• Research in Mathematical Education
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• v.15 no.1
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• pp.81-91
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• 2011

The aim of this study was to explore the grade 1-3 students' geometrical thinking level descriptors based on van Hiele level descriptors. The data were collected through collection of geometric curriculum materials such as indicators and learning standards in Basic Education Core Curriculum and mathematics textbook for grades 1-3. The findings were found that 1) Inconsistency between descriptors appeared on mathematics curriculum and Thai mathematics textbooks. 2) Using topics on textbooks as criterion for exploring 5 of 7 descriptors appeared on Thai mathematics textbook indicated geometrical thinking levels based on van Hiele's model merely level 0 (Visualization) across textbooks for grades 1-3.

• Journal of Korean Elementary Science Education
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• v.29 no.4
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• pp.401-413
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• 2010

This study analyzed the kinds and frequencies of descriptors in 154 articles in ERIC data base on the 4th day of January in 2010. The titles of the articles includes the words, 'scientific literacy'. As each descriptor is constituted of two words and over, in this study the first word in the descriptor was defined as 'restrictive word' and the rest word(s) as 'target word(s)'. The results are as follows. First, the descriptors which show high frequencies of target words are the traditionally important themes of scientific literacy education. Target words which show relatively high frequency are 'education', 'literacy', 'instruction' and 'countries'. Low frequency word is 'curriculum', which has various restrictive words and represents wide differentiation. Second, among the descriptors which show low frequencies of target words, relatively high frequency descriptors are '(and)society', 'change', 'secondary education', 'concepts', and 'biology', which have been given more attention in scientific literacy research than the rest descriptors. Third, the number of the descriptors that shows largely distributed pattern A, which happens over 15 years continuously, is over the half of all analyzed descriptors, which shows that they have been the major objectives in researches about scientific literacy. Most descriptors of pattern A shows normal distribution of frequency or the trends of increasing frequency as the time is nearer. Fourth, The descriptors are divided into four groups according to the time span. Each research trends are as follows. In later 80s, the research which emphasizes the importance of the sociality and technology in all level school science curriculum. In later 90s the research for educational change of inquiry-centered science curriculum which considers technological literacy in social contexts. In earlier 2000s the research that scientists and science teachers develop science curricula mostly related to scientific principles and thinking in chemistry and biology especially. In later 2000s case studies which relates teaching methods and science process activities to students' attitudes, scientific concepts and curricula.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.468-488
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• 2016

The paper proposes a novel framework for 3D face verification using dimensionality reduction based on highly distinctive local features in the presence of illumination and expression variations. The histograms of efficient local descriptors are used to represent distinctively the facial images. For this purpose, different local descriptors are evaluated, Local Binary Patterns (LBP), Three-Patch Local Binary Patterns (TPLBP), Four-Patch Local Binary Patterns (FPLBP), Binarized Statistical Image Features (BSIF) and Local Phase Quantization (LPQ). Furthermore, experiments on the combinations of the four local descriptors at feature level using simply histograms concatenation are provided. The performance of the proposed approach is evaluated with different dimensionality reduction algorithms: Principal Component Analysis (PCA), Orthogonal Locality Preserving Projection (OLPP) and the combined PCA+EFM (Enhanced Fisher linear discriminate Model). Finally, multi-class Support Vector Machine (SVM) is used as a classifier to carry out the verification between imposters and customers. The proposed method has been tested on CASIA-3D face database and the experimental results show that our method achieves a high verification performance.

• Journal of Korea Game Society
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• v.11 no.3
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• pp.63-72
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• 2011

In this paper, we propose a novel database creation and retrieval method of feature descriptors to support real-time marker-less tracking in the augmented reality environments. Each feature descriptor is encoded by integer and multi-level database is created in order to retrieve a feature descriptor efficiently. The retrieval of a feature descriptor is performed as follows: Firstly, candidate feature descriptors are searched by traversing the multi-level database. Secondly, the euclidean distance between input feature descriptor and each candidate one is compared. The shortest one is retrieved. The proposed method is 16 ms faster than previous KD-Tree method for each feature descriptor.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.176-190
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• 2018

This paper presents a novel convolutional neural network based multi-feature fusion learning method for non-rigid 3D model retrieval, which can investigate the useful discriminative information of the heat kernel signature (HKS) descriptor and the wave kernel signature (WKS) descriptor. At first, we compute the 2D shape distributions of the two kinds of descriptors to represent the 3D model and use them as the input to the networks. Then we construct two convolutional neural networks for the HKS distribution and the WKS distribution separately, and use the multi-feature fusion layer to connect them. The fusion layer not only can exploit more discriminative characteristics of the two descriptors, but also can complement the correlated information between the two kinds of descriptors. Furthermore, to further improve the performance of the description ability, the cross-connected layer is built to combine the low-level features with high-level features. Extensive experiments have validated the effectiveness of the designed multi-feature fusion learning method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.208-214
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• 2021

Recently, much of the intelligent security scenario and criminal investigation demands for matching photo and non-photo. Existing face recognition system can not sufficiently guarantee these needs. In this paper, we propose an algorithm to improve the performance of heterogeneous face recognition systems by reducing the different modality between sketches and photos of the same person. The proposed algorithm extracts each image's texture features through texture descriptors (gray level co-occurrence matrix, multiscale local binary pattern), and based on this, generates a transformation matrix through eigenfeature regularization and extraction techniques. The score value calculated between the vectors generated in this way finally recognizes the identity of the sketch image through the score normalization methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1A
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• pp.142-155
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• 2000

In this paper, we propose an efficient policing mechanism for Markov model-based traffic descriptors of VBR MPEG video traffic. A VBR video sequence is described by a set of traffic descriptors using a scene-basedMarkov model to the network for the effective resource allocation and accurate QoS prediction. The networkmonitors the input traffic from the source using a proposed new policing method. for policing the steady statetransition probability of scene states, we define two representative monitoring parameters (mean holding andrecurrence time) for each state. For frame level cell rate policing of each scene state, accumulated average cellrates for the frame types are compared with the model parameters. We propose an exponential bounding functionto accommodate dynanic behaviors during the transient period. Our simulation results show that the proposedpolicing mechanism for Markovian traffic descriptors monitors the sophisticated traffic such as MPEG videoeffectively and well protects network resources from the nalicious or misbehaved traffic.

• Journal of Information Science Theory and Practice
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• v.7 no.1
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• pp.29-38
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• 2019

Information retrieval is the challenge of the Web 2.0 world. The experiment of knowledge organisation in the context of abundant information available from various sources proves a major hurdle in obtaining information retrieval with greater precision and recall. The fast-changing landscape of information organisation through social networking sites at a personal level creates a world of opportunities for data scientists and also library professionals to assimilate the social data with expert created data. Thus, folksonomies or social tags play a vital role in information organisation and retrieval. The comparison of these user-created tags with expert-created index terms, author keywords and title words, will throw light on the differentiation between these sets of data. Such comparative studies show revelation of a new set of terms to enhance subject access and reflect the extent of similarity between user-generated tags and other set of terms. The CiteULike tags extracted from 5,150 scholarly journal articles in marine science were compared with corresponding Aquatic Science and Fisheries Abstracts descriptors, author keywords, and title terms. The Jaccard similarity coefficient method was employed to compare the social tags with the above mentioned wordsets, and results proved the presence of user-generated keywords in Aquatic Science and Fisheries Abstracts descriptors, author keywords, and title words. While using information retrieval techniques like stemmer and lemmatization, the results were found to enhance keywords to subject access.

• The Journal of Korean Association of Computer Education
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• v.7 no.5
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• pp.111-120
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• 2004

The MPEG-7 standard defines a set of descriptors that extracts low-level features such as color, texture and object shape from an image and generates metadata in order to represent these extracted information. But the matching performance for image mining ma y not be satisfactory by u sing only on e of these features. Rather than by combining these features we can achieve a better query performance. In this paper we propose a new image retrieval technique for image mining that combines the features extracted from MPEG-7 visual color and texture descriptors. Specifically, we use only some specifications of Scalable Color Descriptor (SCD) and Non-Homogeneous Texture Descriptor also known as Edge Histogram Descriptor (EHD) for the implementation of the color and edge histograms respectively. MPEG-7 standard defines $l_{1}$-norm based matching in EHD and SCD. But in our approach, for distance measurement, we achieve a better result by using cosine similarity coefficient for color histograms and Euclidean distance for edge histograms. Our approach toward this system is more experimental based than hypothetical.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.1 s.307
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• pp.39-44
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• 2006

In this paper, search result list synthesis method is proposed using borda count method for still image retrieval based on MPEG-7 descriptors. MPEG-7 standardizes descriptors that extract feature information from media data. In many cases, using a single descriptor lacks of correctness, it is suggested to use multiple descriptors to enhance retrieval efficiency. In this paper, retrieval efficiency enhancement is achieved by combining multiple search results which are from each descriptor. In combining search result, newly calculated borda count method is proposed. Comparing current frequency compensated calculation, rank considered frequency compensation is used to score animage in database. This combining method is considered in Content based image retrieval system with relevance feedback algorithm which uses high level information from system user. In each relevance iteration step, adoptive borda count method is used to calculate score of images.