• Title/Summary/Keyword: Stochastic analysis

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Call Admission Control Techniques of Mobile Communication System using SRN Models (SRN 모델을 이용한 이동통신 시스템의 호 수락 제어 기법)

  • 로철우
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.39 no.12
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    • pp.529-538
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    • 2002
  • Conventional method to reduce the handoff call blocking probability(PBH) in mobile communication system is to reserve a predetermined number of channels only for handoff calls. To determine the number of reserved channels, an optimization problem, which is generally computationally heavily involved, must be solved. In this Paper, we propose a call admission control (CAC) scheme that can be used to reduce the PBH without reserving channels in advance. For this, we define a new measure, gain, which depends on the state of the system upon the arrival of a new call. The proposed CAC decision rule relies on the gain computed when a new call arrives. SRN, an extended stochastic Petri nets, provides compact modeling facilities for system analysis can be calculated performance index by appropriate reward to the model. In this Paper, we develop SRN models which can perform the CAC with gain. The SRN models are 2 level hierarchical models. The upper layer models are the structure state model representing the CAC and channel allocation methods considering QoS with multimedia traffic The lower layer model Is to compute the gain under the state of the upper layer models.

Analysis and probabilistic modeling of wind characteristics of an arch bridge using structural health monitoring data during typhoons

  • Ye, X.W.;Xi, P.S.;Su, Y.H.;Chen, B.
    • Structural Engineering and Mechanics
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    • v.63 no.6
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    • pp.809-824
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    • 2017
  • The accurate evaluation of wind characteristics and wind-induced structural responses during a typhoon is of significant importance for bridge design and safety assessment. This paper presents an expectation maximization (EM) algorithm-based angular-linear approach for probabilistic modeling of field-measured wind characteristics. The proposed method has been applied to model the wind speed and direction data during typhoons recorded by the structural health monitoring (SHM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. In the summer of 2015, three typhoons, i.e., Typhoon Chan-hom, Typhoon Soudelor and Typhoon Goni, made landfall in the east of China and then struck the Jiubao Bridge. By analyzing the wind monitoring data such as the wind speed and direction measured by three anemometers during typhoons, the wind characteristics during typhoons are derived, including the average wind speed and direction, turbulence intensity, gust factor, turbulence integral scale, and power spectral density (PSD). An EM algorithm-based angular-linear modeling approach is proposed for modeling the joint distribution of the wind speed and direction. For the marginal distribution of the wind speed, the finite mixture of two-parameter Weibull distribution is employed, and the finite mixture of von Mises distribution is used to represent the wind direction. The parameters of each distribution model are estimated by use of the EM algorithm, and the optimal model is determined by the values of $R^2$ statistic and the Akaike's information criterion (AIC). The results indicate that the stochastic properties of the wind field around the bridge site during typhoons are effectively characterized by the proposed EM algorithm-based angular-linear modeling approach. The formulated joint distribution of the wind speed and direction can serve as a solid foundation for the purpose of accurately evaluating the typhoon-induced fatigue damage of long-span bridges.

Big Data and Knowledge Generation in Tertiary Education in the Philippines

  • Fadul, Jose A.
    • Journal of Contemporary Eastern Asia
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    • v.13 no.1
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    • pp.5-18
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    • 2014
  • This exploratory study investigates the use of a computational knowledge engine (WolframAlpha) and social networking sites (Gmail, Yahoo and Facebook) by 200 students at De La Salle-College of Saint Benilde, their "friends" and their "friends of friends" during the 2009 through 2013 school years, and how this appears to have added value in knowledge generation. The primary aim is to identify what enhances productiveness in knowledge generation in Philippine Tertiary Education. The phenomenological approach is used, therefore there are no specific research questions or hypotheses proposed in this paper. Considering that knowledge generation is a complex phenomenon, a stochastic modelling approach is also used for the investigation that was developed specifically to study un-deterministic complex systems. A list of salient features for knowledge generation is presented as a result. In addition to these features, various problem types are identified from literature. These are then integrated to provide a proposed framework of inclusive (friendly) and innovative social networks, for knowledge generation in Philippine tertiary education. Such a framework is necessarily multidisciplinary and useful for problem-solving in a globalized and pluralist reality. The implementation of this framework is illustrated in the three parts of the study: Part 1: Online lessons, discussions, and examinations in General Psychology, Introduction to Sociology, and Life and Works of Jose Rizal, for the author's students in De La Salle-College of Saint Benilde; Part 2: Facebook Report analytics of students and teachers, their friends and their friends of friends via WolframAlpha; and Part 3: Social Network Analysis of the people and groups influencing the courses' scope-and-sequence in the new General Education Curriculum for Tertiary Schools and Institutions in the Philippines.

Pitching Motion Analysis of Floating Spar-buoy Wind Turbine of 2MW Direct-drive PMSG (2 MW 영구자석 직접 구동형 부유식 스파 부이 풍력 발전기의 피칭 운동해석)

  • Shin, Pyungho;Kyong, Namho;Choi, Jungchul;Ko, Heesang
    • Journal of the Korean Solar Energy Society
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    • v.37 no.1
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    • pp.1-14
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    • 2017
  • A series of coupled time domain simulations considering stochastic waves and wind based on five 1-h time-domain analyses are performed in normal operating conditions. Power performance and tower base Fore-Aft bending moment and pitching motion response of the floating spar-buoy wind turbine with 2 MW direct-drive PMSG have been analyzed by using HAWC2 that account for aero-hydro-servo-elastic time domain simulations. When the floating spar-buoy wind turbine is tilted in the wind direction, maximum of platform pitching motion is close to $4^{\circ}$. Statistical characteristics of tower base Fore-Aft bending moment of floating spar-buoy wind turbine are compared to that of land-based wind turbine. Maximum of tower base Fore-Aft bending moment of floating spar-buoy wind turbine and land-based wind is 94,448 kNm, 40,560 kNm respectively. This results is due to changes in blade pitch angle resulting from relative motion between wave and movement of the floating spar-buoy wind turbine.

Accuracy Improvement of GPS/Levelling using Least Square Collocation (Least Square Collocation에 의한 GPS/Leveling의 정확도 개선)

  • Yun Hong-Sic;Lee Dong Ha
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.23 no.4
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    • pp.385-392
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    • 2005
  • This paper describes an accuracy analysis of newly developed gravimetric geoid and an improvement of developed geoid using GPS/Levelling data. We developed the KGEOID05 model corrected with the correction term. The correction term is modelled using the difference between GPS/Levelling derived geoidal heights and gravimetric geoidal heights. The stochastic model used in the calculation of correction term is the least squares collocation technique based on second-order Markov covariance function. 373 GPS stations were used to model the correction term. The standard deviation of KGEOID05 is about 11 cm and it indicates that we can be determined accurate heights ($2{\sim}3\;cm$) when we made precise modelling using KGEOID05 and a few GPS measurements for the local area.

Analysis of Cosmic Radiation Dose of People by Abroad Travel (일반인들의 항공여객기 이용 시 우주방사선 피폭선량 비교 분석)

  • Jang, Donggun;Shin, Sanghwa
    • Journal of radiological science and technology
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    • v.41 no.4
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    • pp.339-344
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    • 2018
  • Humans received an exposure dose of 2.4 mSv of natural radiation per year, of which the contribution of spacecraft accounts for about 75%. The crew of the aircraft has increased radiation exposure doses based on cosmic radiation safety management regulations There is no reference to air passengers. Therefore, in this study, we measured the radiation exposure dose received in the sky at high altitude during flight, and tried to compare the radiation exposure dose received by ordinary people during flight. We selected 20 sample specimens, including major tourist spots and the capital by continent with direct flights from Incheon International Airport. Using the CARI-6/6M model and the NAIRAS model, which are cosmic radiation prediction models provided at the National Radio Research Institute, we measured the cosmic radiation exposure dose by the selected flight and departure/arrival place. In the case of exposure dose, Beijing was the lowest at $2.87{\mu}Sv$ (NAIRAS) and $2.05{\mu}Sv$ (CARI - 6/6M), New York had the highest at $146.45{\mu}Sv$ (NAIRAS) and $79.42{\mu}Sv$ (CARI - 6/6M). We found that the route using Arctic routes at the same time and distance will receive more exposure dose than other paths. While the dose of cosmic radiation to be received during flight does not have a decisive influence on the human body, because of the greater risk of stochastic effects in the case of frequent flights and in children with high radiation sensitivity Institutional regulation should be prepared for this.

A Study on the Development of Performance Evaluation Method for the Stormwater Treatment Wetland (비점오염관리를 위한 강우유출수 처리습지의 성능평가방법 개발)

  • Kim, Young Ryun;Kim, Sang Dan;Lee, Suk Mo;Sung, Kijun;Song, Kyo Ook;Son, Min Ho
    • Journal of Korean Society on Water Environment
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    • v.29 no.3
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    • pp.354-364
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    • 2013
  • The performance of the stormwater wetlands can be significantly influenced by antecedent stormwater in storage at the commencement of a stormevent. As inflows are intermittent and stochastic in nature, the evaluation of the treatment efficiency of a stormwater wetland should be considered by runoff capture and water treatment characteristics during interevent periods. In this study, analytical probabilistic model is applied to identity runoff capture rate and treatment efficiency of the stormwater wetland. To achieve this, continuous rainfall data recorded in Busan for 31 years has been analyzed to derive the runoff capture rate, and 1st order kinetic decay constants ($k_V$, 1/d) are calculated from regression analysis to identify pollutants removal during interevent periods. The results show that about 60.9% of annual average runoff is captured through the stormwater wetland. The annual average treatment efficiencies of SS, BOD, COD, TN and TP is about 11.4, 8.9, 9.8, 4.3 and 9.6%, respectively. The analytical model has been compared with the numerical model and it shows that analytical model is valid. Performance evaluation methods developed in this study has the advantages of considering characteristics of rainfall-runoff, facility type and pollutant removal.

Impact Assessment of Climate Change on Hydrologic Components and Water Resources in Watershed (기후변화에 따른 유역의 수문요소 및 수자원 영향평가)

  • Kim Byung Sik;Kim Hung Soo;Seoh Byung Ha;Kim Nam Won
    • Proceedings of the Korea Water Resources Association Conference
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    • 2005.05b
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    • pp.143-148
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    • 2005
  • The main purpose of this study is to suggest and evaluate an operational method for assessing the potential impact of climate change on hydrologic components and water resources of regional scale river basins. The method, which uses large scale climate change information provided by a state of the art general circulation model(GCM) comprises a statistical downscaling approach and a spatially distributed hydrological model applied to a river basin located in Korea. First, we construct global climate change scenarios using the YONU GCM control run and transient experiments, then transform the YONU GCM grid-box predictions with coarse resolution of climate change into the site-specific values by statistical downscaling techniques. The values are used to modify the parameters of the stochastic weather generator model for the simulation of the site-specific daily weather time series. The weather series fed into a semi-distributed hydrological model called SLURP to simulate the streamflows associated with other water resources for the condition of $2CO_2$. This approach is applied to the Yongdam dam basin in southern part of Korea. The results show that under the condition of $2CO_2$, about $7.6\% of annual mean streamflow is reduced when it is compared with the observed one. And while Seasonal streamflows in the winter and autumn are increased, a streamflow in the summer is decreased. However, the seasonality of the simulated series is similar to the observed pattern and the analysis of the duration cure shows the mean of averaged low flow is increased while the averaged wet and normal flow are decreased for the climate change.

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The Forecasting of Monthly Runoff using Stocastic Simulation Technique (추계학적 모의발생기법을 이용한 월 유출 예측)

  • An, Sang-Jin;Lee, Jae-Gyeong
    • Journal of Korea Water Resources Association
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    • v.33 no.2
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    • pp.159-167
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    • 2000
  • The purpose of this study is to estimate the stochastic monthly runoff model for the Kunwi south station of Wi-stream basin in Nakdong river system. This model was based on the theory of Box-Jenkins multiplicative ARlMA and the state-space model to simulate changes of monthly runoff. The forecasting monthly runoff from the pair of estimated effective rainfall and observed value of runoff in the uniform interval was given less standard error then the analysis only by runoff, so this study was more rational forecasting by the use of effective rainfall and runoff. This paper analyzed the records of monthly runoff and effective rainfall, and applied the multiplicative ARlMA model and state-space model. For the P value of V AR(P) model to establish state-space theory, it used Ale value by lag time and VARMA model were established that it was findings to the constituent unit of state-space model using canonical correction coefficients. Therefore this paper confirms that state space model is very significant related with optimization factors of VARMA model.

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The Bayesian Analysis for Software Reliability Models Based on NHPP (비동질적 포아송과정을 사용한 소프트웨어 신뢰 성장모형에 대한 베이지안 신뢰성 분석에 관한 연구)

  • Lee, Sang-Sik;Kim, Hee-Cheul;Kim, Yong-Jae
    • The KIPS Transactions:PartD
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    • v.10D no.5
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    • pp.805-812
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    • 2003
  • This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process (NHPP) and performs Bayesian inference using prior information. The failure process is analyzed to develop a suitable mean value function for the NHPP; expressions are given for several performance measure. The parametric inferences of the model using Logarithmic Poisson model, Crow model and Rayleigh model is discussed. Bayesian computation and model selection using the sum of squared errors. The numerical results of this models are applied to real software failure data. Tools of parameter inference was used method of Gibbs sampling and Metropolis algorithm. The numerical example by T1 data (Musa) was illustrated.