• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3272-3285
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• 2016

Recently, Vector of Locally Aggregated Descriptors (VLAD) has been proposed to index image by compact representations, which encodes powerful local descriptors and makes significant improvement on search performance with less memory compared against the state of art. However, its performance relies heavily on the size of the codebook which is used to generate VLAD representation. It indicates better accuracy needs higher dimensional representation. Thus, more memory overhead is needed. In this paper, we enhance VLAD image representation by using two level hierarchical-codebooks. It can provide more accurate search performance while keeping the VLAD size unchanged. In addition, hierarchical-codebooks are used to construct multiple inverted files for more accurate non-exhaustive search. Experimental results show that our method can make significant improvement on both VLAD image representation and non-exhaustive search.

• Journal of the Korean Society of Earth Science Education
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• v.5 no.1
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• pp.8-19
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• 2012

The purpose of this study is to: analyze the characteristics on ill-structured problem-solving process; examine the type of memories used in their monitoring. The data were primary collected from observation and secondary the semi-structured in-depth interviews based on analysis of observation results with two students who belong to science school and a guidance. The findings of this study revealed that the ill-structured problems possess multiple representations and the upper level's problem have several sub-problems. And multiple steps simultaneously exist in particular stage of problem-solving process that is not single sequential but complex flow and have high frequency of discussion step. Type of memories used in ill-structured problems include idiosyncratic memories which is related in personal histories such as school performance, problem-related memories, abstract rules and intuition.

• The Journal of Korea Robotics Society
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• v.9 no.1
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• pp.1-10
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• 2014

In recent years, the research of 3D mapping technique in urban environments obtained by mobile robots equipped with multiple sensors for recognizing the robot's surroundings is being studied actively. However, the map generated by simple integration of multiple sensors data only gives spatial information to robots. To get a semantic knowledge to help an autonomous mobile robot from the map, the robot has to convert low-level map representations to higher-level ones containing semantic knowledge of a scene. Given a 3D point cloud of an urban scene, this research proposes a method to recognize the objects effectively using 3D graph model for autonomous mobile robots. The proposed method is decomposed into three steps: sequential range data acquisition, normal vector estimation and incremental graph-based segmentation. This method guarantees the both real-time performance and accuracy of recognizing the objects in real urban environments. Also, it can provide plentiful data for classifying the objects. To evaluate a performance of proposed method, computation time and recognition rate of objects are analyzed. Experimental results show that the proposed method has efficiently in understanding the semantic knowledge of an urban environment.

• Journal of English Language & Literature
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• v.56 no.4
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• pp.597-618
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• 2010

This paper discusses American disability theater's representations of disability identity and disability identity politics. Dramatists John Belluso and Lynn Manning, among others, present characters with disabilities who experience oppressions at multiple, interlocking levels of domination on the basis of disability, race, and ethnicity. In Manning's Shoot, the black, blind hero iterates episodes in which he experienced discrimination and insults in encounters with whites who used derogatory racist words or belittled him and with some school children who taunted him for just being blind. This play, as in Manning's solo performance, Weights, presents narratives of a blind person traversing multiple locations of oppression in "a long litany of losses" in a white-dominated and ableist society. Belluso's Gretty Good Time similarly weaves together stories of disabled women, Gretty and Hideko, who bond together to resist the dominant ideology that reduces them into titillating commodities of mass consumption. Hideko's story serves the two-fold function of both affirming the specificity of her individual experience as an ethnic other and espousing the communal experience of stigmatization she shares with other disabled women like Gretty. In these plays, the intersection of the identity categories of disability, race, and ethnicity highlights the diversity of the body and the fluidity of boundaries, foregounding the specificity of disabled bodies, while at the same time overthrowing the hierarchical binarism between disabled and "normal" bodies.

• Asia Pacific Journal of Corpus Research
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• v.4 no.2
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• pp.75-87
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• 2023

This paper presents a revised version of the vocabulary analyzer for self-reflection (VACSR), called VACSR v.2.0. The initial version of the VACSR automatically analyzes the occurrences and the level of vocabulary items in the transcribed texts, indicating the frequency, the unused vocabulary items, and those not belonging to either scale. However, it overlooked words with multiple parts of speech due to their identical headword representations. It also needed to provide more explanatory result tables from different corpora. VACSR v.2.0 overcomes the limitations of its predecessor. First, unlike VACSR v.1, VACSR v.2.0 distinguishes words that are different parts of speech by syntactic parsing using Stanza, an open-source Python library. It enables the categorization of the same lexical items with multiple parts of speech. Second, VACSR v.2.0 overcomes the limited clarity of VACSR v.1 by providing precise result output tables. The updated software compares the occurrence of vocabulary items included in classroom corpora for each level of the Common European Framework of Reference-Japan (CEFR-J) wordlist. A pilot study utilizing VACSR v.2.0 showed that, after converting two English classes taught by a preservice English teacher into corpora, the headwords used mostly corresponded to CEFR-J level A1. In practice, VACSR v.2.0 will promote users' reflection on their vocabulary usage and can be applied to teacher training.

• Journal of Educational Research in Mathematics
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• v.20 no.3
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• pp.203-219
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• 2010

Several studies have reported on how and what mathematically gifted students develop superior ability or creativity in geometry and algebra. However, there are lack of studies in probability area, though there are a few trials of probability education for mathematically gifted students. Moreover, less attention has paid to the strategies to develop gifted students' creativity. This study has drawn three teaching strategies for creativity development based on literature review embedding: cognitive conflict, multiple representations, and social interaction. We designed a series of tasks via reconstructing, so called Simpson's paradox to meet these strategies. The findings showed that the gifted students made Quite a bit of improvement in creativity while participating in reflective thinking and active discussion, doing internal and external connection, translating representations, and investigating basic assumption.

• Korean Journal of Cognitive Science
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• v.21 no.4
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• pp.603-625
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• 2010

Neural representation of a visual object is distributed across visual cortex and overlapped with those of many other objects. Thus repeating an object facilitates the recognition of the object while it impairs the recognition of other objects. These effects are called repetition priming and antipriming, respectively. Two experiments investigated a new phenomenon of repetition antipriming, in which a repeated object itself is antiprimed. The learning stage presented object pictures which were degraded at various levels. Participants determined how recognizable each object was. Then, the test stage presented the intact version of the object pictures and made participants to perform a categorization task. Both Experiment 1 and 2 found that the processing of the objects that had been recognized were facilitated (repetition priming) while the processing of the objects that had been perceptually ambiguous were impaired (repetition antipriming). These findings suggest that experiencing a perceptually ambiguous object might enhance the connection between feature-level representations and multiple object-level representations, which impairs the subsequent recognition of the repeated object.

• Journal of Internet Computing and Services
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• v.1 no.1
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• pp.47-62
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• 2000

Geographic Information System(GIS) deal with data which can potentially be useful for a wida range of applications. However, the information needs of each application usually vary, specially in resolution, detail level, and representation style, as defined in the modeling phase of the geographic database design. To be able to deal with such diverse needs, the GIS must after features that allow multiple representations for each geographic entity of phenomenon. This paper addresses the problem of formal definition of the objects and their relationships on geographical information systems. The geographical data is divided in two main classes: geo-objects and geo-fields, which describe discrete and continuous representations of spatial reality. I will study the classes and the roles of relationships over geo-fields, geo-objects and nongeo-objects. Therefore, this paper will contribute the efficient design of geographical class hierarchy schema by means of formalizing attribute-domains of classes.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.301-307
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• 2024

This study introduces a novel cascade fusion architecture aimed at enhancing thermal images across various scale conditions. The processing of thermal images at multiple scales has been challenging due to the limitations of existing methods that are designed for specific scales. To overcome these limitations, this paper proposes a unified framework that utilizes cascade feature fusion to effectively learn multi-scale representations. Confidence maps from different image scales are fused in a cascaded manner, enabling scale-invariant learning. The architecture comprises end-to-end trained convolutional neural networks to enhance image quality by reinforcing mutual scale dependencies. Experimental results indicate that the proposed technique outperforms existing methods in multi-scale thermal image enhancement. Performance evaluation results are provided, demonstrating consistent improvements in image quality metrics. The cascade fusion design facilitates robust generalization across scales and efficient learning of cross-scale representations.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.571-576
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• 2024

Ontologies are created by domain experts, but the same content may be expressed differently by each expert due to different understandings of domain knowledge. Since the ontology standardization is still lacking, multiple ontologies can be exist within the same domain, resulting in a phenomenon called the ontology heterogeneity. Therefore, we propose a novel ontology matching method that combines SCBOW(: Siames Continuois Bag Of Words) and BERT(: Bidirectional Encoder Representations from Transformers) models to solve the ontology heterogeneity issue. Ontologies are expressed as a graph and the SimRank algorithm is used to solve the one-to-many problem that can occur in ontology matching problems. Experimental results showed that our approach improves performance by about 8% over traditional matching algorithm. Proposed method can enhance and refine the alignment technology used in ontology matching.