• Journal of Gastric Cancer
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• v.14 no.4
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• pp.259-265
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• 2014

Purpose: Survival analysis of gastric cancer patients requires knowledge about factors that affect survival time. This paper attempted to analyze the survival of patients with incomplete registered data by using imputation methods. Materials and Methods: Three missing data imputation methods, including regression, expectation maximization algorithm, and multiple imputation (MI) using Monte Carlo Markov Chain methods, were applied to the data of cancer patients referred to the cancer institute at Imam Khomeini Hospital in Tehran in 2003 to 2008. The data included demographic variables, survival times, and censored variable of 471 patients with gastric cancer. After using imputation methods to account for missing covariate data, the data were analyzed using a Cox regression model and the results were compared. Results: The mean patient survival time after diagnosis was $49.1{\pm}4.4$ months. In the complete case analysis, which used information from 100 of the 471 patients, very wide and uninformative confidence intervals were obtained for the chemotherapy and surgery hazard ratios (HRs). However, after imputation, the maximum confidence interval widths for the chemotherapy and surgery HRs were 8.470 and 0.806, respectively. The minimum width corresponded with MI. Furthermore, the minimum Bayesian and Akaike information criteria values correlated with MI (-821.236 and -827.866, respectively). Conclusions: Missing value imputation increased the estimate precision and accuracy. In addition, MI yielded better results when compared with the expectation maximization algorithm and regression simple imputation methods.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.2
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• pp.87-93
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• 2018

This Study Propose A New Approach To Impliment A Intelligent Robot Control Based on Voice Recognition For Smart Factory Automation Since human usually communicate each other by voices, it is very convenient if voice is used to command humanoid robots or the other type robot system. A lot of researches has been performed about voice recognition systems for this purpose. Hidden Markov Model is a robust statistical methodology for efficient voice recognition in noise environments. It has being tested in a wide range of applications. A prediction approach traditionally applied for the text compression and coding, Prediction by Partial Matching which is a finite-context statistical modeling technique and can predict the next characters based on the context, has shown a great potential in developing novel solutions to several language modeling problems in speech recognition. It was illustrated the reliability of voice recognition by experiments for humanoid robot with 26 joints as the purpose of application to the manufacturing process.

• Journal of Convergence for Information Technology
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• v.9 no.8
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• pp.35-44
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• 2019

The purpose of this study is to find out quantitative vulnerability assessment about COTS(Commercial Off The Shelf) O/S based I&C System. This paper analyzed vulnerability's lifecycle and it's impact. this paper is to develop a quantitative assessment of overall cyber security risks and vulnerabilities I&C System by studying the vulnerability analysis and prediction method. The probabilistic vulnerability assessment method proposed in this study suggests a modeling method that enables setting priority of patches, threshold setting of vulnerable size, and attack path in a commercial OS-based measurement control system that is difficult to patch an immediate vulnerability.

• The Journal of the Acoustical Society of Korea
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• v.26 no.4
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• pp.144-152
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• 2007

Conventional research works on the classification of the heart sound signal have been done mainly with the artificial neural networks. But the analysis results on the statistical characteristic of the heart sound signal have shown that the HMM is suitable for modeling the heart sound signal. In this paper, we model the various heart sound signals representing different heart diseases with the HMM and find that the classification rate is much affected by the clustering of the heart sound signal. Also, the heart sound signal acquired in real environments is a continuous signal without any specified starting and ending points of time. Hence, for the classification based on the HMM, the continuous cyclic heart sound signal needs to be manually segmented to obtain isolated cycles of the signal. As the manual segmentation will incur the errors in the segmentation and will not be adequate for real time processing, we propose a variant of the ergodic HMM which does not need segmentation procedures. Simulation results show that the proposed method successfully classifies continuous heart sounds with high accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.12
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• pp.1815-1827
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• 1993

In this paper, we evaluate the performance of a Futurebus based multiprocessor system with MESI cache coherence protocol for four bus transaction types. Graphical symbols and compiler of SLAM II are used in modeling and simulation. A steady-state probability of each state for MESI protocol is computed by a Markov chain. The probability of each state is used as an input value for a correct simulation. Processor utilization, memory utilization, bus utilization, and the waiting time for bus arbitration are measured in terms of the number of processors, the hit ratio of cache memory, the probability of internal operation, and bus bandwidth.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5B
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• pp.809-819
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• 2000

This paper deals with an optimal capacity allocation problem and performance analysis in Advanced Information Communication Processing System(AICPS). AICPS is a gateway system interconnection PSTN(Public Switched Telephone Network), ISDN(Intergrated Services Digital Network), PSDN(Packet Switched Data Network), internet, Frame Relay and ATM together. This study considers not only ISDN and Internet but also user behavior of On-line service which is analyzed by Markov process. A call blocking probability of TNAS and INAS is computed by Erlang's formula. Then, PNAS and WNAS's call blocking probability are computed by Stochastic knapsack modeling. The result is compared with result of simulation. Finally, we allocate an optimal capacity minimizing total call blocking probability.

• Spatial Information Research
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• v.2 no.1
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• pp.47-51
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• 1994

The purpose of the study is to establ ish models of land Cover (use) prediction system for development and management of land resources using remotely sensed data as well as ancillary data in the context of multi-dis¬ciplinary approach in the application to CheJoo Island. The model adopts multi-date processing techniques and is a spatial/temporal land-Cover projection strategy emerged as a synthesis of the probability tra-nsition model and the discrimnant-analys is model. A discriminant modelis applied to all pixels in CheJoo landscape plane to predict the most likely change in land Cover. The probability transition model provides the number of these pixels that will convert to different land Cover in a given future time increment. The syntheric model predicts the future change in land Cover and its volume of pixels in the landscape plane.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.3
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• pp.63-72
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• 2015

This paper presents the issue that is predicting the movement of an agent in an enclosed space by using the MDP (Markov Decision Process). Recent researches on the optimal path finding are confined to derive the shortest path with the use of deterministic algorithm such as $A^*$ or Dijkstra. On the other hand, this study focuses in predicting the path that the agent chooses to escape the limited space as time passes, with the stochastic method. The MDP reward structure from GIS (Geographic Information System) data contributed this model to a feasible model. This model has been approved to have the high predictability after applied to the route of previous armed red guerilla.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1186-1190
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• 1995

This paper is focused on the formulation of explicit closed-form functions describing the performance measures of the general flexible manufacturing system (FMS)according to the strategy of material handling system(MHS). the performance measures such as the production rate, the production lead-time and the utilization rate of the general FMS are expressed, respectively, as the explicit closed-form functions of the part processing time, the service rate of the material handling system (MHS) and the number of machine tools in the FMS. For this, the gensral FMS is presented as a generalized stochastic Petri net model, then, the moment generating function (MGF) based approach is applied to obtain the steady-state probabity formulation. Based on the steady-state formulation, the explicit closed-form functions for performance measures of the probability FMS can be obtained. Finally, the analytical results are compared with the Petri net simulation results to verify the validity of the suggested method. The paper is of significance in the sense that it provides a comprehensive formula for performance measures of the FMS even to the industry engineers and academic reademic resuarchers who have no background on Markov chain analysis method or Petrinet modeling

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.2
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• pp.139-151
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• 1997

An ATM switching system may be designed so that communications between processors of its control part can be performed via its switching network rather than a separate inter-processor communications (IPC) network. In such a system, there should be interfaces to convent IPC traffic from message format to cell format and vice versa, that is, mechanisms to perform the SAR (Segmentation And Reassembly) sublayer functions. In this paper, we concern the cell reassembly mechanism among them, mainly focussed on buffer management schemes. We consider a few alternatives to implement cell reassembly function block, namely, separated buffering, reserved buffering and shared buffering in this paper. In case of separated and reserved buffering, we employ a continuous time Markov chain for the performance evaluation of cell reassembly mechanism, judicially defining the states of the mechanism. Performance measures such as measage loss probability, mean number of message queued in buffer and average reassembly delay are obtianed in closed forms. In case of shared buffering, we compare the alternatives for implementing cell reassembly function block using simulation because it is almost impossible to analyze the mechanism of shared buffering by analytical modeling. Some illustrations are given for the performance analysis of the alternatives to implement cell reassembly function block.