• The Journal of the Acoustical Society of Korea
• /
• v.23 no.1
• /
• pp.82-89
• /
• 2004

This paper describes how to reduce the effect of an occupation threshold by that the transform of mixture components of HMM parameters is controlled in hierarchical tree structure to prevent from over-adaptation. To reduce correlations between data elements and to remove elements with less variance, we employ PCA (principal component analysis) and ICA (independent component analysis) that would give as good a representation as possible, and decline the effect of over-adaptation. When we set lower occupation threshold and increase the number of transformation function, ordinary WLLR adaptation algorithm represents lower recognition rate than SI models, whereas the proposed MLLR adaptation algorithm represents the improvement of over 2% for the word recognition rate as compared to performance of SI models.

• International Journal of CAD/CAM
• /
• v.5 no.1
• /
• pp.99-109
• /
• 2005

This paper introduces an approach to an ontology-based multi-level knowledge framework for a knowledge management system for discrete-product development. Participants in a product life cycle want to share comprehensive product knowledge without any ambiguity and heterogeneity. However, previous knowledge management approaches are limited in providing those aspects: therefore, we suggest an ontology-based multi-level knowledge framework (OBMKF). The bottom level, the axiom, specifies the semantics of concepts and relations of knowledge so ambiguity can be alleviated. The middle level is a product development knowledge map; it defines the concepts and the relations of the product domain knowledge and guides the engineer to process their engineering decisions. The middle level is then classified further into more detailed levels, such as generic product level, specific product level, product version level, and manufactured item level, according to the various viewpoints. The top level is specialized knowledge for a specific domain that gives the solution of a specific task or problem. It is classified into three knowledge types: expert knowledge, engineering function knowledge, and data-analysis-based knowledge. This proposed framework is based on ontology to accommodate a comprehensive range of knowledge and is represented with first-order logic to maintain a uniform representation.

• Journal of Korean Elementary Science Education
• /
• v.37 no.2
• /
• pp.161-172
• /
• 2018

This study investigated the changes in representation on analogies that elementary science-gifted students generated by using Algodoo program to explain the electric current. After the students were taught about the 'components in circuit and their function' and 'electric current' with teacher centered analogy and PhET program for 4 class hours, they generated analogies to the electric circuit. Then they compared the similarity between generated analogy and target concept and matched it to the target concept. The result revealed that the battery, light bulb, and electric wire were changed according to the change of representations on free electrons. And they generated more proper analogies reflected the target concept when represented the free electrons by the circular particles than the water. From these results, we can say that generating analogy using Algodoo program is the effective education activity to help students understand abstract concept by visualizing it more easily and simply.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.2
• /
• pp.564-582
• /
• 2015

This paper proposes a novel swarm intelligence optimization method which integrates bacterial foraging optimization (BFO) with quantum computing, called quantum bacterial foraging optimization (QBFO) algorithm. In QBFO, a multi-qubit which can represent a linear superposition of states in search space probabilistically is used to represent a bacterium, so that the quantum bacteria representation has a better characteristic of population diversity. A quantum rotation gate is designed to simulate the chemotactic step for the sake of driving the bacteria toward better solutions. Several tests are conducted based on benchmark functions including multi-peak function to evaluate optimization performance of the proposed algorithm. Numerical results show that the proposed QBFO has more powerful properties in terms of convergence rate, stability and the ability of searching for the global optimal solution than the original BFO and quantum genetic algorithm. Furthermore, we examine the employment of our proposed QBFO for cognitive radio spectrum allocation. The results indicate that the proposed QBFO based spectrum allocation scheme achieves high efficiency of spectrum usage and improves the transmission performance of secondary users, as compared to color sensitive graph coloring algorithm and quantum genetic algorithm.

• Journal of the Korea Computer Graphics Society
• /
• v.24 no.3
• /
• pp.43-48
• /
• 2018

In this paper, we present a method for removing shadows from scanned documents. Compared to the existing methods such as one based on image pyramid representation or adaptive thresholding, our method produces more robust and higher quality results. The basic idea of the approach is to use the local image statistics and to separate interesting regions from the image such as the regions around letters and figures. For the separated regions, we adaptively adjust the local brightness and contrast, and apply the sigmoid function to the intensity values as well to enhance the clarity of the image. For separated the other empty regions, we apply the gradient-base image hole filling method to fill the region with smooth color change.

• Water for future
• /
• v.20 no.2
• /
• pp.117-126
• /
• 1987

A Synthetic unit hydrograph method was suggested for the representation of a direct runoff hydrograph with empirical geomorphologic laws and geomorphologic parameters by applying geomorphologic instantaneous unit hydrograph theory and Rossois results of application of GIUH theory to the Nash Model which is a linear reservoir model. The shape parameter m and scale parameter k can be derived by the Horton's empirical geomorphologic laws $R_A,R_B,R_L$ when ordered according to Strahler's ordering Scheme, main stream length and using the maximum velocity for the dynamic characteristics of a river basin, The derived response function was tested on some observed flood datas and showed promising. For the determination of the shape parameter m, eq. (16) was showed applying and m showed a good regression with the size of basin area.

• Korean Journal of Child Studies
• /
• v.36 no.3
• /
• pp.139-154
• /
• 2015

The purpose of this study was to explore the process of scientific thinking as it is revealed through the cases of constructive play for young children. For this purpose, the researcher observed and interviewed six four-year-olds in the Jaemi Class while recording them with a camcorder during a free choice activity class in the morning from April 23 to June 25, 2012. The observations were analyzed in chronological order according to the changes of theories and structure as presented by the children themselves. The process of scientific thinking in constructive play for young children can be divided into presentation of naive theories, the abandonment of naive theories according to repetitive experiences and the discovery of inconsistency, the representation of alternative theories, and the abandonment of alternative theories according to repetitive experiences and the discovery of contradictions. On the basis of the results, constructive play has proved to serve a valuable educational function by inducing scientific thinking processes in children. On the basis of this finding, the researcher suggests the need to provide appropriate educational support to teachers.

• International Journal of Fluid Machinery and Systems
• /
• v.8 no.3
• /
• pp.169-182
• /
• 2015

When simulating the dynamic behaviour of a hydro power plant, it is essential to have a good representation of the turbine behaviour. The pressure transients in the system occurs because the flow changes, which the turbine defines. The flow through the turbine is a function of the pressure, the speed of rotation and the wicket gate opening and is, most often described in a performance diagram or Hill diagram. In the Hill diagram, the efficiency is drawn like contour lines, hence the name. A turbines Hill diagram is obtained by performance tests on scaled model in a laboratory. However, system dynamic simulations have to be performed in the early stage of a project, before the turbine manufacturer has been chosen and the Hill diagram is known. Therefore one have to rely on diagrams for a turbine with similar speed number. The Hill diagram is drawn through measured points, so for using the diagram in a simulation program, one have to iterate in the diagram based on curve fitting of the measured points. This paper describes an alternative method. By means of the Euler turbine equation, it is possible to set up two differential equations which represents the turbine performance with good enough accuracy for the dynamic simulations. The only input is the turbine's main geometry, the runner blade in- and outlet angle and the guide vane angle at best efficiency point of operation (BEP). In the paper, simulated turbine characteristics for a high head Francis turbine, and for a reversible pump turbine are compared with laboratory measured characteristics.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.4
• /
• pp.293-301
• /
• 2001

This paper reviews three methods to compute a pointwise confidence interval of neuro-fuzzy models and compares their estimation perfonnanee through simulations. The eOITl.putation methods under consideration include stacked generalization using cross-validation, predictive error bar in regressive models, and local reliability measure for the networks employing a local representation scheme. These methods implemented on the neuro-fuzzy models are applied to the problems of simple function approximation and chaotic time series prediction. The results of reliability estimation are compared both quantitatively and qualitatively.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.8 no.1
• /
• pp.82-86
• /
• 2008

The article presents ARTMAP and Fuzzy BK-Product approach underwater obstacle avoidance for the Autonomous underwater Vehicles (AUV). The AUV moves an unstructured area of underwater and could be met with obstacles in its way. The AUVs are equipped with complex sensorial systems like camera, aquatic sonar system, and transducers. A Neural integrated Fuzzy BK-Product controller, which integrates Fuzzy logic representation of the human thinking procedure with the learning capabilities of neural-networks (ARTMAP), is developed for obstacle avoidance in the case of unstructured areas. In this paper, ARTMAP-Fuzzy BK-Product controller architecture comprises of two distinct elements, are 1) Fuzzy Logic Membership Function and 2) Feed-Forward ART component. Feed-Forward ART component is used to understanding the unstructured underwater environment and Fuzzy BK-Product interpolates the Fuzzy rule set and after the defuzzyfication, the output is used to take the decision for safety direction to go for avoiding the obstacle collision with the AUV. An on-line reinforcement learning method is introduced which adapts the performance of the fuzzy units continuously to any changes in the environment and make decision for the optimal path from source to destination.