• Research in Community and Public Health Nursing
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• v.29 no.4
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• pp.510-519
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• 2018

Purpose: The purpose of this meta-analysis isto identify social psychological factors related to quality of life and estimate the effect sizes of the factors among patients with strokes. Methods: Thirteen studies with a total of 1,814 patients published from the earliest records to January 8, 2017 were selected through a systematic process of searching the literature, and evaluated against influencing factors of quality of life and their effect sizes. Pooled effect sizes were calculated using the random effect model. Meta-analysis was conducted by R software. Results: The following influencing factors had a strong association with quality of life with stroke: depression (r=-.50; 95% CI: -0.63~-0.46), activities of daily living (r=.46; 95% CI: 0.35~0.56), and social support (r=.40; 95% CI: 0.24~0.53). Conclusion: The findings confirm that depression, activities of daily living and social support are associated with quality of life among patients with stroke survivors. We recommend that any intervention program to improve the quality of life with stroke patients consider addressing these modifiable influencing factors.

• Animal Bioscience
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• v.37 no.7
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• pp.1185-1195
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• 2024

Objective: This meta-analysis aimed to evaluate the impact of wilted and unwilted silage on various parameters, such as nutrient content, fermentation quality, bacterial populations, and digestibility. Methods: Thirty-six studies from Scopus were included in the database and analyzed using a random effects model in OpenMEE software. The studies were grouped into two categories: wilting silage (experiment group) and non-wilting silage (control group). Publication bias was assessed using a fail-safe number. Results: The results showed that wilting before ensiling significantly increased the levels of dry matter, water-soluble carbohydrates, neutral detergent fiber, and acid detergent fiber, compared to non-wilting silage (p<0.05). However, wilting significantly decreased dry matter losses, lactic acid, acetic acid, butyric acid, and ammonia levels (p<0.05). The pH, crude protein, and ash contents remained unaffected by the wilting process. Additionally, the meta-analysis revealed no significant differences in bacterial populations, including lactic acid bacteria, yeast, and aerobic bacteria, or in vitro dry matter digestibility between the two groups (p>0.05). Conclusion: Wilting before ensiling significantly improved silage quality by increasing dry matter and water-soluble carbohydrates, as well as reducing dry matter losses, butyric acid, and ammonia. Importantly, wilting did not have a significant impact on pH, crude protein, or in vitro dry matter digestibility.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.931-938
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• 2006

It is important to operate an education resources which could be integrated to an system. But most of existing education information system was not developed with standardization. It is need the core education asset and reusable education service to make a good education system. Consequently, it is needed to use Sharable Content Object Reference Model(SCORM) based contents managing in order to reuse the contents of education. And it needs assembling and producing method with reusable core asset of education system to develop the application program for education. In this thesis, we study the Teaching-Learning supporting system to support systematic education resources. Teaching-Learning support system is developed of educational domain assess through development process based on Model Driven Architecture(MDA) and core asset on each stage. Application program of education is developed using MDA automatic tool through analyzing and designing for contents storage which is based on contents meta model. We finally can develop the application software of education with low cost and high productivity by raising the reusability of education contents and by using the core asset to the whole development process.

• Journal of the Korea Society for Simulation
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• v.29 no.4
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• pp.95-109
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• 2020

In this paper, an optimal manufacturing system design problem in an automotive body assembly lines is introduced when various costs such as equipment investment costs are considered. Meta-model methodology based on simulation results has been used for estimating the performances of the system such as production rate and work-in-process levels. The objective function is minimizing total cost which satisfies the target production rate. The investment costs such as robots, buffers, transportation equipment, and the inventory holding cost of work-in-process have been included in the objective function. Harmony search method has been used for optimization.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.379-384
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• 2011

The scope of the problems that could be solved by monitoring and the improvement of the recognition time is directly correlated to the performance of the management function of the business process. However, the current monitoring process of business activities decides whether to apply warnings or not by assuming a fixed environment and showing expressions based on the design rules. Also, warnings are applied by carrying out the measuring process when the event attribute values are inserted at every point. Therefore, there is a limit for distinguishing the range of occurrence and the level of severity in regard to the new external problems occurring in a complicated environment. Such problems cannot be ed. Also, since it is difficult to expand the range of problems which can be possibly evaluated, it is impossible to evaluate any unexpected situation which could occur in the execution period. In this paper, a process-evaluating model based on the goal scenario is suggested to provide constant services through the current monitoring process in regard to the service demands of the new scenario which occurs outside. The new demands based on the outside situation are analyzed according to the goal scenario for the process activities. Also, by using the meta-heuristic algorithm, a similar process model is found and identified by combining similarity and interrelationship. The process can be stopped in advance or adjusted to the wanted direction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1773-1793
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• 2023

Automated machine learning, often referred to as "AutoML," is the process of automating the time-consuming and iterative procedures that are associated with the building of machine learning models. There have been significant contributions in this area across a number of different stages of accomplishing a data-mining task, including model selection, hyper-parameter optimization, and preprocessing method selection. Among them, preprocessing method selection is a relatively new and fast growing research area. The current work is focused on the recommendation of preprocessing methods, i.e., feature subset selection (FSS) algorithms. One limitation in the existing studies regarding FSS algorithm recommendation is the use of a single learner for meta-modeling, which restricts its capabilities in the metamodeling. Moreover, the meta-modeling in the existing studies is typically based on a single group of data characterization measures (DCMs). Nonetheless, there are a number of complementary DCM groups, and their combination will allow them to leverage their diversity, resulting in improved meta-modeling. This study aims to address these limitations by proposing an architecture for preprocess method selection that uses ensemble learning for meta-modeling, namely AutoFE-Sel. To evaluate the proposed method, we performed an extensive experimental evaluation involving 8 FSS algorithms, 3 groups of DCMs, and 125 datasets. Results show that the proposed method achieves better performance compared to three baseline methods. The proposed architecture can also be easily extended to other preprocessing method selections, e.g., noise-filter selection and imbalance handling method selection.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.5
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• pp.501-507
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• 2010

Structural optimization is performed to minimize the weight of a RC building structure, which has eight floors above ground and three underground, under gravity, wind, and seismic loads. Design optimization problem is formulated to find the values of the design variables that minimize the volume while satisfying various design and side constraints. To solved the optimization problem posed, several design techniques equipped in PIAnO, a commercial PIDO tool, are used. DOE is used to generate training points and structural analysis is performed using MIADS Gen, a general-purpose structural analysis CAE tool. Then, meta-models are generated from structural analysis results and accuracies of meta-models are evaluated. Next, design optimization is performed by using the verified meta-models and optimization technique equipped in PIAnO. Finally, we obtained optimal results, which could demonstrate the effectiveness of our design method.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.5
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• pp.23-29
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• 2013

Recent advances in printing technology have increased the productivity of the roll-to-roll (R2R) printing process for printed circuitry. In the R2R printed electronics, characteristics of printed and coated layers are one of the most important issues that determine the functional quality of final products. The slot-die technology can coat a large area with high uniformity using low-viscosity materials; determining the process parameters is important to obtain excellent coating qualities. In this study, a viscocapillary model was used to predict qualities of coated layers and patterns. On the basis of analysis results, a novel meta model was derived using design of experiment methodology to improve accuracy. Sensitivity analysis was performed to define major parameters in R2R slot-die coating process. The coating speed was found to most significantly affect the coated layer thickness and was easily controlled. The performance of the proposed model is verified through experimental studies. Based on the statistical analysis results, R2R slot die process can be optimized to guarantee a desired thickness.

• The Journal of Society for e-Business Studies
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• v.24 no.2
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• pp.165-178
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• 2019

In an environment transformed by smart factories, measuring the current level of the manufacturing system, deriving improvement targets and tasks and increasing the level of manufacturing competitiveness become the basic activities of the company. However, research on the component analysis and maturity assessment to ensure the future competitiveness of the company is in progress and in the early stages. This study analyzed the existing research on various models, development process, and framework for manufacturing system. In addition, we designed a structural model by deriving the components of future manufacturing system through smart factory related maturity assessment studies. We designed a meta-model that includes an assesment model and a transformation model, and derived the framework development process to propose an integrated framework for the maturity assessment of the future manufacturing system. We verified it by applying it into an actual evaluation project of smart factory.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.452-459
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• 2023

The core power control is an important issue for the study of dynamic characteristics in China initiative accelerator driven subcritical system (CiADS), which has direct impact on the control strategy and safety analysis process. The CiADS is an experimental facility that is only controlled by the proton beam intensity without considering the control rods in the current engineering design stage. In order to get the optimized operation scheme with the stable and reliable features, the variation of beam intensity using the continuous and periodic control approaches has been adopted, and the change of collimator and the adjusting of duty ratio have been proposed in the power control process. Considering the neutronics and the thermal-hydraulics characteristics in CiADS, the physical model for the core power control has been established by means of the point reactor kinetics method and the lumped parameter method. Moreover, the multi-inputs single-output (MISO) logical structure for the power control process has been constructed using proportional integral derivative (PID) controller, and the meta-heuristic algorithm has been employed to obtain the global optimized parameters for the stable running mode without producing large perturbations. Finally, the verification and validation of the control method have been tested based on the reference scenarios in considering the disturbances of spallation neutron source and inlet temperature respectively, where all the numerical results reveal that the optimization method has satisfactory performance in the CiADS core power control scenarios.