• Title/Summary/Keyword: Variability Model

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A Variability Description Technique for Software Product Line: OVDL (소프트웨어 프로덕트라인 가변성 기술 기법: OVDL)

  • Lee, Ji Hyun;Kang, Sung Won
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.11
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    • pp.739-746
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    • 2013
  • Variability of the software product line that differentiates member products within a product line must be described with precise meaning and visualized so as easy to select. Moreover, it should be easy to manage. Variability description approaches can largely be divided into two approaches, integrated variability description approach and orthogonal variability description approach. Orthogonal Variability Description Language (OVDL) was developed for clear and precise description of variability without ambiguity. This paper validates the variability description capability of OVDL by translating the variability models of Inter-Working Function (IWF) product line described by using Orthogonal Variability Model (OVM) notations into variability descriptions in OVDL.

A 2-D numerical research on spatial variability of concrete carbonation depth at meso-scale

  • Pan, Zichao;Ruan, Xin;Chen, Airong
    • Computers and Concrete
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    • v.15 no.2
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    • pp.231-257
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    • 2015
  • This paper discusses the spatial variability of the carbonation depth caused by the mesoscopic structure of the concrete and the influence of the spatial variability on the thickness of the concrete cover. To conduct the research, a method to generate the random aggregate structure (RAS) based on polygonal particles and a simplified numerical model of the concrete carbonation at meso-scale are firstly developed. Based on the method and model, the effect of the aggregate properties including shape, content and gradation on the spatial variability of the carbonation depth is comprehensively studied. The results show that a larger degree of the spatial variability will be obtained by using (1) the aggregates with a larger aspect ratio; (2) a larger aggregate content; (3) the gradation which has more large particles. The proper sample size and model size used in the analysis are also studied. Finally, a case study is conducted to demonstrate the influence of the spatial variability of the carbonation depth on the proper thickness of the concrete cover. The research in this paper not only provides suggestions on how to decrease the spatial variability, but also proposes the method to consider the effect of the spatial variability in designing the thickness of the concrete cover.

THEORETICAL CONSIDERATIONS ON THE VARIABILITY OF ACTIVE GALACTIC NUCLEI

  • PARK SEOK JAE
    • Journal of The Korean Astronomical Society
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    • v.29 no.spc1
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    • pp.97-98
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    • 1996
  • Variability of active galactic nuclei is now a well-known phenomenon. This remains to be fully explained by a theoretical model of the central engine. Time scales of AGN variability seem to range continuously from hours up to months. The short time scale variability must be related to the phenomena on the event horizon of the black hole, while the long one to those in the accretion disk or surrounding matter. Based on the axisymmetric, nonstationary model of the central engine, we discuss theoretical considerations on the variability of active galactic nucleus.

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The Characteristics of Signal versus Noise SST Variability in the North Pacific and the Tropical Pacific Ocean

  • Yeh, Sang-Wook;Kirtman, Ben P.
    • Ocean Science Journal
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    • v.41 no.1
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    • pp.1-10
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    • 2006
  • Total sea surface temperature (SST) in a coupled GCM is diagnosed by separating the variability into signal variance and noise variance. The signal and the noise is calculated from multi-decadal simulations from the COLA anomaly coupled GCM and the interactive ensemble model by assuming both simulations have a similar signal variance. The interactive ensemble model is a new coupling strategy that is designed to increase signal to noise ratio by using an ensemble of atmospheric realizations coupled to a single ocean model. The procedure for separating the signal and the noise variability presented here does not rely on any ad hoc temporal or spatial filter. Based on these simulations, we find that the signal versus the noise of SST variability in the North Pacific is significantly different from that in the equatorial Pacific. The noise SST variability explains the majority of the total variability in the North Pacific, whereas the signal dominates in the deep tropics. It is also found that the spatial characteristics of the signal and the noise are also distinct in the North Pacific and equatorial Pacific.

Variability Dependency Analysis for Generating Business Process Models based on Variability Decisions (가변성 결정기반 BPM 생성을 위한 가변성 의존관계 분석)

  • Moon, Mi-Kyeong
    • The KIPS Transactions:PartD
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    • v.16D no.5
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    • pp.791-800
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    • 2009
  • Recently, the business process family model (BPFM), which is new approachfor assuring businessflexibility and enhancing reuse in application development with service oriented architecture (SOA), was proposed. The BPFM is a model which can explicitly represent the variabilities in business process family by using the variability analysis method of software product line. Many business process models (BPM) can be generated automatically through decision and pruning processes from BPFM. At this time, the variabilities tend to have inclusive or exclusive dependencies between them. This affects the decision and pruning processes. So far, little attention has been given to the binding information of variability dependency in the BPFM. In this paper, we propose an approach for analyzing various types of dependency relationships between variabilities and representing the variability and their relationships as a dependency analysis model. Additionally, a method which can trace the variabilities affected by a decision on the dependency analysis model is presented. The case study shows that the proposed approach helps to reduce the number of variability decision and to solve a disagreement of functions in BPM produced by incorrectly deciding the variability.

A Variability Analysis on the Flatfish Production and Revenue using Expectation Hypotheses and GARCH Model

  • Yoon, Hyung-Mo;Yoon, Ji-Young
    • The Journal of Fisheries Business Administration
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    • v.48 no.2
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    • pp.1-17
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    • 2017
  • This work studies the variability of flatfish sales revenue. The theoretical analysis draws functions for equilibrium price and quantity using expectation hypotheses. The functions include unpredictable phenomenon with dummy variable and GARCH. The equilibrium function, using adaptive expectation hypothesis, contains the independent variables of supply and demand, while the equilibrium function, embodying rational expectation hypothesis, includes only the independent variables of supply side, because the demand side disappears by the information extraction process theoretically, if economic subjects build the expectation rational. The empirical analysis shows: the variability of flatfish production has a spillover effect on the variability of revenue with the adaptive expectation hypothesis. In the case when the model has a rational expectation hypothesis, the variability of flatfish production has a spillover effect on the revenue (the mean equation of GARCH model). This study indicates that there is the variability in flatfish production and sales revenue, and the spillover effect between them. The result can help to build of the rational system for the fishery income stability.

Analysis on the Variability of Rainfall at the Seoul Station during Summer Season Using the Variability of Parameters of a Stochastic Rainfall Generation Model (추계학적 강우모형의 매개변수 변동을 통한 서울지역 여름철 강우 변동특성 분석)

  • Cho, Hyungon;Kim, Gwangseob;Yi, Jaeeung
    • Journal of Korea Water Resources Association
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    • v.47 no.8
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    • pp.693-701
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    • 2014
  • In this study a stochastic rainfall generation model is used to analyze the structural variability of rainfall events since it has limitations in the traditional approach of measuring rainfall variability according to different durations. The NSRPM(Neyman-Scott Rectangular Pulse Model) is a stochastic rainfall generation model using a point process with 5 model parameters which is widely used in hydrologic fields. The five model parameters have physical meaning associated with rainfall events. The model parameters were estimated using hourly rainfall data from 1973 to 2011 at Seoul stations. The variability of model parameter estimates was analyzed and compared with results of traditional analysis.

Probabilistic Analysis of Reinforced Concrete Beam and Slab Deflections Using Monte Carlo Simulation

  • Choi, Bong-Seob;Kwon, Young-Wung
    • KCI Concrete Journal
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    • v.12 no.2
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    • pp.11-21
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    • 2000
  • It is not easy to correctly predict deflections of reinforced concrete beams and one-way slabs due to the variability of parameters involved in the calculation of deflections. Monte Carlo simulation is used to assess the variability of deflections with known statistical data and probability distributions of variables. A deterministic deflection value is obtained using the layered beam model based on the finite element approach in which a finite element is divided into a number of layers over the depth. The model takes into account nonlinear effects such as cracking, creep and shrinkage. Statistical parameters were obtained from the literature. For the assessment of variability of deflections, 12 cases of one-way slabs and T-beams are designed on the basis of ultimate moment capacity. Several results of a probabilistic study are presented to indicate general trends indicated by results and demonstrate the effect of certain design parameters on the variability of deflections. From simulation results, the variability of deflections relies primarily on the ratio of applied moment to cracking moment and the corre-sponding reinforcement ratio.

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Intra-night optical variability of AGN in COSMOS field

  • Kim, Joonho;Karouzos, Marios;Im, Myungshin;Kim, Dohyeong;Jun, Hyunsung;Lee, Joon Hyeop;Pallerola, Mar Mezcua
    • The Bulletin of The Korean Astronomical Society
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    • v.41 no.2
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    • pp.64.2-64.2
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    • 2016
  • Optical variability is one way to probe the nature of the central engine of AGN at smaller linear scales and previous studies have shown that optical variability is more prevalent at longer timescales and at shorter wavelengths. Especially, intra-night variability can be explained through the damped random walk model but small samples and inhomogeneous data have made constraining this model hard. To understand the properties and physical mechanism of optical variability, we are performing the KMTNet Active Nuclei Variability Survey (KANVaS). Test data of KMTNet in the COSMOS field was obtained over 2 separate nights during 2015, in B, V, R, and I bands. Each night was composed of 5 and 9 epochs with ~30 min cadence. To find AGN in the COSMOS field, we applied multi-wavelength selection methods. Different selection methods means we are looking different region in unification model of AGN, and 100~120, 400~500, 50~100 number of AGN are detected in X-ray, mid-infrared, and radio selection of AGN, respectively. We performed image convolution to reflect seeing fluctuation, then differential photometry between the selected AGN and nearby stars to achieve photometric uncertainty ~0.01mag. We employed one of the standard time-series analysis tools to identify variable AGN, chi-square test. Preliminarily results indicate that intra-night variability is found for X-ray selected, Type1 AGN are 23.6%, 26.4%, 21.3% and 20.7% in the B, V, R, and I band, respectively. The majority of the identified variable AGN are classified as Type 1 AGN, with only a handful of Type 2 AGN showing evidence for variability. The work done so far confirms that there are type and wavelength dependence of intra-night optical variability of AGN.

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Impact of climate variability and change on crop Productivity (기후변화에 따른 작물 생산성반응과 기술적 대응)

  • Shin Jin Chul;Lee Chung Geun;Yoon Young Hwan;Kang Yang Soon
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2000.11a
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    • pp.12-27
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    • 2000
  • During the recent decades, he problem of climate variability and change has been in the forefront of scientific problems. The objective of this study was to assess the impact of climate variability on crop growth and yield. The growth duration was the main impact of climate variability on crop yield. Phyllochronterval was shortened in the global worming situations. A simple model to describe developmental traits was provided from heading data of directly seeded rice cultivars and temperature data. Daily mean development rate could be explained by the average temperature during the growth stage. Simple regression equation between daily mean development rate(x) and the average temperature(y) during the growth period as y = ax + b. It can be simply modified as x = 1/a $\ast$ (y-b). The parameters of the model could depict the thermo sensitivity of the cultivars. On the base of this model, the three doubled CO2 GCM scenarios were assessed. The average of these would suggest a decline in rice production of about 11% if we maintained the current cultivars. Future cultivar's developmental traits could be suggested by the two model parameters.

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