• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.491-501
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• 2002

Case-based reasoning is emerging as a leading methodology for the application of artificial intelligence. CBR is a reasoning methodology that exploits similar experienced solutions, in the form of past cases, to solve new problems. Hybrid model achieves some convergence of the wide proliferation of credit evaluation modeling. As a result, Hybrid model showed that proposed methodology classify more accurately than any of techniques individually do. It is confirmed that proposed methodology predicts significantly better than individual techniques and the other combining methodologies. The objective of the proposed approach is to determines a set of weighting values that can best formalize the match between the input case and the previously stored cases and integrates fuzzy sit concepts into the case indexing and retrieval process. The GA is used to search for the best set of weighting values that are able to promote the association consistency among the cases. The fitness value in this study is defined as the number of old cases whose solutions match the input cases solution. In order to obtain the fitness value, many procedures have to be executed beforehand. Also this study tries to transform financial values into category ones using fuzzy logic approach fur performance of credit evaluation. Fuzzy set theory allows numerical features to be converted into fuzzy terms to simplify the matching process, and allows greater flexibility in the retrieval of candidate cases. Our proposed model is to apply an intelligent system for bankruptcy prediction.

• Journal of Yeungnam Medical Science
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• v.30 no.1
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• pp.4-9
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• 2013

Leptin, a 16-kDa cytokine, is secreted by adipose tissue in response to the surplus of fat store. Thereby, the brain is informed about the body's energy status. In the hypothalamus, leptin triggers specific neuronal subpopulations (e.g., POMC and NPY neurons) and activates several intracellular signaling events, including the JAK/STAT, MAPK, PI3K, and mTOR pathway, which eventually translates into decreased food intake and increased energy expenditure. Leptin signal is inhibited by a feedback inhibitory pathway mediated by SOCS3. PTP1B involves another inhibitory pathway of leptin. Leptin potently promotes fat mass loss and body weight reduction in lean subjects. However, it is not widely used in the clinical field because of leptin resistance, which is a common feature of obesity characterized by hyperleptinemia and the failure of exogenous leptin administration to provide therapeutic benefit in rodents and humans. The potential mechanisms of leptin resistance include the following: 1) increases in circulating leptin-binding proteins, 2) reduced transport of leptin across the blood-brain barrier, 3) decreased leptin receptor-B (LRB), and/or 4) the provocation of processes that diminish cellular leptin signaling (inflammation, endoplasmic reticulum stress, feedback inhibition, etc.). Thus, interference of the cellular mechanisms that attenuate leptin signaling improves leptin action in cells and animal models, suggesting the potential utility of these processes as points of therapeutic intervention. Various experimental trials and compounds that improve leptin resistance are introduced in this paper.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.179-184
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• 1999

When the steel containing Si is oxidated in hi temperature, Re2O3, Red scale is made on the metal side as the spike phase, and this scale invasion into matrix. Therefore, it affects the feature, after rolling. It is reported that the role of Si is FeO/Fe2SiO4 eutectic compound, but Si can not affect pure iron independently. There must be Ni, then the spike phase can exist. Prominence and depression made by Ni that is necessity at the process to work iron. Therefore, in this study after the change of the amount of Ni in pure iron and steel and oxidation, the structure of the oxide and the surface, and the distribution of the elements were considered. In conclusion, at 100$0^{\circ}C$, 110$0^{\circ}C$, 120$0^{\circ}C$ the curves of oxidation weight are all S curves. Especially, in the beginning of oxidation as the amount of Ni increase, the amount of oxidation also increase. Practical steel has less oxidation than pure steel added Ni. There is much FeO in Fe-Ni alloy, compare to practical steel which has much Fe3O4. Especially, we could know considerable Ni was concentrated on the metal side in Fe-Ni alloy, practical steel. and the surface of the scale.

• International Journal of Contents
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• v.8 no.1
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• pp.23-29
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• 2012

Multiple expression levels of genes obtained using time series microarray experiments have been exploited effectively to enhance understanding of a wide range of biological phenomena. However, the unique nature of microarray data is usually in the form of large matrices of expression genes with high dimensions. Among the huge number of genes presented in microarrays, only a small number of genes are expected to be effective for performing a certain task. Hence, discounting the majority of unaffected genes is the crucial goal of gene selection to improve accuracy for disease diagnosis. In this paper, a non-Gaussian weight matrix obtained from an incremental model is proposed to extract useful features of multivariate time series microarrays. The proposed method can automatically identify a small number of significant features via discovering hidden variables from a huge number of features. An unsupervised hierarchical clustering representative is then taken to evaluate the effectiveness of the proposed methodology. The proposed method achieves promising results based on predictive accuracy of clustering compared to existing methods of analysis. Furthermore, the proposed method offers a robust approach with low memory and computation costs.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.2
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• pp.67-72
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• 2005

Overwintering capacity, closely related to winter hardiness, of Chinese milk vetch planted with different sowing times and sowing practices was investigated to improve the incorporation into cropping system in Korea. The tolerance to low temperature was evaluated with $LT_50$ using leaf disc leaching method. Dry weight of CMV was reduced remarkably with delayed planting from Sep. 5 to Oct. 20. The differences in tolerance to freezing temperature were not conspicuous among CMV genotypes, however, the differences between genotype (collections at different regions) were due to the plant architecture, mainly to the leaf angle. The crouching genotype collected at central region of Korean peninsula, which showed excellent freezing tolerant, has planophile leaves. The feature of internal constituents of CMV genotypes did not show any noticeable differences with respect to the freezing tolerance which evaluated by leaf disc leaching experiment. To overcome the poor overwintering capacity, tolerant genotype should be developed by selection with considering the plant architecture. The reduction of CMV growth during overwintering period was ameliorated with furrow-sowing under late-sown condition, therefore, when the CMV is inevitably sown late after recommended time, the seeds should be sown on furrow to overcome the cold stress.

• The Journal of the Korea Contents Association
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• v.7 no.6
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• pp.52-59
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• 2007

This paper presents a greedy method for user-steered mesh segmentation, which is based on the merging priority metric defined for representing the geometric properties of meaningful parts. The priority metric is a weighted function composed of five geometric parameters: distribution of Gaussian map, boundary path concavity, boundary path length, cardinality, and segmentation resolution. This scheme can be extended without any modification only by defining more geometric parameters and adding them. Our experimental results show that the shapes of segmented parts can be controlled by setting up the weight values of geometric parameters.

• The Korean Journal of Applied Statistics
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• v.25 no.5
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• pp.829-835
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• 2012

When the input features are generated by factors in a classification problem, it is more meaningful to identify important factors, rather than individual features. The $F_{\infty}$-norm support vector machine(SVM) has been developed to perform automatic factor selection in classification. However, the $F_{\infty}$-norm SVM may suffer from estimation inefficiency and model selection inconsistency because it applies the same amount of shrinkage to each factor without assessing its relative importance. To overcome such a limitation, we propose the adaptive $F_{\infty}$-norm ($AF_{\infty}$-norm) SVM, which penalizes the empirical hinge loss by the sum of the adaptively weighted factor-wise $L_{\infty}$-norm penalty. The $AF_{\infty}$-norm SVM computes the weights by the 2-norm SVM estimator and can be formulated as a linear programming(LP) problem which is similar to the one of the $F_{\infty}$-norm SVM. The simulation studies show that the proposed $AF_{\infty}$-norm SVM improves upon the $F_{\infty}$-norm SVM in terms of classification accuracy and factor selection performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5322-5342
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• 2016

In vehicle-to-vehicle (V2V) networks, where selfishness degrades node activity, countermeasures for collaboration enforcement must be provided to enable application of a sage and efficient network environment. Because vehicular networks feature both high mobility and various topologies, selfish behavior judgment and establishment of a stable routing protocol become intensely challenging. In this paper, a two-phase-based generous cooperative routing protocol (called GEC) is presented for V2V networks to provide resistance to selfishness. To detect selfish behaving vehicles, a packet forwarding watchdog and an average connection rate based on the multipath weight method are used, where evidence is gathered from different watchdogs. Then, multihop relay decisions are made using a generous cooperative algorithm based on game theory. Finally, through buffering of the multiple end-to-end paths and judicious choice of optimal cooperative routes, route maintenance phase is capable of dealing with congestion and rapidly exchanging traffic. Specifically, it is proved that the GEC is theoretically subgame perfect. Simulation results show that for V2V networks with inherently selfish nodes, the proposed method isolates uncooperative vehicles and is capable of accommodating both the mobility and congestion circumstances by facilitating information dissemination and reducing end-to-end delay.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.191-194
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• 2011

문서를 이루는 단어들의 빈도수가 지수법칙(power law)를 따른다는 지프의 법칩(Zipf's law)이 있다. 이러한 단어분포를 고려하여 문서의 토픽을 찾아내는 기계학습법이 디리쉴레 프로세스(Dirichlet process) 이다. 이를 발전시켜서 데이터의 잠재 요인(latent factor)들을 베이즈 확률모델에 기반한 샘플링 바탕으로 찾는 방법이 인디언 뷔페 과정(Indian buffet process) 이다. 우리는 25가지의 특징(feature)들에 대한 점수(rating)들이 볼드(blood oxygen dependent level) 신호와 함께 주어지는 PBAIC 2007 데이터에 주성분 분석법(principal component analysis)를 적용했다. PBAIC 2007 데이터는 비디오 게임을 수행하며 기능적뇌영상(functional magnetic resonance imaging, fMRI) 촬영을 하여 얻어진 공개데이터이다. 우리의 연구에서는 주성분 분석법을 이용하여 10개의 독립 성분(independent component)들을 찾았다. 그리고 1.75초 마다 촬영된 BOLD 신호와 10개의 고유벡터(eigenvector)들간의 내적을 취하여 가중치(weight)를 구하였다. 성분들의 가중치를 낮은 순서로 정렬함으로써 각 시간마다 주도적으로 영향을 미치는 성분들을 알아낼 수 있었다.

• Smart Structures and Systems
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• v.1 no.4
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• pp.325-338
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• 2005

Utilizing robotic based reconfigurable nodal structural health monitoring systems has many advantages over static or human positioned sensor systems. However, creating a robot capable of traversing a variety of civil infrastructures is a difficult task, as these structures each have unique features and characteristics posing a variety of challenges to the robot design. This paper outlines the design and implementation of a novel robotic platform for deployment on ferromagnetic structures as an enabling structural health monitoring technology. The key feature of this design is the utilization of an attachment device which is an advancement of the common magnetic base found in the machine tool industry. By mechanizing this switchable magnetic circuit and redesigning it for light weight and compactness, it becomes an extremely efficient and robust means of attachment for use in various robotic and structural health monitoring applications. The ability to engage and disengage the magnet as needed, the very low power required to do so, the variety of applicable geometric configurations, and the ability to hold indefinitely once engaged make this device ideally suited for numerous robotic and distributed sensor network applications. Presented here are examples of the mechanized variable force magnets, as well as a prototype robot which has been successfully deployed on a large construction site. Also presented are other applications and future directions of this technology.