• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.11
• /
• pp.739-746
• /
• 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.

• Journal of Korea Society of Industrial Information Systems
• /
• v.20 no.3
• /
• pp.51-60
• /
• 2015

Traceability targets provision of information to stakeholders required for analyzing impacts among artifacts due to changes. Unlike single product development, in software product line developing the family of products the complexity of maintaining and managing traceability between two life cycles, domain and application engineering is so high. Accordingly, variability traceability management approach centred on orthogonal variability model that manages variability separated from development artifacts has been conceptually proposed, but its efficiency has not verified yet. This paper verifies whether orthogonal variability model based traceability can provide required traceability through an example. As the results, the OVM-based variability tracing method supports well to narrow down artifacts affected by the changes. However, the method does not support tracing the exact artifacts or exact part of an artifact affected by the change.

• Korean Management Science Review
• /
• v.12 no.1
• /
• pp.111-124
• /
• 1995

With the increasing interest of reducing process variation, statistical process control has served the pivotal tool in most industrial quality programs. In this study, system analyses have been performed associated with a cost incorporated version of a process control, a quadratic loss-based X over bar control chart model. Specifically, two issues, the capital/research investments for improvement of a system and the precision of a parameter estimation, have been addressed and discussed. Through the analysis of experimental results, we show that process variability is seen to be one of the most important sources of loss and quality improvement efforts should be directed to reduce this variability. We further derive the results that, even if the optimal designs may be sensitive, the model appears to be robust with regard to misspecification of parameters. The approach and discussion taken in this study provide a meaningful guide for proper process control. We conclude this study with providing general comments.

• Journal of Mechanical Science and Technology
• /
• v.20 no.3
• /
• pp.366-375
• /
• 2006

In this paper, it is intended to introduce a method to solve multi-objective optimization problems and to evaluate its performance. In order to verify the performance of this method it is applied for a vertical roller mill for Portland cement. A design process is defined with the compromise decision support problem concept and a design process consists of two steps: the design of experiments and mathematical programming. In this process, a designer decides an object that the objective function is going to pursuit and a non-linear optimization is performed composing objective constraints with practical constraints. In this method, response surfaces are used to model objectives (stress, deflection and weight) and the optimization is performed for each of the objectives while handling the remaining ones as constraints. The response surfaces are constructed using orthogonal polynomials, and orthogonal array as design of experiment, with analysis of variance for variable selection. In addition, it establishes the relative influence of the design variables in the objectives variability. The constrained optimization problems are solved using sequential quadratic programming. From the results, it is found that the method in this paper is a very effective and powerful for the multi-objective optimization of various practical design problems. It provides, moreover, a reference of design to judge the amount of excess or shortage from the final object.

• Atmosphere
• /
• v.20 no.2
• /
• pp.111-130
• /
• 2010

An uncertainty assessment for precipitation datasets simulated by Atmosphere-Ocean Coupled General Circulation Model (AOGCM) is conducted to provide reliable climate scenario over East Asia. Most of results overestimate precipitation compared to the observational data (wet bias) in spring-fall-winter, while they underestimate precipitation (dry bias) in summer in East Asia. Higher spatial resolution model shows better performances in simulation of precipitation. To assess the uncertainty of spatiotemporal precipitation in East Asia, the cyclostationary empirical orthogonal function (CSEOF) analysis is applied. An annual cycle of precipitation obtained from the CSEOF analysis accounts for the biggest variability in its total variability. A comparison between annual cycles of observed and modeled precipitation anomalies shows distinct differences: 1) positive precipitation anomalies of the multi-model ensemble (MME) for 20 models (thereafter MME20) in summer locate toward the north compared to the observational data so that it cannot explain summer monsoon rainfalls across Korea and Japan. 2) The onset of summer monsoon in MME20 in Korean peninsula starts earlier than observed one. These differences show the uncertainty of modeled precipitation. Also the comparison provides the criteria of annual cycle and correlation between modeled and observational data which helps to select best models and generate a new MME, which is better than the MME20. The spatiotemporal deviation of precipitation is significantly associated with lower-level circulations. In particular, lower-level moisture transports from the warm pool of the western Pacific and corresponding moisture convergence significantly are strongly associated with summer rainfalls. These lower-level circulations physically consistent with precipitation give insight into description of the reason in the monsoon of East Asia why behaviors of individually modeled precipitation differ from that of observation.

• Atmosphere
• /
• v.28 no.4
• /
• pp.457-467
• /
• 2018

This study investigated the variability of spring (March-May) forest fire risk in Korea for the period 1991~2017 and analyzed its relationship with large-scale climate factors. The Forest Weather Index (FWI) representing the meteorological risk for forest fire occurrences calculated based on observational data and its relationship with large-scale climate factors were analyzed. We performed the empirical orthogonal function (EOF) analysis on the spring FWI. The leading EOF mode of FWI accounting for about 70% of total variability was found to be highly correlated with total number of forest fire occurrences in Korea. The high FWI, forest fire occurrence risk, in Korea, is associated with warmer atmosphere temperature in midwest Eurasia-China-Korea peninsula, cyclonic circulation anomaly in northeastern China-Korea peninsula-northwest pacific, westerly wind anomaly in central China-Korea peninsula, and low humidity in Korea. These are further related with warmer sea surface temperature and enhanced outgoing longwave radiation over Western Pacific, which represents a typical condition for a La $Ni\tilde{n}a$ episode. This suggests that large-scale climate factors over East Asia and ENSO could have a significant influence on the occurrence of spring forest fires in Korea.

• Asian-Australasian Journal of Animal Sciences
• /
• v.20 no.2
• /
• pp.160-165
• /
• 2007

Dispersion parameters for the number of piglets born alive were estimated using a repeatability and random regression model. Six sow breeds/lines were included in the analysis: Swedish Landrace, Large White and both crossbred lines between them, German Landrace and their cross with Large White. Fixed part of the model included sow genotype, mating season as month-year interaction, parity and weaning to conception interval as class effects. The age at farrowing was modelled as a quadratic regression nested within parity. The previous lactation length was fitted as a linear regression. Random regressions for parity on Legendre polynomials were included for direct additive genetic, permanent environmental, and common litter environmental effects. Orthogonal Legendre polynomials from the linear to the cubic power were fitted. In the repeatability model estimate of heritability was 0.07, permanent environmental effect as ratio was 0.04, and common litter environmental effect as ratio was 0.01. Estimates of genetic parameters with the random regression model were generally higher than in the repeatability model, except for the common litter environmental effect. Estimates of heritability ranged from 0.06 to 0.10. Permanent environmental effect as a ratio increased along a trajectory from 0.03 to 0.11. Magnitudes of common litter effect were small (around 0.01). The eigenvalues of covariance functions showed that between 7 and 8 % of genetic variability was explained by individual genetic curves of sows. This proportion was mainly covered by linear and quadratic coefficients. Results suggest that the random regression model could be used for genetic analysis of litter size.

• Structural Engineering and Mechanics
• /
• v.75 no.4
• /
• pp.425-434
• /
• 2020

Practical non-synoptic fluctuating wind often exhibits nonstationary features and should be modeled as nonstationary random processes. Generally, the coherence function of the fluctuating wind field has time-varying characteristics. Some studies have shown that there is a big difference between the fluctuating wind field of the coherent function model with and without time variability. Therefore, it is of significance to simulate nonstationary fluctuating wind field with time-varying coherent function. However, current studies on the numerical simulation of nonstationary fluctuating wind field with time-varying coherence are very limited, and the proposed approaches are usually based on the traditional spectral representation method with low simulation efficiency. Especially, for the simulation of multi-variable wind field of large span structures such as transmission tower-line, not only the simulation is inefficient but also the matrix decomposition may have singularity problem. In this paper, it is proposed to conduct the numerical simulation of nonstationary fluctuating wind field in one-spatial dimension with time-varying coherence based on the wavenumber-frequency spectrum. The simulated multivariable nonstationary wind field with time-varying coherence is transformed into one-dimensional nonstationary random waves in the simulated spatial domain, and the simulation by wavenumber frequency spectrum is derived. So, the proposed simulation method can avoid the complicated Cholesky decomposition. Then, the proper orthogonal decomposition is employed to decompose the time-space dependent evolutionary power spectral density and the Fourier transform of time-varying coherent function, simultaneously, so that the two-dimensional Fast Fourier transform can be applied to further improve the simulation efficiency. Finally, the proposed method is applied to simulate the longitudinal nonstationary fluctuating wind velocity field along the transmission line to illustrate its performances.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2008.05a
• /
• pp.299-303
• /
• 2008

In this study, an uncertainty assessment for surface air temperature(T2m) and precipitation(PCP) over East Asia is carried out. The data simulated by the intergovermental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) Atmosphere-Ocean coupled general circulation Model (AOGCM) are used to assess the uncertainty. Examination of the seasonal uncertainty of T2m and PCP variabilities shows that spring-summer cold bias and fall warm bias of T2m are found over both East Asia and the Korea peninsula. In contrast, distinctly summer dry bias and winter-spring wet bias of PCP over the Korea peninsula is found. To investigate the PCP seasonal variability over East Asia, the cyclostationary empirical orthogonal function(CSEOF) analysis is employed. The CSEOF analysis can extract physical modes (spatio-temporal patterns) and their undulation (PC time series) of PCP, showing the evolution of PCP. A comparison between spatio-temporal patterns of observed and modeled PCP anomalies shows that positive PCP anomalies located in northeastern China (north of Korea) of the multi-model ensemble(MME) cannot explain properly the contribution to summer monsoon rainfalls across Korea and Japan. The uncertainty of modeled PCP indicates that there is disagreement between observed and MME anomalies. The spatio-temporal deviation of the PCP is significantly associated with lower- and upper-level circulations. In particular, lower-level moisture transports from the warm pool of the western Pacific and corresponding moisture convergence significantly contribute to summer rainfalls. These lower- and upper-level circulations physically consistent with PCP give a insight of the reason why differences between modeled and observed PCP occur.

• Ocean and Polar Research
• /
• v.31 no.1
• /
• pp.11-29
• /
• 2009

Variability of sea surface temperature (SST) in the Japan/East Sea (JES) was studied using complex empirical orthogonal function (CEOF) analysis. Two daily data sets were analyzed: (1) New Generation 0.05o-gridded SST from Tohoku University, Japan (July 2002-July 2006), and (2) 0.25o-gridded SST from the Japan Meteorological Agency (October 1993-November 2006). Linkages with wind stress curl were revealed using 6-h 1o-gridded surface zonal and meridional winds from ancillary data of the Sea- WiFS Project, a special National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) product (1998-2005). SST anomalies (SSTA) were obtained by removing the seasonal signal, estimated as the leading mode of the CEOF decomposition of the original SST. Leading CEOF modes of residual SSTA obtained from both data sets were consistent with each other and were characterized by annual, semiannual, and quasi-biennial time scales estimated with 95% statistical significance. The Semiannual Mode lagged 2 months behind the increased occurrence of the anticyclonic (AC) wind stress curl over the JES. Links to dynamic processes were investigated by numerical simulations using an oceanic model. The suggested dynamic forcings of SSTA are the inflow of subtropical water into the JES through the Korea Strait, divergence in the surface layer induced by Ekman suction, meridional shifts of the Subarctic Front in the western JES, AC eddy formation, and wind-driven strengthening/weakening of large-scale currents. Events of west-east SSTA movement were identified in July-September. The SSTA moved from the northeastern JES towards the continental coast along the path of the westward branch of the Tsushima Current at a speed consistent with the advective scale.