and can be generated in a dynamic manner. As each node of PNN structure, we use several types of high-order polynomial such as linear, quadratic and modified quadratic, and it is connected as various kinds of multi-variable inputs. The conventional PNN depends on the experience of a designer that select the number of input variables, input variable and polynomial type. Therefore it is very difficult to organize optimized network. The proposed algorithm leads to identify and select the number of input variables, input variable and polynomial type by using Genetic Algorithms(GAs). The aggregate performance index with weighting factor is proposed as well. The study is illustrated with tile NOx omission process data of gas turbine power plant for application to nonlinear process. In the sequel the proposed model shows not only superb predictability but also high accuracy in comparison to the existing intelligent models.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.343-350
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• 2000

In this paper, we propose the Multi-FPNN(Fuzzy Polynomial Neural Networks) model based on FNN and PNN(Polyomial Neural Networks) for optimal system identifacation. Here FNN structure is designed using fuzzy input space divided by each separated input variable, and urilized both in order to get better output performace. Each node of PNN structure based on GMDH(Group Method of Data handing) method uses two types of high-order polynomials such as linearane and quadratic, and the input of that node uses three kinds of multi-variable inputs such as linear and quadratic, and the input of that node and Genetic Algorithms(GAs) to identify both the structure and the prepocessing of parameters of a Multi-FPNN model. Here, HCM clustering method, which is carried out for data preproessing of process system, is utilized to determine the structure method, which is carried out for data preprocessing of process system, is utilized to determance index with a weighting factor is used to according to the divisions of input-output space. A aggregate performance inddex with a wegihting factor is used to achieve a sound balance between approximation and generalization abilities of the model. According to the selection and adjustment of a weighting factor of this aggregate abjective function which it is acailable and effective to design to design and optimal Multi-FPNN model. The study is illustrated with the aid of two representative numerical examples and the aggregate performance index related to the approximation and generalization abilities of the model is evaluated and discussed.

• Journal of the Korean Chemical Society
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• v.35 no.5
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• pp.512-519
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• 1991

The axial ligations of nitrogenous bases (pyridine, imidazole, 1-methylimidazole and 2,6-lutidine) to Zn(II)-, Cu(II)-, and Ni(II)-tetrakis(o-chlorophenyl)porphyrin(o-ClTPP), and -tetraphenylporphyrin (TPP) were investigated in organic solvents $(CH_2Cl_2,\;C_6H_6,\;CH_3NO_2,\;(CH_3)_2CO,\;CHCl_3,\;DMF\;and\;DMSO)$ and at 0.01M of ionic strength. The equilibrium constants for the ligation reactions of methalloporphyrins were determined using spectrophotometric method at 15∼35${\circ}C$. In case of M(II)-TPP the equilibrium constants K were considerably larger than those of M(II)-(o-Cl)TPP, depending on steric effect of the porphyrin. The linear relationships between logK of the axial ligation and $pK_a$ of nitrogenous base were shown in M(II)-TPP, but not in M(II)-(o-Cl)TPP. The stabilities of MTPP(L) were controlled by the reation enthalpy and entropy, while those of M(o-Cl)TPP almost by the reaction entropy. The coordinating power of solvent to the methalloporphyrin were also studied in $CHCl_3,\;(CH_3)_2CO$, DMF and DMSO. From those results the solvent effects on the equilibrium constants were discussed.

• Journal of Biomedical Engineering Research
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• v.23 no.3
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• pp.197-205
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• 2002

The objectives of this Paper is to implement a diagnostic classifier of differential laryngeal diseases from acoustic signals acquired in a noisy room. For this Purpose, the voice signals of the vowel /a/ were collected from Patients in a soundproof chamber and got mixed with noise. Then, the acoustic Parameters were analyzed, and hierarchical neural networks were applied to the data classification. The classifier had a structure of five-step hierarchical neural networks. The first neural network classified the group into normal and benign or malign laryngeal disease cases. The second network classified the group into normal or benign laryngeal disease cases The following network distinguished polyp. nodule. Palsy from the benign laryngeal cases. Glottic cancer cases were discriminated into T1, T2. T3, T4 by the fourth and fifth networks All the neural networks were based on multilayer perceptron model which classified non-linear Patterns effectively and learned by an error back-propagation algorithm. We chose some acoustic Parameters for classification by investigating the distribution of laryngeal diseases and Pilot classification results of those Parameters derived from MDVP. The classifier was tested by using the chosen parameters to find the optimum ones. Then the networks were improved by including such Pre-Processing steps as linear and z-score transformation. Results showed that 90% of T1, 100% of T2-4 were correctly distinguished. On the other hand. 88.23% of vocal Polyps, 100% of normal cases. vocal nodules. and vocal cord Paralysis were classified from the data collected in a noisy room.

• Journal of Biomedical Engineering Research
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• v.23 no.2
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• pp.109-117
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• 2002

Electrogastrography(EGG) is a noninvasive method for measuring gastric electrical activity on the abdomen resulting from gastric muscle. EGG signals have a very low frequency range (0.0083 ~0.15 Hz) and extremely low amplitude(10~100 uV). Consequently, EGG signal is easily influenced by other noises. Both finite impulse response(FIR) and infinite impulse response (IIR) filters need high orders or have phase distortions for passing very narrow bandwidth of the EGG signal. In this study, we decomposed EGG signals using a wavelet multiresolution method with Daubechies mother wavelet. The EGG signals were decomposed to seven levels. We reconstructed signal by summing the decomposed signals from level four to seven. To evaluate the performance of the wavelet multiresolution filter(WMF) with simulated EGG signal using two kinds of FIR and four kinds of IIR filters., we used two indices; signal to noise ratio(SNR) and reconstruction squared error(RSE). The SNR of WMF had 9.5, 6.9, and 4.7 dB bigger than that of the other filters at different noise levels, respectively. Also, The RSE of WMF had $1.22{\times}10^6, 1.16{\times}10^6, 1.02{\times}10^6$ smaller than that of the other filters at different noise levels, respectively. The WMF performed better in the SNR and RSE than two kinds of FIR and four kinds of IIR filters.

• Tunnel and Underground Space
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• v.27 no.4
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• pp.243-252
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• 2017

Since the failure behavior of transversely isotropic rocks is significantly different from that of isotropic rocks, it is necessary to develop a transversely isotropic rock failure function in order to evaluate the stability of rock structures constructed in transversely isotropic rock masses. In this study, a spatial distribution function for strength parameters of transversely isotropic rocks is proposed, which is based on the Cassini oval curve proposed by 17th century astronomer Giovanni Domenico Cassini to model the orbit of the Sun around the Earth. The proposed distribution function consists of two model parameters which could be identified through triaxial compression tests on transversely isotropic rock samples. The original Mohr-Coulomb (M-C) failure function is extended to a three-dimensional transversely isotropic M-C failure function by employing the proposed strength parameter distribution function for the spatial distributions of the friction angle and cohesion. In order to verify the suitability of the transversely isotropic M-C failure function, both the conventional triaxial compression and true triaxial compression tests of transversely isotropic rock samples are simulated. The predicted results from the numerical experiments are consistent with the failure behavior of transversely isotropic rocks observed in the actual laboratory tests. In addition, the simulated result of true triaxial compression tests hints that the dependence of rock strength on intermediate principal stress may be closely related to the distribution of the microstructures included in the rock samples.

• Journal of radiological science and technology
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• v.39 no.4
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• pp.549-555
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• 2016

This study was an evaluation of the significance of each parameter through aimed at pregnant women subjected to screening test(integrated test) in predicting risk of Down syndrome. We retrospectively analysed the correlation of risk of Down's syndrome with Nuchal Translucency(NT) images measured by ultrasound, Pregnancy Associated Plasma Protein A(PAPP-A), alpha-fetoprotein(AFP), unconjugated estriol(uE3), human chorionic gonadotrophin(hCG) and Inhibin A by maternal serum. As a result, a significant correlation with NT, uE3, hCG, Inhibin A is revealed with Down's syndrome risk(P<.001). In ROC analysis, AUC of Inhibin A is analysed as the biggest predictor of Down's syndrome(0.859). And the criterion for cut-off was inhibin A 1.4 MoM(sensitivity 81.8%, specificity 75.9%). In conclusion, Inhibin A was the most useful in parameters to predict Down's syndrome in the integrated test. If we make up for the weakness based on the cut-off value of parameters they will be able to be used as an independent indicator in the risk of Down's syndrome screening.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.5
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• pp.412-423
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• 2000

By using the relation between stress intensity factor and AE parameter, new approach method for assessing the crack length and detectability of crack was proposed. Laboratory experiment was carried out to identify AE characteristics of fatigue cracks for compact tension specimen. The relationship between a stress intensity factor and AE signals activity as well as conventional AE parameter analysis was discussed. As a result, the features of specific parameter such as the length of crack growth the AE energy, the AE peak amplitude, and the cumulative AE hits, showed the almost same trend in their increase as the number of fatigue cycle increased. From the comparisons of peak amplitude and AE energy with stress intensity factor, it was verified that the higher stress intensity factors generated AE signals with higher peak amplitude and a larger number of AE counts. If we can get more reliable database for the relation between AE parameters and stress intensity factor, this approach will provide a good information for evaluating both the existence of crack and the minimum detectable size of crack.