• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.127-132
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• 2006

K-NN (k-Nearest Neighbors), which is a well-known instance-based learning algorithm, simply stores entire training patterns in memory, and uses a distance function to classify a test pattern. K-NN is proven to show satisfactory performance, but it is notorious formemory usage and lengthy computation. Various studies have been found in the literature in order to minimize memory usage and computation time, and NGE (Nested Generalized Exemplar) theory is one of them. In this paper, we propose RPA (Recursive Partition Averaging) and IRPA (Incremental RPA) which is an incremental version of RPA. RPA partitions the entire pattern space recursively, and generates representatives from each partition. Also, due to the fact that RPA is prone to produce excessive number of partitions as the number of features in a pattern increases, we present IRPA which reduces the number of representative patterns by processing the training set in an incremental manner. Our proposed methods have been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1B
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• pp.64-72
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• 2004

Multiprotocol Label Switching (MPLS) has been developed as a key technology to enhance the reliability, manageability and overall quality of service of core If networks with connection-oriented tunnel LSP and traffic engineering such as constraint-based routing, explicit routing, and restoration. In this paper, we propose a control bandwidth borrowing scheme that maximizes the utilization of tunnel LSPs or physical links by an extension to the RSVP-TE label distribution protocol. MPLS-based core switching network and VPN services rely on the establishment of connection-oriented tunneled LSPs that are configured or predefined by network management systems. The mechanism of network management system varies from (i) a relatively static LSP establishment accounting, to (ii) a dynamic QoS routing mechanisms. With the use of hierarchical LSPs, the extra bandwidth that is unused by the trunk (outer) LSPs should be fully allocated to their constituent end-to-end user traffic (inner) LSPs in order to maximize their utilization. In order to find out the unused extra bandwidth in tunnel LSP or physical link and redistribute these resources to constituent LSPs, we expend the functionality of RSVP-TE and the found unused extra bandwidth is redistributed with a weight-based recursive redistribution scheme. By the extended RSVP-TE and proposed recursive redistributed scheme, we could achieve the instantaneous maximized utilization of tunnel LSP or physical link suffering from the potential under-utilization problem and guarantee the end-to-end QoS requirements. With the proposed scheme, network manager can manage more effectively the extra available bandwidth of hierarchical LSPs and maximize the instantaneous utilization of the tunneled LSP resources.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.253-260
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• 2018

The acoustic communication channel in shallow underwater is typically shown as time-varying multipath fading channel characteristics. The received signal through channel transmission cause inter-symbol interference (ISI) owing to multiple components of different time delay and amplitude. To compensate for this, several techniques have been used, and one of them is acoustic equalizer. In this study, we used four equalizers - feed forward equalizer (FFE), decision directed equalizer (DDE), decision feedback equalizer (DFE) and combination DDE with DFE to compensate ISI. And we applied two adaptive algorithms to adjust coefficient of equalizers - normalized least mean square algorithm and recursive least square algorithm. As result, we found that it has a significant performance improvement over 6 dB on SNR in nonlinear equalizer. By combination of DFE and DDE has almost best performance in any case.

• Journal of the Korea Concrete Institute
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• v.17 no.6 s.90
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• pp.939-946
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• 2005

The stiffness properties of heterogeneous concrete materials and their degradation were investigated at different-levels of observations with aids of the opportunities and limitations of multi-resolution wavelet analysis. The successive Haw transformations lead to a recursive separation of the stiffness properties and the response into coarse-and fine-scale features. In the limit, this recursive process results in a homogenization parameter which is an average measure of stiffness and strain energy capacity at the coarse scale. The basic concept of multi-resolution analysis is illustrated with one and two-dimensional model problems of a two-phase particulate composite representative of the morphology of concrete materials. The computational studies include the meso-structural features of concrete in the form of a hi-material system of aggregate particles which are immersed in a hardened cement paste taking due to account of the mismatch of the two elastic constituents.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.7-13
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• 2021

This study develops an artificial intelligence prediction system for Fine particulate Matter(PM2.5) based on the deep learning algorithm GAN model. The experimental data are closely related to the changes in temperature, humidity, wind speed, and atmospheric pressure generated by the time series axis and the concentration of air pollutants such as SO2, CO, O3, NO2, and PM10. Due to the characteristics of the data, since the concentration at the current time is affected by the concentration at the previous time, a predictive model for recursive supervised learning was applied. For comparative analysis of the accuracy of the existing models, CNN and LSTM, the difference between observation value and prediction value was analyzed and visualized. As a result of performance analysis, it was confirmed that the proposed GAN improved to 15.8%, 10.9%, and 5.5% in the evaluation items RMSE, MAPE, and IOA compared to LSTM, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.1 no.1
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• pp.85-93
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• 1997

In this paper, a novel method for obtaining spectra of short pulses is proposed. This method will be well-applied to perform spectral analyses of ultrashort laser pulses which are known to be difficult to evaluate their exact forms in frequency domain because of their narrow-width characteristics in time domain. It must be noted that the method can be represented by a recursive formula derived from the PRS(partial-response signaling) model, and thus more easily available for numerical solutions than the conventional methods such as consecutive differentiations and convolutions. The pulses whose fundamental frames can be exactly determined or approximately represented by truncated Fourier series have well-behaving conditions for applications of this new method. Moreover, the transversal 9-type PRS model can offer various approximations for spectral analyses of ultrashort pulses currently used in transmission systems.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.618-622
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• 2008

In this paper, we suggest new music composition algorithm based on fractal theory. User can define and control fractal shape by setting an initial state and production rules in L-System. We generate an asymmetric fractal tree based on L-System and probability. Then a music is generated by the fractal tree image using sonification techniques. We introduce two composition algorithm using the fractal tree. First, monophonic music can be generated by mapping x and y axis to velocity and pitch, respectively Second, harmonic music also can be generated by mapping x and y axis to time and pitch, respectively Using our composition algorithm, user can easily generate a music which has repeated pattern created by recursive feature of fractal, and a music which has structure similar to fractal tree image.

• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.29-33
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• 2007

In this paper, time-varying parameter of passive telemetry RF sensor system is estimated using RLS(Rescursive $\leq$* Square) algorithm. In order to overcome the problems such as power limits and complication that general RF sensor system including IC chip has, the principle of inductive coupling is applied to model sensor system The model parameter is rearranged for applying RLS algorithm based on mathematical model to the derived model using inductive coupling principle. Time variant parameter of rearranged model is estimated using forgetting factor, and in case measured data is contaminated by noise and modelling error, the performance of RLS algorithm characterized by the convergence of squared error sum is verified by simulation.

• 한국전산유체공학회:학술대회논문집
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• 2010.05a
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• pp.487-490
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• 2010

A fluid transient analysis on the pipe network of bipropellant propulsion system is conducted through numerical parametric studies in which unsteady friction results are compared with quasi-steady friction results and also show the pressure drop results during the liquid apogee engine firing. The fluid transient analysis program has verified through comparing with the original Zielke model, the full and recursive convolution model and quasi-steady model as a reference. And the pressure drop program also has verified through comparing with results of the well-known program, EPANET2. The bipropellant propulsion system has two different fluids as fuel and oxidizer, and mostly they are hypergolic combination so that the valve opening and closing of the thrusters, that cause the pressure waves, shall take place simultaneously to get proper performance. The different physical properties of the fuel and oxidizer result in the different responsive to the same valve opening and closing. The response results may be helpful to know the characteristics of the bipropellant propulsion system and design it.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.5
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• pp.566-572
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• 2014

Recently, indoor navigation has been applied in large convention centers by using wireless sensor networks (WSNs), which provide not only a user's path to be traveled but also orientation and shopping information to increase user's convenience. This paper presents the localization system for estimating relative coordinates without pre-deployment of the reference node based on ultra wide band (UWB) ranging system, which is relatively suitable for indoor localization compared to other wireless communications, and azimuth sensor. The proposed localization system which consists of an azimuth sensor and a mobile node composed of three nodes estimates relative coordinates of the reference node without applying any recursive and time consumption algorithms. Also, in the process of estimating relative coordinates of the reference node, ranging errors are minimized through the proposed technique and the number of nodes can be reduced. Experimental results show the feasibility and validity of the proposed system.