• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.641-642
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• 2006

The purpose of this work is to investigate the effect of work load on heart rate variability (HRV) which is widely used marker of the autonomic nervous system activity. Average heart rate, rating of perceived exertion, and the power spectrum of heart rate variability were investigated in seven healthy males during exercise at various work loads. The subjects were divided into two groups according to the average heart rate during exercise, group 1 with lower heart rate and group 2 with higher heart rate. HF component showed decrease followed by increase with workload. Accordingly, the LF/HF ratio showed increase followed by decrease with workload. The peak in LF/HF ratio of group 1 was at the lower workload than that of group 2.

• The Journal of the Acoustical Society of Korea
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• v.25 no.1E
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• pp.1-7
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• 2006

This study examines the reflection characteristic of a thin transition layer of the ocean bottom showing variability with respect to depth. In order to model the surficial sediment simply, we reduce the Biot model to the depth dependent wave equation for the pseudo fluid using the fluid approximation (weak frame approximation). From the reduced equation, the difference between the inherent frequency dependency of the reflection and the frequency dependency resulting from a thin transition layer is investigated. Using Tang's depth porosity profile model of the surficial sediment [D. Tang et al., IEEE J. Oceanic Eng., vol.27(3), 546-560(2002)], we numerically simulated the reflection loss and investigated the contribution from both frequency dependencies. In addition, the effects of different sediment type and varying depth structure of the sediment are discussed.

• Journal of Biosystems Engineering
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• v.33 no.5
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• pp.362-369
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• 2008

There is developing interest in precision agriculture in Korea, despite the fact that typical Korean fields are less than 1 ha in size. Describing within-field variability in typical Korean production settings is a fundamental first step toward determining the size of management zones and the inter-relationships between limiting factors, for establishment of site-specific management strategies. Measurements of rice (Oriza Sativa L) yield, chlorophyll content, and soil properties were obtained in a small (100-m by 30-m) Korean rice paddy field. Yield data were manually collected on 10-m by 5-m grids (180 samples with 3 samples in each of 60 grid cells) and chlorophyll content was measured using a Minolta SPAD 502 in 2-m by 2-m grids. Soil samples were collected at 275 points to compare results from sampling at different scales. Ten soil properties important for rice production in Korea were determined through laboratory analyses. Variogram analysis and point kriging with and without median polishing were conducted to determine the variability of the measured parameters. Influence of variogram model selection and other parameters on the interpretation of the data was investigated. For many of the data, maximum values were greater than double the minimum values, indicating considerable spatial variability in the small paddy field, and large-scale spatial trends were present. When variograms were fit to the original data, the limits of spatial dependency for rice yield and SP AD reading were 11.5 m and 6.5 m, respectively, and after detrending the limits were reduced to 7.4 m and 3.9 m. The range of spatial dependency for soil properties was variable, with several having ranges as short as 2 m and others having ranges greater than 30 m. Kriged maps of the variables clearly showed the presence of both large-scale (trend) variability and small-scale variability in this small field where it would be reasonable to expect uniformity. These findings indicate the potential for applying the principles and technology of precision agriculture for Korean paddy fields. Additional research is needed to confirm the results with data from other fields and crops.d similar tendency with the result for the frequency less than 20 Hz, but the width of change was reduced highly.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.456-463
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• 2009

The preconsolidation pressure has been commonly determined by oedometer test. However, it can also be determined by in-situ test, such as piezocone test with theoretical and(or) empirical correlations. Recently, Neural Network(NN) theory was applied and some models were proposed to estimate the preconsolidation pressure or OCR. However, since the optimization process of synaptic weights of NN model is dependent on the initial synaptic weights, NN models which are trained with different initial weights can't avoid the variability on prediction result for new database even though they have same structure and use same transfer function. In this study, Committee Neural Network(CNN) model is proposed to improve the initial weight dependency of multi-layered neural network model on the prediction of preconsolidation pressure of soft clay from piezocone test result. It was found that even though the NN model has the optimized structure for given training data set, it still has the initial weight dependency, while the proposed CNN model can improve the initial weight dependency of the NN model and provide a consistent and precise inference result than existing NN models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1238-1259
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• 2024

Previous studies on joint optimization of computation offloading and service caching policies in Mobile Edge Computing (MEC) have often neglected the impact of dependency-aware subtasks, edge server resource constraints, and multiple users on policy formulation. To remedy this deficiency, this paper proposes a many-objective joint optimization dependency-aware task offloading and service caching model (MaJDTOSC). MaJDTOSC considers the impact of dependencies between subtasks on the joint optimization problem of task offloading and service caching in multi-user, resource-constrained MEC scenarios, and takes the task completion time, energy consumption, subtask hit rate, load variability, and storage resource utilization as optimization objectives. Meanwhile, in order to better solve MaJDTOSC, a many-objective evolutionary algorithm TSMSNSGAIII based on a three-stage mating selection strategy is proposed. Simulation results show that TSMSNSGAIII exhibits an excellent and stable performance in solving MaJDTOSC with different number of users setting and can converge faster. Therefore, it is believed that TSMSNSGAIII can provide appropriate sub-task offloading and service caching strategies in multi-user and resource-constrained MEC scenarios, which can greatly improve the system offloading efficiency and enhance the user experience.

• Asia-Pacific Journal of Atmospheric Sciences
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• v.54 no.4
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• pp.599-610
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• 2018

The goal of this study was to statistically analyse the variability of global irradiance and ultraviolet erythemal (UVER) irradiance and their interrelationships with global and UVER irradiance, global clearness indices and ozone. A prediction of short-term UVER solar irradiance values was also obtained. Extreme values of UVER irradiance were included in the data set, as well as a time series of ultraviolet irradiance variability (UIV). The study period was from 2005 to 2014 and approximately 250,000 readings were taken at 5-min intervals. The effect of the clearness indices on global irradiance variability (GIV) and UIV was also recorded and bi-dimensional distributions were used to gather information on the two measured variables. With regard to daily GIV and UIV, it is also shown that for global clearness index ($k_t$) values lower than 0.6 both global and UVER irradiance had greater variability and that UIVon cloud-free days ($k_t$ higher than 0.65) exceeds GIV. To study the dependence between UIVand GIV the ${\chi}^2$ statistical method was used. It can be concluded that there is a 95% probability of a clear dependency between the variabilities. A connection between high $k_t$ (corresponding to cloudless days) and low variabilities was found in the analysis of bidimensional distributions. Extreme values of UVER irradiance were also analyzed and it was possible to calculate the probable future values of UVER irradiance by extrapolating the values of the adjustment curve obtained from the Gumbel distribution.

• Structural Engineering and Mechanics
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• v.39 no.6
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• pp.877-893
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• 2011

Response spectra of earthquake ground motions are important in the earthquake-resistant design and reliability analysis of structures. The formulation of the response spectrum in the frequency domain efficiently computes and evaluates the stochastic response spectrum. The frequency information of the excitation can be described using different functional forms. The shapes of the calculated response spectra of the excitation show strong magnitude and site dependency, but weak distance dependency. In this paper, to compare the effect of the earthquake ground motion variables, the contribution of these sources of variability to the response spectrum's uncertainty is calculated by using a stochastic analysis. The analytical results show that earthquake source factors and soil condition variables are the main sources of uncertainty in the response spectra, while path variables, such as distance, anelastic attenuation and upper crust attenuation, have relatively little effect. The presented formulation of dynamic structural response in frequency domain based only on the frequency information of the excitation can provide an important basis for the structural analysis in some location that lacks strong motion records.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.682-686
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• 2007

Construction project has been more complex and bigger as various demands of the times. But current schedule management method in construction project uses only PERT or CPM made in 1950s without innovation. Also current schedule management focuses on not information flow between activities and variability of information exchanged but result. This paper suggest using the DSM(Dependency Structure Matrix) in schedule management of construction project to overcome limitations of current scheduling tools. DSM has been introduced as a new theory in construction industry in 1990s at the United States, but its application is still insufficient in domestic field due to the absence of systematic study.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.3
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• pp.43-59
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• 1995

This paper presents a method for estimating the population variability distribution of the failure parameter (failure rate or failure probability) for each failure mode considered in PSA (Probabilistic Safety Assessment). We focus on the utilization of generic estimates from various industry compendia for the estimation. The estimates are complicated statistics of failure data from plants. When the failure data referred in two or more sources are overlapped, dependency occurs among the estimates provided by the sources. This type of problem is first addressed in this paper. We propose methods based on ML-II estimation in Bayesian framework and discuss the characteristics of the proposed estimators. The proposed methods are easy to apply in real field. Numerical examples are also provided.