• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.178-184
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• 2003

Case-based reasoning (CBR) often shows significant promise for improving effectiveness of complex and unstructured decision making. Consequently, it has been applied to various problem-solving areas including manufacturing, finance and marketing. However, the design of appropriate case indexing and retrieval mechanisms to improve the performance of CBR is still challenging issue. Most of previous studies to improve the effectiveness for CBR have focused on the similarity function or optimization of case features and their weights. However, according to some of prior researches, finding the optimal k parameter for k-nearest neighbor (k-NN) is also crucial to improve the performance of CBR system. Nonetheless, there have been few attempts which have tried to optimize the number of neighbors, especially using artificial intelligence (AI) techniques. In this study, we introduce a genetic algorithm (GA) to optimize the number of neighbors to combine. This study applies the new model to the real-world case provided by an online shopping mall in Korea. Experimental results show that a GA-optimized k-NN approach outperforms other AI techniques for purchasing behavior forecasting.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.389-398
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• 2007

Case-based reasoning (CBR) is one of the most popular prediction techniques for medical diagnosis because it is easy to apply, has no possibility of overfitting, and provides a good explanation for the output. However, it has a critical limitation - its prediction performance is generally lower than other artificial intelligence techniques like artificial neural networks (ANNs). In order to obtain accurate results from CBR, effective retrieval and matching of useful prior cases for the problem is essential, but it is still a controversial issue to design a good matching and retrieval mechanism for CBR systems. In this study, we propose a novel approach to enhance the prediction performance of CBR. Our suggestion is the simultaneous optimization of feature weights, instance selection, and the number of neighbors that combine using genetic algorithms (GAs). Our model improves the prediction performance in three ways - (1) measuring similarity between cases more accurately by considering relative importance of each feature, (2) eliminating redundant or erroneous reference cases, and (3) combining several similar cases represent significant patterns. To validate the usefulness of our model, this study applied it to a real-world case for evaluating cytological features derived directly from a digital scan of breast fine needle aspirate (FNA) slides. Experimental results showed that the prediction accuracy of conventional CBR may be improved significantly by using our model. We also found that our proposed model outperformed all the other optimized models for CBR using GA.

• Journal of the Korean Society of Food Science and Nutrition
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• v.14 no.3
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• pp.305-313
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• 1985

There is a trend that the total number of cancer cases is steadily increasing as the population grows. It has been estimated that 85% of the cancer rate in the U.S. is attributed to environmental factors. Among the environmental factors, diet and nutrition appear to be related to the largest number of human cancers. Diet and nutrition might be related to cancer by several mechanisms. Food may contain a direct carcinogen or precursors that become carcinogens by spontanous reactions, or by host metabolism, or through the actions of microbial flora. Chemicals that cause cancers generally have reactive electrophilic centers which can combine with electron-rich atoms in nucleic acids and cause cancers by changing the genetic activity of the cells. A variety of factors in foods might be involved in the etiology of carcinogenesis. Chemicals in food that cause cancers include carcinogens of plants and animal origin and also those in drinking water. Other then these, fungal metabolites alcohol, asbestos, heavy metals, pesticides, and food additives might be included as food carcinogenesis. The method of cooking foods also might contribute to carcinogenesis. Some chemicals in foods act as promoters in carcinogenesis. Prevention of cancers by dietary practises have received much interest. Consumption of certain vegetables or cellulose can reduce carcinogenic activity of several compounds. A variety of antioxidants or micronutrients may be effective anticarciongens. Glutathione in the soluble fraction of the cells, is a major defense against oxidative and alkylating carcinogens. Recently anticarcinogenic activity of chlorophyll was demonstrated. Daily consumption of milk appears to effectively reduce stomach cancer.

• Journal of Elementary Mathematics Education in Korea
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• v.17 no.1
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• pp.129-142
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• 2013

The purpose of this study was to investigate the typical characteristics of mathematics education of Japan. In order to achieve this goal, we focused the journal 'Arithmetic Education' from 2007 to 2011. This journal has published by the Japan Society of Mathematical Education and 6 issues each year. A total of 133 articles related with mathematics education were analyzed. The typical characteristics of Japan's research for mathematics education were as follows: The number of single author of article were 98 cases (74%), and those of two co-authors were 21 cases (16%). There are some unusual research topic for mathematics education such as 'combined class'. 'cultural pluralism' and 'mathematics learning disabled children'. The articles 'statistical methods related to educational evaluation', 'statistical analysis for educational evaluation' and 'the relationship between number and quantity on the quaternion number' are very interesting results to the readers who know the basics of statistics and algebra. We may find many researcher who majored pure mathematics in the University of Educations in Korea. So we hope that they may write the paper which combine the pure mathematics and mathematics education. The education survey conducted by the policy is actually very meaningful. If the researcher can connect these surveys to the field of education, then the readers can see a nice paper in the journal of elementary mathematics education in Korea. Finally, it is very difficult to find that counterstatement paper for the results of the other's.

• Journal of the Korean Mathematical Society
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• v.53 no.3
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• pp.645-689
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• 2016

This article gives upper bounds on the number of Fourier-Jacobi coefficients that determine a paramodular cusp form in degree two. The level N of the paramodular group is completely general throughout. Additionally, spaces of Jacobi cusp forms are spanned by using the theory of theta blocks due to Gritsenko, Skoruppa and Zagier. We combine these two techniques to rigorously compute spaces of paramodular cusp forms and to verify the Paramodular Conjecture of Brumer and Kramer in many cases of low level. The proofs rely on a detailed description of the zero dimensional cusps for the subgroup of integral elements in each paramodular group.

• Korean Journal of Mathematics
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• v.30 no.3
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• pp.525-532
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• 2022

Let 𝓟_n denote the space of all complex polynomials $P(z)=\sum\limits_{j=0}^{n}{\alpha}_jz^j$ of degree n. Let P ∈ 𝓟_n, for any complex number α, D_αP(z) = nP(z) + (α - z)P'(z), denote the polar derivative of the polynomial P(z) with respect to α and B_n denote a family of operators that maps 𝓟_n into itself. In this paper, we combine the operators B and D_α and establish certain operator preserving inequalities concerning polynomials, from which a variety of interesting results can be obtained as special cases.

• Asia pacific journal of information systems
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• v.16 no.1
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• pp.71-84
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• 2006

Case-based reasoning (CBR) is a reasoning technique that reuses past cases to find a solution to the new problem. It often shows significant promise for improving effectiveness of complex and unstructured decision making. It has been applied to various problem-solving areas including manufacturing, finance and marketing for the reason. However, the design of appropriate case indexing and retrieval mechanisms to improve the performance of CBR is still a challenging issue. Most of the previous studies on CBR have focused on the similarity function or optimization of case features and their weights. According to some of the prior research, however, finding the optimal k parameter for the k-nearest neighbor (k-NN) is also crucial for improving the performance of the CBR system. In spite of the fact, there have been few attempts to optimize the number of neighbors, especially using artificial intelligence (AI) techniques. In this study, we introduce a genetic algorithm (GA) to optimize the number of neighbors to combine. This study applies the novel approach to Korean stock market. Experimental results show that the GA-optimized k-NN approach outperforms other AI techniques for stock market prediction.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.535-542
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• 2013

Since case-based reasoning(CBR) has many advantages, it has been used for supporting decision making in various areas including medical checkup, production planning, customer classification, and so on. However, there are several factors to be set by heuristics when designing effective CBR systems. Among these factors, this study addresses the issue of selecting appropriate neighbors in case retrieval step. As the criterion for selecting appropriate neighbors, conventional studies have used the preset number of neighbors to combine(i.e. k of k-nearest neighbor), or the relative portion of the maximum similarity. However, this study proposes to use the absolute similarity threshold varying from 0 to 1, as the criterion for selecting appropriate neighbors to combine. In this case, too small similarity threshold value may make the model rarely produce the solution. To avoid this, we propose to adopt the coverage, which implies the ratio of the cases in which solutions are produced over the total number of the training cases, and to set it as the constraint when optimizing the similarity threshold. To validate the usefulness of the proposed model, we applied it to a real-world target marketing case of an online shopping mall in Korea. As a result, we found that the proposed model might significantly improve the performance of CBR.

• Journal of Korean Society for Quality Management
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• v.51 no.4
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• pp.735-749
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• 2023

Purpose: The purpose of this study is to derive solutions and prevent similar cases from occurring by analyzing the causes of cracks found in temperature cycling tests of rocket motor. Methods: By combining the results of the current state confirmation test, non-destructive test, domestic and foreign rocket motor comparison test, cutting test, and adhesion test according to the number of times to apply mold release agent, a Cause and Effect Diagram analysis was performed to derive the cause of cracks. Results: Through this study, 26 factors that could cause cracking in rocket motors during temperature cycling tests were identified. Through various additional test results, a total of five causes were identified, including chemical and structural design of the joint between the propellant and stress relief insert, omission of procedure in the manufacturing procedures, natural aging due to temperature, and load accumulation due to temperature changes. The fundamental cause was confirmed to be insufficient consideration of the release properties of the propellant and stress relief insert. Conclusion: During the design process, it was confirmed that this could be solved by structurally or chemically designing the insert so that it does not combine with the propellant, or by applying a mold release agent during the manufacturing process.

• Structural Engineering and Mechanics
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• v.56 no.2
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• pp.169-188
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• 2015

There are two types of nonlinear analysis methods for building frameworks depending on the method of modeling the plastification of members including lumped plasticity and distributed plasticity. The lumped plasticity method assumes that plasticity is concentrated at a zero-length plastic hinge section at the ends of the elements. The distributed plasticity method discretizes the structural members into many line segments, and further subdivides the cross-section of each segment into a number of finite elements. When a reinforced concrete member experiences inelastic deformations, cracks tend to spread form the joint interface resulting in a curvature distribution. The program IDARC includes a spread plasticity formulation to capture the variation of the section flexibility, and combine them to determine the element stiffness matrix. In this formulation, the flexibility distribution in the structural elements is assumed to be the linear. The main objective of this study is to evaluate the accuracy of linear flexibility distribution assumed in the spread inelasticity model. For this purpose, nonlinear analysis of two reinforced concrete frames is carried out and the linear flexibility models used in the elements are compared with the real ones. It is shown that the linear flexibility distribution is incorrect assumption in cases of significant gravity load effects and can be lead to incorrect nonlinear responses in some situations.