• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.223-230
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• 2003

Feature-based similarity retrieval has become an important research issue in multimedia database systems. The features of multimedia data are useful for discriminating between multimedia objects (e 'g', documents, images, video, music score, etc.). For example, images are represented by their color histograms, texture vectors, and shape descriptors, and are usually high-dimensional data. The performance of conventional multidimensional data structures(e'g', R- Tree family, K-D-B tree, grid file, TV-tree) tends to deteriorate as the number of dimensions of feature vectors increases. The R＊-tree is the most successful variant of the R-tree. In this paper, we propose a SOM-based R＊-tree as a new indexing method for high-dimensional feature vectors.The SOM-based R＊-tree combines SOM and R＊-tree to achieve search performance more scalable to high dimensionalities. Self-Organizing Maps (SOMs) provide mapping from high-dimensional feature vectors onto a two dimensional space. The mapping preserves the topology of the feature vectors. The map is called a topological of the feature map, and preserves the mutual relationship (similarity) in the feature spaces of input data, clustering mutually similar feature vectors in neighboring nodes. Each node of the topological feature map holds a codebook vector. A best-matching-image-list. (BMIL) holds similar images that are closest to each codebook vector. In a topological feature map, there are empty nodes in which no image is classified. When we build an R＊-tree, we use codebook vectors of topological feature map which eliminates the empty nodes that cause unnecessary disk access and degrade retrieval performance. We experimentally compare the retrieval time cost of a SOM-based R＊-tree with that of an SOM and an R＊-tree using color feature vectors extracted from 40, 000 images. The result show that the SOM-based R＊-tree outperforms both the SOM and R＊-tree due to the reduction of the number of nodes required to build R＊-tree and retrieval time cost.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2209-2211
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• 2004

Unlike the wavelet neural network, since a mother wavelet layer of the self-recurrent wavelet neural network (SRWNN) is composed of self-feedback neurons, it has the ability to store past information of the wavelet. Therefore we propose the prediction method for the nonlinear chaotic time series model using a SRWNN. The SRWNN model is learned for the modeling of a function such that the inputs arc known values of the time series and the output is the value in the future. The parameters of the network are tuned to minimize the difference between the nonlinear mapping of the chaotic time series and the output of SRWNN using the gradient-descent method for the adaptive backpropagation algorithm. Through the computer simulations, we demonstrate the feasibility and the effectiveness of our method for the prediction of the logistic map and the Mackey-Glass delay-differential equation as a nonlinear chaotic time series.

• Journal of Korean Elementary Science Education
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• v.35 no.1
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• pp.54-64
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• 2016

The purpose of this study is to develop instructional strategy which utilizes thinking maps focused on drawing as a measure to enhance science learning motivation, self-directed learning activity and science academic achievement of learners, and to examine the effects of its application. The target unit for this study is 'life cycle of plants' in the fourth grade of elementary school. Two classes of 4th grades of elementary school were selected and divided into two groups. The learners of experimental group have completed thinking map by drawing a picture to express the results to be observed and measured, and used it to arrange the learning contents. The result of this study is as follows. First, it is proven that using thinking maps focused on drawing actually helped improving the motivation of learners to study science. Second, it is proven that this strategy was effective to change their self-directed learning ability in positive ways. Third, it contributed to the improvement of learners' science academic achievement. We found out that the application of this strategy enabled them to enjoy the mapping using drawing, to be immersed in learning, to better recognize the scientific concepts and the structure of learning contents, and to have a positive awareness of the usefulness of thinking maps focused on drawing.

• The Journal of the Acoustical Society of Korea
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• v.14 no.2
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• pp.101-112
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• 1995

In order to construct a feature map-based phoneme classification system for speech recognition, two procedures are usually required. One is clustering and the other is labeling. In this paper, we present a phoneme classification system based on the Kohonen's Self-Organizing Feature Map (SOFM) for clusterer and labeler. It is known that the SOFM performs self-organizing process by which optimal local topographical mapping of the signal space and yields a reasonably high accuracy in recognition tasks. Consequently, SOFM can effectively be applied to the recognition of phonemes. Besides to improve the performance of the phoneme classification system, we propose the learning algorithm combined with the classical K-mans clustering algorithm in fine-tuning stage. In order to evaluate the performance of the proposed phoneme classification algorithm, we first use totaly 43 phonemes which construct six intra-class feature maps for six different phoneme classes. From the speaker-dependent phoneme classification tests using these six feature maps, we obtain recognition rate of $87.2\%$ and confirm that the proposed algorithm is an efficient method for improvement of recognition performance and convergence speed.

• 한국방재학회:학술대회논문집
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• 2009.02b
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• pp.36-42
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• 2009

A series of heavy rainfall, typhoon and earthquake disasters caused a proportionately large number of deaths among the elderly in the year 2004 in Japan. In response to these tragedies, the national government set up committees to reduce damage within the disaster vulnerable population for the next three years. The discussions in the committee led to a new conceptualization that disaster vulnerability was caused by a lack of interaction between a person's special needs and the environment's capacity and resources to meet them. This person-in-environment model of hazard vulnerability was applied to those who resided in the Nankai-Tonankai tsunami hazard-prone area. 123 home care service users were interviewed in terms of their self-evacuation ability, degree of social isolation, and building weakness as well as tsunami exposure risks. Results were quantified and scores of person-in-environmentmodel hazard vulnerability were obtained. These scores were then used to visualize socially created vulnerability by means of weighted kernel density mapping of both persons with special needs (PSN's) and persons with special needs at times of disaster (PSND's).

• Research in Community and Public Health Nursing
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• v.27 no.4
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• pp.410-422
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• 2016

Purpose: This study evaluated the effects of a cultural competence training program for public health nurses (PHNs) using intervention mapping. Methods: An embedded mixed method design was used. Forty-one PHNs (experimental: 21, control: 20) and forty marriage migrant women (MMW) (20, in each group) who were provided nursing care by PHN participated in the study. The experimental group was provided with a four-week cultural competence program consisting of an eight hour offline and online course, e-mail newsletters and social networking services (BAND). Transcultural Self-efficacy (TSE) of the PHNs, client-nurse trust, and satisfaction with nursing care of MMW were measured. Ten PHNs in the experimental group were interviewed after the experimental study. Results: The experimental group showed a significantly greater improvement in TSE, client-nurse trust, and satisfaction with nursing care than did the control group. Six themes emerged from qualitative data: (a) Recognizing cultural differences, (b) Being interested in the multicultural policy, (c) Trying to communicate in MMW's own language, (d) Providing medical information using internet and smart phone, (e) Embracing culturally diverse people into society, and (f) Requiring ongoing cultural competence training. Conclusion: Cultural competence training enabled PHNs to provide culturally competent care and contribute to MMW's health outcomes.

• The Korean Journal of Rehabilitation Nursing
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• v.18 no.2
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• pp.153-164
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• 2015

Purpose: This study was conducted to develop a community capacity builded exercise maintenance program for frail elderly women. Methods: As a guideline to develop the exercise maintenance program, the intervention mapping framework, including needs assessment, setting program goals, selecting theory-informed intervention methods, producing program components, planning program implementation and evaluation, was used. Focus group interviews with public health nurses and frail elderly women were conducted for needs assessment. Intervention strategies and components were formulated based on community capacity theory. Results: The developed exercise maintenance program consisted of strategies focusing on leadership development, partnership construction, organization development, community systematization of dimension of community capacity. A exercise maintenance program using health leader, health contract, exercise pocketbook, rhythmic activity suiting song and self-help group was included. Conclusion: The intervention mapping method was found to be useful to develop theory-based valid and community capacity builded exercise maintenance strategies for frail elderly women.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.43-49
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• 2016

This paper presents the design and implementation of virtual aquarium by generating 3D models of fishes that are colored by viewers in an aim to create interaction among viewers and aquarium. The virtual aquarium system is composed of multiple texture extraction modules, a single interface module and a single display module. The texture extraction module recognize the QR code on the canvas to get information of the predefined mapping table and then extract the texture data for the corresponding 3D model. The scanned image is segmented and warp transformed onto the texture image by using the mapping information. The extracted texture is transferred to the interface module to save on the server computer and the interface module sends the fish code and texture information to the display module. The display module generates a fish on the virtual aquarium by using predefined 3D model with the transmitted texture. The fishes on the virtual aquarium have three different swimming methods: self-swimming, autonomous swimming, and leader-following swimming. The three different swimming methods are discussed in this paper. The future study will be the implementation of virtual aquarium based on storytelling to further increase interactions with the viewer.

• The Plant Pathology Journal
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• v.17 no.2
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• pp.67-70
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• 2001

Medicago truncatula is a diploid legume plant related to the forage crop alfalfa. Recently, it has been chosen as a model species for genomic studies due to its small genome, self-fertility, short generation time, and high transformation efficiency. M. truncatula engages in symbiosis with nitrogen-fixing soil bacterium Rhizobium meliloti. M. truncatula mutants that are defective in nodulation and developmental processes have been generated. Some of these mutants exhibited altered phenotypes in symbiotic responses such as root hair deformation, expression of nodulin genes, and calcium spiking. Thus, the genes controlling these traits are likely to encode functions that are required for Nod-factor signal transduction pathways. To facilitate genome analysis and map-based cloning of symbiotic genes, a bacterial artificial chromosome library was constructed. An efficient polymerase chain reaction-based screening of the library was devised to fasten physical mapping of specific genomic regions. As a genomics approach, comparative mapping revealed high levels of macro- and microsynteny between M. truncatula and other legume genomes. Expressed sequence tags and microarray profiles reflecting the genetic and biochemical events associated with the development and environmental interactions of M. truncatula are assembled in the databases. Together, these genomics programs will help enrich our understanding of the legume biology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2042-2059
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• 2019

Digital shadow puppet has traditionally relied on expensive motion capture equipments and complex design. In this paper, a low-cost driven technique is presented, that captures human pose estimation data with simple camera from real scenarios, and use them to drive virtual Chinese shadow play in a 2.5D scene. We propose a special method for extracting human pose data for driving virtual Chinese shadow play, which is called 2.5D human pose estimation. Firstly, we use the 3D human pose estimation method to obtain the initial data. In the process of the following transformation, we treat the depth feature as an implicit feature, and map body joints to the range of constraints. We call the obtain pose data as 2.5D pose data. However, the 2.5D pose data can not better control the shadow puppet directly, due to the difference in motion pattern and composition structure between real pose and shadow puppet. To this end, the 2.5D pose data transformation is carried out in the implicit pose mapping space based on self-network and the final 2.5D pose expression data is produced for animating shadow puppets. Experimental results have demonstrated the effectiveness of our new method.