• 제목/요약/키워드: cluster mapping

검색결과 131건 처리시간 0.025초

예비유아교사의 유아환경교육에 대한 개념도 연구 (A Study on Pre-Service Early Childhood Teachers' Perception on Children's Environmental Education Using Concept Mapping)

  • 이효빈;권연희;안정은
    • 한국보육지원학회지
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    • 제16권5호
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    • pp.105-126
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    • 2020
  • Objective: This study aimed to reveal pre-service early childhood teachers' perception of children's environmental education using concept mapping and demonstrating its importance. Methods: Based on Kane and Trochim's(2007) procedure, 33 pre-service early childhood teachers conducted brainstorming and statement writing, and then the importance of selected statements were rated by 202 pre-service early childhood teachers. Selected statements were analyzed through multidimensional scaling and hierarchical cluster analysis. Results: Pre-service early childhood teachers perceived children's environmental education as concept mapping with 2-dimensions and eight clusters. The following eight clusters were established (1) daily practice through hands on experience, (2) nature environment, (3) recognizing and coping with environmental issues, (4) environmental preservation practices, (5) environmental sensitivity and consideration, (6) purpose of children's environmental education, (7) necessity for children's environmental education (8) Practice through connection with child's home and community. And then among the eight clusters, the most important was recognized as 'daily practice through hands on experience', and among the statements 'young children learn through the method of playing in nature and experience nature' was considered the most important. Conclusion/Implications: Based on these results, we discuss the importance of children's environmental education of pre-service early childhood teachers and how to support to develop teacher's training program.

면적과 지연 시간을 고려한 CLB 구조의 CPLD 저전력 기술 매핑 알고리즘 (A CLB based CPLD Low-power Technology Mapping Algorithm consider Area and Delay time)

  • 김재진;조남경;전종식;김희석
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 하계종합학술대회 논문집 II
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    • pp.1169-1172
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    • 2003
  • In this paper, a CLB-based CPLD low-power technology mapping algorithm consider area and delay time is proposed. To perform low power technology mapping for CPLD, a given Boolean network have to be represented to DAG. The proposed algorithm are consist of three step. In the first step, TD(Transition Density) calculation have to be performed. In the second step, the feasible clusters are generated by considering the following conditions: the number of output, the number of input and the number of OR-terms for CLB(Common Logic Block) within a CPLD. The common node cluster merging method, the node separation method, and the node duplication method are used to produce the feasible clusters. In the final step, low power technology mapping based on the CLBs is packing the feasible clusters into the several proper CLBs. The proposed algorithm is examined by using benchmarks in SIS. In the case of that the number of OR-terms is 5, the experiments results show that reduce the power consumption by 30.73% comparing with that of TEMPLA, and 17.11% comparing with that of PLAmap respectively.

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Salient Object Detection Based on Regional Contrast and Relative Spatial Compactness

  • Xu, Dan;Tang, Zhenmin;Xu, Wei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제7권11호
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    • pp.2737-2753
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    • 2013
  • In this study, we propose a novel salient object detection strategy based on regional contrast and relative spatial compactness. Our algorithm consists of four basic steps. First, we learn color names offline using the probabilistic latent semantic analysis (PLSA) model to find the mapping between basic color names and pixel values. The color names can be used for image segmentation and region description. Second, image pixels are assigned to special color names according to their values, forming different color clusters. The saliency measure for every cluster is evaluated by its spatial compactness relative to other clusters rather than by the intra variance of the cluster alone. Third, every cluster is divided into local regions that are described with color name descriptors. The regional contrast is evaluated by computing the color distance between different regions in the entire image. Last, the final saliency map is constructed by incorporating the color cluster's spatial compactness measure and the corresponding regional contrast. Experiments show that our algorithm outperforms several existing salient object detection methods with higher precision and better recall rates when evaluated using public datasets.

Analytic Study of Acquiring KANSEI Information Regarding the Recognition of Shape Models

  • Wang, Shao-Chi;Hiroshi Kubo;Hiromitsu Kikita;Takashi Uozumi;Tohru Ifukube
    • 한국감성과학회:학술대회논문집
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    • 한국감성과학회 2002년도 춘계학술대회 논문집
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    • pp.266-269
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    • 2002
  • This paper explores a fundamental study of acquiring the users' KANSEI information regarding the recognition of shape models. Since there are many differences such as background differences and knowledge differences among users, they will produce different evaluations based on their KANSEI even when an identical shape model is presented. Cluster analysis is proved to be available for catching a group tendency and for constructing a mapping relation between a description of the shape model and the HANSEl database. In order to investigate an analogical relation and a mutual influence in our consciousness, first, we made a questionnaire that asked subjects to represent images having different colors and shape cones by using 4 pairs of adjectives (KANSEI words). Next, based on the cluster analysis of the questionnaire using a fuzzy set theory, we proposed a hypothesis showing how the analogical relation and the mutual influence work in our mind while viewing the shape models. Furthermore, how the properties of KANSEI depend on their descriptions was also investigated by virtue of the cluster analysis. This work will be valuable to construct a personal KANSEI database regarding the Shape Model Processing System.

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모듈화한 신경 회로망을 이용한 광대역 음성 복원 (Wideband Speech Reconstruction Using Modular Neural Networks)

  • 우동헌;고참한;강현민;정진희;김유신;김형순
    • 대한음성학회지:말소리
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    • 제48호
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    • pp.93-105
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    • 2003
  • Since telephone channel has bandlimited frequency characteristics, speech signal over the telephone channel shows degraded speech quality. In this paper, we propose an algorithm using neural network to reconstruct wideband speech from its narrowband version. Although single neural network is a good tool for direct mapping, it has difficulty in training for vast and complicated data. To alleviate this problem, we modularize the neural networks based on appropriate clustering of the acoustic space. We also introduce fuzzy computing to compensate for probable misclassification at the cluster boundaries. According to our simulation, the proposed algorithm showed improved performance over the single neural network and conventional codebook mapping method in both objective and subjective evaluations.

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지적 구조 분석을 위한 MDS 지도 작성 방식의 비교 분석 (A Comparison Analysis of Various Approaches to Multidimensional Scaling in Mapping a Knowledge Domain's Intellectual Structure)

  • 이재윤
    • 한국문헌정보학회지
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    • 제41권2호
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    • pp.335-357
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    • 2007
  • 다차원척도법(MDS)은 지적 구조의 시각화를 위해서 오랫동안 사용되어 왔다. 그러나 MDS는 지적 구조를 시각적으로 표현하는데 있어서 세부 구조의 표현력이 취약하다는 약점을 가지고 있다. 이 연구에서는 상관계수 행렬의 가공 방식과 MDS 알고리즘을 조합한 여섯 가지 MDS 지도 작성 방식을 파악한 다음, 실제 지적 구조 데이터에 적용하여 비교해보았다. 실험 결과에서 가장 나쁜 방식으로 파악된 것은 가장 널리 사용되고 있는 방식으로서, 상관계수행렬로부터 유클리드 거리를 산출한 후 ALSCAL 알고리즘으로 MDS 지도를 작성하는 방식인 것으로 나타났다. 반면에 가장 좋은 방식은 상관계수를 z점수로 표준화하여 유클리드 거리를 산출한 후 PROXSCAL 알고리즘를 사용하는 방식이었다. 결론적으로 MDS 처리 과정을 주의깊게 구성한다면 더 구체적이고 명확한 지적 구조를 파악할 수 있음이 확인되었다.

글리치 전력소모 감소를 이용한 CPLD 저전력 알고리즘 연구 (A Study of CPLD Low Power Algorithm using Reduce Glitch Power Consumption)

  • 허화라
    • 디지털산업정보학회논문지
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    • 제5권3호
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    • pp.69-75
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    • 2009
  • In this paper, we proposed CPLD low power algorithm using reduce glitch power consumption. Proposed algorithm generated a feasible cluster by circuit partition considering the CLB condition within CPLD. Glitch removal process using delay buffer insertion method for feasible cluster. Also, glitch removal process using same method between feasible clusters. The proposed method is examined by using benchmarks in SIS, it compared power consumption to a CLB-based CPLD low power technology mapping algorithm for trade-off and a low power circuit design using selective glitch removal method. The experiments results show reduction in the power consumption by 15% comparing with that of and 6% comparing with that of.

Determining the Optimal Number of Signal Clusters Using Iterative HMM Classification

  • Ernest, Duker Junior;Kim, Yoon Joong
    • International journal of advanced smart convergence
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    • 제7권2호
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    • pp.33-37
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    • 2018
  • In this study, we propose an iterative clustering algorithm that automatically clusters a set of voice signal data without a label into an optimal number of clusters and generates hmm model for each cluster. In the clustering process, the likelihood calculations of the clusters are performed using iterative hmm learning and testing while varying the number of clusters for given data, and the maximum likelihood estimation method is used to determine the optimal number of clusters. We tested the effectiveness of this clustering algorithm on a small-vocabulary digit clustering task by mapping the unsupervised decoded output of the optimal cluster to the ground-truth transcription, we found out that they were highly correlated.

RGB 공간상의 국부 영역 블록의 왜곡척도를 고려한 칼라 영상 양자화 (Color image quantization considering distortion measure of local region block on RGB space)

  • 박양우;이응주;김경만;엄태억;하영호
    • 한국통신학회논문지
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    • 제21권4호
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    • pp.848-854
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    • 1996
  • Many image display devices allow only a limited number of colors to be simultaneously displayed. in disphaying of natural color image using color palette, it is necessary to construct an optimal color palette and the optimal mapping of each pixed of the original image to a color from the palette. In this paper, we proposed the clustering algorithm using local region block centered one color cluster in the prequantized 3-D histogram. Cluster pairs which have the least distortion error are merged by considering distortion measure. The clustering process is continued until to obtain the desired number of colors. The same as the clustering process, original color value. The proposed algorithm incroporated with a spatial activity weighting value which is reflected sensitivity of HVS quantization errors in smoothing region. This method produces high quality display images and considerably reduces computation time.

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Extra-tidal stars around globular clusters NGC 5024 and NGC 5053 and their chemical abundances

  • Chun, Sang-Hyun;Lee, Jae-Joon
    • 천문학회보
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    • 제43권2호
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    • pp.40.2-40.2
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    • 2018
  • NGC 5024 and NGC 5053 are among the most metal-poor globular clusters in the Milky Way. Both globular clusters are considered to be accreted from dwarf galaxies (like Sagittarius dwarf galaxy or Magellanic clouds), and common stellar envelope and tidal tails between globular clusters are also detected. We present a search for extra-tidal cluster member candidates around these globular clusters from APOGEE survey data. Using 20 chemical elements (e.g., Fe, C, Mg, Al) and radial velocities, t-distributed stochastic neighbour embedding (t-SNE), which identifies an optimal mapping of a high-dimensional space into fewer dimensions, was explored, and we find that globular cluster stars are well separated from the field stars in 2-dimensional map from t-SNE. We also find that some stars selected in t-SNE map are placed outside of the tidal radius of the clusters. The proper motion of stars outside tidal radius is also comparable to that of globular clusters, which suggest that these stars are tidally decoupled from the globular clusters. We manually measure chemical abundances for the clusters and extra-tidal stars, and discuss the association of extra-tidal stars with the clusters.

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