• Journal of KIISE:Computing Practices and Letters
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• v.7 no.6
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• pp.684-695
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• 2001

Recent recommender system uses a method of combining collaborative filtering system and content based filtering system in order to solve sparsity and first rater problem in collaborative filtering system. Collaborative filtering systems use a database about user preferences to predict additional topics. Content based filtering systems provide recommendations by matching user interests with topic attributes. In this paper, we describe a method for discovery of user preference through combining two techniques for recommendation that allows the application of machine learning algorithm. The proposed collaborative filtering method clusters user using genetic algorithm based on items categorized by Naive Bayes classifier and the content based filtering method builds user profile through extracting user interest using relevance feedback. We evaluate our method on a large database of user ratings for web document and it significantly outperforms previously proposed methods.

• ALGAE
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• v.31 no.4
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• pp.391-401
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• 2016

To develop an easy and rapid method of quantifying lipid contents of marine dinoflagellates, we quantified lipid contents of common dinoflagellate species using a colorimetric method based on the sulpho-phospho-vanillin reaction. In this method, the optical density measured using a spectrophotometer was significantly positively correlated with the known lipid content of a standard oil (Canola oil). When using this method, the lipid content of each of the dinoflagellates Alexandrium minutum, Prorocentrum micans, P. minimum, and Lingulodinium polyedrum was also significantly positively correlated with the optical density and equivalent intensity of color. Thus, when comparing the color intensity or the optical density of a sample of a microalgal species with known color intensities or optical density, the lipid content of the target species could be rapidly quantified. Furthermore, the results of the sensitivity tests showed that only $1-3{\times}10^5cells$ of P. minimum and A. minutum, $10^4cells$ of P. micans, and $10^3cells$ of L. polyedrum (approximately 1-5 mL of dense cultures) were needed to determine the lipid content per cell. When the lipid content per cell of 9 dinoflagellates, a diatom, and a chlorophyte was analyzed using this method, the lipid content per cell of these microalgae, with the exception of the diatom, were significantly positively correlated with cell size, however, volume specific lipid content per cell was negatively correlated with cell size. Thus, this sulpho-phospho-vanillin method is an easy and rapid method of quantifying the lipid content of autotrophic, mixotrophic, and heterotrophic dinoflagellate species.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.473-482
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• 2008

In this paper we propose an expert system for content-based image retrieval with object database. The proposed system finds keyword by using knowledge-base and feature of extracted object, and retrieves image by using keyword based image retrieval method. The system can decrease error of image retrieval and save running time. The system also checks whether similar objects exist or not. If not, user can store information of object in object database. Proposed system is flexible and extensible, enabling experts to incrementally add more knowledge and information. Experimental results show that the proposed system is more effective than existing content-based image retrieval method in running time and precision.

• Journal of the Semiconductor & Display Technology
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• v.10 no.3
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• pp.75-81
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• 2011

This paper presents a novel method for image classification based on a hybrid genetic algorithm (GA) and support vector machine (SVM) approach which can significantly improve the classification performance for content-based image retrieval (CBIR). Though SVM has been widely applied to CBIR, it has some problems such as the kernel parameters setting and feature subset selection of SVM which impact the classification accuracy in the learning process. This study aims at simultaneously optimizing the parameters of SVM and feature subset without degrading the classification accuracy of SVM using GA for CBIR. Using the hybrid GA and SVM model, we can classify more images in the database effectively. Experiments were carried out on a large-size database of images and experiment results show that the classification accuracy of conventional SVM may be improved significantly by using the proposed model. We also found that the proposed model outperformed all the other models such as neural network and typical SVM models.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.991-1000
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• 2020

We propose a content-based image retrieval system that uses a combination of completed local binary pattern (CLBP) and color autocorrelogram. CLBP features are extracted on a multi-resolution multi-direction filtered domain of value component. Color autocorrelogram features are extracted in two dimensions of hue and saturation components. Experiment results revealed that the proposed method yields a lot of improvement when compared with the methods that use partial features employed in the proposed method. It is also superior to the conventional CLBP, the color autocorrelogram using R, G, and B components, and the multichannel decoded local binary pattern which is one of the latest methods.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.1090-1100
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• 2021

Recently, as indoor activities increase due to the spread of infectious diseases, the metaverse is attracting attention. Metaverse refers to content in which the virtual world and the real world are closely related, and its representative platform technology is VR(Virtual Reality). However, since VR hardware is difficult to access in terms of cost, the concept of streaming-based cloud VR has emerged. This study proposes a server configuration and deployment method in an edge network when metaverse content involving multiple users operates based on cloud VR. The proposed algorithm deploys the edge server in consideration of the network and computing resources and client location for cloud VR, which requires a high level of computing resources while at the same time is very sensitive to latency. Based on simulation, it is confirmed that the proposed algorithm can effectively reduce the total network traffic load regardless of the number of applications or the number of users through comparison with the existing deployment method.

• Proceedings of the Korea Concrete Institute Conference
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• 2005.11a
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• pp.367-370
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• 2005

In this study, air meter method and capacitance measurement method to apply economically at quality control of ready-mixed concrete among various unit water content measurement technique was selected. Then, it was evaluated estimating performance of unit water content according to the change of water-binder ratio and unit water content. Also, it was examined influence about error occurrence of unit water content by change of properties of used materials. Finally, based on this study, it was proposed fundamental data to utilize measurement technique of unit water content to quality control. of ready-mixed concrete in construction field.

• Journal of IKEEE
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• v.7 no.2 s.13
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• pp.210-217
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• 2003

A novel characteristic value extraction method based on mathematical morphology is proposed. Morphological spatial frequency defined by morphological pattern distribution function is introduced and applied to define a new feature called ‘average height.' The average height is used to define a characteristic value which is to be used to generate an index key value for content-based image retrieval. Superiority of the method was proved for various images by experiment. Furthermore the fact that the proposed method does not need threshold to obtain binary image provides its applicability to content-based image retrieval.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5592-5609
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• 2017

JPEG steganography detection is an active research topic in the field of information hiding due to the wide use of JPEG image in social network, image-sharing websites, and Internet communication, etc. In this paper, a new steganalysis method for content-adaptive JPEG steganography is proposed by integrating the evolutionary feature selection and classifier ensemble selection. First, the whole framework of the proposed steganalysis method is presented and then the characteristic of the proposed method is analyzed. Second, the feature selection method based on genetic algorithm is given and the implement process is described in detail. Third, the method of classifier ensemble selection is proposed based on Pareto evolutionary optimization. The experimental results indicate the proposed steganalysis method can achieve a competitive detection performance by compared with the state-of-the-art steganalysis methods when used for the detection of the latest content-adaptive JPEG steganography algorithms.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.497-502
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• 2003

Content-based video copy detection is a complementary approach to watermarking. As opposed to watermarking, which relies on inserting a distinct pattern into the video stream, video copy detection techniques match content-based signatures to detect copies of video. Existing typical content-based copy detection schemes have relied on image matching which is based on key frame detection. This paper proposes a motion directional histogram, which is quantized and accumulated the direction of motion, for video copy detection. The video clip is represented by a motion directional histogram as a 1-dimensional graph. This method is suitable for real time indexing and counting the TV CF verification that is high motion video clips.