• Proceedings of the Korean Information Science Society Conference
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• 2007.10a
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• pp.34-35
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• 2007

• The Journal of the Acoustical Society of Korea
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• v.23 no.3
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• pp.253-261
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• 2004

In this paper, a new voice personality transformation method is proposed. which modifies speaker-dependent feature variables in the speech signals. The proposed method takes the cepstrum vectors and pitch as the transformation paremeters, which represent vocal tract transfer function and excitation signals, respectively. To transform these parameters, a multiple response classification and regression tree (MR-CART) is employed. MR-CART is the vector extended version of a conventional CART, whose response is given by the vector form. We evaluated the performance of the proposed method by comparing with a previously proposed codebook mapping method. We also quantitatively analyzed the performance of voice transformation and the complexities according to various observations. From the experimental results for 4 speakers, the proposed method objectively outperforms a conventional codebook mapping method. and we also observed that the transformed speech sounds closer to target speech.

• The Journal of Korean Association of Computer Education
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• v.18 no.5
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• pp.63-70
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• 2015

In the environment that the complex conditions need to be satisfied, skyline query have been applied to various field. To processing a skyline query in centralized scheme, several techniques have been suggested and recently map/reduce platform based approaches has been proposed which divides data space into multiple partitions for the vast volume of multidimensional data. However, the performances of these approaches are fluctuated due to the uneven data loading between servers and redundant tasks. Motivated by these issues, this paper suggests a novel technique called MR-DEAP which solves the uneven data loading using the random sampling. The experimental result gains the proposed MR-DEAP outperforms MR-Angular and MR-BNL scheme.

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.18-29
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• 2007

In this paper we present a system that classifies brain MR images by using 2 level decision tree learning. There are two kinds of information that can be obtained from images. One is the low-level features such as size, color, texture, and contour that can be acquired directly from the raw images, and the other is the high-level features such as existence of certain object, spatial relations between different parts that must be obtained through the interpretation of segmented images. Learning and classification should be performed based on the high-level features to classify images according to their semantic meaning. The proposed system applies decision tree learning to each level separately, and the high-level features are synthesized from the results of low-level classification. The experimental results with a set of brain MR images with tumor are discussed. Several experimental results that show the effectiveness of the proposed system are also presented.

• Journal of Internet Computing and Services
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• v.9 no.1
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• pp.9-19
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• 2008

This paper propose the issue of connecting nested NEMO (Network Nobility) networks to global IPv6 networks, while supporting IPv6 mobility. Specifically, we consider a self-addressing including topology information IPv6-enabled NEMO infrastructure. The proposed self-organization addressing protocol automatically organized mobile routers into free architecture and configuration their global IPv6 addresses. BU(binding update) to MR own HA and internal rouging, hosed on longest prefix matching and soft state routing cache, are specially designed for IPv6-based NEMO. In conclusion, numeric analysis ore conducted to show more efficiency of the proposed routing protocols than other RO (Route Optimization) approaches.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.166-168
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• 2004

지리정보시스템에 대한 응용분야가 확대되면서 지리정보시스템의 기반이 되는 데이터베이스의 성능에 대한 정확한 평가가 중요하게 인식된다. 이때 지리정보시스템의 기반이 되는 데이터베이스는 일반적인 데이터베이스와는 달리 공간 질의와 비공간 질의가 동시에 처리될 수 있어야 하므로 이를 위한 효율적인 색인 구성이 요구되며 이에 대한 성능의 명가가 특별히 중요하다. 본 논문에서는 주기억 데이터베이스 기반의 지리정보시스템에 적합하도록 비공간 색인과 공간 색인을 별도로 두는 이중 색인 구성을 제안하고 실제 색인이 지리정보시스템에 적용되었을 때 그에 이 시스템에 대한 성능을 평가하였다. 실험을 통친 색인에 따른 데이터베이스의 성능비교도 함께 측정하였다. 지리정보시스템을 위한 주기억 데이터베이스에 T-tree와 MR-tree가 비공간 및 공간색인을 위해 적용되었을 때 데이터가 증가하여도 질의에 대한 속도가 거의 변화가 없는 우수한 성능을 보여주는 것을 확인할 수 있었다.

• Journal of Electrical Engineering and Technology
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• v.10 no.2
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• pp.670-675
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• 2015

Medical imaging is one of the most powerful tools for gaining information about internal organs and tissues. It is a challenging task to develop sophisticated image analysis methods in order to improve the accuracy of diagnosis. The objective of this paper is to develop a Computer Aided Diagnostics (CAD) scheme for Brain Tumour detection from Magnetic Resonance Image (MRI) using active contour models and to investigate with several approaches for improving CAD performances. The problem in clinical medicine is the automatic detection of brain Tumours with maximum accuracy and in less time. This work involves the following steps: i) Segmentation performed by Fuzzy Clustering with Level Set Method (FCMLSM) and performance is compared with snake models based on Balloon force and Gradient Vector Force (GVF), Distance Regularized Level Set Method (DRLSE). ii) Feature extraction done by Shape and Texture based features. iii) Brain Tumour detection performed by various tree classifiers. Based on investigation FCMLSM is well suited segmentation method and Random Forest is the most optimum classifier for this problem. This method gives accuracy of 97% and with minimum classification error. The time taken to detect Tumour is approximately 2 mins for an examination (30 slices).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2C
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• pp.100-109
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• 2003

A differential index assignment scheme is proposed for the image encoding system in which a variable-length tree-structured vector quantizer is adopted. Each source vector is quantized into a terminal node of VLTSVQ and each terminal node is represented as a unique binary vector. The proposed index assignment scheme utilizes the correlation between interblocks of the image to increase the compression ratio with the image quality maintained. Simulation results show that the proposed scheme achieves a much higher compression ratio than the conventional one does and that the amount of the bit rate reduction of the proposed scheme becomes large as the correlation of the image becomes large. The proposed encoding scheme can be effectively used to encode R images whose pixel values we, in general, highly correlated with those of the neighbor pixels.

• Journal of Plant Biology
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• v.8 no.1_2
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• pp.11-18
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• 1965

Since Taquet's first discovery of wild P. yedoensis at Mt. Halla, Korea, in 1908, its morphological chracteristics and question of origin of cultivated yedoensis have given controversies to the botanists. Takenaka, through his experiments on the hybridity of cultivated P. yedoensis, recently holds the opinion that P. yedoensis might have originated in Izu peninsula, Japan. The author presents the summarized report on the wild P. yedoensis and its putative parents based on his 2 years' investigated carried out at Mt. Halla during his breeding experiment of genus Prunus. The species of cherry tree used in the present investigation were identified by Prof. Mankyu Park and Mr. Jonghyu Pu, Korean taxonomists. 1) Wild cherry trees which grow wild in Mt. Halla and whose blooming season is April are mostly P. subhirtella var. pendula form. ascendens and P. donarium P. yedoensis is rare in number, around 10 individuals, having been found in a half century. 2) Individuals of wild yedoensis are variable in some of their morphological characteristics. This is, also, true in other species of Prunus. 3) Wild yedoensis whose vigorous growth, sterility, and rarity in number suggest hybrid origin, has intermediate characteristics between the P. subhirtella and P. donarium. 4) Due to the abnormal weather of the island and various environmental factors such as havbitats, some of the early-blooming subhirtella and late-blooming donarium would bloom at the same time, giving these two species the changes to cross. 5) Wild yedoensis is slightly different in some of its quantitative characters from cultivated species.

• Structural Engineering and Mechanics
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• v.23 no.5
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• pp.455-468
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• 2006

Smart structural systems are defined as ones that demonstrate the ability to modify their characteristics and/or properties in order to respond favorably to unexpected severe loading conditions. The performance of such a task requires a set of additional components to be integrated within such systems. These components belong to three major categories, sensors, processors and actuators. It is wellknown that all structural systems entail some level of uncertainty, because of their extremely complex nature, lack of complete information, simplifications and modeling. Similarly, sensors, processors and actuators are expected to reflect a similar uncertain behavior. As it is imperative to be able to evaluate the impact of such components on the behavior of the system, it is as important to ensure, or at least evaluate, the reliability of such components. In this paper, a system model for reliability assessment of smart structural systems is outlined. The presented model is considered a necessary first step in the development of a reliability assessment algorithm for smart structural systems. The system model outlines the basic components of the system, in addition to, performance functions and inter-relations among individual components. A fault tree model is developed in order to aggregate the individual underlying component reliabilities into an overall system reliability measure. Identification of appropriate limit states for all underlying components are beyond the scope of this paper. However, it is the objective of this paper to set up the necessary framework for identifying such limit states. A sample model for a three-story single bay smart rigid frame, is developed in order to demonstrate the proposed framework.