• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2004.08a
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• pp.55-62
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• 2004

In this study, the effects of Ca content and processing variables on hot rolling properties of gravity cast AZ31-xCa alloys were evaluated systematically. The number and length of side crack were decreased with increasing preheating temperature and decreasing reduction ratio per pass and Ca content. The UTS and YS were not strongly dependent on the Ca content but the elongation decreased with increasing Ca content. The decrease of elongation in Ca containing alloys was least when the sheets were fabricated under preheating temperature of $400^{\circ}C$ and reduction ratio per pass of $15\%$. The sheets had the sound external features with little side cracks by homogenization of gravity cast AZ31-xCa alloys before hot rolling. In the cases of AZ31-xCa alloys containing under $1wt.\%$ Ca, the annealed sheets after homogenization and hot rolling had the similar tensile properties to those of AZ31 sheet.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_2
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• pp.665-672
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• 2012

Amid rapidly increasing imagery inputs and their volume in a remote sensing imagery database, Content-Based Image Retrieval (CBIR) is an effective tool to search for an image feature or image content of interest a user wants to retrieve. It seeks to capture salient features from a 'query' image, and then to locate other instances of image region having similar features elsewhere in the image database. For a CBIR approach that uses texture as a primary feature primitive, designing a texture descriptor to better represent image contents is a key to improve CBIR results. For this purpose, an extended feature vector combining the Gabor filter and co-occurrence histogram method is suggested and evaluated for quantitywise and qualitywise retrieval performance criterion. For the better CBIR performance, assessing similarity between high dimensional feature vectors is also a challenging issue. Therefore a number of distance metrics (i.e. L1 and L2 norm) is tried to measure closeness between two feature vectors, and its impact on retrieval result is analyzed. In this paper, experimental results are presented with several CBIR samples. The current results show that 1) the overall retrieval quantity and quality is improved by combining two types of feature vectors, 2) some feature is better retrieved by a specific feature vector, and 3) retrieval result quality (i.e. ranking of retrieved image tiles) is sensitive to an adopted similarity metric when the extended feature vector is employed.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.2
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• pp.152-157
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• 2010

The development of computer and internet has introduced various types of media - such as, image, audio, video, and voice - to the traditional text-based information. However, most of the information retrieval systems are based only on text, which results in the absence of ability to use available information. By utilizing the available media, one can improve the performance of search system, which is commonly called content-based retrieval and content-based image retrieval system specifically tries to incorporate the analysis of images into search systems. In this paper, a content-based image retrieval system using HSI color space, ART2 algorithm, and SOM algorithm is introduced. First, images are analyzed in the HSI color space to generate several sets of features describing the images and an SOM algorithm is used to provide candidates of training features to a user. The features that are selected by a user are fed to the training part of a search system, which uses an ART2 algorithm. The proposed system can handle the case in which an image belongs to several groups and showed better performance than other systems.

• Korean Journal of Agricultural Science
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• v.45 no.4
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• pp.749-760
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• 2018

In Korea, the largest agricultural lands are paddy fields which have poor infiltration and drainage properties. Recently, the Korean government has pursued cultivating upland crops in paddy fields to reduce overproduced rice in Korea. For this policy to succeed, it is critical to understand the topographic information of paddy fields and its effects on upland crops cultivated in the soils of paddy fields. The objective of this study was to characterize the growth properties of sesame and perilla from paddy fields with three soil topographic features and soil water effects which were induced by the topographic features of the sesame and perilla. The crops were planted in paddy fields located in Miryang, Gyeongnam with different topographies: mountain foot slope, local valley and alluvial plain. Soil water contents and groundwater levels were measured every hour during the growing season. The paddy field of the mountain foot slope was significantly effective in alleviating wet injury for the sesame and perilla in the paddy fields. The paddy field of the mountain foot slope had a decreased average soil water content and groundwater level during cultivation. Stress day index (SDI) from the alluvial plain paddy field had the greatest values from both crops and the smallest from the ones from the paddy field of the mountain foot slope. This result means that sesame and perilla had the smallest stress from the soil water content of the paddy field on the mountain foot slope and the greatest stress from the soil water content of the alluvial plain. It is important to consider the topography of paddy fields to reduce wet injury and to increase crop yields.

• ETRI Journal
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• v.20 no.3
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• pp.272-283
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• 1998

In this paper, we propose efficient content-based image retrieval methods using the automatic extraction of the low-level visual features as image content. Two new feature extraction methods are presented. The first one os an advanced color feature extraction derived from the modification of Stricker's method. The second one is a texture feature extraction using some DCT coefficients which represent some dominant directions and gray level variations of the image. In the experiment with an image database of 200 natural images, the proposed methods show higher performance than other methods. They can be combined into an efficient hierarchical retrieval method.

• Journal of KIISE:Software and Applications
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• v.35 no.10
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• pp.608-615
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• 2008

In Knowledge Q&A services where information is created by unspecified users, document quality is an important factor of user satisfaction with search results. Previous work on quality prediction of Knowledge Q&A documents evaluate the quality of documents by using non-textual information, such as click counts and recommendation counts, and focus on enhancing retrieval performance by incorporating the quality measure into retrieval model. Although the non-textual information used in previous work was proven to be useful by experiments, data sparseness problem may occur when predicting the quality of newly created documents with such information. To solve data sparseness problem of non-textual features, this paper proposes new features for document quality prediction, namely text-confidence features, which indicate how trustworthy the content of a document is. The proposed features, extracted directly from the document content, are stable against data sparseness problem, compared to non-textual features that indirectly require participation of service users in order to be collected. Experiments conducted on real world Knowledge Q&A documents suggests that text-confidence features show performance comparable to the non-textual features. We believe the proposed features can be utilized as effective features for document quality prediction and improve the performance of Knowledge Q&A services in the future.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.6
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• pp.17-21
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• 2000

Typical image features such as color, shape, and texture are used in content based image retrieved. Retrieval which uses only one image feature has little performance in case that the content of image is complex or database contains many images. So, many approaches for integrating these features have been studied. However, the problem of these approaches is how to appropriately weight the image features at query time. In this paper, we propose a new retrieval method using automatically weighted image features. We perform computer simulations in test database which consists of various kinds of images. The experimental results show that the proposed method has better performance than previous works, which use fixed weight for each feature mostly, in respect to several performance cvaluations such as precision vs recall, retrieval efficiency, and ranking measure.

• Asia pacific journal of information systems
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• v.31 no.2
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• pp.197-219
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• 2021

Social media platforms have become prominent channels for e-commerce, and the role of social network sites' (SNS) content marketing is expanding as a strategic marketing communication approach to attract and retain consumers and increase sales. In this study, we focused on South Korea market and explored the influence of linguistic complexity and informality on consumer engagement. In particular, we identified the importance of complexity, focusing on its negative effects, as well as the moderating effect of commerce features to minimize these effects. Specifically, content length, hashtags, long words, and average sentence length significantly and negatively impacted consumer engagement. The influence of emojis, an informality variable, was not statistically significant. Shoppable tags, a commerce feature that provides both advertising explicitness and shopping convenience, were a moderating factor in the influence of complexity. Our findings provide new insights for content marketing researchers, and have practical implications for social media managers and content developers.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.743-748
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• 2004

In this paper, we propose a probabilistic Korean parsing model using a syntactic feature, a functional feature, a content feature, and a site feature of a syntactic object for effective syntactic disambiguation. It restricts grammar rules to binary-oriented form to deal with Korean properties such as variable word order and constituent ellipsis. In experiments, we analyze the parsing performance of each feature combination. Experimental results show that the combination of different features is preferred to the combination of similar features. Besides, it is remarkable that the function feature is more useful than the combination of the content feature and the size feature.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.10B
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• pp.1902-1911
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• 1999

In this paper we present a content-based image retrieval algorithm using the visual feature vectors which describe the spatial characteristics of objects. The proposed technique uses the Gaussian mixture model(GMM) to represent multi-colored objects and the expectation maximization(EM) algorithm is employed to estimate the maximum likelihood(ML) parameters of the model. After image segmentation is performed based on GMM, the shape and color features are extracted from each object using Fourier descriptors and color histograms, respectively. Image retrieval consists of two steps: first, the shape-based query is carried out to find the candidate images whose objects have the similar shapes with the query image and second, the color-based query is followed. The experimental results show that the proposed algorithm is effective in image retrieving by using the spatial and visual features of segmented objects.