• Advances in nano research
• /
• 제9권3호
• /
• pp.147-156
• /
• 2020

This research is related to nonlinear stability analysis of advanced microbeams reinforced by Graphene Platelets (GPLs) considering generic geometrical imperfections and thermal loading effect. Uniform, linear and nonlinear distributions of GPLs in transverse direction have been considered. Imperfection sensitivity of post-bucking behaviors of the microbeam to different kinds of geometric imperfections have been examined. Geometric imperfection is first considered to be identical as the first buckling mode, then a generic function is employed to consider sine-type, local-type and global-type imperfectness. Modified couple stress theory is adopted to incorporate size-dependent behaviors of the beam at micro scale. The post-buckling problem is solved analytically to derive load-amplitude curves. It is shown that post-buckling behavior of microbeam is dependent on the type geometric imperfection and its magnitude. Also, post-buckling load can be enhanced by adding more GPLs or selecting a suitable distribution for GPLs.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제53권3호
• /
• pp.135-144
• /
• 2004

In this paper, we propose competitive fuzzy polynomial neurons-based advanced Self-Organizing Neural Networks(SONN) architecture for optimal model identification and discuss a comprehensive design methodology supporting its development. The proposed SONN dwells on the ideas of fuzzy rule-based computing and neural networks. And it consists of layers with activation nodes based on fuzzy inference rules and regression polynomial. Each activation node is presented as Fuzzy Polynomial Neuron(FPN) which includes either the simplified or regression polynomial fuzzy inference rules. As the form of the conclusion part of the rules, especially the regression polynomial uses several types of high-order polynomials such as linear, quadratic, and modified quadratic. As the premise part of the rules, both triangular and Gaussian-like membership (unction are studied and the number of the premise input variables used in the rules depends on that of the inputs of its node in each layer. We introduce two kinds of SONN architectures, that is, the basic and modified one with both the generic and the advanced type. Here the basic and modified architecture depend on the number of input variables and the order of polynomial in each layer. The number of the layers and the nodes in each layer of the SONN are not predetermined, unlike in the case of the popular multi-layer perceptron structure, but these are generated in a dynamic way. The superiority and effectiveness of the Proposed SONN architecture is demonstrated through two representative numerical examples.

• 기술혁신연구
• /
• 제2권1호
• /
• pp.256-276
• /
• 1994

This paper aims at identifying the desirable R'||'&'||'D life cycle related to government-industry cooperative R'||'&'||'D. It is based on a case study associated with the relationship between cooperation and cooperation in information in information communications sector. It presents three types of R'||'&'||'D life cycle to achieve a technological enhancement as high as possible with limited resources. The first case of R'||'&'||'D project is of "advanced type". In the generic technology phase, government takes a leading role jointly in R'||'&'||'D activities, but, in after the applied research phase, the domestic firms take the lead. This kind of cooperation can be made when competition between domestic firms is highly intense, and the technological knowledges of participating firms are at internationally competitive levels. The second type of "less-advanced type"; the firms of a country(more often a small country) lag behind in technology level, and the penetration of foreign firms in the market is limited. In this case, government takes full charge of R'||'&'||'D activities up to the applied research phase, due to the low technology level and insufficient financial resources of private firms. Lastly, this paper presents and R'||'&'||'D life cycle of "strategic" type. This applies to the case in which domestic firm with less financial resources make an attempt to increase their technological knowledges while the government, in turn, contributes to strengthen the international competitiveness of domestic industry.

• KIEE International Transaction on Systems and Control
• /
• 제12D권1호
• /
• pp.12-17
• /
• 2002

We propose a new category of neurofuzzy networks- Self-organizing Neural Networks(SONN) with fuzzy polynomial neurons(FPNs) and discuss a comprehensive design methodology supporting their development. Two kinds of SONN architectures, namely a basic SONN and a modified SONN architecture are dicussed. Each of them comes with two types such as the generic and the advanced type. SONN dwells on the ideas of fuzzy rule-based computing and neural networks. Simulation involves a series of synthetic as well as experimental data used across various neurofuzzy systems. A comparative analysis is included as well.

• Transactions on Control, Automation and Systems Engineering
• /
• 제3권1호
• /
• pp.43-50
• /
• 2001

In this paper, we propose the design procedure of advance Polynomial Neural Networks(PNN) architecture for optimal model identification of complex and nonlinear system. The proposed PNN architecture is presented as the generic and advanced type. The essence of the design procedure dwells on the Group Method of Data Handling(GMDH). PNN is a flexible neural architecture whose structure is developed through learning. In particular, the number of layers of the PNN is not fixed in advance but is generated in a dynamic way. In this sense, PNN is a self-organizing network. With the aid of three representative numerical examples, compari-sons show that the proposed advanced PNN algorithm can produce the model with higher accuracy than previous other works. And performance index related to approximation and generalization capabilities of model is evaluated and also discussed.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
• /
• pp.806-808
• /
• 2000

We propose a new Dynamic Multilayer Perceptorn(DMP) architecture for optimal model identification of complex and nonlinear system in this paper. The proposed DMP scheme is presented as the generic and advanced type based on the GMDH(Group Method of Data Handling) method for the limitation of GMDH under only two system input variables. It is worth stressing that the number of the layers and the nodes in each layer of the DMP are not predetermined, unlike in the case of the popular multilayer perceptron structure, but these are generated in a dynamic manner. The experimental part of the study comes with representative nonlinear static system. Comparative analysis is included and shows that a new DMP can produce the model with higher accuracy than previous other works.

• Industrial Engineering and Management Systems
• /
• 제11권4호
• /
• pp.310-330
• /
• 2012

Scheduling is an important tool for a manufacturing system, where it can have a major impact on the productivity of a production process. In manufacturing systems, the purpose of scheduling is to minimize the production time and costs, by assigning a production facility when to make, with which staff, and on which equipment. Production scheduling aims to maximize the efficiency of the operation and reduce the costs. In order to find an optimal solution to manufacturing scheduling problems, it attempts to solve complex combinatorial optimization problems. Unfortunately, most of them fall into the class of NP-hard combinatorial problems. Genetic algorithm (GA) is one of the generic population-based metaheuristic optimization algorithms and the best one for finding a satisfactory solution in an acceptable time for the NP-hard scheduling problems. GA is the most popular type of evolutionary algorithm. In this survey paper, we address firstly multiobjective hybrid GA combined with adaptive fuzzy logic controller which gives fitness assignment mechanism and performance measures for solving multiple objective optimization problems, and four crucial issues in the manufacturing scheduling including a mathematical model, GA-based solution method and case study in flexible job-shop scheduling problem (fJSP), automatic guided vehicle (AGV) dispatching models in flexible manufacturing system (FMS) combined with priority-based GA, recent advanced planning and scheduling (APS) models and integrated systems for manufacturing.

• Nuclear Engineering and Technology
• /
• 제54권3호
• /
• pp.860-866
• /
• 2022

An accurate prediction of the pressure drop along the flow paths is crucial in the design of advanced passive systems cooled by heavy liquid metal coolants. To date, a generic pressure drop correlation over spacer grids by Rehme has been applied extensively, which was obtained from substantial experimental data with multiple types of components. However, a few experimental studies have reported that the correlation may give large discrepancies. To provide a more reliable correlation for ring-type spacer grids, the current numerical study aims at figuring out the most critical factor among four hypothetical parameters, namely the flow area blockage ratio, number of fuel rods, type of fluid, and thickness of the spacer grid in the flow direction. Through a set of computational fluid dynamics simulations, we observed that the flow area blockage ratio dominantly influences the pressure loss characteristics, and thus its dependence should be more emphasized, whereas the other parameters have little impact. Hence, we suggest a new correlation for the drag coefficient as C_B = C_ν,m/ε^2.7, where C_ν,m is formulated by a nonlinear fit of simulation data such that C_ν,m = -11.33 ln(0.02 ln(Re_b)).

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2003년도 하계학술대회 논문집 D
• /
• pp.2519-2521
• /
• 2003

In this paper, we propose Self-Organizing Fuzzy Polynomial Neural Networks(SOFPNN) architecture for optimal model identification and discuss a comprehensive design methodology supporting its development. It is shown that this network exhibits a dynamic structure as the number of its layers as well as the number of nodes in each layer of the SOFPNN are not predetermined (as this is the case in a popular topology of a multilayer perceptron). As the form of the conclusion part of the rules, especially the regression polynomial uses several types of high-order polynomials such as linear, quadratic, and modified quadratic. As the premise part of the rules, both triangular and Gaussian-like membership function are studied and the number of the premise input variables used in the rules depends on that of the inputs of its node in each layer. We introduce two kinds of SOFPNN architectures, that is, the basic and modified one with both the generic and the advanced type. The superiority and effectiveness of the proposed SOFPNN architecture is demonstrated through nonlinear function numerical example.

• 한국초등과학교육학회지:초등과학교육
• /
• 제19권2호
• /
• pp.57-74
• /
• 2000

Students' concepts of scientific phenomena have become a point of focus in science education research. This study investigated into developmental process and mechanism of the students' respiration concept through a cross-age study. This study utilized the 1st, 3rd, 6th grade elementary students to find out changes in student's understanding of the concept of respiration. The 1st and 3rd grade level students were interviewed what the respiration mean and whether each of living things respires, etc. The 6th grade students were interviewed and tested. Respiration is a word that students come across often in everyday life. It was found that they were more likely to associate respiration with its more common concept of breathing or gas exchange as opposed to its more scientific definition as the process in which nutrients are oxidized to provide energy. This trend didn't improve as they advanced grade. This is an indication that the knowledge system of student is split into a generic knowledge system and scientific knowledge system. Understanding of concept increased and differentiated across grade levels but that understanding was limited. They overcome their tendency to base their understanding of respiration on their understanding of human phenomena and learn to integrate their understanding of biological phenomena through a one organ - one role type of logic. They also intuitively explain everything based on their own experience.