• Journal of Intelligence and Information Systems
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• v.3 no.2
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• pp.83-91
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• 1997

DELVAUX is an inductive learning environment that learns Bayesian classification rules from a set o examples. In DELVAUX, a genetic a, pp.oach is employed to learn the best rule-set, in which a population consists of rule-sets and rule-sets generate offspring by exchanging some of their rules. We have explored a meta-learning a, pp.oach in the DELVAUX learning environment to improve the classification performance of the DELVAUX system. The meta-learning a, pp.oach learns the bias of a classifier so that it can evaluate the prediction made by the classifier for a given example and thereby improve the overall performance of a classifier system. The paper discusses the meta-learning a, pp.oach in details and presents some empirical results that show the improvement we can achieve with the meta-learning a, pp.oach.

• Journal of Wetlands Research
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• v.11 no.1
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• pp.49-64
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• 2009

Rainfall-runoff models are used for efficient management, distribution, planning, and design of water resources in accordance with the process of hydrologic cycle. The models simplify the transition of rainfall to runoff as rainfall through different processes including evaporation, transpiration, interception, and infiltration. As the models simplify complex physical processes, gaps between the models and actual rainfall events exist. For more accurate simulation, appropriate models that suit analysis goals are selected and reliable long-term hydrological data are collected. However, uncertainty is inherent in models. It is therefore necessary to evaluate reliability of simulation results from models. A number of studies have evaluated uncertainty ingrained in rainfall-runoff models. In this paper, Meta-Gaussian method proposed by Montanari and Brath(2004) was used to assess uncertainty of simulation outputs from rainfall-runoff models. The model, which estimates upper and lower bounds of the confidence interval from probabilistic distribution of a model's error, can quantify global uncertainty of hydrological models. In this paper, Meta-Gaussian method was applied to analyze uncertainty of simulated runoff outputs from $Vflo^{TM}$, a physically-based distribution model and HEC-HMS model, a conceptual lumped model.

• Research in Community and Public Health Nursing
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• v.29 no.3
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• pp.359-370
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• 2018

Purpose: The purpose of this study is to identify effects of the variables of Health Action Process Approach (HAPA) Model on physical activity. Methods: This study has conducted a systematic literature review and meta-analysis. Sixteen articles were searched through electronic databases (PsycINFO, PubMed, CINAHL, Web of science, Science Direct, RISS, KMBASE, KoreaMed, KISS, DBpia) and additional journals from 2000 to July, 2017. To estimate the effect size (ES), the meta-analysis of the studies was performed by using Comprehensive Meta-Analysis programs. Results: The overall effect size of the variables of HAPA on physical activity was median (ES=.28). Of the core variables of HAPA model, action control (ES=.43) showed the largest effect size, followed by coping self-efficacy (ES=.31) and planning (ES=.31).Additional variables were identified as preparatory behavior (ES=.39) and past physical activity (ES=.24). Through the moderator effect analysis, the effect size was higher in the volitional phase than in the motivational phase, and higher in the healthy group than in the patient group. The higher the proportion of males and the lower the age, the larger the effect size. Conclusion: This finding shows empirical evidence that all core variables of the HAPA model are useful for predicting physical activity. We propose the use of the HAPA model to develop physical activity promotion intervention.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.733-737
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• 2008

강우-유출(Rainfall Runoff, R-R)모형은 수자원계획과 관리를 위하여 가장 보편적으로 이용되는 도구로 홍수, 가뭄 등과 같은 극한 사상의 예측 또는 물수지 분석에 사용되고 있다. 오랜 기간 많은 수문학자들이 강우-유출 모형의 불확실성 개선 및 정량화하기 위하여 노력하였으나, 여전히 중요한 수문학적 과제로 남아있다. 이에 본 연구에서는 강우-유출 모형의 불확실성을 정량화하는데 목적을 두고 물리적 기반의 분포형 모형과 개념적 준 분포형 모형을 중랑천 유역에 적용하여 그 결과를 비교하였다.

• Genomics & Informatics
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• v.14 no.4
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• pp.173-180
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• 2016

The meta-analysis has become a widely used tool for many applications in bioinformatics, including genome-wide association studies. A commonly used approach for meta-analysis is the fixed effects model approach, for which there are two popular methods: the inverse variance-weighted average method and weighted sum of z-scores method. Although previous studies have shown that the two methods perform similarly, their characteristics and their relationship have not been thoroughly investigated. In this paper, we investigate the optimal characteristics of the two methods and show the connection between the two methods. We demonstrate that the each method is optimized for a unique goal, which gives us insight into the optimal weights for the weighted sum of z-scores method. We examine the connection between the two methods both analytically and empirically and show that their resulting statistics become equivalent under certain assumptions. Finally, we apply both methods to the Wellcome Trust Case Control Consortium data and demonstrate that the two methods can give distinct results in certain study designs.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2072-2087
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• 1999

As software size ever increases and user's requirements become more and more sophisticated., the importance of software quality is more and more emphasized. However, we are not satisfied for the present techniques on detecting errors and checking consistency in the object-oriented design model. This paper proposes a systematic approach which produces implementable rules to detect errors and check consistency. At first, the meta-models for UML diagrams are constructed, generalized meta-rules are reduced from the meta-models, and then the meta-rules are applied to produce the implementable rules. This approach enables to pursue the completeness of the rules and the automation of rule application. An example of rule application shows the feasibility of the rule application.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2008.10b
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• pp.104-112
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• 2008

As the information and communications market goes more uncertain, foresight activities becomes more important. A number of foresight activities, such as trend analysis, have been used to predict customer needs. However previous studies tend to lack objectivity and systematization. In this study, we suggest a meta analysis methodology which combines both top-down and bottom-up approach in order to systematize the analysis process. Secondly, we applied this approach to ICT market to identify essential future technologies. Based on the result from the meta analysis, we have constructed the future technology roadmap.

• International journal of advanced smart convergence
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• v.11 no.3
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• pp.150-156
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• 2022

Recently, the use of Unreal Engine for animation production is increasing. In this situation, Unreal Engine's 'MetaHuman Creator' helps make it easier to apply realistic characters to animation. In this regard, we tried to produce animations using 'MetaHuman' and verify the effectiveness and differences from the animation production process using only Maya software. To increase the efficiency of the production process, the animation process was made with Maya software. We tried to import animation data from Unreal Engine and go through the process of making animations, and try to find out if there are any problems. And we tried to compare animations made with realistic 'MetaHuman' characters and animation works using cartoon-type characters. The use of the same camera lens in realistic character animations and cartoon character animations produced based on the same scenario was judged to be the cause of the lack of realistic animation screen composition. The analysis revealed that a different approach from the existing animation camera lens selection is required for the selection of the camera lens in the production of realistic animation.

• Industrial Engineering and Management Systems
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• v.13 no.2
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• pp.163-171
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• 2014

Under amazing increase in markets and certain demand on qualified service in the delivery system, global logistic optimization is becoming a keen interest to provide an essential infrastructure coping with modern competitive prospects. As a key technology for such deployment, we have been engaged in the practical studies on vehicle routing problem (VRP) in terms of Weber model, and developed a hybrid approach of meta-heuristic methods and the graph algorithm of minimum cost flow problem. This paper extends such idea to multi-depot VRP so that we can give a more general framework available for various real world applications including those in green or low carbon logistics. We show the developed procedure can handle various types of problem, i.e., delivery, direct pickup, and drop by pickup problems in a common framework. Numerical experiments have been carried out to validate the effectiveness of the proposed method. Moreover, to enhance usability of the method, Google Maps API is applied to retrieve real distance data and visualize the numerical result on the map.

• Structural Engineering and Mechanics
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• v.65 no.6
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• pp.707-719
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• 2018

In this article, a new method is introduced to improve the local search capability of meta-heuristic algorithms using the projection of the path on the border of constraints. In a mathematical point of view, the Gradient Projection Method is applied through a new approach, while the imposed limitations are removed. Accordingly, the gradient vector is replaced with a new meta-heuristic based vector. Besides, the active constraint identification algorithm, and the projection method are changed into less complex approaches. As a result, if a constraint is violated by an agent, a new path will be suggested to correct the direction of the agent's movement. The presented procedure includes three main steps: (1) the identification of the active constraint, (2) the neighboring point determination, and (3) the new direction and step length. Moreover, this method can be applied to some meta-heuristic algorithms. It increases the chance of convergence in the final phase of the search process, especially when the number of the violations of the constraints increases. The method is applied jointly with the authors' newly developed meta-heuristic algorithm, entitled Star Graph. The capability of the resulted hybrid method is examined using the optimal design of truss and frame structures. Eventually, the comparison of the results with other meta-heuristics of the literature shows that the hybrid method is successful in the global as well as local search.