• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.415-418
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• 2003

Fuzzy modelling has the approximation property far the given input-output relationship. Especially, Takagi-Sugeno fuzzy models are widely used because they show very good performance in the nonlinear function approximation problem. But generally there is not the systematic method incorporating the human expert's knowledge or experience in fuzzy rules and it is not easy to End the membership function of fuzzy rule to minimize the output error as well. The ANFIS (Adaptive Network-based Fuzzy Inference Systems) is one of the neural network based fuzzy modelling methods that can be used with various type of fuzzy rules. But in this model, it is the problem to End the optimum number of fuzzy rules in fuzzy model. In this paper, a new fuzzy modelling method based on the ANFIS and pruning techniques with the measure named impact factor is proposed and the performance of proposed method is evaluated with several simulation results.

• Nuclear Engineering and Technology
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• v.41 no.1
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• pp.1-10
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• 2009

The safe and reliable performance of fusion and fission plants depends on the choice of suitable materials and an assessment of long-term materials degradation. These materials are degraded by their exposure to extreme conditions; it is necessary, therefore, to address the issue of long-term damage evolution of materials under service exposure in advanced plants. The empirical approach to the study of structural materials and fuels is reaching its limit when used to define and extrapolate new materials, new environments, or new operating conditions due to a lack of knowledge of the basic principles and mechanisms present. Materials designed for future Gen IV systems require significant innovation for the new environments that the materials will be exposed to. Thus, it is a challenge to understand the materials more precisely and to go far beyond the current empirical design methodology. Breakthrough technology is being achieved with the incorporation in design codes of a fundamental understanding of the properties of materials. This paper discusses the multi-scale, multi-code computations and multi-dimensional modelling undertaken to understand the mechanical properties of these materials. Such an approach is envisaged to probe beyond currently possible approaches to become a predictive tool in estimating the mechanical properties and lifetimes of materials.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.352-366
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• 2021

To decrease Europe's harmful emissions, the European Union aims to substantially increase its offshore wind energy capacity. To further develop offshore wind energy, investment in ever-larger construction vessels is necessary. However, this market is characterised by seemingly unpredictable growth of market demand, turbine capacity and distance from shore. Currently it is difficult to deal with such market uncertainty within the ship design process. This research aims to develop a method that is able to deal with market uncertainty in early ship design by increasing knowledge when design freedom is still high. The method uses uncertainty modelling prior to the requirement definition stage by performing global research into the market, and during the concept design stage by iteratively co-evolving the vessel design and business case in parallel. The method consists of three parts; simulating an expected market from data, modelling multiple vessel designs, and an uncertainty model that evaluates the performance of the vessels in the market. The case study into offshore wind foundation installation vessels showed that the method can provide valuable insight into the effect of ship parameters like main dimensions, crane size and ship speed on the performance in an uncertain market. These results were used to create a value robust design, which is capable of handling uncertainty without changes to the vessel. The developed method thus provides a way to deal with market uncertainty in the early ship design process.

• Journal of Korean Society for Quality Management
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• v.38 no.3
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• pp.294-312
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• 2010

Data Technology (DT) is a new technology which deals with data collection, data analysis, information generation from data, knowledge generation from modelling and future prediction. DT is a newly emerged interdisciplinary science & technology in this 21st century knowledge society. Even though the main body of DT is applied statistics, it also contains management information system (MIS), quality management, process system analysis and so on. Therefore, it is an interdisciplinary science and technology of statistics, management science, industrial engineering, computer science and social science. In this paper, first of all, the definition of DT is given, and then the effects and the basic properties of DT, the differences between IT and DT, the 6 step process for DT application, and a DT example are provided. Finally, the relationship among DT, e-Statistics and Data Mining is explained, and the direction of DT development is proposed.

• Steel and Composite Structures
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• v.2 no.5
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• pp.355-378
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• 2002

Use of composite steel construction with precast hollow core slabs is now popular in the UK, but the present knowledge in shear capacity of the headed shear studs for this type of composite construction is very limited. Currently, all the information is based on the results obtained from experimental push-off tests. A finite element model to simulate the behaviour of headed stud shear connection in composite beam with precast hollow core slabs is described. The model is based on finite element method and takes into account the linear and non-linear behaviour of all the materials. The model has been validated against the test results, for which the accuracy of the model used is demonstrated. Parametric studies showing the effect of the change in transverse gap size, transverse reinforcement diameter and in-situ concrete strength on the shear connection capacity are presented.

• Journal of the Korea Safety Management & Science
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• v.14 no.2
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• pp.177-183
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• 2012

Obtaining and applying information is considered as a critical task in the modern informationized society. Finding the one's necessary information and processing it into a detailed knowledge are becoming more priortized in the enormous amount of information. Data modelling is the process that does not only reflect the demands of the user but the one that also facilitates the user's comprehension of the model itself. Ultimately, data modelling fully supports the processes that are requisite for the implementation of a data base and minimizes the alternations of the model during the development of applications.

• Journal of Educational Research in Mathematics
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• v.14 no.1
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• pp.39-69
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• 2004

This paper investigates the teaching and learning of Linear function relating functional contexts and suggests the improved methods of representation-shift through this analysis. The methods emphasize the link between students' preacquired knowledge of mathematical representations and the way of using those. This methods are explanatory teaching, teaching and teaming based on modelling perspectives or tasks (interpretation, prediction, translation and scaling). We categorize the 8th grade middle school students' errors on the linear function relating real contexts and make a comparative study of the error-remedial effects and the teaching and teaming methods. We present the results of a study in which representation-shift methods based on modelling perspectives and tasks are more effective in terms of flexible connection of representations and error remediation. Also, We describe how students used modelling perspective-taking to explain and justify their conceptual models, to assess the quality of their models and to make connection to other mathematical representation during the problem solving focusing on the students' self-diagnosis.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.211-220
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• 2021

The aim of the study is to implement a factor analysis of the determinants of pricing in a state-regulated competitive market using economic and mathematical modelling methods and to develop ways to improve the pricing environment of the market under study. The purpose of the work defines the main objectives: (i) to investigate the features of the competitive model of the Ukrainian flour market; (ii) to analyse the current price conjuncture of the flour market and the dynamics of the main determinants of pricing; (iii)to develop ways of improving the price situation on the flour market on the basis of the factor analysis on the results of economic and mathematical modelling. In order to ensure the reliability and validity of the research results, the following methods were applied: the logical-dialectical method of scientific knowledge in the study of the main theoretical aspects of flour market functioning, the method of logical generalisation and synthesis, comparison, factor analysis, correlation and regression analysis, the graphical method, etc. It has been shown that pricing in a state-regulated competitive market has its own characteristics. For example, in the flour market the price of goods cannot be influenced by producers (sellers) by any methods, therefore determinants of pricing by indirect influence have been taken into account. The five-factor power model of wheat flour price has been constructed. It was substantiated that the price of wheat flour in Ukraine is mostly influenced by consumer price index (0.92 %). The received complex model of wheat flour price may be used also for medium-term forecasting and working out the ways of price formation optimization in the flour market.

• Journal of Contemporary Eastern Asia
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• v.13 no.1
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• pp.5-18
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• 2014

This exploratory study investigates the use of a computational knowledge engine (WolframAlpha) and social networking sites (Gmail, Yahoo and Facebook) by 200 students at De La Salle-College of Saint Benilde, their "friends" and their "friends of friends" during the 2009 through 2013 school years, and how this appears to have added value in knowledge generation. The primary aim is to identify what enhances productiveness in knowledge generation in Philippine Tertiary Education. The phenomenological approach is used, therefore there are no specific research questions or hypotheses proposed in this paper. Considering that knowledge generation is a complex phenomenon, a stochastic modelling approach is also used for the investigation that was developed specifically to study un-deterministic complex systems. A list of salient features for knowledge generation is presented as a result. In addition to these features, various problem types are identified from literature. These are then integrated to provide a proposed framework of inclusive (friendly) and innovative social networks, for knowledge generation in Philippine tertiary education. Such a framework is necessarily multidisciplinary and useful for problem-solving in a globalized and pluralist reality. The implementation of this framework is illustrated in the three parts of the study: Part 1: Online lessons, discussions, and examinations in General Psychology, Introduction to Sociology, and Life and Works of Jose Rizal, for the author's students in De La Salle-College of Saint Benilde; Part 2: Facebook Report analytics of students and teachers, their friends and their friends of friends via WolframAlpha; and Part 3: Social Network Analysis of the people and groups influencing the courses' scope-and-sequence in the new General Education Curriculum for Tertiary Schools and Institutions in the Philippines.

• Journal of the Korea Safety Management & Science
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• v.15 no.3
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• pp.133-141
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• 2013

As a work analysis technique, Work Domain Analysis (WDA) aims to identify the design knowledge structure of a work domain that human operators interact with through human-system interfaces. Abstraction hierarchy (AH) is a multi-level, hierarchical knowledge representation framework for modeling the functional structure of any kinds of systems. Thus, WDA based on AH aims to identify the functional knowledge structure of a work domain. AH has been used in a range of work domains and problems to model their functional knowledge structure and has proven its generality and usefulness. However, many of researchers and system designers have reported that it is never easy to understand the concepts underlying AH and use it effectively for WDA. This would be because WDA is a form of work analysis that is different from other types of work analysis techniques such as task analysis and AH has several unique characteristics that are differentiated from other types of function analysis techniques used in systems engineering. With this issue in mind, this paper introduces the concepts of WDA based on AH and offers a comprehensive list of references. Next, this paper proposes a set of principles for effectively applying AH for work domain analysis, which are developed based on the author's experiences, consultation with experts, and literature reviews.