• Title/Summary/Keyword: Markov process model

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Performance Analysis of Error Control Techniques Using Forward Error Correction in B-ISDN (B-ISDN에서 Forward Error Correction을 이용한 오류제어 기법의 성능분석)

  • 임효택
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.9A
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    • pp.1372-1382
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    • 1999
  • The major source of errors in high-speed networks such as Broadband ISDN(B-lSDN) is buffer overflow during congested conditions. These congestion errors are the dominant sources of errors in 1high-speed networks and result in cell losses. Conventional communication protocols use error detection and retransmission to deal with lost packets and transmission errors. However, these conventional ARQ(Automatic Repeat Request) methods are not suitable for the high-speed networks since the transmission delay due to retransmissions becomes significantly large. As an alternative, we have presented a method to recover consecutive cell losses using forward error correction(FEC) in ATM(Asynchronous Transfer Mode)networks to reduce the problem. The performance estimation based on the cell discard process model has showed our method can reduce the cell loss rate substantially. Also, the performance estimations in ATM networks by interleaving and IP multicast service are discussed.

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Cost-Effectiveness Analysis of Glimepiride or Pioglitazone in Combination with Metformin in Type-2 Diabetic Patients (제2형 당뇨병 환자에 대한 메트포르민-글리메피리드 병합요법과 메트포르민-피오글리타존 병합요법의 비용-효과분석)

  • Lim, Kyung-Hwa;Shin, Hyun-Taek;Sohn, Hyun-Soon;Oh, Jung-Mi;Lee, Young-Sook
    • Korean Journal of Clinical Pharmacy
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    • v.19 no.2
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    • pp.96-104
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    • 2009
  • 배경: 당뇨병 환자에게 관상동맥심질환은 생존률, 건강 상태 유지 및 삶의 질에 주요한 영향을 미치는 합병증이며 적극적인 당뇨병 치료는 이러한 심혈관 합병증을 예방할 수 있으나 당뇨병의 적극적 치료와 관리에는 많은 비용이 소요된다. 목적: 제2형 당뇨병 환자를 대상으로 메트포르민과 글리메피리드 병합요법과 메트포르민과 피오글리타존 병합요법의 비용-효과성을 비교하고자 하였다. 연구방법: 마르코프 코호트 프로세스(Markov Cohort Process Model) 모형을 이용하여 비용-효과분석을 실시하였다. 연장된 수명 (life years gained, LYG)과 삶의 질(quality)을 보정하여 증가된 QALYs를 주요 효과 지표로 측정하였고, 총비용으로는 직접의료비용과, 환자와 가족의 교통비를 직접비의료비용으로 고려하였고 환자와 가족의 시간비용을 간접비용으로 포함하였다. 연구결과: 비용-효과분석 결과, 메트포르민과 글리메피리드 병합요법의 경우 총 비용은 5,962,288원, 효과는 7.94LYG, 6.43QALY이었다. 반면 메트포르민과 피오글리타존 병합요법은 총 비용 10,982,243원, 효과 8.62LYG, 6.99QALY으로, 점증적 비용-효과비(ICER)는 7,402,663원/LYG과 8,934,546원/QALY 이었다. 결론: 우리 사회의 연장된 수명(LYG)에 따른 지불의사가 700만원 이하인 경우는 메트포르민과 글리메피리드 병합요법이 비용-효과적인 대안이며 700만원 이상인 경우에는 메트포르민과 피오글리타존 병합요법이 비용-효과적인 대안이 될 수 있다.

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A Study On Intelligent Robot Control Based On Voice Recognition For Smart FA (스마트 FA를 위한 음성인식 지능로봇제어에 관한 연구)

  • Sim, H.S.;Kim, M.S.;Choi, M.H.;Bae, H.Y.;Kim, H.J.;Kim, D.B.;Han, S.H.
    • 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.

The Analysis of Potential Reduction of CO2 Emission In Soil and Vegetation due to Land use Change (토지이용변화에 따른 식생 및 토양의 이산화탄소 저감잠재량 분석)

  • Lee, Dong-Kun;Park, Chan
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.12 no.2
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    • pp.95-105
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    • 2009
  • Land Use Changes (LUCs) have effects on greenhouse gas emissions and carbon stocks in soil and vegetation. Therefore, predictions for LUC are very important for achieving quantitative targets of $CO_2$ reduction rates. Some research exists on carbon fluxes and carbon cycles to estimate carbon stocks in terrestrial ecosystems in Korea. However, these researches have limitations in terms of helping us understand future potential reductions of $CO_2$ that reflect the influence of LUC. The aim of this study is to analyze the reduction levels of $CO_2$ emissions while considering LUC scenarios that effect carbon fluxes for LCS basic study in the year 2030. In this study, a common approach to model the effects of LUC on carbon stocks is the use of CA-Markov technical process with LUC patterns in the past. Potential reduction of $CO_2$ is calculated by change of land use that contains different soil organic carbon, each land use type, and biomass in vegetation. An IPCC analytical method of natural carbon sink and coefficient results from previous study in Korea is used as a calculation method for potential reduction of $CO_2$. As a result, 12,419 KtC will be reduced annually, which is 8.3% percent of 2005 $CO_2$ emissions in Korea. This will result in 3,226 hundred million won of economic efficiency. In conclusion, conservation of natural carbon sinks is necessary even if the amount of potential reduction change is little.

An Extraction Method of Meaningful Hand Gesture for a Robot Control (로봇 제어를 위한 의미 있는 손동작 추출 방법)

  • Kim, Aram;Rhee, Sang-Yong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.27 no.2
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    • pp.126-131
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    • 2017
  • In this paper, we propose a method to extract meaningful motion among various kinds of hand gestures on giving commands to robots using hand gestures. On giving a command to the robot, the hand gestures of people can be divided into a preparation one, a main one, and a finishing one. The main motion is a meaningful one for transmitting a command to the robot in this process, and the other operation is a meaningless auxiliary operation to do the main motion. Therefore, it is necessary to extract only the main motion from the continuous hand gestures. In addition, people can move their hands unconsciously. These actions must also be judged by the robot with meaningless ones. In this study, we extract human skeleton data from a depth image obtained by using a Kinect v2 sensor and extract location data of hands data from them. By using the Kalman filter, we track the location of the hand and distinguish whether hand motion is meaningful or meaningless to recognize the hand gesture by using the hidden markov model.

A Smart DTMC-based Handover Scheme Using Vehicle's Mobility Behavior Profile (차량의 이동성 행동 프로파일을 이용한 DTMC 기반의 스마트 핸드오버 기법)

  • Han, Sang-Hyuck;Kim, Hyun-Woo;Choi, Yong-Hoon;Park, Su-Won;Rhee, Seung-Hyuong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.6B
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    • pp.697-709
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    • 2011
  • For improvement of wireless Internet service quality at vehicle's moving speed, it is advised to reduce the service disruption time by reducing the handover frequency on vehicle's moving path. Particularly, it is advantageous to avoid the handover to cell whose dwell time is short or can be ignored in terms of service continuity and average throughput. This paper proposes the handover scheme that is suitable for vehicle in order to improve the wireless Internet service quality. In the proposed scheme, the handover process continues to be learned before being modeled to Discrete-Time Markov Chain (DTMC). This modeling reduces the handover frequency by preventing the handover to cell that could provide service sufficiently to passenger even when vehicle passed through the cell but there was no need to perform handover. In order to verify the proposed scheme, we observed the average number of handovers, the average RSSI and the average throughput on various moving paths that vehicle moved in the given urban environment. The experiment results confirmed that the proposed scheme was able to provide the improved wireless Internet service to vehicle that moved to some degree of consistency.

An Enhanced Reverse-link Traffic Control and its Performance Analysis in cdma2000 1xEV-DO Systems (cdma2000 1xEV-DO 시스템에서 개선된 역방향 트래픽 제어와 성능 분석)

  • Yeo, Woon-Young
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.9A
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    • pp.891-899
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    • 2008
  • The cdma2000 1xEV-DO system controls the data rates of mobile terminals based on a binary overload indicator from the base station and a simple probabilistic model. However, this traffic control scheme has difficulty in controlling the reverse-link traffic load effectively and in guaranteeing a stable operation of the reverse link because each mobile terminal determines the next data rate autonomously. This paper proposes a new trafRc control scheme to improve the system stability, and analyzes the proposed scheme by modeling it as a discrete-time Markov process. The numerical results show that the maximum data rate of the proposed scheme is much higher than that of the conventional one. Moreover, the proposed scheme does not modify the standard physical channel structure, so it is compatible to the existing 1xEV-DO system.

Dynamic Human Pose Tracking using Motion-based Search (모션 기반의 검색을 사용한 동적인 사람 자세 추적)

  • Jung, Do-Joon;Yoon, Jeong-Oh
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.7
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    • pp.2579-2585
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    • 2010
  • This paper proposes a dynamic human pose tracking method using motion-based search strategy from an image sequence obtained from a monocular camera. The proposed method compares the image features between 3D human model projections and real input images. The method repeats the process until predefined criteria and then estimates 3D human pose that generates the best match. When searching for the best matching configuration with respect to the input image, the search region is determined from the estimated 2D image motion and then search is performed randomly for the body configuration conducted within that search region. As the 2D image motion is highly constrained, this significantly reduces the dimensionality of the feasible space. This strategy have two advantages: the motion estimation leads to an efficient allocation of the search space, and the pose estimation method is adaptive to various kinds of motion.

Analysis of Cell Variation of ATM Transmission for the Poisson and MMPP Input Model in the TDMA Method (TDMA 방식에서 포아송 입력과 MMPP 입력 모델에 따른 ATM 전송의 셀 지연 변이 해석)

  • Kim, Jeong-Ho;Choe, Gyeong-Su
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.3
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    • pp.512-522
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    • 1996
  • To provide broadband ISDN service for the users in scattered locations, the application of satellite communications network is seriously considered. To trans mit ATM cells efficiently in satellite communications, it is effective to use TDM A method. However, it is necessary to have a method to compensate the cell delayvari-ation caused by the difference between TDMA and ATM. This paper optimized the cell control time(Tc) when traffic inputs have poisson or markov modulated poisson process by applying cell delay variation characteristics of time stamp method, which has the most advantages among compensation methods or cell delay variation. This paper also intorduces a method of reducing the cell clumping phenomena by adapting discrete time stamp method, including the analysis and evalutation of the range of required quality of CDV distribution by ATM transmission.The result of the experiment shows that CDV distribution-range can be controlled to 1.2$\times$Tc which reduces overall cell delay variation by discrrete time stamp method.

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Conformer with lexicon transducer for Korean end-to-end speech recognition (Lexicon transducer를 적용한 conformer 기반 한국어 end-to-end 음성인식)

  • Son, Hyunsoo;Park, Hosung;Kim, Gyujin;Cho, Eunsoo;Kim, Ji-Hwan
    • The Journal of the Acoustical Society of Korea
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    • v.40 no.5
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    • pp.530-536
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    • 2021
  • Recently, due to the development of deep learning, end-to-end speech recognition, which directly maps graphemes to speech signals, shows good performance. Especially, among the end-to-end models, conformer shows the best performance. However end-to-end models only focuses on the probability of which grapheme will appear at the time. The decoding process uses a greedy search or beam search. This decoding method is easily affected by the final probability output by the model. In addition, the end-to-end models cannot use external pronunciation and language information due to structual problem. Therefore, in this paper conformer with lexicon transducer is proposed. We compare phoneme-based model with lexicon transducer and grapheme-based model with beam search. Test set is consist of words that do not appear in training data. The grapheme-based conformer with beam search shows 3.8 % of CER. The phoneme-based conformer with lexicon transducer shows 3.4 % of CER.