• Journal of Internet Computing and Services
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• v.14 no.2
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• pp.1-13
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• 2013

Recent advance and popularization of smart devices and web application services based on cloud computing have made end-users to directly produce and, at the same time, consume the image contents. This leads to demands of unified contents management services. Thus, this paper proposestag clustering method based on semantic similarity for effective image categorization. We calculate the cost of semantic similarity between tags and cluster tags that are closely related. If tags are in a cluster, we suppose that images with them are also in a same cluster. Furthermore, we could recommend tags for new images on the basis of initial clusters.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.24-27
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• 2008

As shown in Wikipedia, tagging or cross-linking through major key-words improves the readability of documents. Recently, the Semantic Web rises the importance of social tagging as a key feature of the Web 2.0 and Tag Cloud has emerged as its crucial phenotype. In this paper we provides an efficient method of automated keyword tagging based on controlled term collection, where the computational complexity of O(mN) - if pattern matching algorithm is used - can be reduced to O(mlogN) - if Information Retrieval is adopted - while m is the length of target document and N is the total number of candidate terms to be tagged. The result shows that IR-based tagging speeds up 5.6 times compared with fast pattern matching algorithm.

• Journal of the Korean Society of Food Culture
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• v.38 no.1
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• pp.26-37
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• 2023

This study applied the text frequency method to analyze the crops prevalent during the Chosunwangjoshilrok dynasty, and categorized the results by each king. Contemporary perception of grains was observed by examining the staple crop types. Staple species were examined using the word cloud and semantic network analysis. Totally, 101,842 types of crop consumption were recorded during the Chosunwangjoshilrok period. Of these, 51,337 (50.4%) were grains, 50,407 (49.5%) were beans, and 98 (0.1%) were seeds. Rice was the most frequently consumed grain (37.1%), followed by pii (11.9%), millet (11.3%), barley (4.5%), proso (0.8%), wheat (0.6%), buckwheat (0.1%), and adlay (0.05%). Grain chronological frequency in the Choseon dynasty was determined to be 15,520 cases in the 15^th century (30.2%), 11,201 cases in the 18^th century (21.8%), 9,421 cases in the 17^th century (18.4%), 9,113 cases in the 16^th century (17.8%), and 6,082 cases in the 19^th century (11.8%). Interest in grain amongst the 27 kings of Choseon was evaluated based on the frequency of records. The 15^th century King Sejong recorded the maximum interest with 13,363 cases (13.1%), followed by King Jungjo (8,501 cases in the 18^th century; 8.4%), King Sungjong (7,776 cases in the 15^th century; 7.6%).

• Journal of KIBIM
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• v.13 no.4
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• pp.96-105
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• 2023

This study focuses on developing a building object recognition technology for efficient use in the remodeling of buildings constructed without drawings. In the era of the 4th industrial revolution, smart technologies are being developed. This research contributes to the architectural field by introducing a deep learning-based method for automatic object classification and recognition, utilizing point cloud data. We use a TD3D network with voxels, optimizing its performance through adjustments in voxel size and number of blocks. This technology enables the classification of building objects such as walls, floors, and roofs from 3D scanning data, labeling them in polygonal forms to minimize boundary ambiguities. However, challenges in object boundary classifications were observed. The model facilitates the automatic classification of non-building objects, thereby reducing manual effort in data matching processes. It also distinguishes between elements to be demolished or retained during remodeling. The study minimized data set loss space by labeling using the extremities of the x, y, and z coordinates. The research aims to enhance the efficiency of building object classification and improve the quality of architectural plans by reducing manpower and time during remodeling. The study aligns with its goal of developing an efficient classification technology. Future work can extend to creating classified objects using parametric tools with polygon-labeled datasets, offering meaningful numerical analysis for remodeling processes. Continued research in this direction is anticipated to significantly advance the efficiency of building remodeling techniques.

• Journal of Internet Computing and Services
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• v.19 no.3
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• pp.67-77
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• 2018

This paper suggests that LOD establishes its own link policy and publishes it to LOD cloud to provide identity among entities in different LODs. For specifying the link policy, we proposed vocabulary set founded on RDF model as well. We implemented Policy based In-depth Searching and Cleansing(PISC for short) system that proceeds in-depth searching across LODs by referencing the link policies. PISC has been published on Github. LODs have participated voluntarily to LOD cloud so that degree of the entity identity needs to be evaluated. PISC, therefore, evaluates the identities and cleanses the searched entities to confine them to that exceed user's criterion of entity identity level. As for searching results, PISC provides entity's detailed contents which have been collected from diverse LODs and ontology customized to the content. Simulation of PISC has been performed on DBpedia's 5 LODs. We found that similarity of 0.9 of source and target RDF triples' objects provided appropriate expansion ratio and inclusion ratio of searching result. For sufficient identity of searched entities, 3 or more target LODs are required to be specified in link policy.

• ETRI Journal
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• v.36 no.5
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• pp.741-751
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• 2014

Smart TV is expected to bring cloud services based on virtualization technologies to the home environment with hardware and software support. Although most physical resources can be shared among virtual machines (VMs) using a time sharing approach, allocating the proper amount of memory to VMs is still challenging. In this paper, we propose a novel mechanism to dynamically balance the memory allocation among VMs in virtualized Smart TV systems. In contrast to previous studies, where a virtual machine monitor (VMM) is solely responsible for estimating the working set size, our mechanism is symbiotic. Each VM periodically reports its memory usage pattern to the VMM. The VMM then predicts the future memory demand of each VM and rebalances the memory allocation among the VMs when necessary. Experimental results show that our mechanism improves performance by up to 18.28 times and reduces expensive memory swapping by up to 99.73% with negligible overheads (0.05% on average).

• Journal of the Korea Society of Computer and Information
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• v.22 no.9
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• pp.91-97
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• 2017

IoT (Internet of Things) systems are based on heterogeneous hardware systems of different types of devices interconnected each other, ranging from miniaturized and low-power wireless sensor node to cloud servers. These IoT systems composed of heterogeneous hardware utilize data sets collected from a particular set of sensors or control designated actuators when needed using open APIs created through abstraction of devices' resources associated to service applications. However, previously existing IoT services have been usually developed based on vertical platforms, whose sharing and exchange of data is limited within each industry domain, for example, healthcare. Such problem is called 'data silo', and considered one of crucial issues to be solved for the success of establishing IoT ecosystems. Also, IoT services may need to dynamically organize their services according to the change of status of connected devices due to their mobility and dynamic network connectivity. We propose a way of dynamically composing IoT services under the concept of WoT (Web of Things) where heterogeneous devices across different industries are fully integrated into the Web. Our approach allows developers to create IoT services or mash them up in an efficient way using Web objects registered into multiple standardized horizontal IoT platforms where their resources are discoverable and accessible. A Web-based service composition tool is developed to evaluate the practical feasibility of our approach under real-world service development.

• The Research Journal of the Costume Culture
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• v.12 no.3
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• pp.369-378
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• 2004

The objectives of this study were to measure the preference and purchase intention on Korean traditional motifs and to investigate the relationship among preference, purchase intention, and sensibility. The subjects consisted of 217 male and 351 female US undergraduate students. The experimental materials used in this study were 48 stimuli and a questionnaire, composed of 7-point semantic differential scales of 17 bi-polar adjectives. The data were analyzed by ANOVA, Duncan's multiple range test, Regression, and t-test. The major findings were as follows; First, interpretation type and application object had significant effects on the preference, while category and interpretation type had significant effects on the purchase intension. The application of Korean traditional motifs for pattern design was preferred to their application for clothing design. Decorative type was found to be more related to the preference and purchase intention than the other interpretation types of realistic, stylized and abstract types. The purchase intention on crain motif was lower than the other categories of lotus and cloud motifs. Second, in overall, the preference on Korean traditional motifs was higher than purchase intention. Third, the preference and purchase intention were affected mainly by 'Quality' image, a component of sensibility, followed by 'Cheerfulness' image, but not affected by 'Simplicity' and 'Modernity' image.

• Journal of Information Processing Systems
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• v.5 no.3
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• pp.159-166
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• 2009

As shown in Wikipedia, tagging or cross-linking through major keywords in a document collection improves not only the readability of documents but also responsive and adaptive navigation among related documents. In recent years, the Semantic Web has increased the importance of social tagging as a key feature of the Web 2.0 and, as its crucial phenotype, Tag Cloud has emerged to the public. In this paper we provide an efficient method of automated in-text keyword tagging based on large-scale controlled term collection or keyword dictionary, where the computational complexity of O(mN) - if a pattern matching algorithm is used - can be reduced to O(mlogN) - if an Information Retrieval technique is adopted - while m is the length of target document and N is the total number of candidate terms to be tagged. The result shows that automatic in-text tagging with keywords filtered by Information Retrieval speeds up to about 6 $\sim$ 40 times compared with the fastest pattern matching algorithm.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.4
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• pp.727-739
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• 2021

The purpose of this study is to present the objective evaluation semantic scale of avant-garde design. Apparel majors were asked to express associative vocabulary, design development, and final design intentions for the avant-garde, and the final 70 copies were used for analysis. The results found the item style was shown often in the order of dress, coat, and combination of shirt and pants. In order, the silhouettes appeared as atypical, complex, square, and triangular; the decorations appeared as feathers, frills, and round sculptures; and the idea method appeared as extreme, association, and removal method. In examining the relations of associative words and idea designs, the dress had relations with associative words such as 'peculiar,' 'futuristic,' 'fancy,' 'Comme des Garcons,' and 'deconstruction.' As for the relationship between the idea design and the expression image vocabulary, it was found that 'one piece' recalled 'huge,' 'volume,' 'abundant,' 'peculiar,' and 'unknown,' while 'coat' recalled 'huge,' 'big silhouette,' and 'padding.' In conducting the word cloud technique, the overall design showed the central keywords were 'huge,' 'big silhouette,' 'unbalance,' 'feather,' 'structural,' 'unknown,' and 'frill,' in order.