• Title/Summary/Keyword: Bayesian

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Difference State Number of CHMM Model to Improve the Performance of SCCRS (한국어 음성/문자 공용인식기의 성능향상을 위한 가변 상태수 CHMM모델의 구성)

  • Suk Soo-Young;Kim Min-Jung;Kim Kwang-Soo;Jung Ho-Youl;Chung Hyun-Yeol
    • Proceedings of the Acoustical Society of Korea Conference
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    • spring
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    • pp.95-98
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    • 2002
  • 문자인식 또는 음성인식을 위해 사용되어지는 CHMM(Continuous Hidden Markov Model)모델은 일반적으로 모델의 상태수를 일정한 수로 고정하는 고정 상태수 모델 구조를 가지고 있으나, 이는 개별적인 인식 단위의 특성을 고려하지 않은 경우로써 이를 고려한 가변 상태수 모델을 사용할 경우 인식률 향상을 기대할 수 있다. 개별적인 인식 단위에 적합한 모델 상태수를 결정하는 방법으로 파라미터 히스토그램 방법과, BIC(Bayesian Information Criterion)방법을 사용하는 것이 대표적이다. 이들 방법들은 개별적인 인식단위의 우도값만을 향상시키기 위한 방법으로 전체인식률과 직접적으로 비례하지는 않는다. 따라서, 본 논문에서는 고정 상태수를 갖는 모델 적용 방법과 인식단위별 상태수 변화에 따른 인식률을 비교하였으며, 이를 바탕으로 각 모델별 상태수를 달리하는 가변 상태수 CHMM모델 구성 방법을 제안한다. 제안된 가변상태수 모델의 유효성을 확인하기 위해 음성/문자 공용인식기 중 필기체 문자 인식에 적용한 결과 제안한 LM(Local Maximum)으로 구성된 가변 상태수 모델이 MLE와 BIC로 구성된 모델과 인식률 면에서는 거의 동일한 성능을 유지하면서 전체 상태수는 MLE 모델에 비해 $31\%$, BIC로 구성된 모델에 비해 $22\%$ 감소를 나타내어 제안한 모델의 유효성을 확인할 수 있었다.

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Operational modal analysis of a long-span suspension bridge under different earthquake events

  • Ni, Yi-Qing;Zhang, Feng-Liang;Xia, Yun-Xia;Au, Siu-Kui
    • Earthquakes and Structures
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    • v.8 no.4
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    • pp.859-887
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    • 2015
  • Structural health monitoring (SHM) has gained in popularity in recent years since it can assess the performance and condition of instrumented structures in real time and provide valuable information to the asset's manager and owner. Operational modal analysis plays an important role in SHM and it involves the determination of natural frequencies, damping ratios and mode shapes of a constructed structure based on measured dynamic data. This paper presents the operational modal analysis and seismic response characterization of the Tsing Ma Suspension Bridge of 2,160 m long subjected to different earthquake events. Three kinds of events, i.e., short-distance, middle-distance and long-distance earthquakes are taken into account. A fast Bayesian modal identification method is used to carry out the operational modal analysis. The modal properties of the bridge are identified and compared by use of the field monitoring data acquired before and after the earthquake for each type of the events. Research emphasis is given on identifying the predominant modes of the seismic responses in the deck during short-distance, middle-distance and long-distance earthquakes, respectively, and characterizing the response pattern of various structural portions (deck, towers, main cables, etc.) under different types of earthquakes. Since the bridge is over 2,000 m long, the seismic wave would arrive at the tower/anchorage basements of the two side spans at different time instants. The behaviors of structural dynamic responses on the Tsing Yi side span and on the Ma Wan side span under each type of the earthquake events are compared. The results obtained from this study would be beneficial to the seismic design of future long-span bridges to be built around Hong Kong (e.g., the Hong Kong-Zhuhai-Macau Bridge).

New Species of Termitomyces (Lyophyllaceae, Basidiomycota) from Sabah (Northern Borneo), Malaysia

  • Seelan, Jaya Seelan Sathiya;Yee, Chong Shu;Fui, Foo She;Dawood, Mahadimenakbar;Tan, Yee Shin;Kim, Min-Ji;Park, Myung Soo;Lim, Young Woon
    • Mycobiology
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    • v.48 no.2
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    • pp.95-103
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    • 2020
  • The genus Termitomyces (Lyophyllaceae, Basidiomycota) is often associated with fungus-feeding termites (Macrotermitinae) due to their strong symbiotic relationships. The genus is widely found exclusively in certain regions of Africa and Asia. They are recognized as edible mushroom within Southeast Asia as well. But it is often misidentified based on morphology by the local communities especially in Malaysia for Chlorophyllum molybdites which is a highly poisonous mushroom. Thus, it is necessary to study the genus for Malaysia with the synergy of using both morphological and molecular identification. In this study, we aim to describe another new species as an addition to the genus Termitomyces found within Sabah, Malaysia. We generated two new sequences (nrLSU and mtSSU) for the new species and a total of 28 nrLSU and mtSSU sequences were retrieved from GenBank for the phylogenetic analysis using maximum likelihood and Bayesian inferences. We identified that the new collection from Sabah province is a new species and named as Termitomyces gilvus based on the termites found in the mound. A phylogeny tree made from the concatenated genes of LSU and mtSSU suggests that T. gilvus is closely related to T. bulborhizus from China. According to our results, the combination of molecular and morphology proved to be a robust approach to re-evaluate the taxonomic status of Termitomyces species in Malaysia. Additional surveys are needed to verify the species diversity and clarify their geographic distribution.

Robustness Estimation for Power and Water Supply Network : in the Context of Failure Propagation (피해파급에 대한 고찰을 통한 전력 및 상수도 네트워크의 강건성 예측)

  • Lee, Seulbi;Park, Moonseo;Lee, Hyun-Soo
    • Korean Journal of Construction Engineering and Management
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    • v.19 no.3
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    • pp.33-42
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    • 2018
  • In the aftermath of an earthquake, seismic-damaged infrastructure systems loss estimation is the first step for the disaster response. However, lifeline systems' ability to supply service can be volatile by external factors such as disturbances of nearby facilities, and not by own physical issue. Thus, this research develops the bayesian model for probabilistic inference on common-cause and cascading failure of seismic-damaged lifeline systems. In addition, the authors present network robustness estimation metrics in the context of failure propagation. In order to quantify the functional loss and observe the effect of the mitigation plan, power and water supply system in Daegu-Gyeongbuk in South Korea is selected as case network. The simulation results show that reduction of cascading failure probability allows withstanding the external disruptions from a perspective of the robustness improvement. This research enhances the comprehensive understanding of how a single failure propagates to whole lifeline system performance and affected region after an earthquake.

Context-Awareness Modeling Method using Timed Petri-nets (시간 페트리 넷을 이용한 상황인지 모델링 기법)

  • Park, Byung-Sung;Kim, Hag-Bae
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.4B
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    • pp.354-361
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    • 2011
  • Increasing interest and technological advances in smart home has led to active research on context-awareness service and prediction algorithms such as Bayesian Networks, Tree-Dimensional Structures and Genetic prediction algorithms. Context-awareness service presents that providing automatic customized service regarding individual user's pattern surely helps users improve the quality of life. However, it is difficult to implement context-awareness service because the problems are that handling coincidence with context information and exceptional cases have to consider. To overcome this problem, we proposes an Intelligent Sequential Matching Algorithm(ISMA), models context-awareness service using Timed Petri-net(TPN) which is petri-net to have time factor. The example scenario illustrates the effectiveness of the Timed Petri-net model and our proposed algorithm improves average 4~6% than traditional in the accuracy and reliability of prediction.

System identification of soil behavior from vertical seismic arrays

  • Glaser, Steven D.;Ni, Sheng-Huoo;Ko, Chi-Chih
    • Smart Structures and Systems
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    • v.4 no.6
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    • pp.727-740
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    • 2008
  • A down hole vertical seismic array is a sequence of instruments installed at various depths in the earth to record the ground motion at multiple points during an earthquake. Numerous studies demonstrate the unique utility of vertical seismic arrays for studying in situ site response and soil behavior. Examples are given of analyses made at two sites to show the value of data from vertical seismic arrays. The sites examined are the Lotung, Taiwan SMART1 array and a new site installed at Jingliao, Taiwan. Details of the installation of the Jingliao array are given. ARX models are theoretically the correct process models for vertical wave propagation in the layered earth, and are used to linearly map deeper sensor input signals to shallower sensor output signals. An example of Event 16 at the Lotung array is given. This same data, when examined in detail with a Bayesian inference model, can also be explained by nonlinear filters yielding commonly accepted soil degradation curves. Results from applying an ARMAX model to data from the Jingliao vertical seismic array are presented. Estimates of inter-transducer soil increment resonant frequency, shear modulus, and damping ratio are presented. The shear modulus varied from 50 to 150 MPa, and damping ratio between 8% and 15%. A new hardware monitoring system - TerraScope - is an affordable 4-D down-hole seismic monitoring system based on independent, microprocessor-controlled sensor Pods. The Pods are nominally 50 mm in diameter, and about 120 mm long. An internal 16-bit micro-controller oversees all aspects of instrumentation, eight programmable gain amplifiers, and local signal storage.

Malicious Traffic Detection Using K-means (K-평균 클러스터링을 이용한 네트워크 유해트래픽 탐지)

  • Shin, Dong Hyuk;An, Kwang Kue;Choi, Sung Chune;Choi, Hyoung-Kee
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.2
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    • pp.277-284
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    • 2016
  • Various network attacks such as DDoS(Distributed Denial of service) and orm are one of the biggest problems in the modern society. These attacks reduce the quality of internet service and caused the cyber crime. To solve the above problem, signature based IDS(Intrusion Detection System) has been developed by network vendors. It has a high detection rate by using database of previous attack signatures or known malicious traffic pattern. However, signature based IDS have the fatal weakness that the new types of attacks can not be detected. The reason is signature depend on previous attack signatures. In this paper, we propose a k-means clustering based malicious traffic detection method to complement the problem of signature IDS. In order to demonstrate efficiency of the proposed method, we apply the bayesian theorem.

The Comparison of Parameter Estimation for Nonhomogeneous Poisson Process Software Reliability Model (NHPP 소프트웨어 신뢰도 모형에 대한 모수 추정 비교)

  • Kim, Hee-Cheul;Lee, Sang-Sik;Song, Young-Jae
    • The KIPS Transactions:PartD
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    • v.11D no.6
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    • pp.1269-1276
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    • 2004
  • The Parameter Estimation for software existing reliability models, Goel-Okumoto, Yamada-Ohba-Osaki model was reviewed and Rayleigh model based on Rayleigh distribution was studied. In this paper, we discusses comparison of parameter estimation using maximum likelihood estimator and Bayesian estimation based on Gibbs sampling to analysis of the estimator' pattern. Model selection based on sum of the squared errors and Braun statistic, for the sake of efficient model, was employed. A numerical example was illustrated using real data. The current areas and models of Superposition, mixture for future development are also employed.

Estimation of genetic relationships between growth curve parameters in Guilan sheep

  • Hossein-Zadeh, Navid Ghavi
    • Journal of Animal Science and Technology
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    • v.57 no.5
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    • pp.19.1-19.6
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    • 2015
  • The objective of this study was to estimate variance components and genetic parameters for growth curve parameters in Guilan sheep. Studied traits were parameters of Brody growth model which included A (asymptotic mature weight), B (initial animal weight) and K (maturation rate). The data set and pedigree information used in this study were obtained from the Agricultural Organization of Guilan province (Rasht, Iran) and comprised 8647 growth curve records of lambs from birth to 240 days of age during 1994 to 2014. Marginal posterior distributions of parameters and variance components were estimated using TM program. The Gibbs sampler was run 300000 rounds and the first 60000 rounds were discarded as a burn-in period. Posterior mean estimates of direct heritabilities for A, B and K were 0.39, 0.23 and 0.039, respectively. Estimates of direct genetic correlation between growth curve parameters were 0.57, 0.03 and -0.01 between A-B, A-K and B-K, respectively. Estimates of direct genetic trends for A, B and K were positive and their corresponding values were $0.014{\pm}0.003$ (P < 0.001), $0.0012{\pm}0.0009$ (P > 0.05) and $0.000002{\pm}0.0001$ (P > 0.05), respectively. Residual correlations between growth curve parameters varied form -0.52 (between A-K) to 0.48 (between A-B). Also, phenotypic correlations between growth curve parameters varied form -0.49 (between A-K) to 0.47 (between A-B). The results of this study indicated that improvement of growth curve parameters of Guilan sheep seems feasible in selection programs. It is worthwhile to develop a selection strategy to obtain an appropriate shape of growth curve through changing genetically the parameters of growth model.

A Study on Combined DoA Estimation Algorithm using LCMV and Maximum Posterior on Uniform Linear Array Antenna (균일 선형 배열 안테나에서 선형구속최소분산 방법과 사후 추정 확률을 결합한 도래 방향 추정 알고리즘 연구)

  • Lee, Kwan-Hyeong;Park, Sung-Kon;Jeong, Youn-Seo
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.9 no.3
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    • pp.291-297
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    • 2016
  • In this paper, we are comparative analysis of exit algorithm and proposal algorithm for desired target direction of arrival estimation in correlation signal system. Proposed algorithm in this paper is to decrease target direction of arrival an estimation error probability using bayesian, maximum posterior, and MUSIC algorithm in order to decrease direction of arrival error probability as optimize and use linear constrained minimum variance to update weight value. Through simulation, we were comparative analysis proposed algorithm and exit MUSIC algorithm. In case SNR is 10dB and antenna element arrays are 9 and 12, We show the superior performance of the proposed method relative to the class method to decrease of signal estimation error probability about 11% and 13%, respectively.