• The Journal of Korean Academic Society of Nursing Education
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• v.19 no.4
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• pp.558-570
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• 2013

Purpose: In these days, the concept of health literacy becomes important because it is essential to have a clear grasp of patients' basic ability to understand health-care information. Therefore, we intended to discover attributes, antecedents and consequences of health literacy through contextual analysis. Method: Following Rodgers' evolutionary concept analysis, we did a literary review. The databases KMBase, KoreaMed, Kstudy, NDSL, and RISS were searched for articles. Among published literature about health literacy, twenty articles which satisfied the inclusion criteria were chosen. Results: Health literacy consists of three attributes: information seeking, information understanding, and information utilizing. Furthermore antecedents are as follows: health status, health belief, socioeconomic status, and information quality. Finally, we were able to explain the consequences of health literacy by showing improvement of self-care and interaction, and a decrease of social costs. Conclusion: We expect this study to guide the direction of future studies, and as a concept analysis that examines the conceptual attributes in the context of health literacy. Based on the result of this study, the design of a standardized tool and the program of health literacy promotion education need to be developed.

• Korean Institute of Interior Design Journal
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• v.22 no.1
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• pp.75-84
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• 2013

This study focuses on Gilbert Simondon's individuation theory, a core concept of his technological philosophy, and spatial modality in interactive space as the schema of interactive operation. The study examines spatial modality as the technology of an interaction-enabler that has archi-semiotic characteristics in the designed space by aspects of examples. They are based on ideas and properties of a combined environment and the concept of information, which form Simondon's individuation theory. In the process of technological individuation, spatial modality has the characteristics of archi-semiotics from a combined environment and information. The first of the three properties is representation through semiosis and the information surface. Second is the context by relation works and perception, and third are the symbolic aspects, which could create Placeness by meaning. Combining meaningful constructive and deconstructive spaces could result in space for interactive communication. Spatial modality makes it possible to interact with users and spaces. In fact, it could have a particular semiotic mode of address and become a semiotic and contextual base. As a basic investigation of spatial modality, this study will contribute to interactive space design research.

• Speech Sciences
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• v.10 no.4
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• pp.41-55
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• 2003

This paper investigates the tonal patterns of English information structure composed of topic and focus. It has been argued in previous theories that there is a significant relationship between English topic-focus structure and intonation. The English topic is marked with L+H* pitch accent and focus is marked with H* pitch accent. These theories, however, are oversimplified ones since they do not consider the contextual differences of topic and focus. To examine more concrete tonal patterns of English topic and focus, we classified topic into two subcategories of reminding topic and old-information topic. Focus was categorized into three: information focus, contrastive focus, and reference focus. The overall results show that native English speakers are inclined to use both the L+H* and H* pitch accent for the topic and focus of an utterance. We also observe a tendency to deaccentuate the topics given as old information and to mark the topics given as noun phrase with H* pitch accent. As for the intonation of focus, H* pitch accent is the most frequent type of accent, but L+H* also shows a high percentage of implementation especially in the context of correction or contrast.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3182-3198
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• 2019

Vision-based Human Pose Estimation has been considered as one of challenging research subjects due to problems including confounding background clutter, diversity of human appearances and illumination changes in scenes. To tackle these problems, we propose to use a new multi-stage convolution machine for estimating human pose. To provide better heatmap prediction of body joints, the proposed machine repeatedly produces multiple predictions according to stages with receptive field large enough for learning the long-range spatial relationship. And stages are composed of various modules according to their strategic purposes. Pyramid stacking module and dilation module are used to handle problem of human pose at multiple scales. Their multi-scale information from different receptive fields are fused with concatenation, which can catch more contextual information from different features. And spatial and channel information of a given input are converted to gating factors by squeezing the feature maps to a single numeric value based on its importance in order to give each of the network channels different weights. Compared with other ConvNet-based architectures, we demonstrated that our proposed architecture achieved higher accuracy on experiments using standard benchmarks of LSP and MPII pose datasets.

• Journal of English Language & Literature
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• v.57 no.6
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• pp.1017-1041
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• 2011

This study investigates Korean EFL learners' awareness and use of the English existential there-construction by examining data collected from 54 Korean EFL learners of English by means of a pragmalinguistic judgment task and a controlled discourse completion task. The results of the judgment task reveal that lower proficiency learners rated canonical sentences and existentials with a preposed locative best in the communicative situations where the use of existentials would have been most appropriate. A comparison of the ratings by more proficient learners and native speakers shows that existentials received highest ratings by both groups where they are the most natural option, while canonical sentences received significantly higher ratings by the learners. With regard to the production data, learners tended to avoid existentials, but rather relied on canonical sentences. Existentials were rarely used by lower proficiency learners and not used productively even by more proficient learners in the situations where existentials would have been the most natural option. These results suggest that Korean learners' difficulty with the use of existentials is not merely a product of performance limitations, but attributable to limited knowledge about existentials and their syntactic alternatives in terms of contextual appropriateness. Lower proficiency learners lack such knowledge, and more proficient learners, while showing better awareness of the use of existentials, have problems as to the placement of new information when engaging in writing tasks that place lower level of demands on attention to the information status of noun phrases compared to communicative, oral tasks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1868-1887
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• 2024

Recommendation systems research is a subfield of information retrieval, as these systems recommend appropriate items to users during their visits. Appropriate recommendation results will help users save time searching while increasing productivity at work, travel, or shopping. The problem becomes more difficult when the items are geographical locations on the ground, as they are associated with a wealth of contextual information, such as geographical location, opening time, and sequence of related locations. Furthermore, on social networking platforms that allow users to check in or express interest when visiting a specific location, their friends receive this signal by spreading the word on that online social network. Consideration should be given to relationship data extracted from online social networking platforms, as well as their impact on the geolocation recommendation process. In this study, we compare the similarity of geographic locations based on their distance on the ground and their correlation with users who have checked in at those locations. When calculating feature embeddings for users and locations, social relationships are also considered as attention signals. The similarity value between location and correlation between users will be exploited in the overall architecture of the recommendation model, which will employ graph convolution networks to generate recommendations with high precision and recall. The proposed model is implemented and executed on popular datasets, then compared to baseline models to assess its overall effectiveness.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.526-530
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• 2009

In this paper, we propose a contextual information and physics-based contents manipulation method for a mobile augmented reality authoring system. Due to proliferation of ubiquitous computing in information technology(IT) and advances in sensor technology and mobile devices, AR systems that were only possible in PC can be now feasible on mobile devices. In addition, many AR systems have been proposed that utilize sensory data and reflect them into. Thus, the proposed method provides appropriate visual cues for 3D manipulations of the augmented contents. In addition, uses can manipulate the augmented contents with sensory information through the assignment of sensors to the contents. Moreover, it supports not only a physics-based contents loader that enables users to specify physics properties into the contents, but also the transform matrix between AR and physics engine coordinates. To show the feasibility of the proposed method, we implemented a mobile augmented reality authoring system. We believe that the proposed method can be a key factor for context-aware mobile AR authoring system.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.493-503
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• 2014

A hierarchical classification scheme, which can reduce the spectral ambiguity and also reflect crop cultivation patterns from past land-cover maps, is presented for the purpose of the early production of crop classification maps in large-scale crop areas. Specifically, the effects of mixed pixels are minimized not only by applying a hierarchical classification approach based on different spectral characteristics from crop growth cycles, but also by considering temporal contextual information derived from past crop cultivation patterns. The applicability of the presented classification scheme was evaluated by a case study of Iowa State in USA with time-series MODIS 250 m Normalized Difference Vegetation Index(NDVI) data sets and past Cropland Data Layers(CDLs). Corn and soybean, which are major crop types in the study area and also display spectral similarity, could be properly classified by applying different classification stages and accounting for past crop cultivation patterns. The classification result by the presented scheme showed increases of minimum 7.68%p and maximum 20.96%p in overall accuracy, compared with one based on purely spectral information. In addition, the combination of temporal contextual information during classification was less affected by the number of NDVI data sets and the best overall accuracy of 86.63% was achieved. Thus, it is expected that this classification scheme can be effectively used for the early production of large-area crop classification maps in major feed-grain importing countries.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.11-17
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• 2013

With high social demands for the diverse utilizations of forest lands, the illegal forest land use changes have increased. We studied change detection technique to detect changes in forest land use using an object-oriented segmentation of RED bands differencing in multi-temporal aerial photographs. The new object-oriented segmentation method consists of the 5 steps, "Image Composite - Segmentation - Reshaping - Noise Remover - Change Detection". The method enabled extraction of deforested objects by selecting a suitable threshold to determine whether the objects was divided or merged, based on the relations between the objects, spectral characteristics and contextual information from multi-temporal aerial photographs. The results found that the object-oriented segmentation method detected 12% of changes in forest land use, with 96% of the average detection accuracy compared by visual interpretation. Therefore this research showed that the spatial data by the object-oriented segmentation method can be complementary to the one by a visual interpretation method, and proved the possibility of automatically detecting and extracting changes in forest land use from multi-temporal aerial photographs.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.913-924
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• 2022

In this paper, we presented a database construction of undersea images for the Habitats of Ecklonia cava and Sargassum and conducted an experiment for semantic segmentation using state-of-the-art (SOTA) models such as High Resolution Network-Object Contextual Representation (HRNet-OCR) and Shifted Windows-L (Swin-L). The result showed that our segmentation models were superior to the existing experiments in terms of the 29% increased mean intersection over union (mIOU). Swin-L model produced better performance for every class. In particular, the information of the Ecklonia cava class that had small data were also appropriately extracted by Swin-L model. Target objects and the backgrounds were well distinguished owing to the Transformer backbone better than the legacy models. A bigger database under construction will ensure more accuracy improvement and can be utilized as deep learning database for undersea images.