• Journal of the Korea Computer Industry Society
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• v.2 no.11
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• pp.1395-1406
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• 2001

In order to cover a widespread service range, terrestrial/satellite-mixed network is being combined with terrestrial ATM network. This dissertation analyzes and investigates several previously existent CDV compensation methods in order to compensate CDV arising from interfacing satellite TDMA and ATM. Specifically to supplement the problems of timestamp and cell number counting methods, new Variable Timestamp method for CDV compensation is proposed. To evaluate the proposed method, MMPP(Markov Modulated Poisson Process), which can express VBR service very well, is selected as a cell input traffic model of terrestrial transmitting earth station. After several simulation, it is also confirmed that CDV compensation capability for VBR services is very superior to the cell number counting method. In this case, as the timestamp number Nts increases, CDV compensation capability increases, and the CDV distribution length is reduced.

• Communications for Statistical Applications and Methods
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• v.25 no.2
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• pp.131-157
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• 2018

We propose a robust event date model to estimate the date of a target event by a combination of individual dates obtained from archaeological artifacts assumed to be contemporaneous. These dates are affected by errors of different types: laboratory and calibration curve errors, irreducible errors related to contaminations, and taphonomic disturbances, hence the possible presence of outliers. Modeling based on a hierarchical Bayesian statistical approach provides a simple way to automatically penalize outlying data without having to remove them from the dataset. Prior information on individual irreducible errors is introduced using a uniform shrinkage density with minimal assumptions about Bayesian parameters. We show that the event date model is more robust than models implemented in BCal or OxCal, although it generally yields less precise credibility intervals. The model is extended in the case of stratigraphic sequences that involve several events with temporal order constraints (relative dating), or with duration, hiatus constraints. Calculations are based on Markov chain Monte Carlo (MCMC) numerical techniques and can be performed using ChronoModel software which is freeware, open source and cross-platform. Features of the software are presented in Vibet et al. (ChronoModel v1.5 user's manual, 2016). We finally compare our prior on event dates implemented in the ChronoModel with the prior in BCal and OxCal which involves supplementary parameters defined as boundaries to phases or sequences.

• The Journal of the Acoustical Society of Korea
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• v.13 no.5
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• pp.24-31
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• 1994

In this paper, we study continuous speech recognition of Korean language using acoustic models of word juncture coarticulation. To alleviate the performance degradation due to coarticulation problems, we use context-dependent units that model inter-word transitions in addition to intra-word transitions. In all cases the initial phone of each word has to be specified for each possible final phone of the previous word similarly for the final phone of each word. To improve the robustness of the HMM parameters, the covariance matrix is smoothed. We also use position-dependent units to improve the discriminative power between units. Simulation results show that when the improved models of word juncture coarticulation are used. the recognition performance is considerably improved compared to the baseline system using only intra-word units.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.2
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• pp.191-200
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• 2007

We propose the QoS (Quality of Service) assurance model for AMR (Adaptive MultiRate) voice users considering the capacity and service quality jointly in downlink WCDMA system. For this purpose, we introduce a new system performance measure and the number-based AMR mode allocation scheme. The proposed number-based AMR mode allocation can be operated only with the information of total number of ongoing users. Therefore, it can be more simply implemented than the existing power-based allocation. The proposed system performance measure considers the stochastic variations of AMR modes of ongoing users and can be analytically obtained using CTMC (Continuous Time Markov Chain) modeling. In order to validate the proposed analytical model, a discrete event-based simulation model is also developed. The performance measure obtained from the analytical model is in agreement with the simulation results and is expected to be useful for parameter optimization.

• Knowledge Management Research
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• v.10 no.4
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• pp.1-15
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• 2009

국내에서 신용카드는 대표적인 지불 수단으로 정착되었으며 신용카드의 사용자와 신용카드의 발급 매수는 이미 포화상태에 도달해 있다. 이 같은 양적 성장은 정부의 신용카드 활성화 정책과 더불어 신용카드사 간의 과당 경쟁의 영향에 기인하고 있다. 신용차드의 사용층은 대부분의 성인 남녀로 확대되었으며, 특히 복수의 신용카드 소지자를 대상으로 자사가 발급한 신용차드를 사용하게 하기 위한 신용카드사 간의 경쟁이 치열한 상황이다. 이에 따라 신용카드사들이 경쟁사의 카드사용 회원을 자사의 회원으로 확보하는 젓이 불가피하며 마찬가지로 사용 중인 자사의 회원이 경쟁사로 이동하지 않도록 사전에 이탈 징후를 포착하여 유지 캠페인을 수행하는 것이 신용카드사 마케팅의 주요 활동이 되었다. 선행연구에서는 신용카드 회원의 이탈과 관련하여 다양한 데이터마이닝 기법을 이용한 이탈의 특성 분류 연구가 진행되었다. 본 연구는 회원 이탈에 영향을 주는 요인을 효과적으로 발견하기 위한 방법으로 베이지안 네트워크(Bayesian Network)를 활용한다. 특히, 베이지안 네트워크의 일종인 일반 베이지안 네트워크(General Bayesian Network)를 이용하여 회원의 이탈요인에 영향을 주는 요인들의 집합인 마코프 블랭킷(Makov Blanket)을 도출한다. 한편, 마코프 블랭킷에 포함된 변수를 이용해 민감도 분석을 수행하여 영향이 큰 요인을 찾아내고 이를 비즈니스 프로세스에 적용하여 실무적인 의의를 실증하고자 한다.

• The Journal of the Korea Contents Association
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• v.3 no.4
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• pp.55-62
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• 2003

In this paper, a call admission contro(cac) technique is proposed to reduce the dropping probabilities of handoff calls in wireless networks while guaranteeing QoS to the users. The proposed technique is based on the estimated effective load for the target eel if a call is accepted. When the estimated effective load is higher than a predetermined threshold, a nu call is blocked and a handoff call is queued irrespective of the availability channels. The SRN, an extended Stochastic Petri Net, modes are constructed to compare the performance of the techniques. The SRN uses rewards concepts instead of the complicate numerical analysis required for the Markov chain modes. As a result, the SRN modeling techniques provide an easier way to carry out performance analysis for call admission control and channel allocation.

• IE interfaces
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• v.23 no.4
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• pp.357-364
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• 2010

In this study, we consider performance analysis of distance-based registration (DBR). DBR causes a mobile station (MS) to register its location when the distance between the current base station (BS) and the BS in which it last registered exceeds a distance threshold D. In general, DBR has some advantages over the other registration schemes but has a tendency to causes an MS to register more frequently than zone-based registration (ZBR) that is adopted in most of mobile communication systems. The DBR with implicit registration (DBIR) was proposed to improve the performance of DBR. In this study, we point out some problems of the previous analytical model based on continuous time Markov chain and analyze exact performance of the DBIR. We show that the DBIR always outperforms the DBR by using our exact analytical model.

• The Transactions of the Korea Information Processing Society
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• v.7 no.1
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• pp.286-295
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• 2000

We present a novel statistically adaptive method using the Minimum Description Length(MDL) principle for unsupervised segmentation of magnetic resonance(MR) images. In the method, Markov random filed(MRF) modeling of tissue region accounts for random noise. Intensity measurements on the local region defined by a window are modeled by a finite Gaussian mixture, which accounts for image inhomogeneities. The segmentation algorithm is based on an iterative conditional modes(ICM) algorithm, approximately finds maximum ${\alpha}$ posteriori(MAP) estimation, and estimates model parameters on the local region. The size of the window for parameter estimation and segmentation is estimated from the image using the MDL principle. In the experiments, the technique well reflected image characteristic of the local region and showed better results than conventional methods in segmentation of MR images with inhomogeneities, especially.

• ETRI Journal
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• v.37 no.3
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• pp.606-616
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• 2015

In this paper, we propose a novel method for road recognition using 3D point clouds based on a Markov random field (MRF) framework in unstructured and complex road environments. The proposed method is focused on finding a solution for an analysis of traversable regions in challenging environments without considering an assumption that has been applied in many past studies; that is, that the surface of a road is ideally flat. The main contributions of this research are as follows: (a) guidelines for the best selection of the gradient value, the average height, the normal vectors, and the intensity value and (b) how to mathematically transform a road recognition problem into a classification problem that is based on MRF modeling in spatial and visual contexts. In our experiments, we used numerous scans acquired by an HDL-64E sensor mounted on an experimental vehicle. The results show that the proposed method is more robust and reliable than a conventional approach based on a quantity evaluation with ground truth data for a variety of challenging environments.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.249-257
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• 2005

A Markov model for the IEEE 802.11 standard which is the most widely deployed wireless LAN protocol, is designed and the channel throughput is evaluated. The DCF of 802.11, which is based on CSMA/CA protocol, coordinates transmissions onto the shared communication channel. In this paper, under a finite load traffic condition and the assumption of packet loss after the final backoff stage. We present an algorithm to find the transmission probability and derive the formula for the channel throughput. The proposed model is validated through simulation and is compared with the case without packet losses.